Intersectoral collaborations are an integral component of the prevention and control of diseases in a complex health system. On the one hand, One Health (OH) is promoting the establishment of intersectoral collaborations for prevention at the human-animal-environment interface. On the other hand, operationalising OH can only be realized through intersectoral collaborations. This work contributes to broadening the knowledge of the process for operationalising OH by analysing the governance structures behind different initiatives that tackle health problems at the human-animal-environment interface. The cases taken as examples for the analysis are the control and response to rabies and avian influenza under “classical OH”, and the management of floods and droughts for insights into “extended OH”. Data from Ghana and India were collected and compared to identify the key elements that enable ISC for OH. Despite the case studies being heterogeneous in terms of their geographic, economic, social, cultural, and historical contexts, strong similarities were identified on how intersectoral collaborations in OH were initiated, managed, and taken to scale. The actions documented for rabies prevention and control were historically based on one sector being the leader and implementer of activities, while avian influenza management relied more on intersectoral collaborations with clearly defined sectoral responsibilities. The management of the impact of flood and droughts on health provided a good example of intersectoral collaborations achieved by sectoral integration; however, the human health component was only involved in the response stage in the case of Ghana, while for India, there were broader schemes of intersectoral collaborations for prevention, adaptation, and response concerning climate change and disaster.
In the third week of January 2022, the southern districts of Malawi were hit by Cyclone Ana. The worst affected areas were Chikwawa and Nsanje. Four weeks following Cyclone Ana, a rather smaller cyclone, Dumako, hit the same areas, causing more damage. The Partners in Health or Abwenzi Pa Za Umoyo, an international humanitarian nongovernmental organisation that provides primary health care (PHC), organised teams to join Chikwawa District Council – Health, providing PHC assistance in the most affected district (Chikwawa); these teams were joined by three senior residents in family medicine from Kamuzu University of Health Sciences.Contribution: From the experiences of the interventions reported here, it was learnt that a multidisciplinary team of PHC providers is the key to the success of the emergency PHC programmes in times of natural disasters. While immediate PHC may be important at the actual time of disaster, it was learnt that PHC is also very important for continuation of care for chronic conditions, antenatal clinics and other clinics that are interrupted by the disaster. The experiences emphasised the importance of involving the PHC physicians and other PHC cadres in planning PHC programmes in natural disaster-prone areas.
The increasing number and complexity of urban risk and disasters have a significant bearing on the emotional and mental wellbeing of those who are exposed and hamper their responses. Nevertheless, current discourses and approaches to increase resilience tend to focus on broader socio-economic, physical and environmental systems. This reflects a failure by the academic and practitioner communities to consider the potential contribution of human interior dimensions in adaptation planning. Concomitantly, a growing body of knowledge highlights the need to bridge the gap between internal and external (systems) approaches for achieving sustainable transformations. Against this background, this article aims to increase knowledge on the operationalization of such more integrative approaches in marginal settings. Based on a case study of a flood adaptation project in Kibera, Kenya, we assess the need and potential ways to address interior dimensions in the context of project planning, design and implementation. We show how the integration of such dimensions occurs in existing adaptation projects and why this matters. On this basis, we provide methodological and operational recommendations regarding ways to support more integrative approaches that bridge subjective, intersubjective, objective and interobjective perspectives to support transformation.
Urban floods have long-term mental health implications, yet this subject remains largely neglected in flood-related studies. This paper examines the psychological distress (PD) of adults exposed to floods in Ghana. Cross-sectional data involving 767 flood-prone community-dwelling household heads aged ≥20 years were analyzed [mean = 47.3 years (SD = 13.7); males = 61.4%]. We used the Exposure to Flood-related Events Scale, and PD was assessed with the Kessler Psychological Distress Scale (K10). Ordinary Least Squares (OLS) regressions evaluated crude and adjusted associations of flood exposure with PD. The mean scores of PD (37[SD = 8]) and exposure to flood events (6[SD = 3]) significantly varied by age and sex (p < .05). After full adjustment for potential confounders, exposure to flood events was significantly and positively associated with PD index in the total sample (β = 0.030; p < .005), among male participants (β = 0.019; p < .05) and female participants (β = 0.048; p < .001). Furthermore, age-wise analysis revealed significant association of flood exposure with PD in young adults (β = 0.033; p < .001) but not in older adults (β = 0.048; p = .062). Exposure to floods increased the risk of PD. Policy and public health efforts to manage PD should include selective flood reduction interventions, including land use regulations and sustained public education.
As disasters increase in frequency and magnitude with adverse effects on population health, governments will be forced to implement disaster risk management policies that may include forced relocation. Ineffective public consultation has been cited as one reason for failure of these policies. Using the deliberative polling method, this study assessed the capacity of rural communities to participate in flood risk management policy priority setting and the impact of providing accurate and balanced information on policies by comparing pre-and post -deliberation data. The study also assessed the level of trust on whether government and community would use the results of this study. Results indicated strong community support for policy options to reduce vulnerability in communities and strong resistance to relocation. As all the top five ranked policy options were concerned with population pressure, gender, and social service issues, which are all conceptually considered social determinants of a healthy community, this study concludes that public health considerations are central to flood risk policy development and implementation. The study revealed high levels of trust in government and the community relating to flood risk management, which policymakers in low-to-middle income countries can capitalise on for meaningful community consultation for effective disaster risk management.
Recurrent floods have become a major problem in the transboundary Lower Mono River catchment of Togo and Benin, causing more damage and loss of life than any other disaster in the area. The level of understanding about floods and their management can be as diverse as the groups within the communities and thus can present a variety of perspectives. People tend to perceive flood risk and management differently due to their proximity to flood-prone areas and their level of vulnerability as well as their capacity to adapt. Therefore, this study explores the specific perspectives of local communities and experts on floods in the transboundary Mono catchment, which can help to inform better adaptation strategies according to the contexts of each community. We conducted series of focus groups discussions (FGDs) using the Actors, Resources, Dynamics, and Interactions (ARDI) framework to develop mental models of flood management. This approach allowed us to identify the causes and impact of flooding in the area, and to describe the actors and effects of flood events on the main natural resources as well as the dynamics and interactions that drive change and influence flood management in the study area. The results indicate that the perceptions of local communities and experts show both similarities and differences. These differences include (1) perceptions of relevant direct actors, (2) perceptions of resources at stake, and (3) actor-specific resource utilization. Considering these dissimilar views between expert and local community knowledge systems appears to be an important contributing factor to improving flood mitigation efforts in the catchment. Adapting risk communication and measures taken for flood management in accordance with the perceptions of affected communities could greatly increase success, with positive long-term effects for the involved institutions and communities regarding mutual trust-building.
Flooding is one of the most destructive climatic hazards which has affected agricultural activities in the world, especially Sub-Saharan Africa. This article investigated the impact of the recurrent annual floods on food production and how subsistent farmers have adapted to resultant food insecurity in the Sudan Savannah agroecological zone of Ghana. The specific objectives of the study were to understand the nature of flooding (frequency, period and extent of coverage of flood water), how the perennial floods contribute to food insecurity, how farmers adapt to it to contribute towards policy development on flood control and improve food security. Primary data were collected using questionnaires, interviews, focus group discussions and field observation. Secondary data were obtained from documents and reports from NADMO and MOFA. The questionnaires were analyzed using Statistical Package for Social Science and the focus group discussions, interviews, and fieldwork were analyzed manually using content analysis. The findings show that the study areas experience floods every year. Between 2007 and 2018, eleven floods event occurred in the study communities. The floods usually occur around August and September when rainfall is torrential coupled with overflow from the spillage of the Bagre dam upstream. The flooding has resulted in a decline in food production among subsistent farmers. As a result, households in study communities are food insecure. Farmers have learned to cope with floods/food insecurity by engaging in alternative livelihoods such as flood recession farming, dry season farming, petty trading. They have also employed other means such as rationings of food and social networks cope with food insecurity. In all these strategies, women play a critical role as they are largely in charge of food preparation and dishing. The study recommends strengthening of the alternative livelihoods, introduction of short maturing crop varieties, sensitisation of women on the preparation of healthy meals.
This research reviews climate change, flood disasters impacts and food security nexus in northern Ghana. The impacts of climate change include flood disasters which in turn affect food production with subsequent impact on food security. While climate change impact can be positive in some regions, it can be negative in other regions as it could lead to excess or lack of water, which negatively affects food production. Most especially, flood disasters have reportedly become frequent with devastating consequences on food production. Literature further suggests that the frequency of floods and their impacts have the potential to increase in the future. Floods inundate farms, pastures and livestock, which could subsequently reduce crop yields and animal production. Floods also destroys physical infrastructure and disrupts socio-economic activities which are linked to agriculture sector and could affect food production. This eventually decreases food availability, accessibility, utilization, and stability in the region. Northern Ghana has experienced flood disasters with increased frequency, which are related to climate change impacts. Although there is research on climate change, flood disasters, and food security issues in northern Ghana, the literature thus far indicates no clear focus of studies that focuses on the nexus of climate change, flood disasters, and food security of the study site. Thus, this research seeks to review the nexus of climate change, and flood disaster impacts on food security in northern Ghana with their implications on food security in the region. This study has two main research objectives. The first objective of this research is to identify and understand the potential impacts of climate change and flood disasters on food production in the study site. The second research objective is to explain the connection between climate change and flood disasters and the implications of this relationship on food security in the study site. This review study focuses on climate change, flood disasters, and food production to understand the critical impacts of climate change and flood disasters on food security in the northern part of Ghana. The aim of this research is to contribute to literature and discussion of the nexus of climate change, flood disaster impacts and food security sub-Saharan Africa.
In sub-Saharan Africa, land cover change, expansion of hydropower infrastructure, and increased flooding complicate country-level efforts to meet the Sustainable Development Goal target concerning access to safe water. The Water, Energy and Food (WEF) nexus approach recognises that addressing these complex challenges requires cross-sectoral analyses at multiple scales. Building on such an approach, our study examined the interrelationships between land cover change, dam-related flooding and access to safe water via a national-level spatial analysis with local case studies in Malawi and Ghana. Our assessment of the water-food interactions found that areas of overlap between water points and cropland increased from 2000 to 2020 for both countries at national scale, but overlap extent varied greatly depending on the land cover product used. Local-scale exploration of water point installation patterns in Zomba, Malawi confirmed this pattern, highlighting increasing non-governmental funding of borehole installation programmes. Our assessment of water-energy interactions found that flooding mediated by hydropower dams increased for the White Volta Basin in Ghana, thereby increasing inundation of groundwater points. Local-scale focus group discussions revealed flooding resulted in contaminated water sources and high risk of injury or drowning whilst fetching water. Overall, our study highlights how socio-economic drivers are bringing water points, flooding and cropland into closer proximity, requiring flood mitigation measures at water points and agro-chemical management to minimise potential water quality impacts. Given differences between land cover products, we recommend more robust integration of existing land cover products to better monitor these phenomena.
BACKGROUND: The ability of disaster response, preparedness, and mitigation efforts to assess the loss of physical accessibility to health facilities and to identify impacted populations is key in reducing the humanitarian consequences of disasters. Recent studies use either network- or raster-based approaches to measure accessibility in respect to travel time. Our analysis compares a raster- and a network- based approach that both build on open data with respect to their ability to assess the loss of accessibility due to a severe flood event. As our analysis uses open access data, the approach should be transferable to other flood-prone sites to support decision-makers in the preparation of disaster mitigation and preparedness plans. METHODS: Our study is based on the flood events following Cyclone Idai in Mozambique in 2019 and uses both raster- and network-based approaches to compare accessibility to health sites under normal conditions to the aftermath of the cyclone to assess the loss of accessibility. Part of the assessment is a modified centrality indicator, which identifies the specific use of the road network for the population to reach health facilities. RESULTS: Results for the raster- and the network-based approaches differed by about 300,000 inhabitants (~ 800,000 to ~ 500,000) losing accessibility to healthcare sites. The discrepancy was related to the incomplete mapping of road networks and affected the network-based approach to a higher degree. The modified centrality indicator allowed us to identify road segments that were most likely to suffer from flooding and to highlight potential backup roads in disaster settings. CONCLUSIONS: The different results obtained between the raster- and network-based methods indicate the importance of data quality assessments in addition to accessibility assessments as well as the importance of fostering mapping campaigns in large parts of the Global South. Data quality is therefore a key parameter when deciding which method is best suited for local conditions. Another important aspect is the required spatial resolution of the results. Identification of critical segments of the road network provides essential information to prepare for potential disasters.
Flood-induced fatalities are among the more poorly reported effects of flood disasters in many developing countries because of poor data inventory and management. Specific objectives of this study are to assess the spatial and temporal variations in flood fatalities in Nigeria, the most populous country in Africa. The study explored available datasets from the National (Nigerian) Meteorological and Emergency Management Agencies as well as those from the Dartmouth Flood Observatory (DFO) at the University of Colorado Boulder and complemented those with scattered reports from Nigerian newspapers to achieve the stated objectives. Using a mix of statistical and geographical information analysis approaches, the study showed that most of Nigeria is vulnerable to flood, given the nature of the dominant climate that often results in “medium” to “high” rainfall intensity (i.e., rainfall 5 38.1-50.1 mm or > 50.1 mm in 24 h, respectively), inadequate settlement planning/land-use and land-cover management, and dam failure. Analysis of the frequency of the flood-fatality relationship indicates an increase in flood fatalities by 4.7% relative to flood cases between 1985 and 2017. The study complemented the results with information from newspapers and some other non-peer-reviewed documents (especially reports from relevant agencies) and revealed the need for a better flood information management system in the country, especially since the national database and DFO records were not the same. The study concluded that flood fatalities are on the increase but are poorly reported. It thus recommends improved information systems for flood and other disasters and their fatalities in the country.
Rural isolation can limit access to basic services and income-generating opportunities. Among some communities, rainfall induced flooding can cause increased uncertainty where first-mile transportation infrastructure is limited. In Rwanda, this challenge is apparent, where 90% of the population below the poverty line live in rural areas that are typically mountainous with frequent flooding – events that may be increasing in frequency and severity as the climate changes. To reduce these transportation barriers, the non-profit organization Bridges to Prosperity (B2P) plans to construct hundreds of trailbridges in Rwanda between 2018 and 2023. This scale of rural infrastructure services presents an opportunity for experimental investigation of the effects of these new trailbridges on economic, health, agricultural and education outcomes in rural communities. In this paper, we present a cohort study evaluating the potential community benefits of rural trailbridges – including economic, health and social outcomes for Rwandan communities experiencing environmental change. We examined households living near 12 trailbridge sites and 12 comparison sites over February 2019-March 2020. We found that labor market income increased by 25% attributable to the trailbridges. We did not observe any significant effects on agricultural income, education or health outcomes, however given the small sample and short duration of this study we anticipate observing additional outcomes within the recently started 200 site, 4 year trial.
The urban poor in cities of developing countries tend to be the most affected by climate change. This is because of the intersection of their socio-economic characteristics and the hazardous bio-physical environments they inhabit, which usually have limited social services. This study, conducted through interviews with 320 residents of Bauleni and Misisi residential areas of Lusaka, applied the concept of intersectionality to investigate climate risk and social vulnerabilities in informal settlements of Lusaka. The study was based on both quantitative and qualitative data. Quantitative data was analysed using the two-sample proportions Z test and descriptive statistics with the aid of Minitab 17 statistical package, while qualitative data was analysed using thematic analysis with the aid of a qualitative data analysis software called QDA miner. The respondents identified floods, diseases and crime as the major social and climatic risks. Apart from flooding and crime, the risks were not perceived to affect the value of housing in the study sites. This was due to a lack of affordable housing alternatives for the urban poor. The social and climatic risks had differentiated effects on women, men and children. Housing property owners and tenants continue to reside in the risky environments because of the lower cost of land, low cost of living and proximity to the city’s central business district. The study recommends that policy measures aimed at improving informal settlements residents’ well-being should be directed at improving their ability to adjust to and recover from impacts of the climatic disasters and reducing social vulnerabilities.
Nairobi’s settlements are vulnerable to urban flooding exacerbated by anthropogenic factors. Households living in flood-prone areas suffer perennially. However, little scientific evidence exists on the relationship between impacts of flooding and coping strategies in Nairobi’s settlements. In this study, primary data was obtained through ground-truth surveys and administration of questionnaires to 310 households in Nairobi’s crowded informal settlements of Mathare Kosovo and Kibera Mashimoni. Information captured included their bio-data, knowledge and perception of flooding, socio-economic, susceptibility and recovery indicators. Secondary data was mainly from literature review. The findings of the canonical correlation revealed that an insignificant relationship of 0.2964 and 0.2503 existed between flooding impacts and coping strategies adopted by households and communities respectively. Floods caused inaccessibility of houses, workplaces and schools, damages to settlements infrastructure, drowning, diseases and displacement of residents. The indirect impacts were loss of livelihoods, environmental degradation, loss of manhours in traffic jams and economic loss. This study is novel in that it provides empirical scientific evidence on the nexus between impacts of flooding and coping strategies in an urban settlement. It augments existing literature on flood risks in urban settlements. It also provides an entry point for policy and decision makers such as scientists, private sector leaders, urban planners and government technocrats to make informed policy guidelines and intervention strategies.
Flooding is the most frequent natural hazard globally, but evidence of its impact on domestic water point contamination remains limited. This study aimed to assess dam-related flooding’s impact on microbiological contamination of rural water points and to evaluate agreement of satellite-derived flood maps with ground-based observations of water point flooding. Fieldwork took place in two Ghanaian districts frequently flooded following dam overspill. Fifty-seven water points were tested for bacterial parameters during and immediately after flooding. Forty water points were resampled in the dry season, with the remainder having run dry. Ground-based observations of flooding were compared with three satellite-derived flood maps. Boreholes were less contaminated than wells or surface waters (geometric mean E. coli = 20.2, 175.6, and 590.7 cfu/100 ml, respectively). Among groundwater points, a Wilcoxon signed-rank test indicated significantly greater median E. coli and thermotolerant coliform contamination during flooding (p = 0.025 and p < 0.001, respectively), but Shigella, salmonella, and intestinal enterococci counts were not significantly different between seasons. In contrast, among surface water points, E. coli, Shigella, and Salmonella counts were significantly greater in dry season samples (p < 0.005 for all parameters), possibly reflecting a "concentration" effect. Satellite-derived flood maps had no or low agreement with ground-based observations of water point flooding. Although groundwater quality deteriorated during and after flooding, surface waters were the most microbiologically contaminated in both seasons. The greatest public health risk thus occurred where households switched to surface water collection during or following flood season. Flood risk should be assessed before borehole installation and existing flood-prone boreholes remediated to mitigate population exposure to contaminated water.
Floods affect the human security conditions of floodplain residents. The aim of this paper is to explore how residents of the Tana River Delta in Kenya become flood insecure. This paper utilises assemblage theory, particularly the principles of rhizomatic multiplicity to explain the concept of becoming flood insecure. It combines these rhizomatic multiplicity principles with disruptions to the pillars of human security which are becoming afraid, becoming wanting and becoming undignified and their composite conditions of human insecurity to create an analytical framework with which to understand becoming flood insecure. The study sources its data from Focus Group Discussions in 10 sampled villages in the Tana River Delta. The results reveal that becoming flood insecure is a rhizomatic multiplicity and that the pillars and conditions of human security that comprise it are heterogenous and interconnected. The results reveal the conditions of human insecurity in the Tana River Delta as personal, food, water, fuel, housing, health, environment, and political. They also reveal that while children become more flood insecure, they are also the most adaptive. Additionally, the results show that there are transitory conditions of human insecurity, food, housing health, to which people attempt to find local solutions and redundant conditions of human insecurity, political, health, water, personal and environment, to which people cannot find local solutions and public action is required.
Leptospirosis is a waterborne zoonosis (60,000 infections and 1 million deaths annually). Knowledge about the disease in the urban context is surprisingly rare, especially in Africa. Here, we provide the first study of leptospires in waters within an African city. A simple centrifugation-based method was developed to screen waterborne leptospires from remote or poorly areas. Major ions, trace elements, stable isotopes and pathogenic Leptospira were then seasonally investigated in 193 water samples from three neighborhoods of Cotonou (Benin) with different socio-environmental and hydrographic characteristics. Firstly, no leptospire was detected in tap waters. Secondly, although surface contamination cannot be excluded, one groundwater well was found leptospire positive. Thirdly, pathogenic Leptospira mainly contaminated surface waters of temporary and permanent ponds (9.5% and 27.3% of total prevalence, respectively). Isotopic signatures suggest that leptospires occurred in pond waters formed at the beginning of the rainy season following low to moderate rainfall events. Nevertheless, Leptospira-containing waters possess physico-chemical characteristics that are similar to the spectrum of waters sampled throughout the three sites, thus suggesting that Cotonou waters are widely compatible with Leptospira survival. The frequent contact with water exposes Cotonou inhabitants to the risk of leptospirosis which deserves more attention from public health authorities.
BACKGROUND: Floods are the most frequently occurring natural disaster and constitute a significant public health risk. Several operational satellite-based flood detection systems quantify flooding extent, but it is unclear how far the choice of satellite-based flood product affects the findings of epidemiological studies of associated public health risks. Few studies of flooding’s health impacts have used mixed methods to enrich understanding of these impacts. This study therefore aims to evaluate the relationship between two satellite-derived flood products with outpatient attendance and diarrhoeal disease in northern Ghana, identifying plausible reasons for observed relationships via qualitative interviews. METHODS: A convergent parallel mixed methods design combined an ecological time series with focus group discussions and key informant interviews. Through an ecological time series component, monthly outpatient attendance and diarrhoea case counts from health facilities in two flood-prone districts for 2016-2020 were integrated with monthly flooding map layers classified via the Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite sensors. The relationship between reported diarrhoea and outpatient attendance with flooding was examined using Poisson regression, controlling for seasonality and facility catchment population. Four focus group discussions with affected community members and four key informant interviews with health professionals explored flooding’s impact on healthcare delivery and access. RESULTS: Flooding detected via Landsat better predicted outpatient attendance and diarrhoea than flooding via MODIS. Outpatient attendance significantly reduced as LandSat-derived flood area per facility catchment increased (adjusted Incidence Rate Ratio = 0.78, 95% CI: 0.61-0.99, p < 0.05), whilst reported diarrhoea significantly increased with flood area per facility catchment (adjusted Incidence Rate Ratio = 4.27, 95% CI: 2.74-6.63, p < 0.001). Key informants noted how flooding affected access to health services as patients and health professionals could not reach the health facility and emergency referrals were unable to travel. CONCLUSIONS: The significant reduction in outpatient attendance during flooding suggests that flooding impairs healthcare delivery. The relationship is sensitive to the choice of satellite-derived flood product, so future studies should consider integrating multiple sources of satellite imagery for more robust exposure assessment. Health teams and communities should plan spatially targeted flood mitigation and health system adaptation strategies that explicitly address population and workforce mobility issues.
Climate change threatens the health and well-being of populations. We conducted a risk assessment of two climate-related variables (i.e., temperature and rainfall) and associated water, sanitation and hygiene (WASH)-related exposures and vulnerabilities for people living in Mopani District, Limpopo province, South Africa. Primary and secondary data were applied in a qualitative and quantitative assessment to generate classifications of risk (i.e., low, medium, or high) for components of hazard/threat, human exposure, and human vulnerability. Climate-related threats were likely to impact human health due to the relatively high risk of waterborne diseases and WASH-associated pathogens. Vulnerabilities that increased the susceptibility of the population to these adverse outcomes included environmental, human, physical infrastructure, and political and institutional elements. People of low socio-economic status were found to be least likely to cope with changes in these hazards. By identifying and assessing the risk to sanitation services and water supply, evidence exists to inform actions of government and WASH sector partners. This evidence should also be used to guide disaster risk reduction, and climate change and human health adaptation planning.
This longitudinal flood-relief study assessed the impact of the March 2019 Cyclone Idai flood event on E. coli contamination of hand-pumped boreholes in Mulanje District, Malawi. It established the microbiological water-quality safety of 279 community supplies over three phases, each comprising water-quality survey, rehabilitation and treatment verification monitoring. Phase 1 contamination three months after Idai was moderate, but likely underestimated. Increased contamination in Phase 2 at 9 months and even greater in Phase 3, a year after Idai was surprising and concerning, with 40% of supplies then registering E. coli contamination and 20% of supplies deemed ‘unsafe’. Without donor support for follow-up interventions, this would have been missed by a typical single-phase flood-relief activity. Contamination rebound at boreholes successfully treated months earlier signifies a systemic problem from persistent sources intensified by groundwater levels likely at a decade high. Problem extent in normal, or drier years is unknown due to absence of routine monitoring of water point E. coli in Malawi. Statistical analysis was not conclusive, but was indicative of damaged borehole infrastructure and increased near-borehole pit-latrine numbers being influential. Spatial analysis including groundwater flow-field definition (an overlooked sector opportunity) revealed ‘hit-and-miss’ contamination of safe and unsafe boreholes in proximity. Hydrogeological control was shown by increased contamination near flood-affected area and in more recent recharge groundwater otherwise of good quality. Pit latrines are presented as credible e-coli sources in a conceptual model accounting for heterogeneous borehole contamination, wet season influence and rebound behavior. Critical to establish are groundwater level – flow direction, hand-pump plume draw, multiple footprint latrine sources – ‘skinny’ plumes, borehole short-circuiting and fast natural pathway (e.g. fracture flow) and other source influences. Concerted WASH (Water, Sanitation and Hygiene) sector investment in research and policy driving national water point based E. coli monitoring programs are advocated.
BACKGROUND: Malaria epidemics are a well-described phenomenon after extreme precipitation and flooding, which account for nearly half of global disasters over the past two decades. Yet few studies have examined mitigation measures to prevent post-flood malaria epidemics. METHODS: We conducted an evaluation of a malaria chemoprevention program implemented in response to severe flooding in western Uganda. Children ≤12 years of age from one village were eligible to receive 3 monthly rounds of dihydroartemisinin-piperaquine (DP). Two neighboring villages served as controls. Malaria cases were defined as individuals with a positive rapid diagnostic test result as recorded in health center registers. We performed a difference-in-differences analysis to estimate changes in the incidence and test positivity of malaria between intervention and control villages. RESULTS: A total of 554 children received at least one round of chemoprevention with 75% participating in at least two rounds. Compared to control villages, we estimated a 53.4% reduction (aRR 0.47, 95% CI 0.34 – 0.62, p<.01) in malaria incidence and a 30% decrease in the test positivity rate (aRR=0.70, CI 0.50 - 0.97, p=0.03) in the intervention village in the six months post-intervention. The impact was greatest among children receiving the intervention, but decreased incidence was also observed in older children and adults (aRR=0.57, CI 0.38-0.84, p<.01). CONCLUSIONS: Three rounds of chemoprevention with DP delivered under pragmatic conditions reduced the incidence of malaria after severe flooding in western Uganda. These findings provide a proof-of-concept for the use of malaria chemoprevention to reduce excess disease burden associated with severe flooding.
Climate changes in the eastern part of Sahelian regions will induce an increase in rainfalls and extreme climate events. In this area, due to the intense events and floods, malaria transmission, a climate sensitive disease, is thus slowly extending in time to the drought season and in areas close to the border of the desert. Vectors can as well modify their area of breeding. Control programs must be aware of these changes to adapt their strategies.
Human vulnerability to disasters poses a significant concern to water resources management. The present study examined the factors influencing the occurrence of flooding, risk and management strategies in Lagos, Nigeria. A set of questionnaires was administered to 400 respondents in four randomly selected settlements in Lagos State based on perception and observation methods. Descriptive and multivariate statistics and cartographic mapping techniques were employed for data analysis. The result indicates that the majority of the respondents live in a rented room and parlor. The significant flood risks include poor sanitation, a breeding site for mosquitoes, water contamination/waterborne diseases, and mental stress. Factors analysis explains 74.62% of the variance, indicating anthropogenic, natural, and institutional factors influencing flooding in the study area. The dominant flood management measures are clearance of drains, environmental sanitation, public awareness, training/education, while the significant steps taken by the government to ameliorate flooding challenges in the area include awareness, early warning, and education. The study concluded that there exists a significant difference in the factors influencing flooding across the settlements based on the ANOVA result given as: (DWSD F = 19.661, p < 0.05; RI = 41.104, p < 0.05; WIC = 18.123, p < 0.05; HWL = 37.481, p < 0.05; SD = 10.294, p < 0.05). The study contributes to knowledge using cartographic techniques to map the risks of flooding for easy understanding. The study has potential policy implications for planning and interventions in areas vulnerable areas. The study recommended monitoring of construction activities, enforcement of building codes, awareness campaigns, and early warning flood technology for sustainable flood management in the area.
Despite the long-lasting and widespread drought in the Sahel, flood events did punctuate in the past. The concern about floods remains dwarf on the international research and policy agenda compared to droughts. In this paper, we elucidate that floods in the Sahel are now becoming more frequent, widespread, and more devastating. We analyzed gridded daily rainfall data over the period 1981-2020, used photographs and satellite images to depict flood areas and threats, compiled and studied flood-related statistics over the past two decades, and supported the results with peer-reviewed literature. Our analysis revealed that the timing of the maximum daily rainfall occurs from the last week of July to mid-August in the Eastern Sahel, but from the last week of July to the end of August in the Western Sahel. In 2019 and 2020, flash and riverine floods took their toll in Sudan and elsewhere in the region in terms of the number of affected people, direct deaths, destroyed and damaged houses and croplands, contaminated water resources, and disease outbreaks and deaths. Changes in rainfall intensity, human interventions in the physical environment, and poor urban planning play a major role in driving catastrophic floods. Emphasis should be put on understanding flood causes and impacts on vulnerable societies, controlling water-borne diseases, and recognizing the importance of compiling relevant and reliable flood information. Extreme rainfall in this dry region could be an asset for attenuating the regional water scarcity status if well harvested and managed. We hope this paper will induce the hydroclimate scholars to carry out more flood studies for the Sahel. It is only then encumbered meaningful opportunities for flood risk management can start to unveil.
BACKGROUND: Floods have affected 2.3 billion people worldwide in the last 20 years, and are associated with a wide range of negative health outcomes. Climate change is projected to increase the number of people exposed to floods due to more variable precipitation and rising sea levels. Vulnerability to floods is highly dependent on economic wellbeing and other societal factors. Therefore, this systematic review synthesizes the evidence on health effects of flood exposure among the population of sub-Saharan Africa. METHODS: We systematically searched two databases, Web of Science and PubMed, to find published articles. We included studies that (1) were published in English from 2010 onwards, (2) presented associations between flood exposure and health indicators, (3) focused on sub-Saharan Africa, and (4) relied on a controlled study design, such as cohort studies, case-control studies, cross-sectional studies, or quasi-experimental approaches with a suitable comparator, for instance individuals who were not exposed to or affected by floods or individuals prior to experiencing a flood. RESULTS: Out of 2306 screened records, ten studies met our eligibility criteria. We included studies that reported the impact of floods on water-borne diseases (n = 1), vector-borne diseases (n = 8) and zoonotic diseases (n = 1). Five of the ten studies assessed the connection between flood exposure and malaria. One of these five evaluated the impact of flood exposure on malaria co-infections. The five non-malaria studies focused on cholera, scabies, taeniasis, Rhodesian sleeping sickness, alphaviruses and flaviviruses. Nine of the ten studies reported significant increases in disease susceptibility after flood exposure. CONCLUSION: The majority of included studies of the aftermath of floods pointed to an increased risk of infection with cholera, scabies, taeniasis, Rhodesian sleeping sickness, malaria, alphaviruses and flaviviruses. However, long-term health effects, specifically on mental health, non-communicable diseases and pregnancy, remain understudied. Further research is urgently needed to improve our understanding of the health risks associated with floods, which will inform public policies to prevent and reduce flood-related health risks.
Integrating noncommunicable disease (NCD) in health care delivery during emergency response posed a major challenge post-floods in Kerala. Kerala experienced an abnormally high rainfall during mid-2018 where more than 400 people lost their lives. State health officials and the Disaster Response Team were sensitized about the importance of including NCDs in the response action. More than 80% of patients with hypertension and diabetes were not under control in Kerala. Under the state NCD cell, an NCD expert group was consulted for drafting the treatment and referral strategies. Steps to tackle NCDs during the disaster response were formulated. The state NCD cell decided to integrate NCDs in the response measures. The technical guidance document by the World Health Organization South-East Asia Region was consulted to formulate actions. The activities were implemented in 6 steps: prioritizing of major NCDS, patient estimation and drug stock preparation, standard treatment protocol, mapping of referral facilities, public engagement, and daily reporting of NCD consultations. Prioritizing the continuum of care of NCDs during floods among the program managers and care providers was crucial. The health education and communication campaign was done to sensitize the known NCD patients to seek early care. Daily reporting of consultations was established.
Communities are ever-evolving, cities are constantly expanding, and the threat of natural hazards has escalated like never before. Cities can develop and prosper only if their society is resilient to external shocks. Measuring community resilience over time is crucial with the influence of technology and change in community lifestyles. With the frequent onset of floods in Kerala in recent years, the community must be well-prepared for future calamities. Thus, this paper develops a community resilience index for Kerala’s urban flood-prone areas (CRIF) through a rigorous bottom-up approach. The criteria for the index were developed using multi-criteria decision analysis that covered a fuzzy Delphi study, an empirical study using multi-variate probit regression, and an AHP analysis. The fuzzy Delphi study selected seven criteria: ‘social’, ‘economical’, ‘governance/political’, ‘health’, ‘communication/coordination, ‘education’, and ‘infrastructure’ from 65 experts. The empirical study helped apprehend the public’s viewpoints under each criterion. Finally, the AHP analysis helped assign appropriate weights to the criteria which 28 experts designated. The index is also designed according to the Sendai Framework for Disaster Risk Reduction (2015-2030). Further, the CRIF Index is put into action through a case study of the Kochi Municipal Corporation area, and the results are also validated using the Spearman’s rank correlation coefficient method. Results from validation returned a value of 0.7209 for the perceived CRIF method and 0.5798 for the external validation method, which corresponds to a ‘high’ and ‘moderate’ correlation, respectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-022-05299-7.
Recurring floods and erosion result in displacement, which adversely impacts women who are ‘left behind’ when men migrate. Policy and programme measures for disaster response and climate adaptation often perceive women as homogenous, vulnerable groups, instead of addressing underlying structural and conceptual barriers and strengthening their adaptive capacities to disasters and displacement. This article draws upon a political ecology lens to understand gendered recovery processes following disasters across four districts in Assam, northeastern India using empirical research from 2012 to 2018. The findings add nuances to the displacements of women in Assam as being ‘climate-induced’ by showing the different mechanisms of displacement and how it impacts particular groups of women, as well as their differential ways of coping with these changes. This article draws on sustained long-term qualitative research among rural villagers, particularly women, in Assam where migration is connected to riverbank erosion, exacerbated by the construction of a new embankment, and disrupted due to waterlogging caused by embankments and government relocation schemes in order to construct further dams/embankments.
Objective Flood is an annual phenomenon in Assam. This study aims to understand the after flood effects on children in the worst flood-hit districts of Assam during the last decades most devastating flood where more than 1,00,000 people were affected. Study design A cross sectional population-based study was done covering 7512 children of 0-12 years of age in 35 worse flood-affected villages in three districts of lower Assam for nutritional risk profiling, low birth weight and morbidity pattern. Method Anthropometric measurements of the children were compared with standard WHO definitions for nutritional risk profiling. ANOVA was conducted to see any relationship of nutritional status between the age groups and BMI for the districts. Two-factor ANOVA to analyse the effect of ARI on the morbidity status of different districts was done. District-wise and village-wise heat maps were generated to understand different nutritional parameters for analysing which areas within each district are more affected and why. Results The moderate (< 2SD) and severely underweight (< 3SD) children under 5 years of age were highest in the Barpeta district (45.5% and 24.2% respectively). The moderate and severe stunting was highest in Morigaon (47.6%) and Barpeta (24.3%) respectively. The moderate and severe wasting was highest in the Morigaon district (46.1% and 20.6% respectively). All the nutritional indicators were less than the WHO standard. The age-wise and district-wise distribution of nutritional status shows variations in all three districts. Severe underweight was observed highest among 24-35 months' children (50.9%) in Barpeta. The moderate and severe undernutrition status was found to be higher among the age group of 10-12 years of age compared to 5 to 10 years. Conclusion This survey has provided a comprehensive picture of the nutritional status of the targeted children in the worst flood-affected areas. However, attention to its impact on health particularly among those exposed at very early stages in life is still lacking. This kind of rapid assessment helps to understand the health and nutritional status of the vulnerable groups in a deeper way and to plan robust region-specific interventions.
India witness floods during the summer monsoon (June-September) that disproportionately affect the socioeconomic well-being of millions of people. Nonstructural measures such as flood early warning systems play a crucial role in mitigating the impacts; however, these require a proper understanding of flood drivers. The drivers of floods in the Indian river basins have not been examined for the observed and projected future climate. Here using a novel framework, we examine antecedent moisture conditions and precipitation characteristics before high flow events. We estimate the probability of occurrence of flood drivers and their association with peak flood magnitude under the observed and projected future climate in Indian river basins. Multiday precipitation, a proxy to heavy precipitation on wet soil conditions, was found as the predominant flood driver in the observed and projected future climate. We show that multiday precipitation is more prominent driver than extreme soil moisture conditions in larger rivers basins while extreme precipitation drives floods in smaller river basins. The frequency of major drivers of floods is projected to rise in the future, which may pose a greater risk to agriculture and infrastructure under the warming climate.
Natural disasters inflict severe damage on almost the entire spectrum of social and natural habitats. This ranges from housing and shelter, water, food, health, sanitation to information and communication networks, supply of power and energy, transportation infrastructure, and others. Nepal is a risk prone country for Glacial Lake Outburst Flood (GLOF). GLOFs exist as major challenges as they repeatedly cause a heavy toll of life and property. During such a disaster, major challenges are indeed the protection of life, property and vital life-supporting infrastructure. Any delay or laxity in disaster relief can escalate the magnitude of distress for the victims. Thus, rather than trying to take curative measures, it is better to minimize the impacts of GLOF. These measures subsequently help in reducing the magnitude of death and casualties due to a GLOF event. This reduction of impact is often achieved by optimizing preventive measures. For applying necessary deterrent measures, it is essential to disseminate information about the danger beforehand. Early Warning System (EWS) is an important step for such information dissemination for GLOF disaster management and helps to anticipate the risk of disaster and disseminate information to lives at risk. It is impossible and impractical to reduce all GLOF risks, but it is possible to reduce several impacts of a GLOF through the implementation of the EWS. This paper presents the design and implementation of an EWS for monitoring potential outbursts of a glacier lake in the Dudh-Koshi Basin, Nepal.
Torrential rainfall following the monsoon season occurs annually in Pakistan and adversely affects health service delivery and population health. This qualitative study was undertaken in five flood-prone districts to examine district health systems’ performance during floods in Pakistan. The first of its kind study to gather an in-depth assessment of the capacity of district health systems in maintaining healthcare services during floods. Key informant interviews were conducted with 37 district stakeholders and 42 frontline healthcare providers. Nine focus group discussions were also conducted with 56 lady health workers. World Health Organization health systems’ six building blocks framework was utilized to assess the performance of district health systems. The findings illustrated increased reporting of diseases, and domestic and sexual violence against females. The damaged roads and unavailability of transportation during floods affected outreach services in the communities. The inadequate availability of funds resulted in critical gaps in the supply chain for essential medicines and supplies, impeding outreach services. Shortage of female medical staff was reported in addition to poor attention to the training of staff for disaster response. Furthermore, reporting mechansim varied across provinces with daily reporting system of acute illnesses instituted. Moreover, district health systems lacked gender-sensitive responses in responding to flood emergencies. This study identified multiple health system constraints that resulted in poor district health systems’ capacity in delivering essential healthcare services during floods. This study, therefore, highlighted a need to improve district health systems’ capacity in effectively responding to healthcare service needs during floods.
Using household surveys for 2008 and 2011, a multidimensional destitution measure is constructed for Pakistan’s most populated province – Punjab. Using a non-monetary framework for dimensions of health, education and standard of living, the study paints a temporal picture of the extremely impoverished households in districts and towns, while highlighting the impact of the destructive 2010 floods. Results reveal the existence of pervasive destitution, with half of the multidimensionally poor households also identified as destitute. Destitution is higher for rural as compared to urban households, while the geography of destitution highlights its concentration in south-west Punjab, providing insights for targeted interventions.
Pakistan is vulnerable and most affected by adverse impacts of climate change. The study examines the impact of climate change on Pakistan during the year 2022, resulting into unprecedented heatwave and drought in summers followed by the abnormal rains and floods during monsoon season. Agriculture is the backbone of Pakistan’s economy, which has been devastated by both drought and floods. While the flood water is gradually receding, the stagnant contaminated water is causing several health risks for the inhabitants. This research argues that water security is the emerging national security challenge for Pakistan. The article investigates the status of water availability vis-a-vis the burgeoning population, agriculture, and other uses of water. Impact of abnormal melting of glaciers, nonavailability of dams for storage of rainwater, and lack of smart means for agriculture water have been examined to empirically validate the arguments.
Stunting is a significant public health problem in low- and middle-income countries. This study assessed the prevalence of stunting and associated risk factors of stunting among preschool and school-going children in flood-affected areas of Pakistan. A cross-sectional study was conducted by visiting 656 households through multi-stage sampling. Respondent’s anthropometric measurements, socio-demographic information and sanitation facilities were explored. A logistic regression model was used to determine determinants of stunting, controlling for all possible confounders. The overall prevalence of stunting in children was 40.5%, among children 36.1% boys and 46.3% of girls were stunted. The prevalence of stunting in under-five children was 50.7%. Female children (OR=1.35, 95% CI:0.94-2.0), children aged 13-24 months (OR=6.5, 95% CI: 3.0-13.9), mothers aged 15-24 years (OR=4.4, 95% CI: 2.6-7.2), joint family (OR=2.1, 95% CI: 1.4-3.0) did not have access to improved drinking water (OR=3.3, 95% CI: 1.9-5.9), and the toilet facility (OR=2.8, 95% CI, 1.9-4.3), while the children from district Nowshera (OR=1.7, 95% CI: 0.9-3.2) were significantly (P<0.05) associated in univariate analysis. The regression model revealed that child age, maternal age, family type, quality of water, and toilet facility, were the significant (P<0.05) factors contributing to child stunting in the flood-hit areas. Identification of key factors might be helpful for policymakers in designing comprehensive community-based programs for the reduction of stunting in flood-affected areas. In disasters such as flood, the detrimental consequences of the stunting problem could be even more on children. Evidence-based education and care must be provided to the families in the flood-affected regions to reduce the stunting problem. The determinants of stunting should be targeted by making comprehensive policies regarding proper nutrition, livelihood, clean water, and sanitation facilities in flood-hit regions.
There is minimal literature regarding micronutrient deficiencies in flood-affected regions. In our study, we aimed to find the prevalence of micronutrient deficiencies (vitamin A, calcium, zinc, iron, and iodine) among preschool and school-age children in flood-hit areas of Khyber Pakhtunkhwa, Pakistan. In this cross-sectional study, a multi-stage sampling technique was used for the selection of 656 households. Serum micronutrient status was detected in the targeted population in the affected districts. The least significant difference test was used with analysis of variance to determine significant differences in nutrient contents in different areas. Of the total respondents, 90.8% of the children were calcium deficient, 88.3% were zinc deficient, 26.7% were iron deficient, 53.5% were vitamin A deficient, and 39.5% were had an iodine deficiency in flood-affected areas. A significant difference (P < 0.05) was found in different age groups of children for zinc (5.7-42.63 μg/dL) and urinary iodine (69.6-85.4 μg/L). The 10- to 12-year-old age group had a lower serum zinc concentration (5.7 μg/dL), whereas the 1- to 3-year-old age group had a lower urinary iodine concentration (69.6 μg/L) than other groups. There was no significant difference (P > 0.05) between male and female children and various age groups for calcium and iron status. Vitamin A levels were significantly (P < 0.05) different among different age groups (high in age group 4-6 years) and districts. Vitamin A concentration was lower in the Nowshera District, whereas serum iron and zinc were lower in the Dera Ismail Khan District. All the important micronutrients in the population of children were deficient in the flood-affected areas of Pakistan. Therefore, policymakers should implement potential prevention strategies, such as food security, school health nutrition, food fortification, nutrition in the first 1,000 golden days, nutrition knowledge, and awareness of the local population, to reduce the burden of micronutrients deficiencies in flood-affected areas.
Low- and middle-income countries are usually at high risk of malnutrition. Not only that but the prevalence of malnutrition is much higher. It is important to evaluate the determinants of malnutrition in flood-affected areas of Pakistan. The present study examined the prevalence and risk factors of MUAC-based child malnutrition in flood-hit regions of Khyber Pakhtunkhwa, Pakistan. Multi-stage sampling was employed to select 656 households. Finally, 298 children of 6-59 months were selected. MUAC, an independent anthropometric parameter, was used to investigate the nutritional status of children. An automated logistic regression model was used to identify the risk factors of MUAC-based malnutrition. The prevalence of MUAC-based malnutrition was found 46%, including 40.5% females and 52.1% males. More than 90% of people had improved water quality and soap hand washing facility. Almost 17% of respondents had no toilet facility. Through automated logistic model, child age, maternal age, family size, income level, mother education, water quality, toilet facility were the significant determinants (P < .05) of MUAC-based undernutrition in flood affecting the area. The findings suggest that MUAC-based malnutrition can be minimized in flood-hit areas by targeting the listed risk factors. Community-based awareness programs regarding guidance on nutrition might be a key to reducing malnutrition in the target areas.
With accelerating climate change, US coastal communities are experiencing increased flood risk intensity, resulting from accelerated sea level rise and stronger storms. These conditions place pressure on municipalities and local residents to consider a range of new disaster risk reduction programs, climate resilience initiatives, and in some cases transformative adaptation strategies (e.g., managed retreat and relocation from highly vulnerable, low-elevation locations). Researchers have increasingly understood that these climate risks and adaptation actions have significant impacts on the quality of life, well-being, and mental health of urban coastal residents. We explore these relationships and define conditions under which adaptation practices will affect communities and residents. Specifically, we assess climate and environmental stressors, community change, and well-being by utilizing the growing climate change literature and the parallel social science literature on risk and hazards, environmental psychology, and urban geography work, heretofore not widely integrated into work on climate adaptation.
Every year Bangladesh faces enormous damages due to flooding. Facing these damages the Government adopts various recovery approaches. However, the psychological dimension of any disaster is generally overlooked in disaster management. Researchers have found that the spatial distribution of post-disaster mental health can help the authorities to apply recovery procedures where they are most needed. For this research, Posttraumatic Stress Checklist (PCL-5), Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to estimate posttraumatic stress, major depressive disorder and anxiety following three episodes of severe floods in 2017 that affected at least 8 million people. To better understand the spatial pattern of psychological vulnerability and reach a comprehensive scenario of post-disaster mental health, Moran’s I was applied for spatial autocorrelation and Pearson’s correlation and regression analysis for a study of the relationship between the psychological aspects. It was found that psychological vulnerability showed a spatial clustering pattern and that there was a strong positive linear relationship among psychological aspects in the study area. This research might help to adopt disaster management policies that consider the psychological dimension and spatial distribution of various psychological aspects to identify areas characterized by high vulnerability and risk so that they can be reached without delay.
BACKGROUND: Bangladeshi flood survivors are reported with such higher mental disorders that are not ever observed in any other cohorts. Although there are a few studies that assessed mental disorders, suicide or suicidal behaviors are not investigated yet. Hence, the present study for the first time investigated suicidal behaviors and its relationship with socio-demographics, flood effects and psychopathology. METHODS: A cross-sectional interview study was carried out between November and December 2019, after 4/5 months of the flood occurrence. Two completely affected villages from two districts residing in two parts of the country were randomly selected (whereas Manikganj district was less affected by the recent flood compared to Kurigram), and a total of 348 flood survivors were interviewed (45.53 ± 14.85 years). Questions related to basic socio-demographics, flood effects, psychological impacts, and suicidal behaviors were asked in the interviews. RESULTS: In the total sample, 57.5% of flood survivors reported having suicidal ideation, whereas 5.7% and 2.0% madea suicide plan and suicide attempt, respectively. Within two study sites, participants belonging to Kurigram reported significantly higher suicidal ideation compared to Manikganj (84.8% vs 33.2%, χ (2) = 94.475, p<0.001). Belonging to a lower-class family, having less education, and less earning members in the family, being affected severely by the flood, suffering from depression, anxiety, and PTSD, and experiencing financial threat, and economic hardship were suicidal behavior risk factors in the total sample. CONCLUSION: Considering the present findings (ie, suicidality commensurately increases with flood effects), a multi-sectoral policy and its effective implementation should be adopted for alleviating the flood-related psychological burdens.
BACKGROUND: Globally, post traumatic stress disorder (PTSD) is one of the most common psychiatric illnesses following a disaster. We aimed to evaluate the relationship between the socio-economic and flood exposure factors with PTSD, depression and anxiety among the flood-affected populations in Kerala, India. METHODS: A cross-sectional household survey was conducted from November 2019 to January 2020 in Kozhikode district of Kerala, India. Adults (≥ 18 years), who were permanent residents and had been directly exposed to the flood, were invited to take part in the study. Individuals with a history of mental health issues and those who had other stressful situations in the past were excluded. The survey questionnaire was based on three screening tools: (1) PTSD Checklist for DSM-5 (PCL-5); (2) patient health questionnaire (PHQ-9); and (3) generalized anxiety disorder (GAD-7). Data included sociodemographic factors and flood exposure variables. The primary outcome variable was psychiatric morbidity (PTSD, anxiety and depression). RESULTS: A total of 276 respondents (150 males/126 females) participated in the study. A significant correlation was observed between total score on PCL-5 and GAD-7 (r=0.339, p=0.001) and PHQ-9 (r=0.262, p=0.001). Females had significantly higher total PTSD symptom severity scores (8.24±5.88 vs. 6.07±5.22; p=0.001), severity of symptoms of intrusion (4.66±3.60 vs. 3.69±3.20; p=0.04), increased level of anxiety (2.54±1.94 vs. 1.79±1.53; p=0.001) and depression (3.02±2.26 vs. 2.04±1.67; p=0.001) compared to males. However, the gender difference for PTSD symptoms disappeared when controlling for age. CONCLUSION: The findings of this survey revealed that the vast majority of respondents (92 percent females and 87 percent males) still had subclinical psychiatric symptoms one year after the flood. Therefore, tailored psychological interventions are warranted to counter the long-lasting impact of flooding on the mental health of individuals.
INTRODUCTION: Disasters can have deep physical and psychological impact among survivors. An extraordinary southwest monsoon has unleashed floods and landslides in Kerala state in 2018. Adolescents are more vulnerable to psychological impairment after a disaster and trauma during initial stages of life can etch an indelible signature in the individual’s development and may lead to future disorders. OBJECTIVES: 1. To screen for PTSD and associated factors among adolescents 8 months post floods in selected schools in flood-affected areas of Alleppey district of Kerala 2. To compare the proportion of adolescents screened positive for PTSD in public and private schools. METHODOLOGY: A 3-month, Cross-sectional study was done among 670 adolescents in private and public schools using stratified sampling in Alleppey district. The study tool included a structured questionnaire that collected information on sociodemographics, flood-related variables, Trauma screening questionnaire and academic performance. RESULTS: The mean age of the participants was 16.03 ± 0.73 years with almost equal gender distribution. One-third of students reported flood-related damage to house/property, and a few lost their pets. Nearly 50% of the students reported that they still re-experience and get upsetting memories about flood events. The prevalence of probable PTSD noted to be 34.9%. We observed that 31% of students in public school screened positive for PTSD compared to 38.8% of private school students. (odds ratio = 1.409, CI 1.024-1.938). Male gender (Odds ratio = 1.503, CI 1.093-2.069), higher age (Odds ratio = 1.701, CI 1.120-2.585), damage during floods (Odds ratio = 2.566, CI 1.814-3.630), presence of morbidity (Odds ratio = 3.568, CI 1.888-6.743), camp stay (Odds ratio = 3.788, CI 2.364-6.067) and loss of pets (Odds ratio = 3.932, CI 2.019-7.657) were the factors significantly associated with PTSD. We noted a deterioration in academic performance in 45.9% of students who screened positive for PTSD. CONCLUSION AND RECOMMENDATIONS: High prevalence of stress disorder highlights the need for early identification and intervention for PTSD and including trained counsellors as a part of the disaster management team in future.
Rapid and unplanned urbanization has resulted in the settlement and expansion of marginalized communities in flood-prone areas. Consequently, the devastating impacts of urban flooding have increased recently, further augmented by the changing climatic patterns resulting in more frequent flooding. However, to effectively enhance resilience at the community level, it is essential first to understand its components and indicators. This study proposed and tested a methodology to assess community resilience against urban flooding – 57 indicators of resilience were identified, which were classified into six domains, namely social, economic, infrastructural, institutional, natural, and psychological. The data was collected through a questionnaire survey in three com-munities of Rawalpindi, Sialkot, and Muzaffargarh cities in the province of Punjab, Pakistan. The data of resilience indicators were standardized, and an index-based approach was used to assess the community resil-ience in the six domains. The relative importance of each domain was evaluated through input from field experts translated into weights through the analytic hierarchy process method. Thereafter, overall community resilience was constructed, and statistical methods were employed to compare resilience and its domains. A significant difference in resilience was observed among the selected communities. Recommendations based on relative urgency, complexity, and impact were devised to help institutions make informed decisions to improve com-munity resilience against floods.
In the Ganges-Brahmaputra-Meghna delta, covering most of Bangladesh, more than 165 million people live in low-lying coasts facing major extreme climatic events, such as cyclones. This article reviews the current scientific literature publications (2007-2020) in order to define vulnerability in the context of coastal Bangladesh facing cyclonic flooding. Based on this review, a new metric, called the socio-spatial vulnerability index (SSVI), is defined as function of both the probability of the cyclonic flood hazard and the sensitivity of delta inhabitants. The main result shows that the districts of Shariatpur, Chandpur and Barisal situated in the tidal floodplain of the Ganges-Brahmaputra-Meghna delta are in the fourth quartile, i.e., highest category, the most vulnerable areas. These districts are very densely populated (from 870 up to 1400 inhabitants per square kilometer) and exposed to inundation hazards with a large number of vulnerability factors. Finally, the delta’s mouth was identified as a very vulnerable area to cyclonic flooding as well.
Floods are a common natural hazard in Bangladesh, and climate change is expected to further increase flooding frequency, magnitude and extent. Pregnant women in flood contexts could face challenges in utilisation of maternal healthcare. The aim of this paper is to analyse associations between flood exposure and the use of maternal healthcare (antenatal care visits, birth assisted by skilled birth attendants, and giving birth in a health facility) in Bangladesh for pregnancies/births between 2004 and 2018. Bangladesh Demographic and Health Survey data from four surveys in the time period 2007-2018 and data on floods from the Emergency Events Database and the Geocoded Disasters Dataset are analysed using multilevel linear probability models. In line with previous results, we find clear bivariate associations between exposure to flooding and maternal healthcare use. These associations are largely confounded by socioeconomic and demographic variables. In general, exposure to flooding – whether measured as exposure to any floods or severe floods – does not affect maternal healthcare use, and we suggest that the lower usage of maternal healthcare in areas exposed to flooding rather relates to the characteristics of the flood-prone areas and their populations, which also relate to lower maternal healthcare use. However, we find negative associations in some supplementary analyses, which suggest that even if there is no effect of floods on average, specific floods may have negative effects on maternal healthcare use.
Purpose The quality and availability of sexual and reproductive health care are key determinants to reducing maternal mortalities and morbidities in disaster settings; yet, these services are often lacking in developing countries. Reducing maternal mortality and morbidity is currently the main targets of the UN’s Sustainable Development Goal (SDG) 3. The purpose of this study was to develop an intervention package called RHCC (Reproductive Health Kit 8; Capacity building; Community awareness), and to implement and evaluate it in three primary health-care (PHC) facilities in Belkuchi, Bangladesh, in order to improve the quality and availability of post-abortion care (PAC) during the 2017 floods. Design/methodology/approach This research used both quantitative and qualitative methods to develop, implement and assess the RHCC in three flood-prone PHC facilities in Belkuchi. Findings The RHCC was implemented during the floods of 2017. The findings pre- and post-intervention suggest it led to an increase in skilled management among health workers, an increase in the quality of care for clients and the availability of PAC at three PHC facilities during floods. Originality/value Due to its geographic location, Bangladesh is exposed to recurrent floods and cyclones. Evidence-based integrated intervention packages, such as the RHCC, can improve the quality and availability of reproductive health care during disasters at PHC level and, in doing so, can promote the UN’s agenda on “disaster resilient health system” to achieve the SDG 3, and the WHO’s campaign on universal health coverage.
OBJECTIVES: As climate change continues to increase the frequency and severity of flooding in Bangladesh and globally, it becomes increasingly critical to understand the pathways through which flooding influences health outcomes, particularly in lower-income and subsistence-based communities. We aim to assess economic pathways that link flooding to nutritional outcomes among Shodagor fishing families in Bangladesh. METHODS: We examine longitudinal economic data on kilograms of fish caught, the income earned from those fish, and household food expenditures (as a proxy for dietary intake) from before, during, and after severe flooding in August-September of 2017 to enumerate the impacts of flooding on Shodagor economics and nutrition. We also analyze seasonally collected anthropometric data to model the effects of flooding and household food expenditures on child growth rates and changes to adult body size. RESULTS: While Shodagor fishing income declined during the 2017 flooding, food expenditures simultaneously spiked with market inflation, and rice became the predominant expenditure only during and immediately following the flood. Our nutritional models show that children and adults lost more body mass in households that spent more money on rice during the flood. Shodagor children lost an average of 0.36 BMI-for-age z-scores and adults lost an average of 0.32 BMI units during the flooded 2017 rainy season, and these metrics continued to decline across subsequent seasons and did not recover by the end of the study period in 2019. CONCLUSIONS: These results show major flood-induced economic impacts that contributed to loss of child and adult body mass among Shodagor fishing families in Bangladesh. More frequent and severe flooding will exacerbate these nutritional insults, and more work is needed to effectively stabilize household nutrition throughout natural disasters and economic hardship.
We study the educational outcomes of the 1974-75 Bangladesh famine among early life survivors using the 1991 Bangladesh micro-census data. We find that famine adversely affected survivor children in areas that experienced higher rice prices relative to labour wages. However, children living in wealthy households in famine-stricken areas escaped the adverse effects and had similar educational outcomes as those with no famine exposure. We also find that, surprisingly, exposure to a double catastrophe (i.e., concurrent famine and flood) in early life had weaker effects on survivor children’s education than exposure to a single catastrophe. We show that disaster-alleviation mechanisms were more effective in districts affected by double disasters.
The Tista floodplain is one of the major food baskets of North Bengal and is sensitive to a multitude of issues regarding vulnerability. The riparian areas and the river island or charland of the lower Tista River basin in India, specifically from Sevoke to the Indo-Bangladesh border, generally suffer due to flood-prone, river course shifting, limited livelihood activities, low adaptive capacity, and poor accessibility. The present work is conducted to assess the livelihood vulnerability based on the livelihood vulnerability index (LVI) framework of the agriculture-dependent riparian villages and the charlands of the River Tista in the Jalpaiguri district. Total 337 households of five villages from the Mal and Maynaguri block at the left bank of the Tista River were selected to conduct the field survey. The livelihood vulnerability was assessed based on eight major components (viz., socio-demographic profile, health condition, livelihood strategies, food support, water support, climatic variability, flood hazards, and social safety) and 42 sub-components. The three contributing factors, i.e., adaptive capacity, sensitivity, and exposure, have been combined to calculate the livelihood vulnerability employing the LVI and LVI-IPCC methodologies. The outcome of the study exhibit that LVI scored highest in Premganj Majhiali (0.436), followed by Basusuba (0.403), Uttar Marichbari (0.349), Domohani (0.335), and Chat Rarpur village (0.328). According to the LVI-IPCC results, Basusuba has the most vulnerability (0.015), whereas Domohani has the least (0.007). In terms of flood hazard, variations were noticed based on increasing distance from the river. Lack of adaptive capacity prevailed in the villages with significant flooding events. Building awareness of the inhabitants will be an effective way to improve the adaptive capacity of the rural villagers. Therefore, giving priority to the policies depending on the natural environment of the active flood-prone region would make long-term sustainability.
We examine the impact of flooding in Pakistan on child health using satellite data and two household datasets. Flooding may influence child health, as measured by weight-for-height z-score, through two key channels. First, excessive flood waters can catalyze the spread of diarrheal disease, negatively impacting child health. Second, excessive flood waters – even when damaging in some areas – provide water to rice paddies and other agriculture, increasing food availability in the post-flood period. This may positively influence child health. In Pakistan, we find evidence of both channels: floods increase incidence of morbidity (diarrhea and fever) as well as meal frequency in the post flood season. We also find that floods increase dietary diversity, but only in districts with high rice harvesting intensity where flooding may predict favorable growing conditions. Because these mechanisms (disease incidence and dietary adequacy) act against one another, we find weak overall impact of floods on child health. (c) 2021 Elsevier Ltd. All rights reserved.
BACKGROUND: Chengannur, a town in the south Indian state of Kerala, was 1 of the worst affected towns during the floods of 2018. Post-flood, Kerala state was under the threat of many infectious diseases including leptospirosis, but did not report any leptospirosis infections. OBJECTIVES: This study was conducted with the following objectives: (1) Assess the knowledge, attitude and practices regarding the prevention of leptospirosis among the flood affected population and Accredited Social Health Activists (ASHAs) of Chengannur; and (2) Analyze the factors responsible for and contributing to leptospirosis control in the area post flood. METHODOLOGY: A cross-sectional questionnaire based observational study was conducted among 2 groups: the flood affected population, and ASHA. The questionnaire was divided into 3 parts. Part A contained the socio-demographic information. Part B contained questions on assessment of knowledge, attitude, and practices regarding the prevention, and control of leptospirosis. Part C was only for the ASHA involved. RESULTS: The final sample size was 331 (244 from the general population and 87 ASHAs). With respect to knowledge, attitude, and practice, the responses were dichotomized into correct and wrong responses. The mean knowledge score was 9.01 ± 1.08 (maximum score of 10), mean attitude score was of 3.61 ± 0.55 (maximum score of 4) and the mean practice score was 4.12 ± 1.05 (maximum score of 5). CONCLUSION: Knowledge and attitude scores did not significantly differ between the general population and ASHA, but the practice score showed a higher score among the ASHA, all of which could have probably contributed to the prevention of a leptospirosis outbreak in the region.
Neonates and children are more vulnerable to the negative impact of flood-related changes and may have a variety of detrimental negative impacts on their health. They are more prone to get various infectious diseases. They are also more vulnerable to malnutrition during floods. Flooding limits access to clean water as sewage overflows and contaminates nearby water sources. The polluted setting in the flood-affected area makes it difficult to ensure the hygiene of feeding equipment used to prepare infant formula. Breastfeeding may also become less effective due to the lack of privacy for women to breastfeed their kids while living in temporary shelters with other flood victims. In addition, milk production decreases and might even cease due to mothers’ reduced food intake and increased stress levels. Flooding may also cause supplemental feeding to deteriorate. The mothers and other primary caregivers usually lack the resources in affected areas to prepare supplemental diets for their kids, which further harm the babies. There is mounting evidence that children are more likely to develop clogged noses, itchy eyes, hoarseness, skin complications, and sneezing while living in humid areas.
The recent monsoon rains in Pakistan were unprecedented and caused flooding all over Pakistan, especially in Sindh and Balochistan. Following this national disaster, various water-borne and contagious diseases started erupting all over the country. In such a calamity-struck city of Jacobabad, we started receiving cases with a peculiar set of ocular complaints mimicking viral keratoconjunctivitis. Failure to respond to traditional treatment and the unique appearance of these corneal opacities led to a rare diagnosis of Microsporidial Keratoconjunctivitis, which was later confirmed by microscopy and staining of corneal scrapings of the most affected case. In line with published literature, all cases were treated with topical fluoroquinolone and topical anti-fungal therapy, following which the disease was cleared within a week. The disease has seen an upward trend the world over, especially among Asia. To the best of our knowledge, no such cases have been reported in Pakistan as yet. In this case series, we highlight the strong correlation of emergence of microsporidial keratitis in patients following exposure to pooled water bodies after the monsoon rainy season and floods. Moreover, this report will help create awareness in eye professionals regarding the prevention, timely diagnosis and treatment of these rare and emerging cases. Key Words: Keratitis, Spores, Water-borne diseases, Microsporidia.
BACKGROUND: Current literatures seem devoted only on relating climate change with malaria. Overarching all possible environmental determinants of malaria prevalence addressed by scanty literature in Nepal is found apposite research at this moment. This study aims to explore the environmental determinants of malaria prevalence in western Nepal. METHODS: Cross-sectional data collected from community people were used to identify the environmental determinants of malaria prevalence in western Nepal. Probit and logistic regressions are used for identifying determinants. RESULTS: The results reveal that environmental variables: winter temperature (aOR: 2.14 [95% CI: 1.00-4.56]), flooding (aOR: 2.45 [CI: 1.28-4.69]), heat waves (aOR: 3.14 [CI: 1.16-8.46]) and decreasing river water level (aOR: 0.25 [CI: 0.13-0.47]) are found major factors to influence malaria prevalence in western Nepal. Besides, pipeline drinking water (aOR: 0.37 [0.17-0.81]), transportation facility (aOR: 1.18 [1.07-1.32]) and awareness programs (aOR: 2.62 [0.03-6.65]) are exigent social issues to influence malaria prevalence in Nepal. To be protected from disease induced by environmental problems, households have used extra season specific clothes, iron nets and mosquito nets, use of insecticide in cleaning toilet and so on. CONCLUSIONS: Adaptation mechanism against these environmental issues together with promoting pipeline drinking water, transportation facility and awareness programs are the important in malaria control in Nepal. Government initiation with incentivized adaptation mechanism for the protection of environment with caring household attributes possibly help control malaria in western Nepal.
Climate change threatens global sustainability, especially in rural communities of developing countries. In Pakistan, severe impacts of climate change have become evident in the recent past. Large-scale floods in the Indus river system have caused massive damages in the past decade. Also, frequent droughts and heatwaves are among other consequences of the changing climate in the country. Understanding the perspective of local communities regarding climate change adaptation strategies is pivotal to effective policymaking. We surveyed the rural community in the Indus Basin, in southern Punjab, Pakistan, to assess the climate change adaptations currently practiced. We found that the respondents perceive droughts, floods, and disease outbreaks (which are frequently followed by flooding events) as major climate change-induced threats. The respondents used flood and drought-resistant crop varieties, field boundaries (spate irrigation), migration to safe places, and loans as key adaptation strategies. We also assessed the socioeconomic determinants of climate change adaptation behaviour using a binary logistic regression model. Gender, occupation, and education influenced the adaptations to climate change. The present study highlights the need for monetary support to flood-prone communities, better medical facilities, provision of drought and flood-resistant crop varieties, and awareness campaigns to enhance adaptive capacity in the study area.
The Uttarakhand State, known for its Himalayan Mountains, is a territory in Northern India that is extremely vulnerable to earthquakes, landslides, and floods. Currently, due to the COVID-19 outbreak, India is facing the dual challenge of containing a pandemic and responding to natural disasters. This situation can have a negative impact on the health and the economic development of the region, leading to a long-lasting humanitarian crisis that can disrupt even more, the already overburdened health service. In addition, it can pose serious threats to the wellbeing of the population as it complicates physical distancing and other COVID-19 prevention measures. It is of utmost importance to analyse the impact of floods, landslides, and COVID-19 pandemic on the health system of the Uttarakhand State, and how these crises interact with each other.
To support Indigenous communities in preparing for uncertainties such as climate change impacts and unexpected threats to health, there are calls by researchers and community members for decision support tools that meaningfully and sensitively bring together Indigenous contextualized factors such as social dynamics, local- and culture-specific knowledge, and data with academic tools and practices including predictive modeling. This project used a community engaged approach to co-create an agent-based model geographically bounded to a reserve community to examine three community-requested simulations. Community members and researchers co-designed, built, and verified the model simulations: a contaminated water delivery truck; a Pow Wow where a waterborne infectious disease spreads; and a flood which restricts typical movement around the reserve for daily tasks and health care. The simulations’ findings, displayed as both conventional and narrative outputs, revealed management areas where community adaptation and mitigation are needed, including enhancing health service provision in times of disease outbreaks or large community events, and creating back-up plans for overcoming flood impacts to ensure services are accessible for vulnerable members of the community. Recommendations for communities, researchers, and modelers are discussed.
BACKGROUND: Fort McMurray, a city in northern Alberta, Canada, has experienced multiple traumatic events in the last five years, including the 2016 wildfire, the 2020 floods, and the COVID-19 pandemic. Traumatic events often lead to increased mental health burdens in affected communities. OBJECTIVE: To assess if the number of traumatic events experienced by residents of Fort McMurray correlates with the prevalence and severity of mental health issues experienced. METHODOLOGY: A cross-sectional study using an online survey questionnaire was used to gather demographic, trauma (wildfire, flooding, and COVID-19), and clinical information from the resident of Fort McMurray between April 24 to June 2 2021. Likely Generalized Anxiety Disorder (GAD), Major Depressive Disorder (MDD), Post-Traumatic Stress Disorder (PTSD) and low resilience were measured using standardised rating scales. Data were analyzed with SPSS version 26 using Chi-Square tests and multivariate regression analysis. RESULTS: Respondents who experienced COVID-19 and either flood or wildfire traumas (N = 101) were eleven times more likely to have GAD symptoms (OR: 11.39; 95% CI: 1.43-91.04), four times more likely to have likely MDD, (OR: 3.85; 95% CI: .995-14.90), ten times more likely to have likely PTSD (OR: 10.47; 95% CI: 1.28-85.67), and low resilience (OR: 10.56; 95% CI: 1.21-92.17). Respondents who experienced COVID-19, flooding, and wildfire traumas (N = 47) were eighteen times more likely to express GAD symptoms (OR: 18.30; 95% CI: 2.20-152.45) and more than eleven times likely to have likely PTSD (OR: 11.41; 95% CI: 1.34-97.37) in comparison to the respondents who experienced COVID-19 only trauma (N = 19). CONCLUSION: Measures to reduce climate change and associated natural disasters could reduce the impact of cumulative trauma and associated mental health burden in vulnerable populations. It is essential that more mental health resources are mobilised to support communities impacted by multiple natural disasters. HIGHLIGHTS: The number of traumatic disasters experienced in residents of Fort McMurray five years after the 2016 wildfires, a year after the 2020 flooding, and during the COVID-19 pandemic correlates with the prevalence and severity of the mental health conditions reported in this study.
BACKGROUND: Fort McMurray, a city in northern Alberta, Canada, has experienced multiple traumas in the last five years, including the 2016 wildfire, the 2020 floods, and the COVID-19 pandemic. Eighteen months after the wildfire, major depressive disorder (MDD), generalized anxiety disorder (GAD), and Post Traumatic Stress Disorder (PTSD) symptoms were elevated among school board employees in the city. OBJECTIVE: This study aimed to compare employees of the school board and other employees of Fort McMurray in respect to the impact the 2016 wildfires, the 2019 COVID pandemic, and the 2020 floods had on their mental health. METHODOLOGY: A quantitative cross-sectional survey was conducted in Fort McMurray from 24 April to 2 June 2021. Online questionnaires were administered through REDCap and were designed to capture socio-demographic characteristics, clinical as well as wildfire, COVID-19, and flooding-related variables. Mental health outcome variables were captured using self-reported standardized assessment scales. Data were analysed with descriptive statistics, Chi-square/Fisher’s Exact tests, and binary regression analysis. RESULTS: Of the 249 residents who accessed the online survey, 186 completed the survey, giving a response rate of 74.7%. Of these respondents, 93.5% (174) indicated their employment status and were included in the Chi-square analysis. Most of the respondents were female (86.2%, (150)), above 40 years (53.4%, (93)), and were in a relationship (71.3%, (124)). The prevalence values for MDD, GAD and PTSD among respondents were 42.4%, 41.0, and 36.8%, respectively. There was a statistically significant difference between employees of the school board and other employees with respect to likely PTSD prevalence (28% vs. 45%, respectively, p < 0.05), although with other factors controlled for, in a binary logistic regression model, employer type did not significantly predict likely PTSD. CONCLUSIONS: The study has established that likely PTSD symptoms were significantly higher in other employees compared to those of school board employees. Greater exposure to the traumatic events and a greater perceived lack of support from other employers might have contributed to the significantly higher prevalence of PTSD in other employees.
Hurricane Harvey was associated with flood-related damage to chemical plants and oil refineries, and the flooding of hazardous waste sites, including 13 Superfund sites. As clean-up efforts began, concerns were raised regarding the human health impact of possible increased chemical exposure resulting from the hurricane and subsequent flooding. Personal sampling devices in the form of silicone wristbands were deployed to a longitudinal panel of individuals (n = 99) within 45 days of the hurricane and again one year later in the Houston metropolitan area. Using gas chromatography−mass spectroscopy, each wristband was screened for 1500 chemicals and analyzed for 63 polycyclic aromatic hydrocarbons (PAHs). Chemical exposure levels found on the wristbands were generally higher post-Hurricane Harvey. In the 1500 screen, 188 chemicals were detected, 29 were detected in at least 30% of the study population, and of those, 79% (n = 23) were found in significantly higher concentrations (p < 0.05) post-Hurricane Harvey. Similarly, in PAH analysis, 51 chemicals were detected, 31 were detected in at least 30% of the study population, and 39% (n = 12) were found at statistically higher concentrations (p < 0.05) post-Hurricane Harvey. This study indicates that there were increased levels of chemical exposure after Hurricane Harvey in the Houston metropolitan area.
Disparities exist in post-disaster flooding exposure and vulnerable populations bear a disproportionate impact of this exposure. We describe the unequal burden of flooding in a cohort of New York residents following Hurricane Sandy and assess whether the likelihood of flooding was distributed equally according to socioeconomic demographics, and whether this likelihood differed when analyzing self-reported or FEMA flood exposure measures. Residents of New York City and Long Island completed a self-administered survey 1.5-4.0 years after the storm. Multivariable logistic regressions were performed to determine the relationship between sociodemographic characteristics and flood exposure. Participants (n = 1231) residing in areas of the lowest two quartiles of median household income experienced flooding the most often (FEMA/self-reported: <$40,298: 65.3%/42.0%, $40,298-$67,188: 43.3%/32.1%), and these areas contained the highest proportions of non-White participants (<$40,298: 39.1%, $40,298-$67,188: 36.6%) and those with ≤high school education (<$40,298: 35.5%, $40,298-$67,188: 33.6%). Both self-report (p < 0.05) and FEMA (p < 0.05) flood measures indicated that older participants were more likely to live in a household exposed to flooding, while those living in higher-income areas had decreased likelihood of flooding (p < 0.0001). Socioeconomic and age disparities were present in exposure to flooding during Hurricane Sandy. Future disaster preparedness responses must understand flooding from an environmental justice perspective to create effective strategies that minimize disproportionate exposure and its adverse outcomes.
OBJECTIVES: To assess the economic and mental health impacts of COVID-19 in the presence of previous exposure to flooding events. METHODS: Starting in April 2018, the Texas Flood Registry (TFR) invited residents to complete an online survey regarding their experiences with Hurricane Harvey and subsequent flooding events. Starting in April 2020, participants nationwide were invited to complete a brief online survey on their experiences during the pandemic. This study includes participants in the TFR (N = 20,754) and the COVID-19 Registry (N = 8568) through October 2020 (joint N = 2929). Logistic regression and generalized estimating equations were used to examine the relationship between exposure to flooding events and the economic and mental health impacts of COVID-19. RESULTS: Among COVID-19 registrants, 21% experienced moderate to severe anxiety during the pandemic, and 7% and 12% of households had difficulty paying rent and bills, respectively. Approximately 17% of Black and 15% of Hispanic households had difficulty paying rent, compared to 5% of non-Hispanic white households. The odds of COVID-19 income loss are 1.20 (1.02, 1.40) times higher for those who previously had storm-related home damage compared to those who did not and 3.84 (3.25-4.55) times higher for those who experienced Harvey income loss compared to those who did not. For registrants for whom Harvey was a severe impact event, the odds of having more severe anxiety during the pandemic are 5.14 (4.02, 6.58) times higher than among registrants for whom Harvey was a no meaningful impact event. CONCLUSIONS: Multiple crises can jointly and cumulatively shape health and wellbeing outcomes. This knowledge can help craft emergency preparation and intervention programs.
Flood risk assessment requires a quantitative understanding of hazards and vulnerability. In the coastal built environment, the human’s vulnerability to combined hazards due to the floodwater and winds is an integral component of flood risks. The present study aims to reveal the human vulnerability to storm-induced coastal flooding, focusing on New York City during Hurricane Sandy. We develop a physics-based model to quantify individuals’ physical vulnerability, both adults and children, to compound hazards of floodwater and winds. The model accounts for the failure of individuals caused by physical instability due to slipping and toppling. The governing equations consider the balance between the driving and resisting forces and moments applied to an individual concurrently exposed to floodwater and winds. We first calibrate the model using existing measurements in the literature and then implement it to study the vulnerability of New York residents in Manhattan to coastal flooding during Hurricane Sandy. Model results indicate that when combined floodwater and wind hazards were at their highest-level during Sandy, the majority of flooded areas were mainly a hazardous zone for adults and either a failure or drowning zone for children. About 5.4% and 47.4% of the total flooded area became a failure zone, and 19.9% and 42.4% became a drowning zone for adults and children, respectively. We conclude that winds can have a significant impact on the physical instability of individuals. For example, model results for children show that neglecting winds results in a reduction of 97.7% in the area of the failure zone.
Coastal and riverine communities in the United States are largely unprepared for the projected effects of the climate crisis, including more intense storm surges, sea level rise, and increased precipitation. Flooding poses its own hazards, but in recent years, chemical releases triggered by extreme weather, such as hurricanes, have become more frequent, exposing nearby communities to toxic chemicals in the midst of natural disaster. This article reviews the public health implications of chemical releases triggered by extreme weather and provides commentary on possible policy solutions. The Gulf Coast, where there is an abundance of chemical facilities, is particularly vulnerable to these events, one of the latest examples being the August 2020 BioLab chlorine factory fire in Lake Charles, Louisiana, during Hurricane Laura. Low-wealth, Black, and Hispanic communities are disproportionately located near high-risk chemical facilities. The cumulative burden of flooding, toxic chemical releases, and other social stressors borne of systemic racism harms these communities, highlighting a critical environmental injustice. The federal and state governments have failed to develop regulatory safeguards that would prevent chemical releases triggered by extreme storms. State regulators should make facility reporting data available to the public and establish a regulatory regime for aboveground storage tanks. State regulators should also complete an analysis of flood risks to high-risk chemical facilities and impacts on historically disenfranchised communities, require permitted facilities to implement climate-responsive spill preventions practices, and establish a task force that can investigate strategies to prevent climate-driven chemical disaster and engage key stakeholders.
Natural disasters such as floods and hurricanes impact urbanized estuarine environments. Some impacts pose potential environmental and public health risks because of legacy or emerging chemical contamination. However, characterizing the baseline spatial and temporal distribution of environmental chemical contamination before disasters remains a challenge. To address this gap, we propose using systematic evidence mapping (SEM) in order to comprehensively integrate available data from diverse sources. We demonstrate this approach is useful for tracking and clarifying legacy chemical contamination reporting in an urban estuary system. We conducted a systematic search of peer-reviewed articles, government monitoring data, and grey literature. Inclusion/exclusion criteria are used as defined by a Condition, Context, Population (CoCoPop) statement for literature from 1990 to 2019. Most of the peer-reviewed articles reported dioxins/furans or mercury within the Houston Ship Channel (HSC); there was limited reporting of other organics and metals. In contrast, monitoring data from two agencies included 89-280 individual chemicals on a near-annual basis. Regionally, peer-reviewed articles tended to record metals in Lower Galveston Bay (GB) but organics in the HSC, while the agency databases spanned a wider spatial range in GB/HSC. This SEM has shown that chemical data from peer-reviewed and grey literature articles are sparse and inconsistent. Even with inclusion of government monitoring data, full spatial and temporal distributions of baseline levels of legacy chemicals are difficult to determine. There is thus a need to expand the chemical, spatial, and temporal coverage of sampling and environmental data reporting in GB/HSC.
OBJECTIVES: Extensive floodwater damage following hurricane Harvey raised concerns of increase in invasive mould infections (IMIs), especially in immunocompromised patients. To more comprehensively characterize the IMI landscape pre- and post-Harvey, we used a modified, less restrictive clinical IMI (mcIMI) definition by incorporating therapeutic-intent antifungal drug prescriptions combined with an expanded list of host and clinical features. METHODS: We reviewed 103 patients at MD Anderson Cancer Center (Houston, Texas), who lived in Harvey-affected counties and had mould-positive cultures within 12 months pre-/post-Harvey (36 and 67 patients, respectively). Cases were classified as proven or probable IMI (EORTC/MSG criteria), mcIMI, or colonization/contamination. We also compared in-hospital mortality and 42- day survival outcomes of patients with mcIMI pre-/post-Harvey. RESULTS: The number of patients with mould- positive cultures from Harvey-affected counties almost doubled from 36 pre- Harvey to 67 post- Harvey (p < 0.01). In contrast, no significant changes in (mc)IMI incidence post-Harvey nor changes in the aetiological mould genera were noted. However, patients with mcIMIs from flood affected areas had significantly higher in-hospital mortality (p = 0.01). CONCLUSIONS: We observed increased colonization but no excess cases of (mc)IMIs in immunosuppressed cancer patients from affected areas following a large flooding event such as hurricane Harvey.
OBJECTIVES: When Hurricane Harvey struck the coastline of Texas in 2017, it caused 88 fatalities and over US $125 billion in damage, along with increased emergency department visits in Houston and in cities receiving hurricane evacuees, such as the Dallas-Fort Worth metroplex (DFW).This study explored demographic indicators of vulnerability for patients from the Hurricane Harvey impact area who sought medical care in Houston and in DFW. The objectives were to characterize the vulnerability of affected populations presenting locally, as well as those presenting away from home, and to determine whether more vulnerable communities were more likely to seek medical care locally or elsewhere. METHODS: We used syndromic surveillance data alongside the Centers for Disease Control and Prevention Social Vulnerability Index to calculate the percentage of patients seeking care locally by zip code tabulation area. We used this variable to fit a spatial lag regression model, controlling for population density and flood extent. RESULTS: Communities with more patients presenting for medical care locally were significantly clustered and tended to have greater socioeconomic vulnerability, lower household composition vulnerability, and more extensive flooding. CONCLUSIONS: These findings suggest that populations remaining in place during a natural disaster event may have needs related to income, education, and employment, while evacuees may have more needs related to age, disability, and single-parent household status.
INTRODUCTION: Natural disasters are increasingly common and devastating. It is essential to understand children’s health needs during disasters as they are a particularly vulnerable population. The objective of this study was to evaluate pediatric disease burden after Hurricane Harvey compared to the preceding month and the same period in the previous year to inform pediatric disaster preparedness. METHODS: This was a retrospective cross-sectional study of patients seen at pediatric emergency departments (ED) and urgent care centers (UCC) 30 days before (late summer) and after (early fall) the hurricane and from the same time period in 2016. We collected demographic information and the first five discharge diagnoses from a network of EDs and UCCs affiliated with a quaternary care children’s hospital in Houston, Texas. We calculated the odds of disease outcomes during various timeframes using binary logistic regression modeling. RESULTS: There were 20,571 (median age: 3.5 years, 48.1% female) and 18,943 (median age: 3.5 years, 47.3% female) patients in 2016 and 2017, respectively. Inpatient admission rates from the ED a month after Harvey were 20.5%, compared to 25.3% in the same period in 2016 (P<0.001). In both years, asthma and other respiratory illnesses increased from late summer to early fall. After controlling for these seasonal trends, the following diseases were more commonly seen after the hurricane: toxicological emergencies (adjusted odds ratio [aOR]: 2.61, 95% [confidence interval] CI, 1.35-5.05); trauma (aOR: 1.42, 95% CI, 1.32-1.53); and dermatological complaints (aOR: 1.34, 95% CI, 1.23-1.46). CONCLUSION: We observed increases in rashes, trauma, and toxicological diagnoses in children after a major flood. These findings highlight the need for more medication resources and public health and education measures focused on pediatric disaster preparedness and management.
BACKGROUND: Flooding following heavy rains precipitated by hurricanes has been shown to impact the health of people. Earth observations can be used to identify inundation extents for subsequent analysis of health risks associated with flooding at a fine spatio-temporal scale. OBJECTIVE: To evaluate emergency department (ED) visits before, during, and following flooding caused by Hurricane Harvey in 2017 in Texas. METHODS: A controlled before and after design was employed using 2016-2018 ED visits from flooded and non-flooded census tracts. ED visits between landfall of the hurricane and receding of flood waters were considered within the flood period and post-flood periods extending up to 4 months were also evaluated. Modified Poisson regression models were used to estimate adjusted rate ratios for total and cause specific ED visits. RESULTS: Flooding was associated with increased ED visits for carbon monoxide poisoning, insect bite, dehydration, hypothermia, intestinal infectious diseases, and pregnancy complications. During the month following the flood period, the risk for pregnancy complications and insect bite was still elevated in the flooded tracts. SIGNIFICANCE: Earth observations coupled with ED visits increase our understanding of the short-term health risks during and following flooding, which can be used to inform preparedness measures to mitigate adverse health outcomes and identify localities with increased health risks during and following flooding events.
BACKGROUND: Hurricane Florence made landfall in North Carolina in September 2018 causing extensive flooding. Several potential point sources of hazardous substances and Superfund sites sustained water damage and contaminants may have been released into the environment. OBJECTIVE: This study conducted temporal analysis of contaminant distribution and potential human health risks from Hurricane Florence-associated flooding. METHODS: Soil samples were collected from 12 sites across four counties in North Carolina in September 2018, January and May 2019. Chemical analyses were performed for organics by gas chromatography-mass spectrometry. Metals were analyzed using inductively coupled plasma mass spectrometry. Hazard index and cancer risk were calculated using EPA Regional Screening Level Soil Screening Levels for residential soils. RESULTS: PAH and metals detected downstream from the coal ash storage pond that leaked were detected and were indicative of a pyrogenic source of contamination. PAH at these sites were of human health concern because cancer risk values exceeded 1 × 10(-6) threshold. Other contaminants measured across sampling sites, or corresponding hazard index and cancer risk, did not exhibit spatial or temporal differences or were of concern. SIGNIFICANCE: This work shows the importance of rapid exposure assessment following natural disasters. It also establishes baseline levels of contaminants for future comparisons.
IMPORTANCE: Hurricanes and flooding can interrupt health care utilization. Understanding the magnitude and duration of interruptions, as well as how they vary according to hazard exposure, race, and income, are important for identifying populations in need of greater retention in care. OBJECTIVE: To determine how the differential exposure to Hurricane Harvey in August 2017 is associated with changes in utilization of Veterans Health Administration health care. DESIGN, SETTING, AND PARTICIPANTS: This is a retrospective cohort analysis of primary care practitioner (PCP) visits, emergency department visits, and inpatient admissions in the Veterans Health Administration among Texas veterans residing in counties impacted by Hurricane Harvey from 2016 to 2018. Data analysis was performed from September 2020 to May 2021. EXPOSURES: Residential flooding after Hurricane Harvey. MAIN OUTCOMES AND MEASURES: Interrupted time series analysis measured changes in health care utilization over time, stratified by residential flood exposure, race, and income. RESULTS: Of the 99858 patients in the cohort, 89931 (90.06%) were male, and their median (range) age was 58 (21 to 102) years. Compared with veterans in nonflooded areas, veterans living in flooded areas were more likely to be Black (24?ǻ715 veterans [33.80%] vs 4237 veterans [15.85%]) and low-income (14895 veterans [20.37%] vs 4853 veterans [18.15%]). Rates of PCP visits decreased by 49.78% (95% CI, -64.52% to -35.15%) for veterans in flooded areas and by 45.89% (95% CI, -61.93% to -29.91%) for veterans in nonflooded areas and did not rebound until more than 8 weeks after the hurricane. Rates of PCP visits in flooded areas remained lower than expected for 11 weeks among White veterans (-6.99%; 95% CI, -14.36% to 0.81%) and for 13 weeks among racial minority veterans (-7.22%; 95% CI, -14.11% to 0.30%). Low-income veterans, regardless of flood status, experienced greater suppression of PCP visits in the 8 weeks following the hurricane (-13.72%; 95% CI, -20.51% to -6.68%) compared with their wealthier counterparts (-9.63%; 95% CI, -16.74% to -2.26%). CONCLUSIONS AND RELEVANCE: These findings suggest that flood disasters such as Hurricane Harvey may be associated with declines in health care utilization that differ according to flood status, race, and income strata. Patients most exposed to the disaster also had the greatest delay or nonreceipt of care.
In August 2017, after Hurricane Harvey made landfall, almost 52 inches of rain fell during a three-day period along the Gulf Coast Region of Texas, including Harris County, where Houston is located. Harris County was heavily impacted with over 177,000 homes and buildings (approximately 12 percent of all buildings in the county) experiencing flooding. The objective of this study was to measure 13 heavy metals in soil in residential areas and to assess cancer and non-cancer risk for children and adults after floodwaters receded. Between September and November 2017, we collected 174 surface soil samples in 10 communities, which were classified as “High Environmental Impact” or “Low Environmental Impact” communities, based on a composite metric of six environmental parameters. A second campaign was conducted between May 2019 and July 2019 when additional 204 soil samples were collected. Concentrations of metals at both sampling campaigns were higher in High Environmental Impact communities than in Low Environmental Impact communities and there was little change in metal levels between the two sampling periods. The Pollution Indices of lead (Pb), zinc, copper, nickel, and manganese in High Environmental Impact communities were significantly higher than those in Low Environmental Impact communities. Further, cancer risk estimates in three communities for arsenic through soil ingestion were greater than 1 in 1,000,000. Although average soil Pb was lower than the benchmark of the United States Environmental Protection Agency, the hazard indices for non-cancer outcomes in three communities, mostly attributed to Pb, were greater than 1. Health risk estimates for children living in these communities were greater than those for adults.
BACKGROUND: Social inequities affecting minority populations after Hurricane Katrina led to an expansion of environmental justice literature. In August 2017, Hurricane Harvey rainfall was estimated as a 3000- to 20,000-year flood event, further affecting minority populations with disproportionate stroke prevalence. The Stomp Out Stroke initiative leveraged multimedia engagement, creating a patient-centered cerebrovascular health intervention. OBJECTIVE: This study aims to address social inequities in cerebrovascular health through the identification of race- or ethnicity-specific health needs and the provision of in-person stroke prevention screening during two community events (May 2018 and May 2019). METHODS: Stomp Out Stroke recruitment took place through internet-based channels (websites and social networking). Exclusively through web registration, Stomp Out Stroke participants (aged >18 years) detailed sociodemographic characteristics, family history of stroke, and stroke survivorship. Participant health interests were compared by race or ethnicity using Kruskal-Wallis or chi-square test at an α=.05. A Bonferroni-corrected P value of .0083 was used for multiple comparisons. RESULTS: Stomp Out Stroke registrants (N=1401) were 70% (973/1390) female (median age 45 years) and largely self-identified as members of minority groups: 32.05% (449/1401) Hispanic, 25.62% (359/1401) African American, 13.63% (191/1401) Asian compared with 23.63% (331/1401) non-Hispanic White. Stroke survivors comprised 11.55% (155/1401) of our population. A total of 124 stroke caregivers participated. Approximately 36.81% (493/1339) of participants had a family history of stroke. African American participants were most likely to have Medicare or Medicaid insurance (84/341, 24.6%), whereas Hispanic participants were most likely to be uninsured (127/435, 29.2%). Hispanic participants were more likely than non-Hispanic White participants to obtain health screenings (282/449, 62.8% vs 175/331, 52.9%; P=.03). Asian (105/191, 54.9%) and African American (201/359, 55.9%) participants were more likely to request stroke education than non-Hispanic White (138/331, 41.6%) or Hispanic participants (193/449, 42.9%). African American participants were more likely to seek overall health education than non-Hispanic White participants (166/359, 46.2% vs 108/331, 32.6%; P=.002). Non-Hispanic White participants (48/331, 14.5%) were less likely to speak to health care providers than African American (91/359, 25.3%) or Asian participants (54/191, 28.3%). During the 2018 and 2019 events, 2774 health screenings were completed across 12 hours, averaging four health screenings per minute. These included blood pressure (1031/2774, 37.16%), stroke risk assessment (496/2774, 17.88%), bone density (426/2774, 15.35%), carotid ultrasound (380/2774, 13.69%), BMI (182/2774, 6.56%), serum lipids (157/2774, 5.65%), and hemoglobin A(1c) (102/2774, 3.67%). Twenty multimedia placements using the Stomp Out Stroke webpage, social media, #stompoutstroke, television, iQ radio, and web-based news reached approximately 849,731 people in the Houston area. CONCLUSIONS: Using a combination of internet-based recruitment, registration, and in-person assessments, Stomp Out Stroke identified race- or ethnicity-specific health care needs and provided appropriate screenings to minority populations at increased risk of urban flooding and stroke. This protocol can be replicated in Southern US Stroke Belt cities with similar flood risks.
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is the third-leading cause of death worldwide with continuous rise. Limited studies indicate that COPD was associated with major storms and related power outages (PO). However, significant gaps remain in understanding what PO’s role is on the pathway of major storms-COPD. This study aimed to examine how PO mediates the major storms-COPD associations. METHODS: In this time-series study, we extracted all hospital admissions with COPD as the principal diagnosis in New York, 2001-2013. Using distributed lag nonlinear models, the hospitalization rate during major storms and PO was compared to non-major storms and non-PO periods to determine the risk ratios (RRs) for COPD at each of 0-6 lag days respectively after controlling for time-varying confounders and concentration of fine particulate matter (PM(2.5)). We then used Granger mediation analysis for time series to assess the mediation effect of PO on the major storms-COPD associations. RESULTS: The RRs of COPD hospitalization following major storms, which mainly included flooding, thunder, hurricane, snow, ice, and wind, were 1.23 to 1.49 across lag 0-6 days. The risk was strongest at lag3 and lasted significantly for 4 days. Compared with non-outage periods, the PO period was associated with 1.23 to 1.61 higher risk of COPD admissions across lag 0-6 days. The risk lasted significantly for 2 days and was strongest at lag2. Snow, hurricane and wind were the top three contributors of PO among the major storms. PO mediated as much as 49.6 to 65.0% of the major storms-COPD associations. CONCLUSIONS: Both major storms and PO were associated with increased hospital admission of COPD. PO mediated almost half of the major storms-COPD hospitalization associations. Preparation of surrogate electric system before major storms is essential to reduce major storms-COPD hospitalization.
BACKGROUND: Making landfall in Rockport, Texas in August 2017, Hurricane Harvey resulted in unprecedented flooding, displacing tens of thousands of people, and creating environmental hazards and exposures for many more. OBJECTIVE: We describe a collaborative project to establish the Texas Flood Registry to track the health and housing impacts of major flooding events. METHODS: Those who enroll in the registry answer retrospective questions regarding the impact of storms on their health and housing status. We recruit both those who did and did not flood during storm events to enable key comparisons. We leverage partnerships with multiple local health departments, community groups, and media outlets to recruit broadly. We performed a preliminary analysis using multivariable logistic regression and a binomial Bayesian conditional autoregressive (CAR) spatial model. RESULTS: We find that those whose homes flooded, or who came into direct skin contact with flood water, are more likely to experience a series of self-reported health effects. Median household income is inversely related to adverse health effects, and spatial analysis provides important insights within the modeling approach. SIGNIFICANCE: Global climate change is likely to increase the number and intensity of rainfall events, resulting in additional health burdens. Population-level data on the health and housing impacts of major flooding events is imperative in preparing for our planet’s future.
The health benefits of green space are well known, but the health effects of green infrastructure less so. Green infrastructure goes well beyond the presence of green space and refers more to a strategically planned network of natural and seminatural areas, with other environmental features designed and managed to deliver a wide range of ecosystem services and possibly to improve human health. In this narrative review, we found that small green infrastructure, such as green roofs and walls, has the potential to mitigate urban flooding, attenuate indoor temperatures and heat islands, improve air quality, and muffle noise, among other benefits, but these effects have not been linked directly to health. Larger green infrastructure has been associated with reduced temperatures, air pollution, and crimes and violence, but less so with health, although some evidence suggests that it may be beneficial for health (e.g., good health, decreased mortality). Finally, parks and street trees show many health benefits, but it is not clear if they can always be considered green infrastructure.
BACKGROUND: In June 2013, the city of Calgary, Alberta and surrounding areas sustained significant flooding which resulted in large scale evacuations and closure of businesses and schools. Floods can increase stress which may negatively impact perinatal outcomes and mental health, but previous research is inconsistent. The objectives of this study are to examine the impact of the flood on pregnancy health, birth outcomes and postpartum mental health. METHODS: Linked administrative data from the province of Alberta were used. Outcomes included preterm birth, small for gestational age, a new diagnoses of preeclampsia or gestational hypertension, and a diagnosis of, or drug prescription for, depression or anxiety. Data were analyzed using a quasi-experimental difference in difference design, comparing flooded and non-flooded areas and in affected and unaffected time periods. Multivariable log binomial regression models were used to estimate risk ratios, adjusted for maternal age. Marginal probabilities for the difference in difference term were used to show the potential effect of the flood. RESULTS: Participants included 18,266 nulliparous women for the pregnancy outcomes, and 26,956 women with infants for the mental health analysis. There were no effects for preterm birth (DID 0.00, CI: -0.02, 0.02), small for gestational age (DID 0.00, CI: -0.02, 0.02), or new cases of preeclampsia (DID 0.00, CI: -0.01, 0.01). There was a small increase in new cases of gestational hypertension (DID 0.02, CI: 0.01, 0.03) in flood affected areas. There were no differences in postpartum anxiety or depression prescriptions or diagnoses. CONCLUSION: The Calgary 2013 flood was associated with a minor increase in gestational hypertension and not other health outcomes. Universal prenatal care and magnitude of the disaster may have minimized impacts of the flood on pregnant women.
The objective of this study was to identify group-level health outcomes associated with the 2013 Calgary flood on Calgary participants (45-85 years of age) in the Canadian Longitudinal Study on Aging (CLSA). We compared baseline CLSA data collected on Calgary participants during the 6 months prior to and following the flood. Logistic regression models were created to explore whether select psychological outcomes were associated with the flood for participants categorized by evacuation status. Participants living in evacuated communities pre-flood had significantly lower levels of a diagnosed anxiety disorder than non-evacuated communities, which disappeared post-flood. Participants with higher household income were less likely to have post-traumatic stress disorder symptoms, worse self-rated mental health, and lower life satisfaction post-flood. Living alone reduced and female gender increased levels of perceived functional social support post-flood. Although natural disasters can shape research findings, the scope of the data being collected and the representativeness of impacted groups may challenge the ability to detect subtle impacts.
BACKGROUND: Resilience after natural disasters is becoming an increasingly key area of research. In April 2020, parts of Fort McMurray were affected by severe floods. The flooding caused the loss of properties, evacuation of some residents, and effects on their mental health. OBJECTIVE: This study explores the prevalence and associated factors between flood experience and low resilience a year after the 2020 floods in Fort McMurray. METHOD: Data collection was accomplished one year after the flood, from 24 April to 2 June 2021, using an online survey. The data were analyzed with SPSS version 25 using univariate analysis with the chi-squared test and binary logistic regression analysis. RESULTS: The prevalence of low resilience was 37.4%. Respondents under 25 years were nearly 26 times more likely to show low resilience (OR = 0.038; 95% CI 0.004-0.384) than respondents 40 years and above. Responders with a history of depression (OR = 0.258 95% CI: 0.089-0.744) and a history of anxiety (OR = 0.212; CI 95% 0.068-0.661) were nearly four to five times more likely to show low resilience than those without a history. Similarly, respondents willing to receive mental health counselling (OR = 0.134 95% CI: 0.047-0.378) were 7.5 times more likely to show low resilience. Participants residing in the same house before the flood were almost 11 times more likely to show low resilience (OR = 0.095; 95% CI 0.021-0.427) than those who relocated. Participants who received support from the Government of Alberta were less likely to express low resilience than those who received no or limited support (OR = 208.343; 95% CI 3.284-13,218.663). CONCLUSION: The study showed a low resilience rate among respondents following the 2020 flooding in Fort McMurray. Factors contributing to low resilience include age, history of depression or anxiety, and place of residence after the flood. After the flood, receiving support from the government was shown to be a protective factor. Further studies are needed to explore robust risk factors of low resilience and measures to promote normal to high resilience among flood victims in affected communities.
OBJECTIVE: This study assessed the prevalence and correlates of depression following the April 2020 flooding in Fort McMurray. METHODOLOGY: A cross-sectional study design. Questionnaires were self-administered through an anonymous, online survey. Data collected included sociodemographics, flooding-related variables, clinical information, and likely major depressive disorder (MDD) using PHQ-9 scoring. Data were analyzed using descriptive statistics, the chi-square test, and logistic regression at P = < 0.05. RESULTS: Of the 186 respondents who completed the survey, 85.5% (159) of the respondents were females, 14.5% (27) were males, 52.7% (98) were above 40 years of age, and 94% (175) were employed. The prevalence of mild to severe depression among the respondents was 53.7% (75). Respondents who reported that they are unemployed are 12 times more likely to have a moderate to severe depression (OR = 12.16; 95% CI: 1.08-136.26). Respondents who had previously received a mental health diagnosis of MDD are five times more likely to have moderate to severe depression (OR = 5.306; 95% CI: 1.84-15.27). CONCLUSION: This study suggests that flooding could impact the psychosocial and mental health of affected people. There is a need to reassess the existing guidelines on emergency planning for flooding to reduce its impacts on mental health and identify where research can support future evidence-based guidelines.
Few empirical studies have examined environmental equity (EE) within the context of flooding in the United States (US). This paper explores whether lower-income, minority, and vulnerable communities in cities are disproportionately impacted by flooding, as evidenced by Federal Emergency Management Agency (FEMA) designated flood zones. Tampa and Houston, both coastal cities in the US, were investigated to understand flood risk and related equity issues using Geographical Information System (GIS) and statistical analyses. Both approaches allowed us to extract and integrate information from flood hazard maps with census block group-level sociodemographic data. Dasymetric mapping (i.e., binary mapping approach) was performed to calculate population density. Both correlations and logistic regression were used to examine the relationships between sociodemographic characteristics of population and flood risk associated with FEMA flood zones. Our research findings do not suggest any racial and ethnic disparities; however, a measurable inequity is observed in exposure to flood risk across age groups, education level, and income status. Since these vulnerable groups are often unrecognized in hazard-related policy discourses (i.e., preparedness, response, and recovery), the ramifications of these research findings may have significant impacts on EE research relating to flood hazards and related policy formulations.
OBJECTIVES: The aim of this study was to examine social network characteristics and social support (emotional and instrumental support) and to determine how those factors differed between relocating older adults and nonrelocating older adults who were affected by the 2015 flood in South Carolina. METHODS: Twenty-five community-dwelling elderly (CDE) were interviewed between December 2015 and May 2016 to learn about their experiences in the immediate aftermath of the flood. Ego-centric network data were collected with a focus on social network members and the types of flood-related support that these network members provided. RESULTS: Ten of 25 CDE relocated because of the flood. All CDE were more likely to receive social support from female network members and family members than from other acquaintances. Relocating CDE received significantly less emotional support in comparison to nonrelocating CDE. The odds of receiving instrumental support were higher, but nonsignificant, among relocating CDE in comparison to nonrelocating CDE. CONCLUSIONS: The findings around the support provision are concerning particularly because of the additional psychological burden that relocation can place on flood-affected, older adults. Recommendations for public health preparedness strategies are provided in addition to future research directions for examining the well-being of flood-affected, older adults.
We examined the inoculation and stress sensitization explanations concerning mental health outcomes in 223 predominately middle-aged and older adults after a flood (M age = 49.6 years, SD = 17.7 years, range: 18-88 years). In multiple linear regression models, having flood damage was associated with higher levels of posttraumatic stress disorder (PTSD) and depressive symptoms, while social support was associated with fewer symptoms. Greater lifetime trauma and flood-related stress were associated with more symptoms of depression and PTSD, respectively. Older age was associated with more religious coping and fewer depressive and worry symptoms. Future directions for research on postdisaster vulnerabilities and resilience are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Associations of disaster mental health sequelae between children and their parents have been demonstrated, but not using full diagnostic assessment. This study examined children and their parents after a series of disasters in 1982 to investigate associations of their psychiatric outcomes. Members of 169 families exposed to floods and/or dioxin or no disaster were assessed in 1986-1987 with structured diagnostic interviews. This vintage dataset collected several decades ago provides new information to this field because of the methodological rigor that is unparalleled in this literature. Disaster-related PTSD and incident postdisaster disorders in children were associated, respectively with disaster-related PTSD and incident postdisaster disorders in the chief caregiver and mother. More flood-only than dioxin-only exposed parents reported great harm by the disaster, but neither children nor parents in these two groups differed in incident psychiatric disorders. Although this study did not determine the direction of causal influences, its findings suggest that clinicians working with disaster-exposed families should work with children and adult members together, as their mental health outcomes may be intertwined.
PurposeThe current pandemic and ongoing climate risks highlight the limited capacity of various systems, including health and social ones, to respond to population-scale and long-term threats. Practices to reduce the impacts on the health and well-being of populations must evolve from a reactive mode to preventive, proactive and concerted actions beginning at individual and community levels. Experiences and lessons learned from the pandemic will help to better prevent and reduce the psychosocial impacts of floods, or other hydroclimatic risks, in a climate change context.Design/methodology/approachThe present paper first describes the complexity and the challenges associated with climate change and systemic risks. It also presents some systemic frameworks of mental health determinants, and provides an overview of the different types of psychosocial impacts of disasters. Through various Quebec case studies and using lessons learned from past and recent flood-related events, recommendations are made on how to better integrate individual and community factors in disaster response.FindingsResults highlight the fact that people who have been affected by the events are significantly more likely to have mental health problems than those not exposed to flooding. They further demonstrate the adverse and long-term effects of floods on psychological health, notably stemming from indirect stressors at the community and institutional levels. Different strategies are proposed from individual-centered to systemic approaches, in putting forward the advantages from intersectoral and multirisk researches and interventions.Originality/valueThe establishment of an intersectoral flood network, namely the InterSectoral Flood Network of Quebec (RIISQ), is presented as an interesting avenue to foster interdisciplinary collaboration and a systemic view of flood risks. Intersectoral work is proving to be a major issue in the management of systemic risks, and should concern communities, health and mental health professionals, and the various levels of governance. As climate change is called upon to lead to more and more systemic risks, close collaboration between all the areas concerned with the management of the factors of vulnerability and exposure of populations will be necessary to respond effectively to damages and impacts (direct and indirect) linked to new meteorological and compound hazards. This means as well to better integrate the communication managers into the risk management team.
Objective: This study investigated how a flooding disaster impacted family cohesion and resilience. Background: Disasters present challenges for families, often threatening family cohesion. Although there is extensive research on the impacts of disasters on mental health at the individual level, less is known about how family units recover from disasters, and how parental relationship dynamics and parent-child dynamics influence family functioning during and after such traumatic events. Method: Qualitative face-to-face interviews were conducted 1 year after the 2013 southern Alberta flood with 105 parents of children ages 17 years and under. Results: Findings reveal that families who experienced more loss were not necessarily more negatively impacted overall. Some families reported the flood caused them to grow further apart, whereas for others it brought them closer together. Those who reported that the flood brought them closer together demonstrated the following three main social skills: (a) communication, (b) conflict resolution, and (c) coping. Findings also reveal that families have higher levels of cohesiveness and resilience post-disaster when they exhibit these important skills. Conclusion: This research concludes that coming together as a family unit created a supportive space for families to process and reduce the stress generated by the flood event. Families who demonstrate and practice communication, conflict resolution, and coping in the face of challenging events like disasters are more cohesive and resilient.
Climate change is intensifying coastal floods and increasing the risks of traffic disruption in lowlying, coastal communities. Efforts to understand the differential impacts of traffic disruption on communities have led to the concept of traffic resilience which captures the degree to which a traffic system can recover from disruption. Existing proxies of traffic resilience are focused on quantifying travel time delays but lack the important dimension of road safety. In this study, we quantify traffic resilience in terms of the change in non-highway car and pedestrian accident rates during the 5-10 am period as a result of coastal flooding in the San Francisco Bay Area for the 2020-2040 period. We use a regional traffic model to simulate traffic patterns under a range of coastal flood water levels. We use regressions that relate traffic volumes to historical accident rates to estimate accidents rates in the presence of flooding. Our results show that the flooding of highways forces commuters onto local roads passing through residential communities, causing a spike in accident rates. Unlike delays which increase sharply at the higher water levels considered in this study, we project that region-wide peak-hour accident rates may increase substantially at lower water levels.
There is a consensus that future sea-level rise (SLR) will increase the exposure of population and assets to coastal flooding. However, the extent to which SLR affects flood hazards and human vulnerability to flooding in the built environment is not well understood. This study investigates the effects of future SLR on coastal flood hazards and human vulnerability to flooding in New York City’s built environment. With a focus on a hurricane-induced flood event, we utilize a building-scale hydrodynamic model to simulate flood hazards under different 21st-century SLR scenarios. We further implement a human vulnerability model to reveal how the physical vulnerability of individuals to flooding would respond to the effects of SLR on flood hazards. We find that SLR would result in a substantial increase in not only the floodwater depth but also the floodwater velocity in the study area. For example, under a 1.04 m SLR scenario, the increase in the max floodwater speed exceeds 2.7 m/s (1271%) in 5% of the area that was flooded under the no-SLR scenario (control run). Model results show that, due to nonlinear interactions, the floodwater depth simulated by the hydrodynamic model for a SLR scenario could substantially differ from the depth estimated based on a linear addition of the SLR to the control-run floodwater depth. We find that the effects of SLR on flood hazards would, in turn, substantially affect the extent, intensity, and duration of human physical vulnerability to flooding, which could potentially increase the number of injuries and mortalities.
With increasing population growth and urban sprawl, many coastal lowlands are unprecedentedly vulnerable to climate change and its impacts, such as rising sea levels, increasing extreme storm events, and coastal flooding. Quantifying coastal flood vulnerability serves as a tool to identify a system’s weakness, monitor its change, and support making targeted climate adaptation policies. The assessment framework proposed in this research uses principal component analysis (PCA) and a weighting method to build a composite indicator of flood vulnerability index and evaluate the vulnerability for 256 coastal census tracts and 24 municipalities along the coast of Connecticut, USA. The research uses Keiser-Meyer-Olkin (KMO) test and Bartlett’s test of sphericity to test sample adequacy and performs data standardization for all indicators. Through PCA, 30 coastal vulnerability-related indicators were grouped into four major dimensions: hazard exposure, socio-economic, physical/land use and land cover, and natural. The findings highlight the variations of flood vulnerability across highly ur-banized areas, suburban areas, and rural areas; and the gradient from coastal low-elevation region to high-elevation inland area. This variance is unevenly caused by different dimensions although they may trade-off with each other when aggregated, the dominant dimensions play a significant or decisive role in the vulnera-bility assessment. This research built an automatic and objective assessment framework that is flexible enough to be applied at a smaller scale so as to obtain detailed analysis and it can be used as a decision-making support system.
This paper examines communities’ accessibility to critical facilities such as hospitals, emergency medical services, and emergency shelters when facing flooding. We use travel speed reduction to account for flood-induced partial road failure. A modified betweenness centrality metric is also introduced to calculate the criticality of roads for connecting communities to critical facilities. The proposed model and metric are applied to the Delaware road network under 100-year floods. This model highlights the severe critical facility access loss risk due to flood isolation of facilities. The mapped post-flooding accessibility suggests a significant travel time increase to critical facilities and reveals disparities among communities, especially for vulnerable groups such as long-term care facility residents. We also identified critical roads that are vital for post-flooding access to critical facilities. The results of this research can help inform targeted infrastructure investment decisions and hazard mitigation strategies that contribute to equitable community resilience enhancement.
Understanding availability and accessibility of critical infrastructure systems during the pre-disaster phase and evaluating the impact of their possible disruption during the disaster phase are crucial for measuring the vulnerability and resiliency of communities. This study proposes a new quantitative framework for flood risk assessment that helps understand the existing disaster risk and proactively mitigate the impact of infrastructure disruption on communities by systematically analyzing: (1) reliability of a transportation network and (2) vulnerability of residents and critical facilities. The methodology addresses the following infrastructure systems categorized as: (1) distribution-based and (2) facility-based systems. This study has modeled the dependency of the facility-based category on the transportation network and developed a general framework that measures the deficiency in pre-disaster phase and possible disruptions during the disaster response phase. For a cast study, this framework was applied to evaluate the vulnerability and resiliency of emergency facilities in the East Baton Rouge. It was concluded that a detailed analysis of both preexisting conditions and during disaster conditions along with social vulnerability provide a more realistic insight and more accurate benchmark of vulnerability and resiliency of communities pertaining to infrastructure systems. This framework is expected to improve hazard mitigation and decision-making processes in investments and prioritization of infrastructure improvement projects.
BACKGROUND: Satellite observations following flooding coupled with electronic health data collected through syndromic surveillance systems (SyS) may be useful in efficiently characterizing and responding to health risks associated with flooding. RESULTS: There was a 10% (95% Confidence Interval (CI): 1%-19%) increase in asthma related ED visits and 22% (95% CI: 5%-41%) increase in insect bite related ED visits in the flooded ZCTAs compared to non-flooded ZCTAs during the flood period. One month following the floods, diarrhea related ED visits were increased by 15% (95% CI: 4%-27%) for flooded ZCTAs and children and adolescents from flooded ZCTAs had elevated risk for dehydration related ED visits. During the protracted period (2-3 months after the flood period), the risk for asthma, insect bite, and diarrhea related ED visits were elevated among the flooded ZCTAs. Effect modification by reported age, ethnicity and race was observed. CONCLUSION: Combining satellite observations with SyS data can be helpful in characterizing the location and timing of environmentally mediated adverse health outcomes, which may be useful for refining disaster resilience measures to mitigate health outcomes following flooding.
The Centers for Disease Control and Prevention (CDC)/Agency for Toxic Substances and Disease Registry (ATSDR) Social Vulnerability Index (SVI) is a census-based metric that includes 15 socioeconomic and demographic factors split into four themes relevant to disaster planning, response, and recovery. Using CDC/ATSDR SVI, health outcomes, and remote sensing data, we sought to understand the differences in the occurrence of overall and cause-specific emergency department (ED) visits before and after a 2017 flood event in Texas following Hurricane Harvey, modified by different levels of social vulnerability. We used a controlled before-after study design to estimate the association between flooding and overall and cause-specific ED visits after adjusting for the baseline period, seasonal trends, and individual-level characteristics. We estimated rate ratios stratified by CDC/ATSDR SVI quartiles (overall and 4 themes separately) and tested for the presence of effect modification. Positive effect modification was found such that total ED visits from flooded census tracts with moderate, high, and very high levels of social vulnerability were less reduced compared to tracts with the least vulnerability during flooding and the month following the flood event. The CDC/ATSDR SVI socioeconomic status theme, household composition and disability theme, and housing and transportation type theme explained this result. We found predominantly negative effect modification with higher ED visits among tracts with the least vulnerability for ED visits related to insect bites, dehydration, and intestinal infectious diseases.
This paper presents a research study that is a valuable first project in setting the stage for bringing a foresight perspective to the impacts of severe flooding on health, poverty, and equity in Houston, out to the year 2050. Drawing on qualitative and quantitative research gathered from methodologies such as the Delphi and Cross-Impact Analysis combined with insights gained from interviews with subject-matter experts, it explores four alternative, plausible scenarios for Houston’s long-term future. Exploring scenarios that feature the continuation of present-day trends, a system collapse, a system balanced by a new equilibrium, and a system transformation provides an opportunity for stakeholders and policymakers to work together to create a more inclusive future for all city residents.
Maria made a landfall in Puerto Rico on September 20, 2017 as a category 4 hurricane, causing severe flooding, widespread electricity outages, damage to infrastructure, and interruptions in water and wastewater treatment. Small rural community water systems face unique challenges in providing drinking water, which intensify after natural disasters. The purpose of this study was to evaluate the functionality of six very small rural public water systems and one large regulated system in Puerto Rico six months after Maria and survey a broad sweep of fecal, zoonotic, and opportunistic pathogens from the source to tap. Samples were collected from surface and groundwater sources, after water treatment and after distribution to households. Genes indicative of pathogenic Leptospira spp. were detected by polymerase chain reaction (PCR) in all systems reliant on surface water sources. Salmonella spp. was detected in surface and groundwater sources and some distribution system water both by culture and PCR. Legionella spp. and Mycobacteria spp. gene numbers measured by quantitative PCR were similar to nonoutbreak conditions in the continental U.S. Amplicon sequencing provided a nontarget screen for other potential pathogens of concern. This study aids in improving future preparedness, assessment, and recovery operations for small rural water systems after natural disasters.
Hurricanes often flood homes and industries, spreading pathogens. Contact with pathogen-contaminated water can result in diarrhea, vomiting, and/or nausea, known collectively as acute gastrointestinal illness (AGI). Hurricanes Matthew and Florence caused record-breaking flooding in North Carolina (NC) in October 2016 and September 2018, respectively. To examine the relationship between hurricane flooding and AGI in NC, we first calculated the percent of each ZIP code flooded after Hurricanes Matthew and Florence. Rates of all-cause AGI emergency department (ED) visits were calculated from NC’s ED surveillance system data. Using controlled interrupted time series, we compared AGI ED visit rates during the three weeks after each hurricane in ZIP codes with a third or more of their area flooded to the predicted rates had these hurricanes not occurred, based on AGI 2016-2019 ED trends, and controlling for AGI ED visit rates in unflooded areas. We examined alternative case definitions (bacterial AGI) and effect measure modification by race and age. We observed an 11% increase (rate ratio (RR): 1.11, 95% CI: 1.00, 1.23) in AGI ED visit rates after Hurricanes Matthew and Florence. This effect was particularly strong among American Indian patients and patients aged 65 years and older after Florence and elevated among Black patients for both hurricanes. Florence’s effect was more consistent than Matthew’s effect, possibly because little rain preceded Florence and heavy rain preceded Matthew. When restricted to bacterial AGI, we found an 85% (RR: 1.85, 95% CI: 1.37, 2.34) increase in AGI ED visit rate after Florence, but no increase after Matthew. Hurricane flooding is associated with an increase in AGI ED visit rate, although the strength of effect may depend on total storm rainfall or antecedent rainfall. American Indians and Black people-historically pushed to less desirable, flood-prone land-may be at higher risk for AGI after storms.
BACKGROUND: While most prior research has focused on extreme heat, few assessed the immediate health effects of winter storms and associated power outages (PO), although severe storms have become more frequent. This study evaluates the joint and independent health effects of winter storms and PO, snow versus ice-storm, effects by time window (peak timing, winter/transitional months) and the impacts on critical care indicators including numbers of comorbidity, procedure, length of stay and cost. METHODS: We use distributed lag nonlinear models to assess the impacts of winter storm/PO on hospitalizations due to cardiovascular, lower respiratory diseases (LRD), respiratory infections, food/water-borne diseases (FWBD) and injuries in New York State on 0-6 lag days following storm/PO compared with non-storm/non-PO periods (references), while controlling for time-varying factors and PM(2.5). The storm-related hospitalizations are described by time window. We also calculate changes in critical care indicators between the storm/PO and control periods. RESULTS: We found the joint effects of storm/PO are the strongest (risk ratios (RR) range: 1.01-1.90), followed by that of storm alone (1.02-1.39), but not during PO alone. Ice storms have stronger impacts (RRs: 1.04-3.15) than snowstorms (RRs: 1.03-2.21). The storm/PO-health associations, which occur immediately, and some last a whole week, are stronger in FWBD, October/November, and peak between 3:00-8:00 p.m. Comorbidity and medical costs significantly increase after storm/PO. CONCLUSION: Winter storms increase multiple diseases, comorbidity and medical costs, especially when accompanied by PO or ice storms. Early warnings and prevention may be critical in the transitional months and afternoon rush hours.
Rodents can transmit infectious diseases directly to humans and other animals via bites and exposure to infectious salivary aerosols and excreta. Arthropods infected while blood-feeding on rodents can also transmit rodent-borne pathogens indirectly to humans and animals. Environmental events, such as wet winters, cooler summers, heavy rains, and flooding, have precipitated regional rodent-borne infectious disease outbreaks; these outbreaks are now increasing with climate change. The objectives of this review are to inform wilderness medicine providers about the environmental conditions that can precipitate rodent-borne infectious disease outbreaks; to describe the regional geographic distributions of rodent-borne infectious diseases in North America; and to recommend prophylactic treatments and effective prevention and control strategies for rodent-borne infectious diseases. To meet these objectives, Internet search engines were queried with keywords to identify scientific articles on outbreaks of the most common regional rodent-borne infectious diseases in North America. Wilderness medicine providers should maintain high levels of suspicion for regional rodent-borne diseases in patients who develop febrile illnesses after exposure to contaminated freshwater after heavy rains or floods and after swimming, rafting, or paddling in endemic areas. Public health education strategies should encourage limiting human contact with rodents; avoiding contact with or safely disposing of rodent excreta; avoiding contact with contaminated floodwaters, especially contact with open wounds; securely containing outdoor food stores; and modifying wilderness cabins and campsites to deter rodent colonization.
Urban floods can be contaminated with fecal material and pathogens. Evidence on infection risks associated with exposure to waterborne pathogens in urban floods is lacking. We address this gap by assessing the risk of infection from exposure to Giardia lamblia in urban flood water samples in Mexico City using a QMRA. Historical flood data was used to build severity indices and to test for correlations with risk of infection estimates. Results indicate similar maximal pathogen densities in urban flood water samples to those from wastewater treatment plants. Significant positive correlations between risk of G. lamblia infection and severity indices suggest that floods could act as an important source of pathogen transmission in Mexico City. Risk of infection to G. lamblia is greater in the city’s periphery, which is characterized by high marginalization levels. We argue that these risks should be managed by engaging citizens, water, and health authorities in decision making.
Low elevation coastal zones (LECZ) are extensive throughout the southeastern United States. LECZ communities are threatened by inundation from sea level rise, storm surge, wetland degradation, land subsidence, and hydrological flooding. Communication among scientists, stakeholders, policy makers and minority and poor residents must improve. We must predict processes spanning the ecological, physical, social, and health sciences. Communities need to address linkages of (1) human and socioeconomic vulnerabilities; (2) public health and safety; (3) economic concerns; (4) land loss; (5) wetland threats; and (6) coastal inundation. Essential capabilities must include a network to assemble and distribute data and model code to assess risk and its causes, support adaptive management, and improve the resiliency of communities. Better communication of information and understanding among residents and officials is essential. Here we review recent background literature on these matters and offer recommendations for integrating natural and social sciences. We advocate for a cyber-network of scientists, modelers, engineers, educators, and stakeholders from academia, federal state and local agencies, non-governmental organizations, residents, and the private sector. Our vision is to enhance future resilience of LECZ communities by offering approaches to mitigate hazards to human health, safety and welfare and reduce impacts to coastal residents and industries.
Sea level rise has increased the frequency of tidal flooding even without accompanying precipitation in many coastal areas worldwide. As the tide rises, inundates the landscape, and then recedes, it can transport organic and inorganic matter between terrestrial systems and adjacent aquatic environments. However, the chemical and biological effects of tidal flooding on urban estuarine systems remain poorly constrained. Here, we provide the first extensive quantification of floodwater nutrient concentrations during a tidal flooding event and estimate the nitrogen (N) loading to the Lafayette River, an urban tidal sub-tributary of the lower Chesapeake Bay (USA). To enable the scale of synoptic sampling necessary to accomplish this, we trained citizen-scientist volunteers to collect 190 flood water samples during a perigean spring tide to measure total dissolved N (TDN), dissolved inorganic N (DIN) and phosphate concentrations, and Enterococcus abundance from the retreating ebb tide while using a phone application to measure the extent of tidal inundation. Almost 95% of Enterococcus results had concentrations that exceeded the standard established for recreational waters (104 MPN 100 mL(-1)). Floodwater dissolved nutrient concentrations were higher than concentrations measured in natural estuarine waters, suggesting floodwater as a source of dissolved nutrients to the estuary. However, only DIN concentrations were statistically higher in floodwater samples than in the estuary. Using a hydrodynamic model to calculate the volume of water inundating the landscape, and the differences between the median DIN concentrations in floodwaters and the estuary, we estimate that 1,145 kg of DIN entered the Lafayette River during this single, blue sky, tidal flooding event. This amount exceeds the annual N load allocation for overland flow established by federal regulations for this segment of the Chesapeake Bay by 30%. Because tidal flooding is projected to increase in the future as sea levels continue to rise, it is crucial we quantify nutrient loading from tidal flooding in order to set realistic water quality restoration targets for tidally influenced water bodies.
Urban floodwater could lead to significant risk for public and environmental health from mobilization of microbial pathogens and overflow of wastewater treatment systems. Here, we attempted to assess this risk by obtaining metagenomic profiles of antibiotic resistance genes (ARGs), virulence factors (VFs) and pathogens present in floodwater samples collected in urban Atlanta, GA that were categorized in two distinct groups: floods that occurred after periods of drought and those after regular (seasonal) rain events. Even though no major (known) pathogens were present at the limit of detection of our sequencing effort (~3 Gbp/sample), we observed that floodwaters after drought showed a 2.5-fold higher abundance of both ARGs and VFs compared to floodwater after rainy days. These differences were mainly derived by several novel species of the Pseudomonas genus, which were more dominant in the former versus the latter samples and carried several genes to cope with osmotic stress in addition to ARGs and VFs. These results revealed that there are previously undescribed species that become mobilized after flooding events in the Southeast US urban settings and could represent an increased public health risk, especially after periods of drought, which warrants further attention.
Wastewater treatment plants (WWTPs) are among the most important infrastructures, especially in coastal cities with a risk of flooding. During intense floods, runoff volume may exceed the capacity of a WWTP causing plant failures. This paper investigates the impacts of flooding on combined sewer overflows (CSOs) in a WWTP in New York City. The impacts of CSOs after flooding are classified into four terms of health, economic, social, and environmental factors. Different factors are defined to evaluate impacts of CSOs using multi-criteria decision-making of Preference Ranking Organization Method For Enrichment Evaluation and fuzzy technique for order performance by similarity to ideal solution. Since volume and depth were found the most significant factors for the CSO impact assessment, the Gridded Surface Subsurface Hydrologic Analysis model was run to compute flood depth and CSO volume under three treatment plant failure scenarios considering the hurricane Sandy information. Sensitivity analysis revealed that the TSS, BOD, and dissolved oxygen have the highest impacts on CSO. Uncertainty analysis was applied to investigate CSO impact variation. Results show that evaluating the impacts of CSOs in different aspects can give a good idea for flood planning and management with higher efficiency during storms.
Hurricanes and associated stormwater runoff events are expected to greatly impact coastal marine water quality, yet little is known about their immediate effects on microbiological quality of near-shore water. This study sampled Hilo Bay immediately after the impact of Hurricane Lane to understand the spatial and temporal variations of the abundance and diversity of fecal indicator enterococci, common fecal pathogens, and antibiotic resistance genes (ARGs). Water samples from seven sampling sites over 7 days were collected and analyzed, which showed that the overall microbiological water quality parameters [enterococci geometric mean (GM): 6-22 cfu/100 mL] fell within water quality standards and that the temporal dynamics indicated continuing water quality recovery. However, considerable spatial variation was observed, with the most contaminated site exhibiting impaired water quality (GM = 144 cfu/100 mL). The Enterococcus population also showed distinct genotypic composition at the most contaminated site. Although marker genes for typical fecal pathogens (invA for Salmonella, hipO for Campylobacter, mip for Legionella pneumophila, and eaeA for enteropathogenic Escherichia coli) were not detected, various ARGs (ermB, qurS, tetM, blaTEM, and sul1) and integron-associated integrase intI1 were detected at high levels. Understanding the temporal and spatial variation of microbiological water quality at fine granularity is important for balancing economic and recreational uses of coastal water and the protection of public health post the impact of major hurricane events.
Densely populated, low-lying coastal areas are most at-risk for negative impacts from increasing intensity of storm-induced flooding. Due to the effects of global warming and subsequent climate change, coastal temperatures and the magnitude of storm-induced flooding are projected to increase, creating a hospitable environment for the aquatic Vibrio spp. bacteria. A relative risk model analysis was used to determine which census block groups in coastal South Carolina have the highest risk of Vibrio spp. exposure using storm surge flooding as a proxy. Coastal block groups with dense vulnerable sub-populations exposed to storm surge have the highest relative risk, while inland block groups away from riverine-mediated storm surge have the lowest relative risk. As Vibriosis infections may be extremely severe or even deadly, the best methods of infection control will be regular standardized coastal and estuarine water monitoring for Vibrio spp. to enable more informed and timely public health advisories and help prevent future exposure.
Influenza typically causes mild infection but can lead to severe outcomes for those with compromised lung health. Flooding, a seasonal problem in Iowa, can expose many Iowans to molds and allergens shown to alter lung inflammation, leading to asthma attacks and decreased viral clearance. Based on this, the hypothesis for this research was that there would be geographically specific positive associations in locations with flooding with influenza diagnosis. An ecological study was performed using influenza diagnoses and positive influenza polymerase chain reaction tests from a de-identified large private insurance database and Iowa State Hygienic Lab. After adjustment for multiple confounding factors, Poisson regression analysis resulted in a consistent 1% associated increase in influenza diagnoses per day above flood stage (95% confidence interval: 1.00-1.04). This relationship remained after removal of the 2009-2010 influenza pandemic year. There was no associated risk between flooding and influenza-like illness as a nonspecific diagnosis. Associated risks between flooding and increased influenza diagnoses were geographically specific, with the greatest risk in the most densely populated areas. This study indicates that populations who live, work, or volunteer in flooded environments should consider preventative measures to avoid environmental exposures to mitigate illness from influenza in the following year.
Indoor flooding is a leading contributor to indoor dampness and the associated mold infestations in the coastal United States. Whether the prevalent mold genera that infest the coastal flood-prone buildings are different from those not flood-prone is unknown. In the current case study of 28 mold-infested buildings across the U.S. east coast, we surprisingly noted a trend of higher prevalence of indoor Aspergillus and Penicillium genera (denoted here as Asp-Pen) in buildings with previous flooding history. Hence, we sought to determine the possibility of a potential statistically significant association between indoor Asp-Pen prevalence and three building-related variables: (i) indoor flooding history, (ii) geographical location, and (iii) the building’s use (residential versus non-residential). Culturable spores and hyphal fragments in indoor air were collected using the settle-plate method, and corresponding genera were confirmed using phylogenetic analysis of their ITS sequence (the fungal barcode). Analysis of variance (ANOVA) using Generalized linear model procedure (GLM) showed that Asp-Pen prevalence is significantly associated with indoor flooding as well as coastal proximity. To address the small sample size, a multivariate decision tree analysis was conducted, which ranked indoor flooding history as the strongest determinant of Asp-Pen prevalence, followed by geographical location and the building’s use.
BACKGROUND: In August 2017, Hurricane Harvey caused unprecedented flooding across the greater Houston area. Given the potential for widespread flood-related exposures, including mold and sewage, and the emotional and mental toll caused by the flooding, we sought to evaluate the short- and long-term impact of flood-related exposures on the health of Houstonians. Our objectives were to assess the association of flood-related exposures with allergic symptoms and stress among Houston-area residents at two time points: within approximately 30 days (T1) and 12 months (T2) after Hurricane Harvey’s landfall. METHODS: The Houston Hurricane Harvey Health (Houston-3H) Study enrolled a total of 347 unique participants from four sites across Harris County at two times: within approximately 1-month of Harvey (T1, n = 206) and approximately 12-months after Harvey (T2, n = 266), including 125 individuals who participated at both time points. Using a self-administered questionnaire, participants reported details on demographics, flood-related exposures, and health outcomes, including allergic symptoms and stress. RESULTS: The majority of participants reported hurricane-related flooding in their homes at T1 (79.1%) and T2 (87.2%) and experienced at least one allergic symptom after the hurricane (79.4% at T1 and 68.4% at T2). In general, flood-exposed individuals were at increased risk of upper respiratory tract allergic symptoms, reported at both the T1 and T2 time points, with exposures to dirty water and mold associated with increased risk of multiple allergic symptoms. The mean stress score of study participants at T1 was 8.0 ± 2.1 and at T2, 5.1 ± 3.2, on a 0-10 scale. Participants who experienced specific flood-related exposures reported higher stress scores when compared with their counterparts, especially 1 year after Harvey. Also, a supplementary paired-samples analysis showed that reports of wheezing, shortness of breath, and skin rash did not change between T1 and T2, though other conditions were less commonly reported at T2. CONCLUSION: These initial Houston-3H findings demonstrate that flooding experiences that occurred as a consequence of Hurricane Harvey had lasting impacts on the health of Houstonians up to 1 year after the hurricane.
Extensive flooding caused by Hurricane María in Puerto Rico (PR) created favorable conditions for indoor growth of filamentous fungi. These conditions represent a public health concern as contamination by environmental fungi is associated with a higher prevalence of inflammatory respiratory conditions. This work compares culturable fungal spore communities present in homes that sustained water damage after Hurricane María to those present in dry, non-flooded homes. We collected air samples from 50 houses in a neighborhood in San Juan, PR, 12 and 22 months after Hurricane María. Self-reported data was used to classify the homes as flooded, water-damage or dry non-flooded. Fungi abundances, composition and diversity were analyzed by culturing on two media. Our results showed no significant differences in indoor fungal concentrations (CFU/m(3)) one year after the Hurricane in both culture media studied (MEA and G25N). During the second sampling period fungal levels were 2.7 times higher in previously flooded homes (Median = 758) when compared to dry homes (Median = 283), (p-value < 0.005). Fungal profiles showed enrichment of Aspergillus species inside flooded homes compared to outdoor samples during the first sampling period (FDR-adjusted p-value = 0.05). In contrast, 22 months after the storm, indoor fungal composition consisted primarily of non-sporulated fungi, most likely basidiospores, which are characteristic of the outdoor air in PR. Together, this data highlights that homes that suffered water damage not only have higher indoor proliferation of filamentous fungi, but their indoor fungal populations change over time following the Hurricane. Ultimately, after nearly two years, indoor and outdoor fungal communities converged in this sample of naturally ventilated homes.
BACKGROUND: Hurricane Harvey made landfall along the Texas Gulf Coast as a Category 4 hurricane on August 25, 2017, producing unprecedented precipitation that devastated coastal areas. Catastrophic flooding in the City of Houston inundated industrial and residential properties resulting in the displacement and transfer of soil, sediment, and debris and heightening existing environmental justice (EJ) concerns. OBJECTIVES: The primary aim of this study was to evaluate the presence, distribution, and potential human health implications of polycyclic aromatic hydrocarbons (PAHs) in a residential neighborhood of Houston, Texas following a major hurricane. METHODS: Concentrations of PAHs in 40 soil samples collected from a residential neighborhood in Houston, Texas were measured. Spatial interpolation was applied to determine the distribution of PAHs. Potential human health risks were evaluated by calculating toxicity equivalency quotients (TEQs) and incremental excess lifetime cancer risk (IELCR). RESULTS: Total priority PAH concentrations varied across samples (range: 9.7 × 10(1) ng/g-1.6 × 10(4) ng/g; mean: 3.0 × 10(3) ng/g ± 3.6 × 10(3) standard deviation). Spatial analysis indicated a variable distribution of PAH constituents and concentrations. The IELCR analysis indicated that nine of the 40 samples were above minimum standards. CONCLUSIONS: Findings from this study highlight the need for fine scale soil testing in residential areas as well as the importance of site-specific risk assessment. COMPETING INTERESTS: The authors declare no competing financial interests.
Unprecedented inland precipitation and catastrophic flooding associated with Hurricane Harvey potentially redistributed contaminants from industrial sites and transportation infrastructure to recreational areas that make up networks of green infrastructure, creeks, and waterways used for flood control throughout the Greater Houston Area. Sediment samples were collected in parks located near the Buffalo Bayou watershed 1 week after Hurricane Harvey made landfall and again 7 weeks later. Total concentrations of the U.S. Environmental Protection Agency’s (EPA’s) 16 priority polycyclic aromatic hydrocarbons (PAHs) were measured in each sample at both time points. Diagnostic ratios were calculated to improve understanding of potential sources of PAHs after flooding. Diagnostic ratios suggest vehicular traffic to be a potential source for PAHs in parks. Although the concentrations of PAHs in all samples were below EPA actionable levels, given that no background values were available for comparison, it is difficult to quantify the impact flooding from Hurricane Harvey had on PAH concentrations in Houston parks. However, given the high frequency of flooding in Houston, and the concentration of industrial facilities and transportation infrastructure adjacent to recreation areas, these data demonstrate that PAHs were still present after unprecedented flooding. This study may also serve as a baseline for future efforts to understand the environmental health impacts of disasters.
BACKGROUND/OBJECTIVE: Natural disasters (NDs) are calamitous phenomena that can increase the risk of infections in disaster-affected regions. This study aimed to evaluate the frequency of malaria and cutaneous leishmaniasis (CL) before and after earthquakes, floods, and droughts during the past four decades in Iran. METHODS: Malaria and CL data were obtained from the reports of the Ministry of Health and Medical Education in Iran for the years 1983 through 2017. The data of NDs were extracted from the Centre for Research on the Epidemiology of Disasters (CRED). Interrupted time series analysis with linear regression modeling was used to estimate time trends of mentioned diseases in pre- and post-disaster conditions. RESULTS: For the periods preceding the disasters drought and flood, a decreasing time trend for malaria and CL was found over time. The time trend of malaria rate preceding the 1990 earthquake was stable, a downward trend was found after 1990 disaster until 1997 (β coefficient: -10.7; P = .001), and this declining trend was continued after 1997 disaster (β coefficient: -2.7; P = .001). The time trend of CL rate preceding the 1990 earthquake had a declining trend, an upward trend was found after 1990 earthquake until 1999 (β coefficient: +8.7; P = .293), and a slight upward trend had also appeared after 1999 earthquake (β coefficient: +0.75; P = .839). CONCLUSION: The results of the current study indicated the occurrence of earthquakes, floods, and droughts has no significant effect on the frequency of malaria and CL in Iran.
BACKGROUND: Disaster planning and management pose a serious challenge to most countries. These challenges point to insufficient planning to deal with these events. Therefore, it is necessary to pay attention to the methods and characteristics of the decision-making approaches in these events. In this study, we tried to identify most appropriate approaches for the Iranian health system by studying disaster planning approaches. MATERIALS AND METHODS: This study was conducted using mixed methods in 2020-2021 in two phases: qualitative and quantitative. First, we reviewed at the research literature. Our goal was to identify studies that suggested approaches to disaster planning. The next step in this study was a qualitative study using semi-structured interviews. Participants in qualitative phase included managers and employees from different parts of the Iranian health system from the provinces of Golestan, Fars, Khuzestan, Lorestan, Kerman, Sistan, and Baluchestan. RESULTS: By combining approaches taken from literature reviews and qualitative study, four main approaches were identified. The results of our study have shown that disaster response planning approaches include function, risk assessment, capability, and futuristic base. CONCLUSION: This study provides complete overview of disaster planning approaches that enable health professionals to use them to develop response plans. Our findings indicate that in complex and large-scale events such as floods and pandemics, it is necessary to combine the introduced methods for operational planning.
Flash-flooding affected Iran in March 2019 causing the displacement of thousands of people. Social workers established a Child Friendly Space (CFS) and applied comprehensive case management to provide psychosocial support for people who were affected by flooding (PWAF) (n = 565) in a community in Poldokhtar, covering a period of 3 months. Outreach services, involving community-volunteers, providing counseling, establishing CFS, training PWAF for reducing violence, and preventing child abuse were essential social work post-disaster interventions to support vulnerable populations. The article reflects upon the often-neglected role of social workers in post-disaster settings, and brings new material for discussion from the unexplored field of Iranian social workers.
In this paper, we assess the long-term effect of floods on food security (as measured by calorie and micronutrient consumption) by applying an instrumental variable approach to data from the Afghanistan National Risk and Vulnerability Assessment survey. To identify the determinants of this effect, we also estimate how floods affect per capita yearly household income and poverty status. We find that exposure to flooding during a 12-month period decreased daily calorie consumption by approximately 60 kcal while increasing the probability of iron, vitamin A, and vitamin C deficiency by 11, 12, and 27 percentage points, respectively. Controlling for price shocks and income only marginally reduces this flood effect on food security, suggesting that impaired livelihoods (rather than price hikes) are its primary driver. We further determine that exposure to this natural disaster decreases income by about 3% and makes flood-affected households about 3 percentage points more likely to be poor. Lastly, we show that experience of floods is strongly and significantly associated with lower diet quality and quantity, and with engaging in consumption smoothing coping strategies, such as buying food on credit and taking loans. These findings underscore the serious direct impact of floods on both diet and effective behavioral responses to such shocks while emphasizing the need for targeted micronutrient supplementation in disaster relief and food aid measures even after the period of natural disaster emergency.
Flood hazard characteristics play a key role in flood-induced mortality. Therefore, it is crucial to evaluate the associations between these factors and flood fatalities. This case-control study was performed in the flood-prone regions of Iran with recorded flood-induced mortality rates during 2005-2018. In total, 369 subjects completed the survey (123 cases and 246 controls); they were selected from 12 provinces and 30 cities. In this study, descriptive and analytical analyses were carried out to measure flood hazard characteristics. Afterward, the correlation of flood hazard characteristics with flood-induced mortality was measured. According to the descriptive analysis, most deaths occurred in summer, during hours of darkness, in areas with one- and five-year flood return periods, and in floods with short rainfall durations. In addition, the spatial analysis demonstrated that most deaths occurred in flash floods, floods accompanied by bad weather, and floods with floating debris. The results of Chi-square and Fisher’s exact test also indicated significant correlations between darkness, flood return periods, flood behavior, floods with floating debris, bad weather, other hazards, and flood discharge with flood-induced mortality. According to the regression analysis, the variables of flood discharge over 500 m3/s, flash floods, nighttime floods, and floods with floating debris increased the risk of flood-induced mortality 3.64, 1.62, 3.34, and 1.06 times, respectively. Although changing flood hazard characteristics seems to be impossible, damages caused by floods can be decreased and the lives of people can be protected through appropriate preventive and managerial solutions, planning, training, promotion of preparedness, and timely warnings.
The role of climate driving zoonotic diseases’ population dynamics has typically been addressed via retrospective analyses of national aggregated incidence records. A central question in epidemiology has been whether seasonal and interannual cycles are driven by climate variation or generated by socioeconomic factors. Here, we use compartmental models to quantify the role of rainfall and temperature in the dynamics of snakebite, which is one of the primary neglected tropical diseases. We took advantage of space-time datasets of snakebite incidence, rainfall, and temperature for Colombia and combined it with stochastic compartmental models and iterated filtering methods to show the role of rainfall-driven seasonality modulating the encounter frequency with venomous snakes. Then we identified six zones with different rainfall patterns to demonstrate that the relationship between rainfall and snakebite incidence was heterogeneous in space. We show that rainfall only drives snakebite incidence in regions with marked dry seasons, where rainfall becomes the limiting resource, while temperature does not modulate snakebite incidence. In addition, the encounter frequency differs between regions, and it is higher in regions where Bothrops atrox can be found. Our results show how the heterogeneous spatial distribution of snakebite risk seasonality in the country may be related to important traits of venomous snakes’ natural history.
Assessing disaster impacts is the pathway to attain informed decision making to mitigate damages. Currently, these impacts are generally analyzed excluding the environmental consequences of disasters. Thus, this study proposes a novel quantitative method, named multi-dimensional damage assessment (MDDA), that integrates the disaster-related environmental impacts with economic and social losses. For this, Life Cycle Assessment was used to measure environmental impacts at the endpoint level for the human health area of protection. The unit of assessment used to merge the three damage dimensions was the disability-adjusted life year equivalent (DALYeq). The damages exerted by floods in Peru linked to El Nino in recent decades were selected as the main case study. Furthermore, other natural disasters (e.g., earthquakes) were included in the assessment for the sake of comparability. The results show that El Nino floods in Peru in 1982-83 and 1997-98 presented higher damage per capita, approximately 2.8 times higher, than the event in 2017. Additionally, the assessment showed that economic damages are the most relevant in El Nino floods, whereas social damages are those prevalent for earthquakes. The results demonstrate that MDDA is an effective measurement for the purpose of damage comparison and, therefore, to implement mitigation strategies. The proposed methodology will allow the development of disaster risk mitigation strategies that will cover all damage dimensions and enable the adoption of improved public policies. Finally, MDDA can be applied to compute any complex array of damages that humans may suffer or infringe as a consequence of their interaction with the environment.
The literature documents that individual behavior and climatic change have recently been given more and more space in the definition of company strategies. However, in terms of preparing for catastrophes, few inquiries have been made into the individual propensity to acquire insurance, especially in terms of People with Disabilities (PwD). In this study, we assess the effect of information on the propensity of heads of households to acquire home insurance against forms of natural disasters, particularly flooding. We conduct a survey of over 500 individuals, including blind individuals, to verify the intuition that there is a causal link between the existence of information and the willingness of individuals to acquire flood insurance. The results reveal that visually deficient individuals are approximately 300% more likely to buy this insurance than other individuals. However, when PwD have information regarding the potential risk and harm caused by floods, this marginal effect is attenuated.
People with visual impairments (PwVI) represent a heterogeneous social group who often experience significant disabling barriers in exercising their rights throughout their life course. Understanding dimensions of vulnerability of PwVI to disasters and climate change is an important issue to reduce the culture of neglected disasters. To date, few studies have analyzed visual impairment and disaster risk reduction (DRR) in the countries of Latin America and the Caribbean. This exploratory qualitative research project analyzed how to include PwVI in the DRR policies of Brazil. The research question is: how can we include PwVI in the discussion of DRR and climate change? The response to this question is part of a joint effort that involved a university, a hazard monitoring agency, and three institutions that work with PwVI. The three main results of the project are: (1) a mapping method to identify the exposure of PwVI to landslides and floods, and to create tactile risk maps tailored to them; (2) incorporating the voices of PwVI regarding their vulnerabilities and capacities with respect to disasters and climate change, achieved through shared interaction during 15 face to face interviews and one workshop attended by 100 people; and (3) an initiative of inclusive education to reduce some of the disabling barriers that intensify vulnerability.
People living in areas vulnerable to diseases caused by extreme climate change events, such as semiarid regions, tend to recognize them quickly and, consequently, develop strategies to cope with their effects. Our study investigated the perception of diseases by farmers living in the semiarid region of Northeastern Brazil and the adaptive strategies locally developed and used. To this end, the effect of the incidence and severity of locally perceived diseases on the frequency of adaptive responses adopted by the farmers was tested. The research was conducted in rural communities in the Pernambuco State, Northeastern Region of Brazil. Semi-structured interviews with 143 farmers were conducted to collect information about major drought and rainfall events, the perceived diseases related to these events, and the adaptive strategies developed to mitigate them. The incidence and severity of diseases perceived by farmers were calculated using the Participatory Risk Mapping method and the frequency of adaptive strategies. Our findings demonstrated that few climate change-related diseases were frequently mentioned by farmers, indicating low incidence rates. Among them, direct transmission diseases were the most frequently mentioned. Adaptive strategies to deal with the mentioned diseases related to prophylactic behavior were less mentioned, except if already utilized. Our model demonstrated that incidence was the only explanatory variable with a significant impact on the adaptive strategies used to deal with the effects of these risks on health. Our findings suggest that the estimated incidence of diseases should be considered in the development of predictive climate change models for government policy measures for the public health security of populations in areas of greater socio-environmental vulnerability.
The way newspapers frame infectious disease outbreaks and their connection to the environmental determinants of disease transmission matter because they shape how we understand and respond to these major events. In 2017, following an unexpected climatic event named “El Niño Costero,” a dengue epidemic in Peru affected over seventy-five thousand people. This paper examines how the Peruvian news media presented dengue, a climate-sensitive disease, as a public health problem by analyzing a sample of 265 news stories on dengue from two major newspapers published between January 1st and December 31st of 2017. In analyzing the construction of responsibility for the epidemic, I find frames that blamed El Niño Costero’s flooding and Peru’s poorly prepared cities and public health infrastructure as the causes of the dengue outbreak. However, when analyzing frames that offer solutions to the epidemic, I find that news articles call for government-led, short-term interventions (e.g., fogging) that fail to address the decaying public health infrastructure and lack of climate-resilient health systems. Overall, news media tended to over-emphasize dengue as requiring technical solutions that ignore the root causes of health inequality and environmental injustice that allow dengue to spread in the first place. This case speaks to the medicalization of public health and to a long history of disease-control programs in the Global South that prioritized top-down technical approaches, turning attention away from the social and environmental determinants of health, which are particularly important in an era of climate change.
The transmission of leptospirosis is conditioned by climatic variables. In northeastern Argentina leptospirosis outbreaks occur mainly in coincidence with periods of abundant precipitation and high hydrometric level. A Susceptible-Infectious-Recovered Epidemiological Model (SIR) is proposed, which incorporates hydroclimatic variables for the three most populated cities in the area (Santa Fe, Paraná and Rosario), during the 2009-2018 period. Results obtained by solving the proposed SIR model for the 2010 outbreak are in good agreement with the actual data, capturing the dynamics of the leptospirosis outbreak wave. However, the model does not perform very well in the last months of the year when isolated cases appear outside the outbreak periods, probably due to non- climatic factors not explicitly considered in the present version of the model. Nevertheless, the dynamic modeling of infectious diseases considering hydroclimatic variables constitutes a climatic service for the public health system, not yet available in Argentina.
The relationship between hydrometeorological disasters and the health of affected populations is still hardly discussed in Rio Grande do Sul (RS), Brazil. Hepatitis A is a disease that involves health and urban environment issue and is an avoidable disease. This study aims to analyze the relationship between flood areas and waterborne diseases, in this case, Hepatitis A. A database of confirmed cases of Hepatitis A and flood events in the municipality of Encantado-RS, Brazil between 2012 and 2014 was structured. These data were analyzed spatially from the kernel estimator of the occurrence points of Hepatitis A cases and correlated to the urban perimeter. It was verified that 44 cases were registered in the three months following the occurrence of flood, an increase of almost 300% in the records of Hepatitis A. The results identified that all the confirmed cases are in the urban area located in the floodplain. This reaffirms the importance of encouraging the formulation and implementation of policies to prevent outbreaks of waterborne diseases post hydrometeorological disaster.
The March 2015 extraordinary hydrometeomlogical event in the Andes cordillera caused severe floods in the southern Atacama Desert. One of the most affected cities was CopiapO (northern Chile) located downstream of the junction between the CopiapO river and its ephemeral tributary Quebrada Paipote. This work analyses the features of this catastrophic flood and relates them with the identified impacts. A large volume of water mixed with fine sediments overflowed the tributary channel generating a flood that affected 72% of the urban area. The rheological (velocity, density and flow regime) and sedimentary features of the flow reveal the occurrence of massive mudflows that infilled the space available inside the buildings, buried the streets with a sandy mud deposit of more than 30 cm medium thickness and collapsed the sewer network. The post-event survey carried out by the Ministry of Housing and Urban Planning (MINVU) was used for the development of fragility curves that allows modelling the probability of damage. Results indicate that the greatest probability of building damage is generated by the accumulation of sediments instead of by the flow depth. On the other hand, once the very fine grain sediments of the top of the deposit dried up, it increased the concentration of post-event suspension particulate matter, causing a health issue. This work highlights the need to understand mudflow processes and their consequences in arid environments to improve urban planning and mitigate future damages since their impacts strongly affect infrastructures and communities.
Background: Several studies have been conducted on the effects of floods on the health of the affected community. We aimed to determine the effects of floods as the most common disaster on hypertension (HTN) as one of the most common noncommunicable diseases (NCDs). Materials and Methods: Four databases including Medline, Scopus, Google Scholar, and ScienceDirect were searched with the search strategy protocol up to the end of June 2021 and with the keywords of flood and high blood pressure or hypertension. Grey literature database and websites of WHO, UNDRR, and PreventionWeb were also searched. After removing duplicate articles, abstracts of the relevant titles were reviewed, and eligible articles were included for full-text review. Finally, the study variables were extracted from selected articles. Results: The search strategy resulted in eight final relevant articles from 48,980 articles. All final articles noted meaningful effect of flood on high blood pressure. There was a positive correlation between anxiety level, property loss, financial loss, physical activity, use of alcoholic beverages, interruption of medication, and medical cares with HTN. Different studies have also reported long-term effects of flooding on blood pressure. Conclusions: The flood has significant effect on high blood pressure in affected population. However, cases of unknown HTN in the affected population should also be considered, so screening is recommended in the affected community.
BACKGROUND: Weather and climate-related disasters, including floods, impact undernutrition through multiple pathways, including food security, inadequate child care practices, and water and sanitation. This review aimed to provide systematic evidence of the impact of floods on undernutrition in children under five years of age in Low and Middle-income countries (LMICs). METHODS: We searched PubMed, Web of Science, Embase, MEDLINE, CINAHL and Scopus for peer-reviewed articles. Popline, WHO Library database (WHOLIS), the International Disaster database (EM-DAT), Food and Agriculture Organisation (FAO), UNICEF and Eldis were searched for grey literature articles. Database searches were first conducted in 2016 and updated in 2020. We included English language articles that reported the effect of floods on undernutrition outcomes in children under 5 years of age in LMICs, without limitation to study design and year of publication. The quality of selected studies was assessed using the National Institutes of Health (NIH) tool for Observational Cohort and Cross-Sectional Studies. RESULTS: Of the 5701 articles identified, 14 met our inclusion criteria. The review noted stunting as the most frequently reported significant form of undernutrition in flood-affected areas. Severe and recurrent floods showed the greatest impact on undernutrition. Due to weak and limited evidence, the study is inconclusive on the most significant forms within the short-term and intermediate periods following floods. On the other hand, stunting was noted as the most frequently reported significant form of undernutrition in the long-term period following floods. There was generally little evidence of the effect of floods on micronutrient deficiencies. Factors associated with child undernutrition in the flood-affected areas included age, gender, diarrhoea, maternal and paternal education, maternal age, household size, land ownership and socioeconomic status. Overall, the quality of the evidence was fairly weak, with the main challenge lying in the inability of the studies to establish causal pathways for the observed effects. CONCLUSIONS: The review suggests clear plans and strategies for preventing and reducing the long-term impact of floods on undernutrition in children under five years. Future research utilising long-term prospective data is indispensable to provide more robust evidence to guide better prevention measures, response decisions and interventions.
While it is well recognized that the frequency and intensity of flood events are increasing worldwide, the environmental, economic, and societal consequences of remobilization and distribution of pollutants during flood events are not widely recognized. Loss of life, damage to infrastructure, and monetary cleanup costs associated with floods are important direct effects. However, there is a lack of attention towards the indirect effects of pollutants that are remobilized and redistributed during such catastrophic flood events, particularly considering the known toxic effects of substances present in flood-prone areas. The global examination of floods caused by a range of extreme events (e.g., heavy rainfall, tsunamis, extra- and tropical storms) and subsequent distribution of sediment-bound pollutants are needed to improve interdisciplinary investigations. Such examinations will aid in the remediation and management action plans necessary to tackle issues of environmental pollution from flooding. River basin-wide and coastal lowland action plans need to balance the opposing goals of flood retention, catchment conservation, and economical use of water.
Flash flood risk assessment, a widely applied technology in preventing catastrophic flash flood disasters, has become the current research hotspot. However, most existing machine learning methods for assessing flash flood risk rely on a single classifier, which is suitable for processing small sets of sample data, but the resulting prediction accuracy and generalization ability are insufficient. Meanwhile, machine learning methods that integrate multiple classifiers are thus far unknown. Extreme Gradient Boosting (XGBoost) is an excellent algorithm for ensemble learning methods which has achieved remarkable results in many fields. It not only optimizes the algorithm but also automatically applies the CPU’s multi-threading to perform parallel calculations, thus greatly improving the model training speed and prediction accuracy. Therefore, this article introduces the XGBoost model for the assessment of flash flood risk, and then combines the two input strategies and the Least squares support vector machine (LSSVM) model to verify its optimal effect, thus proposing the XGBoost-based method for flash flood risk assessment. Subsequently, an attribution analysis was implemented to assess the possible errors of this approach; and finally, a county-level flash flood risk map for Yunnan Province, China, was generated based on the proposed method. The results demonstrate that: (1) XGBoost performs well, with an accuracy of 0.84 in the testing period, and its five indices (precision, recall, accuracy, kappa, and F-score) are all higher than those of LSSVM. (2) The XGBoost-based approach provided the reliable flash flood risk maps, which were validated by another flash flood inventory, although some errors may be attributed to critical environmental factors and statistical disaster location accuracy. (3) The high-risk counties (including high-risk and highest-risk) accounted for 40.3%, with the highest-risk counties mainly concentrated in southeastern Yunnan. This article further addresses the limitations of XGBoost (e.g., as a time-consuming greedy algorithm, the non-necessity of multi-threaded optimization). All of the above results indicate that the XGBoost-based method is an effective method for obtaining high-quality county-level flash flood risk maps, which contributes to the theoretical basis for ongoing county-level flash flood prevention in China.
INTRODUCTION: As a result of destruction and lack of access to vital infrastructures and mental stress, disasters intensify cardiovascular diseases (CVDs) and hence management of CVDs becomes more challenging. The aim of this study is investigating incidence and prevalence of CVDs, morbidity and mortality of CVDs, treatment and management of CVDs at the time of natural disasters. METHODS: In the present systematic review, the articles published in English language until 28. 11. 2020, which studied CVDs in natural disasters were included. The inclusion criteria were CVDs such as myocardial infarction (MI), acute coronary syndrome (ACS), hypertension (HTN), pulmonary edema, and heart failure (HF) in natural disasters such as earthquake, flood, storm, hurricane, cyclone, typhoon, and tornado. RESULT: The search led to accessing 4426 non-duplicate records. Finally, the data of 104 articles were included in quality appraisal. We managed to find 4, 21 and 79 full text articles, which considered cardiovascular diseases at the time of flood, storm, and earthquake, respectively. CONCLUSION: Prevalence of CVD increases after disasters. Lack of access to medication or lack of medication adjustment, losing home blood pressure monitor as a result of destruction and physical and mental stress after disasters are of the most significant challenges of controlling and managing CVDs. By means of quick establishment of health clinics, quick access to appropriate diagnosis and treatment, providing and access to medication, self-management, and self-care incentives along with appropriate medication and non-medication measures to control stress, we can better manage and control cardiovascular diseases, particularly hypertension.
Climate change is increasing the frequency and intensity of extreme precipitation events, the impacts of which disproportionately impact urban populations. Pluvial flooding and flooding related sewer backups are thought to result in an increase in potentially hazardous human-pathogen encounters. However, the extent and nature of associations between flooding events and non-communicable respiratory diseases such as chronic bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) are not well understood. This research seeks to characterize the state of research on flooding and NCRDs through a systematic review of the scientific literature. We conducted a systematic search of PubMed, Web of Science, and Scopus for published scholarly research papers using the terms flooding, monsoon, and tropical storm with terms for common NCRDs such as asthma, COPD, and chronic bronchitis. Papers were included if they covered research studies on individuals with defined outcomes of flooding events. We excluded review papers, case studies, and opinion pieces. We retrieved 200 articles from PubMed, 268 from Web of Science and 203 from Scopus which comprised 345 unique papers. An initial review of abstracts yielded 38 candidate papers. A full text review of each left 16 papers which were included for the review. All papers except for one found a significant association between a severe weather event and increased risk for at least one of the NCRDs included in this research. Our findings further suggest that extreme weather events may worsen pre-existing respiratory conditions and increase the risk of development of asthma. Future work should focus on more precisely defining measure of health outcomes using validated tools to describe asthma and COPD exacerbations. Research efforts should also work to collect granular data on patients’ health status and family history and assess possible confounding and mediating factors such as neighborhood water mitigation infrastructure, housing conditions, pollen counts, and other environmental variables.
OBJECTIVE: Information gaps that accompany hurricanes and floods limit researchers’ ability to determine the impact of disasters on population health. Defining key use cases for sharing complex disaster data with research communities and facilitators, and barriers to doing so are key to promoting population health research for disaster recovery. MATERIALS AND METHODS: We conducted a mixed-methods needs assessment with 15 population health researchers using interviews and card sorting. Interviews examined researchers’ information needs by soliciting barriers and facilitators in the context of their expertise and research practices. Card sorting ranked priority use cases for disaster preparedness. RESULTS: Seven barriers and 6 facilitators emerged from interviews. Barriers to collaborative research included process limitations, collaboration dynamics, and perception of research importance. Barriers to data and technology adoption included data gaps, limitations in information quality, transparency issues, and difficulty to learn. Facilitators to collaborative research included collaborative engagement and human resource processes. Facilitators to data and technology adoption included situation awareness, data quality considerations, adopting community standards, and attractive to learn. Card sorting prioritized 15 use cases and identified 30 additional information needs for population health research in disaster preparedness. CONCLUSIONS: Population health researchers experience barriers to collaboration and adoption of data and technology that contribute to information gaps and limit disaster preparedness. The priority use cases we identified can help address information gaps by informing the design of supportive research tools and practices for disaster preparedness. Supportive tools should include information on data collection practices, quality assurance, and education resources usable during failures in electric or telecommunications systems.
Theories of epidemiologic transition analyze the shift in causes of mortality due to changes in risk factors over time, and through processes of urbanization and development by comparing risk factors between countries or over time. These theories do not account for health inequities such as those resulting from environmental injustice, in which minority and lower income residents are more likely to be exposed to environmental hazards or have less access to environmental goods. Neighborhoods with histories of environmental injustice are also at risk for gentrification as they undergo environmental improvements and new greening projects. We aimed to understand how environmental injustice, urban renewal and green gentrification could inform the understanding of epidemiologic risk transitions. We examined 7 case neighborhoods in cities in the United States and Western Europe which were representative in terms of city region and type, which 1) had experienced a history of environmental injustice and 2) exhibited evidence of recent processes of urban renewal and/or gentrification. In each city, we conducted semi-structured qualitative interviews (n = 172) with city representatives, activists, non-profits, developers and residents. Respondents reported health implications of traditional (heavy pollutants, poor social conditions), transitional (decontamination, new amenities), new (gentrification, access to amenities), and emerging (displacement, climate-related risks, re-emergence of traditional exposures) exposures. Respondents reported renewed, complexified and overlapping exposures leading to poor mental and physical health and to new patterns of health inequity. Our findings point to the need for theories of environmental and epidemiologic risk transitions to incorporate analysis of trends 1) on a city-scale, acknowledging that segregation and patterns of environmental injustice have created unequal conditions within cities and 2) over a shorter and more recent time period, taking into account worsening patterns of social inequity in cities.
Urban floods are becoming more and more intense and frequent allover the world. Extreme events are the main triggering factors of such floods, and merit attention for what concerns the urban planning and emergency strategies. Numerical models aimed at investigating the optimal paths for evacuees escaping a flooded urban environment may be used by local authorities to properly understand how to improve people safety and mitigate the flood risk. Implementation of empirical laws in such models to describe the people stability in flooded areas is thus crucial to understand the behavior of evacuees and rescuers during emergency conditions. Laboratory experiments have been undertaken using a physical model representing a human body at quasi-natural scale, towed by an electrical engine in the water at rest. This represents a novel laboratory approach which exploits a non-inertial reference frame in motion with the model. The experimental results, obtained using different combinations of water depth and flow speed, have led to empirical laws which outline the stability conditions occurring when either the model front or the model back faces the flow, these respectively corresponding to Backward Toppling Instability (BTI) and Forward Toppling Instability (FTI). Such laws have been found through comparison with reference literature works, using various statistical methods. The FTI condition has been seen to largely improve the human stability compared to BTI, in contrast to the results of previous literature works, which stated an overall similarity between the results of the two toppling conditions. To better understand the role of the water flow during the different tests, hydraulic forces and moments have been measured. It has been seen that dynamic and static effects are comparable during high-speed conditions, especially due to a relevant fluid-model interaction and an increase of the water-surface level, while dynamic effects are negligible during low-speed conditions. The results of the present contribution can represent an important step forward for the numerical models applied to the framework of urban and emergency planning.
Potentially toxic elements (PTEs) in urban soil environments pose a noticeable risk to both ecosystem and human health; however, only a fraction of the elemental content is available for biota. To better know the potential risk of PTEs in the urban soil environment, geochemical fractionation, bioaccessibility, and potential bioavailability of four PTEs (Cd, Cu, Pb, and Zn) were investigated by the combined use of different methods. The results showed that a high non-residual chemical fraction is related to a high bioavailability of the selected elements. The ranges of labile concentration of Cu, Zn, Cd and Pb in all sampling sites measured by diffusive gradients in thin films (DGT) were 3.5-18.0, 14.2-26.5, 0.09-1.0, and 1.8-15.7 μg/L, respectively. The high non-residual contents pointed out a serious hazard to the urban environment. The bioaccessible concentrations in gastric and lung phases were closely positively correlated with DGT-measured content (r = 0.63-0.99, p < 0.05), suggesting the potential use of DGT for the prediction of PTEs risk to human health. Moreover, the correlation of DGT results with the soluble and reducible fractions of PTEs may allow DGT use for quick screenings of the PTEs fraction potentially mobilizable during flooding events in urban soil environments. Our study suggests that combing DGT, bioaccessibility and biogeochemical fractionation could provide a more accurate assessment of the urban environmental quality and be helpful for pollution control and urban planning.
This study presents a global explanatory analysis of the interplay between the severity of flood losses and human presence in floodplain areas. In particular, we relate economic losses and fatalities caused by floods during 1990-2000, with changes in human population and built-up areas in floodplains during 2000-2015 by exploiting global archives. We found that population and built-up areas in floodplains increased in the period 2000-2015 for the majority of the analyzed countries, albeit frequent flood losses in the previous period 1990-2000. In some countries, however, population in floodplains decreased in the period 2000-2015, following more severe floods losses that occurred in the period 1975-2000. Our analysis shows that (i) in low-income countries, population in floodplains increased after a period of high flood fatalities; while (ii) in upper-middle and high-income countries, built-up areas increased after a period of frequent economic losses. In this study, we also provide a general framework to advance knowledge of human-flood interactions and support the development of sustainable policies and measures for flood risk management and disaster risk reduction.
Deaths and property damage from floods have increased drastically in the past two decades due to various reasons such as increased populations, unplanned developments, and climate change. Such losses from floods can be reduced by issuing timely early warnings and through effective response mechanisms based on situational intelligence during emerging flood situations. This paper presents the outcome of a literature review that was conducted to identify the types and sources of the intelligence required for flood warning and response processes as well as the technology solutions that can be used for offering such intelligence. Twenty-seven different types of intelligence are presented together with the technologies that can be used to extract such intelligence. Furthermore, a conceptual architecture that illustrates how relevant technology solutions can be used to extract intelligence at various stages of a flood cycle for decision-making in issuing early warnings and planning responses is presented.
No abstract available.
Water supply and wastewater systems are essential infrastructure affected by floods. Additional risk is posed in developing countries, where access to sanitation is not universal. Few studies assess the flood risk to the sanitation-health nexus. Therefore, this study aims to present a theoretical and general framework for assessing the resilience of flood-sanitation-public health nexus in urban environments, composed by risk estimation and risk management assessment. The framework was developed from a system analysis approach focusing on central supply systems. Regarding risk assessment, the main vulnerability and exposure factors identified were land use, social vulnerability, coverage of sanitation systems, occurrence of waterborne diseases, number of people affected by floods and intersection with the flood map. From the risk management assessment stage three main typologies of trade-offs and synergies were identified: urban territorial planning versus runoff control, water quality versus sanitation infrastructure and flood management policy versus social behavior.
Modelling urban inundation and its associated health implications is numerous in its many applications. Flood modelling research contains a broad wealth of material, and microbial risk assessment has gained more popularity over the last decade. However, there is still a relative lack of understanding of how the microbial risk can be quantified from urban sewer flooding. This article intends to review the literature encompassing contemporary urban flood modelling approaches. Hydrodynamic and microbial models that can be applied for quantitative microbial risk assessment will be discussed. Consequently, urban sewer flooding will be the focus. This review found that the literature contains a variety of different hazards posed by urban flooding. Yet, far fewer examples encompass microbial risk from sewer system exceedance. To date, there is no evidence of a perfect model or technique, to carry out a quantitative microbial risk assessment from hydrodynamic simulations. The literature details many different methods. We intend to detail the advantages and limitations of each method. Along similar lines, hydraulic data constitutes a large part of the uncertainty which is inherent to this research field. Many studies in the literature detail data paucity and uncertainty in input data. As such, any advancement in this discipline will very likely aid future research.
Leptospirosis is a quintessential one health disease of humans and animals caused by pathogenic spirochetes of the genus Leptospira. Intra- and interspecies transmission is dependent on 1) reservoir host animals in which organisms replicate and are shed in urine over long periods of time, 2) the persistence of spirochetes in the environment, and 3) subsequent human-animal-environmental interactions. The combination of increased flooding events due to climate change, changes in human-animal-environmental interactions as a result of the pandemic that favor a rise in the incidence of leptospirosis, and under-recognition of leptospirosis because of nonspecific clinical signs and severe signs that resemble COVID-19 represents a “perfect storm” for resurgence of leptospirosis in people and domestic animals. Although often considered a disease that occurs in warm, humid climates with high annual rainfall, pathogenic Leptospira spp have recently been associated with disease in animals and humans that reside in semiarid regions like the southwestern US and have impacted humans that have a wide spectrum of socioeconomic backgrounds. Therefore, it is critical that physicians, veterinarians, and public health experts maintain a high index of suspicion for the disease regardless of geographic and socioeconomic circumstances and work together to understand outbreaks and implement appropriate control measures. Over the last decade, major strides have been made in our understanding of the disease because of improvements in diagnostic tests, molecular epidemiologic tools, educational efforts on preventive measures, and vaccines. These novel approaches are highlighted in the companion Currents in One Health by Sykes et al, AJVR, September 2022.
BACKGROUND: Climate change is expected to increase the frequency of flooding events. Although rainfall is highly correlated with mosquito-borne diseases (MBD) in humans, less research focuses on understanding the impact of flooding events on disease incidence. This lack of research presents a significant gap in climate change-driven disease forecasting. OBJECTIVES: We conducted a scoping review to assess the strength of evidence regarding the potential relationship between flooding and MBD and to determine knowledge gaps. METHODS: PubMed, Embase, and Web of Science were searched through 31 December 2020 and supplemented with review of citations in relevant publications. Studies on rainfall were included only if the operationalization allowed for distinction of unusually heavy rainfall events. Data were abstracted by disease (dengue, malaria, or other) and stratified by post-event timing of disease assessment. Studies that conducted statistical testing were summarized in detail. RESULTS: From 3,008 initial results, we included 131 relevant studies (dengue n = 45, malaria n = 61, other MBD n = 49). Dengue studies indicated short-term ( < 1 month) decreases and subsequent (1-4 month) increases in incidence. Malaria studies indicated post-event incidence increases, but the results were mixed, and the temporal pattern was less clear. Statistical evidence was limited for other MBD, though findings suggest that human outbreaks of Murray Valley encephalitis, Ross River virus, Barmah Forest virus, Rift Valley fever, and Japanese encephalitis may follow flooding. DISCUSSION: Flooding is generally associated with increased incidence of MBD, potentially following a brief decrease in incidence for some diseases. Methodological inconsistencies significantly limit direct comparison and generalizability of study results. Regions with established MBD and weather surveillance should be leveraged to conduct multisite research to a) standardize the quantification of relevant flooding, b) study nonlinear relationships between rainfall and disease, c) report outcomes at multiple lag periods, and d) investigate interacting factors that modify the likelihood and severity of outbreaks across different settings. https://doi.org/10.1289/EHP8887.
In recent years, natural disasters such as hurricanes and floods have become more frequent, which usually leads to the pollution of drinking water. Drinking contaminated water may cause public health emergencies. The demand for healthy drinking water in disaster-affected areas is huge and urgent. Therefore, it is necessary to develop a simple water treatment technology suitable for emergencies. Inspired by nature, a fractional spray method was used to prepare graded purification material under mild conditions. The material consists of a calcium alginate isolation layer and a functional layer composed of calcium alginate, polyethylenimine, and water-based polyurethane, which can purify complex pollutants in water such as heavy metals, oils, pathogens, and micro/nano plastics through percolation. It does not require additional energy and can purify polluted water only under gravity. A disposable paper cup model was also designed, which can be used to obtain purified water by immersing in polluted water directly without other filtering devices. The test report shows that the water obtained from the paper cup was deeply purified. This design makes the material user-friendly and has the potential as a strategic material. This discovery can effectively improve the safety of drinking water after disasters and improve people’s quality of life.
INTRODUCTION: Exposure to natural hazards such as fire, drought, floods, and earthquakes can have negative impacts on physical and mental health and wellbeing. The social and structural factors contributing to individual and community vulnerability also influence responses to disaster and the resulting consequences on health and wellbeing. Experiencing disasters like bushfires amplifies the impacts of inequality, magnifying existing disparities and contributing to additional psychological burdens of grief, trauma and adaptive challenge. There is a need to understand how vulnerability can influence responses to disaster, and to identify factors that develop and foster resilience in the context of increasing disasters and vulnerability. MATERIALS AND METHODS: This protocol will describe the methodology of two scoping reviews: the first will describe the mental health outcomes of vulnerable populations after droughts and bushfires; the second will identify and describe strategies that promote community resilience in vulnerable populations in the context of a disaster. A thorough search will be conducted in relevant databases. Studies will be limited to English language. The reviews will be reported using the 22-item checklist for the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Methodological quality of the included papers will be assessed using the Joanna Briggs Institute’s critical appraisal tools. RESULTS & CONCLUSIONS: The two scoping reviews described in this protocol will have broad relevance in the context of increasing and intensifying disasters, and will especially consider the compounded impact of disaster on vulnerable communities. Findings will contribute directly to the design and implementation of solutions to improve post-disaster health and wellbeing and community resilience.
Responding to infrastructural damage in the aftermath of natural disasters at a national, regional, and local level poses a significant challenge. Damage to road networks, clean water supply, and sanitation infrastructures, as well as social amenities like schools and hospitals, exacerbates the circumstances. As safe water sources are destroyed or mixed with contaminated water during a disaster, the risk of a waterborne disease outbreak is elevated in those disaster-affected locations. A country such as Haiti, where a large quantity of the population is deprived of safe water and basic sanitation facilities, would suffer more in post-disaster scenarios. Early warning of waterborne diseases like cholera would be of great help for humanitarian aid, and the management of disease outbreak perspectives. The challenging task in disease forecasting is to identify the suitable variables that would better predict a potential outbreak. In this study, we developed five (5) models including a machine learning approach, to identify and determine the impact of the environmental and social variables that play a significant role in post-disaster cholera outbreaks. We implemented the model setup with cholera outbreak data in Haiti after the landfall of Hurricane Matthew in October 2016. Our results demonstrate that adding high-resolution data in combination with appropriate social and environmental variables is helpful for better cholera forecasting in a post-disaster scenario. In addition, using a machine learning approach in combination with existing statistical or mechanistic models provides important insights into the selection of variables and identification of cholera risk hotspots, which can address the shortcomings of existing approaches.
Why have some countries done significantly better than others in fighting the Covid-19 pandemic? Had some countries been better prepared than others? This paper attempts to shed light on these questions by examining the role of climate risk and culture in explaining the cross-country variation in the Covid-19 mortality, while controlling for other potential drivers. In our analysis, we consider climate risk, readiness to climate change and individualism as main indicators reflecting the climate and culture status of individual countries. Using data from 110 countries, we find that the greater the climate risk; the lower the readiness to climate change and the more individualistic the society, the higher the pandemic mortality rate. We also present a series of sensitivity checks and show that our findings are robust to different specifications, alternative definitions of the mortality rate; and different estimation methods. One policy implication arising from our results is that countries that were better prepared for the climate emergency were also better placed to fight the pandemic. Overall, countries in which individuals look after each other and the environment, creating sustainable societies, are better able to cope with climate and public health emergencies.
The present paper aims at verifying the awareness and preparedness of urban and local planners to cope with NaTech risk, together with the availability of dedicated tools. Since most of the natural events that can trigger technological hazards are influenced by climate change (i.e. flood, heavy rains, storms, etc.), NaTech risk is expected to be strongly increasing in the next years. However, dedicated NaTech planning actions and methods or tools to support them are still rarely available. The requirements of European Adaptation Strategy for Climate were examined considering the issues posed by the Seveso III Directive in terms of NaTech, focusing on the strategies adopted in the European countries, and in particular in Italy. Based on such analysis, a ‘NaTech tool’ dedicated to local planners was developed. Practical and easy to use methods and procedures were proposed in order to allow the use of the method by the local authorities, in the absence of sectorial experts.
BACKGROUND: The purpose of this study was to describe and analyse the most severe casualties from the flash flood and mudslides occurring on 14 July 2021 in Germany, focusing on patients who were treated in the closest and largest level I trauma centre in the region the disaster occurred. METHODS: A single-centre retrospective study design was employed, and all patients treated because of the flooding and mudslides who needed inpatient treatment were documented. Data on each patient’s demographic characteristics, type of injury, number of surgeries, duration of hospitalisation, operation time, revision rate, injury severity score (ISS), and complications were collected. The primary outcome measure was status at discharge. RESULTS: Within the first week after the flood, a total of 63 patients were documented. Forty-one patients were treated on an outpatient basis in the emergency unit, and 22 patients were hospitalised. Of those hospitalised, 15 patients needed surgical treatment in the operation theatre. The most common injuries were fractures of the lower extremity (n = 7) and soft tissue wounds (n = 4). Overall, 20 surgeries were performed; the mean hospital stay was 7.2 ± 6.4 days, and the mean ISS was 5.7 ± 2.7. CONCLUSION: The July 2021 flood disaster was one of the largest in German history. The included patients showed complex injuries of various types. Because of the effects of climate change, orthopaedic surgeons might face higher numbers of casualties affected by natural disasters. Learning more about the management and profile of these injuries can become a future challenge for orthopaedic and trauma surgeons.
In addition to global population growth due to migration from rural areas to urban areas, population density is constantly increasing in certain regions, thereby necessitating the introduction of new settlements in these regions. However, in the selection of settlement areas, no sufficient preliminary examinations have been conducted; consequently, various natural disasters may cause significant life and property losses. Herein, the most suitable settlement areas were determined using GIS (geographic information systems) in Canik District, where the population is continuously increasing. Therefore, this study aimed to incorporate a new perspective into studies on this subject. Within the scope of the study, landslide and flood risks, which are among the most important natural disasters in the region, were primarily evaluated, and high-risk areas were determined. Elevation, slope, aspect, curvature, lithology, topographic humidity index (TWI), and proximity to river parameters were used to produce flood susceptibility maps. A digital elevation model (DEM) of the study area was produced using contours on the 1/25,000 scaled topographic map. The elevation, slope, aspect, curvature, and TWI parameters were produced from the DEM using the relevant analysis routines of ArcGIS software. The raster map of each parameter was divided into 5 subclasses using the natural breaks classification method. In the reclassified raster maps, the most flood-sensitive or flood-prone subclasses were assigned a value of 5, and the least sensitive subclasses were assigned a value of 1. Then, the reclassified maps of the 7 parameters were collected using the “map algebra” function of ArcGIS 10.5 software, and the flood susceptibility index (FSI) map of the study area was obtained. The flood susceptibility map of the study area was obtained by dividing the FSI into 5 subclasses (very low, low, moderate, high, and very high) according to the natural breaks classification method. Thereafter, suitable and unsuitable areas in terms of biocomfort, which affects people’s health, peace, comfort, and psychology and is significant in terms of energy efficiency, were determined. At the last stage of the study, the most suitable settlement areas that were suitable in terms of both biocomfort and low levels of landslide and flood risks were determined. The calculated proportion of such areas to the total study area was only 2.1%. Therefore, because these areas were insufficient for the establishment of new settlements, areas that had low landslide and flood risks but were unsuitable for biocomfort were secondarily determined; the ratio of these areas was calculated as 56.8%. The remaining areas were inconvenient for the establishment of settlements due to the risk of landslides and floods; the ratio of these areas was calculated as 41.1%. This study is exemplary in that the priority for the selection of settlement areas was specified, and this method can be applied for selecting new settlements for each region considering different criteria. Due to the risk of landslides or flooding in the study area, the areas unsuitable for establishing a settlement covered approximately 41.1% of the total study area. The areas that had low flood and landslide risks but were suitable for biocomfort constituted only 2.1% of the study area. In approximately 56.8% of the study area, the risk of landslides or floods was low, and these areas were unsuitable in terms of biocomfort. Therefore, these areas were secondarily preferred as settlement areas. The most suitable areas for settlements constituted only 0.19% of the total study area, and these areas will not be able to meet the increasing demand for settlement area. Therefore, it is recommended to select areas that do not have the risk of landslides and floods but are unsuitable for biocomfort. This study reveals that grading should be performed in the selection of settlement areas. When choosing a settlement area in any region, possible natural disasters in the region should be identified first, and these disasters should be ordered in terms of their threat potential. Moreover, biocomfort areas suitable for settlements should be considered. In the next stages of settlement area selection, the criteria that affect the peace and comfort of people, such as distance to pollution sources, distance to noise sources, and proximity to natural areas, should also be evaluated. Thus, a priority order should be created for the selection of settlement areas using various other criteria.
BACKGROUND: Large-scale epidemics of haemorrhagic fever with renal syndrome (HFRS) have been reported mostly in Asia and Europe, with around 100,000 people affected each year. In the Southeast Europe, Balkan region, HFRS is endemic disease with approximately 100 cases per year. Our aim was to describe epidemiological characteristics of HFRS in five Western Balkan (WB) countries and to describe correlation between HFRS incidence and major meteorological event that hit the area in May 2014. METHODS: National surveillance data of HFRS from Bosnia and Herzegovina, Croatia, Montenegro, North Macedonia and Serbia obtained from 1 January 2006 to 31 December 2015 were collected and analysed. RESULTS: In a 10-year period, a total of 1,065 HFRS patients were reported in five WB countries. Cumulative incidence rate ranged from 0.05 to 15.80 per 100.000 inhabitants (in North Macedonia and Montenegro respectively). Increasing number of HFRS cases was reported with a peak incidence in three specific years (2008, 2012, and 2014). Average incidence for the entire area was higher in males than females (5.63 and 1.90 per 100.000 inhabitants respectively). Summer was the season with the highest number of cases and an average incidence rate of 1.74/100.000 inhabitants across 10-year period. Haemorrhagic fever with renal syndrome incidence was significantly increased (7.91/100.000 inhabitants) in 2014, when a few months earlier, severe floods affected several WB countries. A strong significant negative correlation (r = -.84, p < .01) between the monthly incidence of HFRS and the number of months after May's floods was demonstrated for the total area of WB. CONCLUSION: Our findings demonstrate that the HFRS incidence had similar distribution (general, age, sex and seasonality) across majority of the included countries. Summer was the season with the highest recorded incidence. Common epidemic years were detected in all observed countries as well as a negative correlation between the monthly incidence of HFRS and the number of months after May's cyclone.
Background: Children and adolescents are considered to be particularly vulnerable to the psychological effects of climate change, such as extreme weather events. What are the protective factors and stressors for the mental health of the young population after extreme weather events in Germany? Methods: Nine semi-structured interviews with representatives of occupational groups providing care to children, adolescents, and political stakeholders were conducted in Simbach am Inn, a German town affected by flooding in 2016. The interviews were analyzed using qualitative content analysis according to Mayring. Results: The interviews show that the parents’ dealing with what they had experienced and the concern for their relatives were the most influential stressors for children and adolescents. As protective factors, they felt that conversations with familiar people and restoring a certain “normality” were particularly important. The interviewees described both, the time of the flooding, and the time after the initial state of shock had subsided, as particularly stressful. Consequently, the experts reported on children and adolescents acutely complaining of fear, helplessness, and extreme tension. Nevertheless, the demand for psychological care increased only slightly after the flooding in Simbach am Inn. Conclusion: The social environment of children and adolescents is essential for their psychological well-being after an extreme weather event. Research, especially on children and adolescents who have already been affected, must increase in order to be able to describe influencing factors even more precisely, to protect individuals from adverse mental health effects, and to identify healthcare requirements.
Demand for reducing mental health impacts from flooding through collective flood defence is elicited using a contingent valuation method with a sequential hypothetical scenario, which accounts for human resilience and experience. A two-step model fits the survey data: it combines a binary sample selection rule to distinguish protesters and participants with a Tobit model to accommodate true zero responses among participants. Results show that non-symptoms-specific information on mental health risk may bias the willingness to pay downward. Risk-averse individuals who have taken self-insurance protection measures are willing to pay for additional protection through collective defence. Feelings, such as worries and anxiety related to flooding, drive the demand, which supports the risk-as-feelings hypothesis for mental health protection from flooding. Inexperience rather than experience of flooding is found to increase demand, which indicates that individual mental resilience to flooding may increase after an event as posited by the inoculation hypothesis.
This exploratory study empirically shows how community social capital is related to post-disaster depression, whereas most disaster mental health research has focused on posttraumatic stress disorder. We tested the validity of earlier found multilevel social and individual mechanisms of posttraumatic stress for symptoms of post-disaster depression. We used data (n = 231) from a community study after a flood in Morpeth (2008), a rural town in northern England. At the salutary community level, our multilevel analyses showed that, in communities with high social capital, individuals employ less individual social support and coping effort, which protects individuals from developing symptoms of depression. Yet, on the ‘dark’ individual level of our model, we found that perceiving the disaster as less traumatic after a year was related to more feelings of depression in contrast to previous findings for posttraumatic stress. Our explanation of this finding is that, when the appraisal of the disaster as threatening fades into the background, individuals may perceive the full scope of the disaster aftermath and start to feel depressed. We also found that more social support is related to more depression. Although depressed people may attract or receive more social support, this social support can paradoxically become disabling by reinforcing a sense of dependence, thereby undermining self-esteem and leading to feelings of helplessness. Our results imply that to curb post-disaster depression, boosting community level social capital may be an important starting point for building resilience. At the same time, interventionists need to identify risk groups for whom the stressful experience becomes less intrusive and who experience the burden of dependency on an unequal relationship with ones’ social inner circle.
OBJECTIVE: Gender differences in posttraumatic stress disorder (PTSD) prevalence and severity are well established; there is also growing evidence that men and women develop PTSD symptoms differently. This article aims to examine gender differences in the relationship between PTSD symptoms and personality traits according to the Five Factor model (FFM), based on the data from different studies conducted in Poland. METHOD: The meta-analysis method and path analyses were conducted on the data from seven studies, including 1,182 women and 1,150 men. Five studies were carried out among motor vehicle accident survivors, one from fire and flood victims. All of the studies had a cross-sectional design. RESULTS: All FFM traits were significantly related to PTSD symptoms. Neuroticism showed the strongest relationship. Further analyses revealed a moderated mediation of this relationship: It was stronger for men and mediated by peritraumatic emotions and dissociation for women. CONCLUSIONS: The results indicate that PTSD development is mediated by peritraumatic factors, but this mediation is moderated by gender. Men with higher Neuroticism are at particular risk of developing PTSD. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
Many risk factors for PTSD have been identified in flood victims. Yet, some have been under-explored, like cognitive coping, which has been identified as a risk factor for PTSD for other traumatic events. Moreover, while flooding can affect places that are important to individuals (e.g. their home and neighbourhood), the role of sense of place in PTSD has been neglected. The objective of this research is to investigate the potential role of under-explored individual and situational risk factors in PTSD in flood victims. To this end, the following var-iables were measured in 79 French flood victims: sense of place (with sense of place scale), cognitive coping (with CERQ), and PTSD (with PCL-5). Results showed that the more individuals use inappropriate cognitive emotional regulation strategies, the more attached they are to their home and city, and the higher their PTSD scores. These results can help to target vulnerable people and improve care.
Background: Disasters negatively impact mental health and well-being. Studying how people adapt and recover after adversity is crucial for disaster preparedness and response. Objective: This study examined how differentially affected communities harness their resources to adapt to the aftermath of a flood. We predicted that stronger individual, interpersonal, and community resources protect against psychosocial resource loss and, through that, are related to fewer symptoms of posttraumatic stress and depression and higher life satisfaction. We also predicted that these effects would be stronger in a flooded community, compared to a threatened, but non-flooded community. Method: Participants were randomly sampled community members from two neighbouring municipalities. One municipality was severely flooded during the 2014 floods in South East Europe (affected community, n (a) = 223), the other was threatened but not flooded (comparison community, n (c) = 224). Interviews were conducted one and a half years after the disaster using the Connor-Davidson Resilience Scale 10-item version, the Multidimensional Scale of Perceived Social Support, the Community Resources Scale, the Psychosocial Resource Loss Scale, the PTSD Checklist for DSM-5, the Center for Epidemiological Studies Depression Scale Revised and the Satisfaction with Life Scale. Results: Stronger individual, interpersonal, and community resources were found to be related to better post-disaster outcomes directly and indirectly through psychosocial resource loss. In the affected community, interpersonal resources and community social capital and engagement were stronger predictors of positive adaptation. In the comparison community, community economic development and trust in community leadership were more important. Conclusion: This study provides evidence that people affected by disasters can harness their individual, interpersonal, and community resources to recover and adapt. Post-disaster interventions should aim to strengthen family and community ties, thus increasing available social support and community connectedness.
BACKGROUND: Natural disasters are typically associated with the emergence of infectious diseases. On 15 June 2010, severe storms caused flooding in the Var department (France). A rumour about increased risk of Staphylococcusaureus skin infections after bathing in the sea began to circulate on Internet a few days after the floods. The aim of this study was to compare the rumour with the true incidence of cases of infection. METHODS: Since 1999, we have been conducting a prospective survey of S. aureus skin infections in our hospital to study their clinical, laboratory and epidemiologic features. We compared data on cases of Staphylococcus skin infection recorded in our institution from 2008 to 2012. RESULTS: We found that there was no increase in S. aureus skin infections after the floods compared to the previous and subsequent years. CONCLUSION: We had a unique opportunity to check the rumoured increase in incidence of infectious disease with the true incidence. In our study, the fear of S. aureus skin infections following flooding proved to be unfounded.
Flash floods are a worldwide threat to humans, which is why they are being intensively studied using historical event records. As measurements and event data increase, databases are becoming increasingly important for flash flood research. However, the recent literature on flood databases lacks technical details as well as discussions about a suitable database design for scientific investigations. In this paper, we thus show how an event database for the investigation of heavy rain-induced flood occurrences can be created. Based on the HiOS dataset (a German dataset with similar to 23,800 flash flood and pluvial flood events), we exemplify the database design and explore the spatiotemporal characteristics of floods caused by heavy rain in Germany. We outline all aspects relevant to database setup: from database requirements and system architecture through table and attribute design to a key and relationship definition. Furthermore, we clarify why a spatial database with interfaces for GIS softwares should be chosen, why a damage-based event definition is preferable to a hydrometeorological definition, and how table attributes support differentiated analyses. By means of the database, we investigated frequency, temporal evolution, spatial distribution and patterns, fatalities and injuries, as well as the seasonality of heavy rain-induced floods in Germany. The results indicate that floods caused by heavy rain occur throughout Germany but with a tendency toward fewer events in the northern direction. Across the country, we identified seven hot spots in urbanized and mountainous regions. Although heavy rain-induced floods in Germany take place mostly between noon and late afternoon, most people are injured and killed in events starting in the evening. Our investigation indicates an increased incidence of flash flood and pluvial flood-related injuries and fatalities in the identified hot spots. Overall, we observe a pronounced summer seasonality of the heavy rain-induced flood events. This study highlights the importance of event databases for flash flood research and advances our understanding of heavy rain-induced flood occurrences in Germany.
Flash floods are one of the harshest natural hazards, having a wide range of substantial impacts for human and environmental health in the short-term and long-term. On 15 November 2017, a high-intensity storm caused a catastrophic flash flood event in the town of Mandra, a western, outer suburb of the Athens Metropolitan Area in Greece. In this study, we determine the aqua regia extractable concentrations of trace elements in residual sediments and associated soils after the flash flood and evaluate the fractionation of contaminants in geochemical compartments. Geochemical data are coupled with physicochemical parameter measurements and mineralogy to identify possible factors explaining the variability of trace element concentrations, while a dilute acid extraction is used to monitor changes of the reactive fraction of the trace elements over the term of 1 year following the flood event. Aqua regia concentrations in flood-deposited sediments reached values of 1 mg/kg (Cd), 24 mg/kg (Co), 183 mg/kg (Cr), 599mg/kg (Cu), 1080 mg/kg (Mn), 195 mg/kg (Ni), 122 mg/kg (Pb) and 945 mg/kg (Zn). Multivariate statistical techniques classified the elements according to their natural or anthropogenic origin. Trace elements of geogenic origin (As, Co, Cr, Mn, Ni) dominate in flood deposited material. The cluster of anthropogenic elements (Cd, Cu, Pb, Zn,) shows significant correlation with total organic carbon and magnetic susceptibility, while a significant seasonal variation has been observed for total organic carbon, Cd and Mn contents in the deposited sediments. Results allow a better understanding of the distribution of elements in the surface cover during and after catastrophic events in urban areas and provide useful information on the long-term exposure of the residents.
Intensive urbanization and related increase of impervious surfaces, causes negative impacts on the hydrological cycle, amplifying the risk of urban floods. These impacts can get even worse due to potential climate change impacts. The urban areas of the Simeto River Valley (SRV), the largest river valley in Sicily (Italy), have been repeatedly hit by intense rainfall events in the last decades that lead to urban flooding, causing several damages and, in some instances, threats to population. In this paper, we present the results of a 10-question survey on climate change and risk perception in 11 municipalities of the SRV carried out within the activities of the LIFE project SimetoRES, which allowed to collect 1143 feedbacks from the residents. The survey investigated: (a) the level of worry about climate change in relation to extreme storms, (b) elements of urban flooding risk preparedness: the direct experience of the residents during heavy rain events, their trust in a civil protection regional alert system, and their knowledge of the correct behavior in case of flood, and (c) the willingness of citizens to implement sustainable drainage actions for climate change adaptation in their own municipality and real estates. The results show that more than 52% of citizens has inadequate knowledge of the correct behavior during flooding events and only 30% of them feel responsible for mitigation of flooding risk. There is a modest willingness by the population to support the construction of sustainable urban drainage infrastructures. A statistical cross-analysis of the answers to the different questions, based on contingency matrices and conditional frequencies, has shown that a greater worry about climate change has no significant impact either on the behavior of people in dangerous situations occurring during flooding events or on the willingness to support financially sustainable solutions. These results suggest that to build a higher worry about climate change and related urban flooding risk is not sufficient to have better preparedness, and that more direct educative actions are necessary in the area.
Flood simulations are important for flood (fatality) risk assessment. This article provides insight into the sensitivity of flood fatality risks to the model resolution of flood simulations and to several uncertain parameters in the loss of life model used. A case study is conducted for river flooding in a polder in the Netherlands (the Bommelerwaard) where the Dutch approach for loss of life estimation is applied. Flood models with resolutions of 100, 25, and 5 m are considered. Results show locally increased mortality rates in higher resolution simulations nearby structures including road embankments, dikes, and culverts. This causes a larger maximum individual risk value (annual probability of death for a person due to flooding) which has consequences for safety standards based on the individual risk criterion. Mortality rate in the breach zone is also affected by representations of buildings as solid objects versus as roughness elements. Furthermore, changes in the loss of life estimation approach via alternative ways of including people’s behaviour, building characteristics, and age of the population, have a significant impact on flood fatality risk. Results from this study can be used to support future risk assessments and decision making with respect to safety standards.
Spring floods in Siberia annually affect local communities. Major urban settlements in the region implemented flood control structures, so rural areas take a heavy beating. In 2018, spring floods severely hit multiple communities in central Yakutia, exposing deficient flood prevention and risk management practices. Notably, Amga village, an important local center, was severely inundated. Hydrological analysis shows that the 2018 flood had a 50-yr return period, and was caused by an ice jam in a nearby channel bend where mid-channel sand bars impede ice movement during breakup. The cold spells of late April and early May in the middle section of the river promote ice-jam development, causing extreme water stage rise. Highest water stage is unrelated to either winter snow water equivalent or early May rainfall. Estimated tangible direct damage to the Amga community equals 5.1B ($81.5M) in 2018 prices, but only 0.13B ($2.1M), or 2.5% of this total, was reclaimed. A questionnaire survey revealed that most residents report important deterioration of drinking water quality and health after flooding. Residents respond positively to risk mitigation actions, implemented by the local and regional authorities, except ice dusting and cutting, and report minor activity of official sources in spreading information on flood progress.
Major floods in Spain in September 9-13, 2019 resulted in seven casualties and massive losses to agriculture, property and infrastructure. This paper investigates the utility of satellite data to: (1) characterize the event when input into a hydrological model, and to provide an accurate picture of the evolution of the floods; and (2) inform meteorologists in real time in order to complement model forecasts. It is shown that the precipitation estimates from the Global Precipitation Measurement (GPM) Core Observatory (GPM-CO, available since 2014) and the merged satellite estimates provide an extraordinary improvement over previous technologies to monitor severe hydrometeorological episodes in near real time. In spite of known biases and errors, these new satellite precipitation estimates can be of broad practical interest to deal with emergencies and long-term readiness, especially for semi-arid areas potentially affected by ongoing global warming. Comparisons of satellite data of the September event with model outputs and more direct observations such as rain gauges and ground radars reinforce the idea that satellites are fundamental for an appropriate management of hydrometeorological events.
OBJECTIVE: Cutaneous larva migrans (CLM) is a parasitic disease seen in people in contact with soil in tropical countries. Almost all cases reported in regions without a tropical climate have a history of travel to a tropical region. AIM: In our study, we aimed to investigate the effect of climate change on CLM cases and the demographic characteristics of these cases. For this purpose, the climate information of the period in which we determined the case series and the characteristics of the patients were investigated. MATERIAL AND METHOD: The study was designed retrospectively. Patient files and pre- and post-treatment photographic archives were reviewed retrospectively. In addition, the region’s weather history over the last 50 years was examined. RESULTS: The records of patients diagnosed with CLM in 2018 were reviewed retrospectively. In total, 22 cases were detected. The common feature of all cases was that they worked as tea pickers. After examining the weather conditions of the period when the cases were commonly reported, it was determined that there was a sharp temperature increase compared with previous years. CONCLUSION: Due to climate change, an increase in the number of CLM cases is observed in non-tropical regions. Since it is considered a disease-specific to tropical regions, the diagnosis may be overlooked in cases outside these regions. However, CLM should be kept in mind as a diagnostic possibility by clinicians practicing in non-tropical regions as well, especially when treating patients who work with soil, such as tea harvesters.
Tools exist to predict fatalities related to floods, but current models do not focus on fatalities in buildings. For example, Storm Xynthia in France in 2010 resulted in 41 drowning deaths inside buildings. Therefore, there has been increasing recognition of the risk of people becoming trapped in buildings during floods. To identify buildings which could expose their occupants to a risk of death in the case of flooding, we propose the use of the extreme vulnerability index (VIE index), which identifies which buildings are at greatest risk of trapping people during floods. In addition, the “mortality function method” is used to further estimate the expected number of fatalities based on (1) groups of vulnerable people (e.g., aged or disabled), (2) the location of buildings in relation to major watercourses, and (3) the configuration of buildings (e.g., single or multiple entries and single or multiple stories). The overall framework is derived from case studies from Storm Xynthia which give a deterministic approach for deaths inside buildings for coastal floods, which is suited for low-lying areas protected by walls or sandy barriers. This methodology provides a tool which could help make decisions for adaptation strategy implementation to preserve human life.
Climate-change induced disasters, like floods, are expected to increase in the future. In outdoor built environments, flood risk to evacuees depends on interactions between floodwater spreading, built environment features, flood-induced modifications, and individuals’ reaction in emergency phases. Disaster risk reduction strategies should mitigate the immediate flood impacts and improve the community resilience, while being easy-toimplement and effectively supporting evacuees during the initial phases of the emergency. Simulation-based methodologies could support safety planners in evaluating the effectiveness of such strategies, especially if basing on a micro-scale-oriented approach that represents emergency interactions between each individual and the surrounding outdoor built environment. This study adopts an existing micro-scale simulator (FlooPEDS) reproducing experimental-based flood evacuation behaviours. According to a behavioural design-based approach, simulation results focus on individual responses in the outdoor built environment through Key Performance Indicators (KPIs) aimed at providing evidence of critical interactions between evacuees, floodwaters and the outdoor built environment. A case study is selected by considering different flood scenarios to test such KPIs. Risk reduction solutions are then provided, and their effectiveness is checked by simulations. Results show the micro-scale and behavioural design-based approach capabilities in proposing multi-scenarios solutions (e.g.: architectural elements to support evacuees; emergency planning).
This paper joins the growing scholarly concern for the sharpening of social and environmental inequalities in European cities, particularly those generated in Eastern Europe by evictions of poor Roma from inner-city areas and by the invisibilization of their extreme conditions. We argue that these processes – evictions and invisibilizations – create a heightened vulnerability to climate change impacts for these individuals. The paper uses secondary survey data on compact Roma groups in Romania and analyses qualitative and cartographic information collected by the authors (2019) in two mid-sized cities in Romania to flesh out the particular slum ecologies that emerge following evictions. The focus is also on the subtle processes of invisibilization that render displaced Roma vulnerable and rob them of the “right to the city” in terms of climate change adaptation. Our finding is that evicted Roma experience innumerable, “routine” weather-related impacts, such as floods, storms or cold. By exploring Roma’s heightened exposure, sensitivity and reduced adaptive capacity, we show how these impacts increase their vulnerability to future extreme weather events. These findings are indicative of a broader process of fragmentation taking place in urban areas throughout Eastern Europe, which render invisible some very real barriers to climate change adaptation.
Floods affected more than 2 billion people worldwide from 1998 to 2017 and their occurrence is expected to increase due to climate warming, population growth and rapid urbanization. Recent approaches for understanding the resilience of transportation networks when facing floods mostly use the framework of percolation but we show here on a realistic high-resolution flood simulation that it is inadequate. Indeed, the giant connected component is not relevant and instead, we propose to partition the road network in terms of accessibility of local towns and define new measures that characterize the impact of the flooding event. Our analysis allows to identify cities that will be pivotal during the flooding by providing to a large number of individuals critical services such as hospitalization services, food supply, etc. This approach is particularly relevant for practical risk management and will help decision makers for allocating resources in space and time.
The increasing rate of anthropic activities in flood-prone areas and the effects of climate change are aggravating the dangers posed by floods to people. One of the main reasons for fatality during flood events is walking through floodwaters. Although authorities strongly advise against walking in flood waters, evacuations or the accessing of flooded areas by emergency services might be necessary. This research proposes a novel approach to increasing resilience by retrofitting existing infrastructures to enhance evacuation and access routes by reducing flood hazard rate based on flood and pedestrian characteristics. The methodology was applied to flash floods in two case studies in the UK, namely Boscastle and Borth, highlighting that retrofitting small regions of the existing roads and pathways to reduce flood hazard can enhance people’s safety during the evacuation, and hence provides a solution to improve the resilience of the existing environment.
Fatalities associated with severe weather, collected from newspapers and other documentary sources, were used to create a corresponding database for the 1961-2020 period for the Czech Republic. Fatalities attributed to floods, windstorms, convective storms, snow and glaze ice, frost, fog, and other severe weather, on the one hand, and vehicle accident fatalities connected with rain, snow, glaze ice, fog, and inclement weather, on the other, were analysed separately for two standard periods, 1961-1990 and 1991-2020. The number of weather-related fatalities between these two periods increased in the flood, windstorm, and especially frost categories, and decreased for the convective storm and fog categories. For snow and glaze ice they were the same. Despite significant differences in both 30-year periods, the highest proportions of fatalities corresponded to the winter months, and in individual fatality characteristics to males, adults, direct deaths, deaths by freezing or hypothermia, and to hazardous behaviour. A statistically significant (p < 0.05) Spearman rank correlation between fatalities and climate variables was only found in the 1991-2020 period for snow/glaze ice-related fatalities, with the number of days with snow cover depth and frost-related fatalities having days with daily minimum temperatures below -5 degrees C or -10 degrees C. Despite the highest proportions of the rain and wet road categories being in the number of vehicle accident fatalities, a statistically significant correlation was only found for the category of snow-related fatalities in the number of days with snowfall. The results and conclusions of this study have to be evaluated in the broader context of climatological, political, economic, and societal changes within the country, and have the potential to be used in risk management.
Although England has been experiencing major floods dating back thousands of years, the hazard is increasing in frequency and intensity, exacerbated by climate risks with potentially serious consequences. Despite attempts to mitigate climate risks (manifested via recurrent flooding) in line with international disaster risk reduction agendas, the impacts/effects of floods continue to increase in England. This is partly due to negligence in inculcating contemporary flood risk perceptions (FRP) into climate risk management (CRM) strategies. This research aims to investigate contemporary FRM in England through a qualitative case study approach in Wainfleet All Saints in Lincolnshire County that experienced unprecedented floods in June 2019. Empirical investigation was conducted with the flood-affected community members and flood managers with oversight of CRM in the region. Key findings reveal the June 2019 floods had both tangible and intangible impacts for the affected community with dreadful effects. Challenges to CRM revealed issues around limited funding; climate changes’ potential to increase flood risk and low community perception of their own risks reflected in poor/none-preparedness for contemporary floods. The multi-agency response to the June 2019 floods was found to be positive, albeit with a few concerns. Based on the analysis of the findings, a series of policy recommendations are proffered with the aim to spur organisational/institutional resilience to CRM. This article underscores the relevance to continuously include contemporary FRP into CRM strategies especially to enhance community participation and involvement in mitigating their own risks.
Managed retreat is increasingly advocated as a means to promote resilience and adaptation to climate change. However, there are various uncertainties and challenges associated with the impacts of displacement and attachments to place. In this context, it is useful to study past examples of relocation to understand how these challenges have been addressed. This paper draws on a case study relocation scheme which took place in Ireland following major flooding in 1954. This represented a radical and comprehensive approach to relocation which sought to address the root causes of vulnerability. The analysis shows that this comprehensive approach was made possible through a connection between managed retreat and land reform. The scheme also faced opposition linked to attachments to place and property. This led to compromises and a failure to fully address the effects of flooding on livelihoods but contributed to resilience through ensuring that family and community ties remained intact. The paper’s distinctive contributions are its analysis of the requirements of transformative approaches to adaptation and relocation, its identification of challenges associated with place and property even in the context of such transformative approaches, and its adding of historical depth to contemporary debates on climate adaptation.
OBJECTIVES: Flooding is associated with increased psychological morbidity; however, the impact of living with the uncertainty of flood risk has not been explored. The aim of this study was to generate insight into individual experiences of living with persistent flood risk, how it affects psychological well-being, and the forms of support deemed appropriate to mitigate psychological risks. STUDY DESIGN: A qualitative study was conducted using semistructured interviews with participants who lived in a persistent flood risk area in Nottinghamshire, UK. METHODS: 40 participants were interviewed. The study adopted an interpretivist constructionist position, and the transcripts were analysed using inductive thematic analysis. RESULTS: Persistent flood risk was seen as a significant stressor, regardless of previous flood history. Some participants reported anxiety in anticipation of a future flood event and demonstrated low self-efficacy, with subsequent feelings of helplessness in responding to flood risk. Individuals who lacked acceptance of flood risk displayed higher anxiety and lower resilience. Recognition of flood risk as a psychological stressor was requested in future support. CONCLUSIONS: Living with the uncertainty of persistent flood risk can have significant psychological impacts. Interventions that facilitate the empowerment of individuals living with persistent flood risk may strengthen psychological resilience.
Increases in the magnitude and frequency of climate and other disruptive factors are placing environmental, economic, and social stresses on coastal systems. This is further exacerbated by land use transformations, urbanization, over-tourism, sociopolitical tensions, technological innovations, among others. A scenario-informed multicriteria decision analysis (MCDA) was applied in the Metropolitan City of Venice integrating qualitative (i.e., local stakeholder preferences) and quantitative information (i.e., climate-change projections) with the aim of enhancing system resilience to multiple climate-related threats. As part of this analysis, different groups of local stakeholders (e.g., local authorities, civil protection agencies, SMEs, NGOs) were asked to identify critical functions that needs to be sustained. Various policy initiatives were considered to support these critical functions. The MCDA was used to rank the initiatives across several scenarios describing main climate threats (e.g., storm surges, floods, heatwaves, drought). We found that many climate change scenarios were considered to be disruptive to stakeholders and influence alternative ranking. The management alternatives acting on physical domain generally enhance resilience across just a few scenarios while cognitive and informative initiatives provided resilience enhancement across most scenarios considered. With uncertainty of multiple stressors along with projected climate variability, a portfolio of cognitive and physical initiatives is recommended to enhance resilience.
Extreme weather events (EWEs) may significantly increase pathogenic contamination of private (unregulated) groundwater supplies. However, due to the paucity of protective guidance, private well users may be ill-equipped to undertake adaptive actions. With rising instances of waterborne illness documented in groundwater-dependent, developed regions such as the Republic of Ireland, a better understanding of well user risk perceptions pertaining to EWEs is required to establish appropriate educational interventions. To this end, the current study employed an online and physical questionnaire to identify current risk perceptions and correspondent predictors among Irish private well users concerning extreme weather. Respondents were elicited via purposive sampling, with 515 private well users elucidating perceived supply contamination risk in the wake of five EWEs between the years 2013-2018 including drought and pluvial flooding. A novel scoring protocol was devised to quantify overall risk perception (i.e. perceived likelihood, severity and consequences) of extreme weather impacts. Overall risk perception of EWEs was found to demonstrate a significant relationship with gender (p = 0.017) and event experience (p < 0.001), with female respondents and those reporting prior event experience exhibiting higher median risk perception scores. Risk perception was additionally mediated by perceived self-efficacy in undertaking supply maintenance (p = 0.001), as well users citing confidence in ability scored significantly lower than those citing no confidence. Two-step cluster analysis identified three distinct respondent subsets based on risk perception of EWEs (high, moderate and low perception), with female respondents and those with a third-level education significantly more likely to fall within the high perception cluster. Study findings affirm that certain demographic, experiential and cognitive factors exert a significant influence on private well user risk perceptions of EWE impacts and highlight potential focal points for future educational interventions seeking to reduce the risk of human infection associated with groundwater and extreme weather.
BACKGROUND: Leptospirosis is the most common zoonotic disease in Tuzla Canton. Objective: Determine the influence of environmental and precipitation factors on the incidence of leptospirosis. METHODS: A retrospective study included 80 patients with leptospirosis. Data on precipitation were obtained from the online database of Federal Hydrometeorological Institute of BiH. OpenStreetMap (OSM) was used for spatial analysis; patients were geolocated and put on a map. Statistical data processing included basic tests of descriptive statistics. RESULTS: In the period between 01.01.2014 and 31.12.2014, 80 patients with leptospirosis confirmed by clinical and serological testing were hospitalized in the Clinic for Infectious Diseases of the University Clinical Center Tuzla. Gender wise, out of 80 patients, 54 were male (67.5% of the total), and 26 were female (32.5%). More patients lived in the countryside: 64/80 (or 89%). The largest number of patients was engaged in agriculture and animal husbandry: 48/80 (or 60%), mostly cows 32/80 (40%), chickens 12/80 (15%), sheep 4/80 (5%) and pigs 3/80 (3.8%). Of the total number of patients, 50 (or 62.5%) had contact with domestic animals: dogs 10/80 (or 12.5%) and cats 5/80 (or 6.3%). Half of 53/80 (66.3%) patients had contact with flooded areas in the study period. The increase in leptospirosis diagnosed patients in the City of Srebrenik was statistically significant for 2014 (p<0.01). CONCLUSION: Leptospirosis in one of the neglected infectious diseases in our area, but the proven increase in the number of infected people after heavy rainfall obliges us to control the risks associated with this disease.
The frequency and severity of flooding events will increase over the coming decades due to global climate change. While close attention has typically been paid to infrastructural and environmental outcomes of flood events, the potential adverse human health consequences associated with post-event consumption from private groundwater sources have received minimal attention, leading to a poor understanding of private well users’ preparedness and the drivers of positive behavioural adoption. The current study sought to quantify the capacity of private well users to cope with flood-triggered contamination risks and identify the social psychological determinants of proactive attitudes in the Republic of Ireland, using a cross-sectional questionnaire incorporating two distinct models of health behaviour, the Health Belief Model and Risk-Attitude-Norms-Ability-Self Regulation model. Adoption of healthy behaviours prior to flooding was evaluated with respect to respondents’ risk exposure, risk experience and risk perception, in addition to systematic supply stewardship under normal conditions. Associations between adoption of protective behaviours and perception, experience and socio-demographic factors were evaluated through multinomial and multiple logistic regressions, while a multi-model inferential approach was employed with the predictors of health behaviour models. Findings suggest that floods are not considered likely to occur, nor were respondents worried about their occurrence, with 72.5% of respondents who reported previous flooding experience failing to adopt protective actions. Prior experience of well water contamination increased adoption of proactive attitudes when flooding occurred (+47%), with a failure to adopt healthy behaviours higher among rural non-agricultural residents (136%). Low levels of preparedness to deal with flood-related contamination risks are a side-effect of the general lack of appropriate well stewardship under normal conditions; just 10.1% of respondents adopted both water treatment and frequent testing, in concurrence with limited risk perception and poor awareness of the nexus between risk factors (e.g. floods, contamination sources) and groundwater quality. Perceived risk, personal norms and social norms were the best predictors of protective behaviour adoption and should be considered when developing future awareness campaigns.
During a 6-week period in November and December 2015, a series of Atlantic Storms swept across the Republic of Ireland (ROI) causing widespread pluvial and fluvial flooding. Flooding was particularly severe in the west and midlands, with rainfall up to 200% above normal in many regions, making it the wettest winter ever recorded. While the infrastructural damage and subsequent costs associated with flood events have, and continue to receive widespread attention, far less coverage is given to the associated adverse human health effects. This is particularly significant in the ROI, which is characterised by the highest crude incidence rates of verotoxigenic E. coli (VTEC) enteritis and cryptosporidiosis in Europe. Accordingly, weekly spatially-referenced infection incidence from July 2015 to June 2016 were employed in concurrence with weekly time-series of cumulative antecedent rainfall, surface water discharge and groundwater level, and high-resolution flood risk mapping. An ensemble of statistical and time-series analyses were used to quantify the influence of flood hydrometeorology on the incidence of confirmed infections. Seasonal decomposition (excluding seasonal patterns and long-term trends) identified a high residual infection peak during April 2016, with space-timing scanning used to identify the location, size and temporal extent of clustering. Excess cases of VTEC enteritis were geographically associated with the midlands, while cryptosporidiosis clusters were widespread. Generalised linear modelling of infection locations show that areas with a surface water body exhibited significantly higher incidence rates for both VTEC (OR: 1.225; p < 0.001) and cryptosporidiosis (OR: 1.363; p < 0.001). ARIMA models show a clear association between rainfall, surface water discharge, groundwater levels and infection incidence, with lagged associations from 16 to 20 weeks particularly strong, thus indicating a link between infection peaks (April 2016) and the flood event which began approximately 18 weeks earlier. All three hydrometeorological variables were associated with the increase in cryptosporidiosis during April 2016, while only surface water discharge was associated with VTEC enteritis. Study findings may be employed for improved risk communication, risk management and surveillance to safeguard public health after large hydrometeorological events.
BACKGROUND: The evidence is sparse regarding the associations between serious mental illnesses (SMIs) prevalence and environmental factors in adulthood as well as the geographic distribution and variability of these associations. In this study, we evaluated the association between availability and proximity of green and blue space with SMI prevalence in England as a whole and in its major conurbations (Greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle). METHODS AND FINDINGS: We carried out a retrospective analysis of routinely collected adult population (≥18 years) data at General Practitioner Practice (GPP) level. We used data from the Quality and Outcomes Framework (QOF) on the prevalence of a diagnosis of SMI (schizophrenia, bipolar affective disorder and other psychoses, and other patients on lithium therapy) at the level of GPP over the financial year April 2014 to March 2018. The number of GPPs included ranged between 7,492 (April 2017 to March 2018) to 7,997 (April 2014 to March 2015) and the number of patients ranged from 56,413,719 (April 2014 to March 2015) to 58,270,354 (April 2017 to March 2018). Data at GPP level were converted to the geographic hierarchy unit Lower Layer Super Output Area (LSOA) level for analysis. LSOAs are a geographic unit for reporting small area statistics and have an average population of around 1,500 people. We employed a Bayesian spatial regression model to explore the association of SMI prevalence in England and its major conurbations (greater London, Birmingham, Liverpool and Manchester, Leeds, and Newcastle) with environmental characteristics (green and blue space, flood risk areas, and air and noise pollution) and socioeconomic characteristics (age, ethnicity, and index of multiple deprivation (IMD)). We incorporated spatial random effects in our modelling to account for variation at multiple scales. Across England, the environmental characteristics associated with higher SMI prevalence at LSOA level were distance to public green space with a lake (prevalence ratio [95% credible interval]): 1.002 [1.001 to 1.003]), annual mean concentration of PM2.5 (1.014 [1.01 to 1.019]), and closeness to roads with noise levels above 75 dB (0.993 [0.992 to 0.995]). Higher SMI prevalence was also associated with a higher percentage of people above 24 years old (1.002 [1.002 to 1.003]), a higher percentage of ethnic minorities (1.002 [1.001 to 1.002]), and more deprived areas. Mean SMI prevalence at LSOA level in major conurbations mirrored the national associations with a few exceptions. In Birmingham, higher average SMI prevalence at LSOA level was positively associated with proximity to an urban green space with a lake (0.992 [0.99 to 0.998]). In Liverpool and Manchester, lower SMI prevalence was positively associated with road traffic noise ≥75 dB (1.012 [1.003 to 1.022]). In Birmingham, Liverpool, and Manchester, there was a positive association of SMI prevalence with distance to flood zone 3 (land within flood zone 3 has ≥1% chance of flooding annually from rivers or ≥0.5% chance of flooding annually from the sea, when flood defences are ignored): Birmingham: 1.012 [1.000 to 1.023]; Liverpool and Manchester: 1.016 [1.006 to 1.026]. In contrast, in Leeds, there was a negative association between SMI prevalence and distance to flood zone 3 (0.959 [0.944 to 0.975]). A limitation of this study was because we used a cross-sectional approach, we are unable to make causal inferences about our findings or investigate the temporal relationship between outcome and risk factors. Another limitation was that individuals who are exclusively treated under specialist mental health care and not seen in primary care at all were not included in this analysis. CONCLUSIONS: Our study provides further evidence on the significance of socioeconomic associations in patterns of SMI but emphasises the additional importance of considering environmental characteristics alongside socioeconomic variables in understanding these patterns. In this study, we did not observe a significant association between green space and SMI prevalence, but we did identify an apparent association between green spaces with a lake and SMI prevalence. Deprivation, higher concentrations of air pollution, and higher proportion of ethnic minorities were associated with higher SMI prevalence, supporting a social-ecological approach to public health prevention. It also provides evidence of the significance of spatial analysis in revealing the importance of place and context in influencing area-based patterns of SMI.
Hydrometeorological hazards comprise a wide range of events, mainly floods, storms, droughts, and temperature extremes. Floods account for the majority of the related disasters in both developed and developing countries. Flooding alters the natural balance of the environment and frequently establish a favorable habitat for pathogens and vectors to thrive. Diseases caused by pathogens that require vehicle transmission from host to host (waterborne) or a host/vector as part of their life cycle (vector-borne) are those most likely to be affected by flooding. Considering the most notable recent destructive floods events of July 2021 that affected several Central Europe countries, we conducted a systematic literature review in order to identify documented sporadic cases and outbreaks of infectious diseases in humans in Europe, where hydrometeorological hazards, mainly floods, were thought to have been involved. The occurrence of water-, rodent-, and vector-borne diseases in several European countries is highlighted, as flooding and the harsh post-flood conditions favor their emergence and transmission. In this context, strategies for prevention and management of infectious disease outbreaks in flood-prone and flood-affected areas are also proposed and comprise pre- and post-flood prevention measures, pre- and post-outbreak prevention measures, as well as mitigation actions when an infectious disease outbreak finally occurs. Emphasis is also placed on the collision of floods, flood-related infectious disease outbreaks, and the evolving COVID-19 pandemic, which may result in unprecedented multi-hazard conditions and requires a multi-hazard approach for the effective disaster management and risk reduction.
Introduction: Flooding causes significant mortality and morbidity, with impacts expected to increase with climate change. Ensuring adequate country-level flood mitigation and response capacity is key. Lifeguards, traditionally used for drowning prevention, may represent an additional workforce for flood emergency response. Methods: Through an anonymous, online survey, we explored experiences, beliefs, and attitudes of a convenience sample of surf lifeguards from Australia and England towards lifeguards’ involvement in flood response. Respondents were recruited via Surf Life Saving Australia and Great Britain and had prior training in flood rescue. Analysis comprised descriptive statistics and thematic coding of free-text responses. Results: Forty-four responses were received (93.2% male, 34.1% aged 50-59 years; 61.4% from Australia; 61.4% with >= 16 years lifesaving experience). Twenty-nine respondents (65.9%) self-reported having previously responded to flooding, 15 of which responded prior to receiving flood training. Lifeguards commonly reported being involved in the flood response phase (n = 28). Respondents identified rescue skills (n = 43; 97.7%), awareness of water conditions (n = 40; 90.9%), and radio communication protocols (n = 40; 90.9%) as relevant in a flood scenario. Respondents broadly agreed lifeguards were an asset in flood response due to transferrable skills, including to bolster existing capacity. However, respondents noted need for greater recognition, for involvement earlier in flood response and for flood-specific training and equipment prior to deployment. Discussion & Conclusions: Lifeguards represent a willing and able workforce to support flood mitigation and response, some of whom are already being tasked with such work. Provision of flood-specific training and equipment are vital, as is addressing intemperability tensions.
Sexual violence is largely absent from studies on violence against women in disasters. The role of men in perpetrating violence against women is overlooked or excused and women are usually blamed in both countries. A review of 2 studies of men’s violence against women after floods and earthquakes in Iran and bushfires in Australia show remarkable similarities. Although cultural contexts and the way gender inequality is established and demonstrated are different, these studies reveal unexpected parallels. The context of disaster lays it bare. Participants of both studies were disaster-affected people in Iran and Australia who revealed the taboos that prevent women speaking of violence that is exacerbated in a disaster context. Men play important roles in preventing and responding to violence against women as the result of their responsibilities and positions at the household and community levels. The objective of this paper was to compare the findings from these studies and consider the difficulties faced in conducting studies related to the roles of men and women roles during and after disaster events.
Several countries have been affected by natural hazards during the COVID-19 pandemic. The combination of the pandemic and natural hazards has led to serious challenges that include financial losses and psychosocial stress. Additionally, this compound disaster affected evacuation decision making, where to evacuate, volunteer participation in mitigation and recovery, volunteer support acceptance, and interest in other hazard risks. This study investigated the impact of COVID-19 on disaster response and recovery from various types of hazards, with regard to preparedness, evacuation, volunteering, early recovery, awareness and knowledge of different types of hazards, and preparedness capacity development. This study targets hazards such as Cyclone Amphan in India, the Kumamoto flood in Japan, Typhoon Rolly in the Philippines, and the California wildfires in the U.S. This study made several recommendations, such as the fact that mental health support must be taken into consideration during COVID-19 recovery. It is necessary to improve the genral condition of evacuation centers in order to encourage people to act immediately. A pandemic situation necessitates a strong communication strategy and campaign with particular regard to the safety of evacuation centers, the necessity of a lockdown, and the duration required for it to reduce the psychological impact. Both national and local governments are expected to strengthen their disaster risk reduction (DRR) capacity, which calls for the multi-hazard management of disaster risk at all levels and across all sectors.
Coastal hazards, particularly cyclones, floods, erosion and storm surges, are emerging as a cause for major concern in the coastal regions of Vijayawada, Andhra Pradesh, India. Serious coastal disaster events have become more common in recent decades, triggering substantial destruction to the low-lying coastal areas and a high death toll. Further, women living in informal and slum housing along the Vijayawada coastline of Andhra Pradesh (CAP), India, suffer from multiple social, cultural and economic inequalities as well. These conditions accelerate and worsen women’s vulnerability among this coastal population. The existing literature demonstrates these communities’ susceptibility to diverse coastal disasters but fails to offer gender-specific vulnerability in urban informal housing in the Vijayawada area. Accordingly, the current study developed a novel gender-specific Women’s Coastal Vulnerability Index (WCVI) to assess the impact of coastal disasters on women and their preparedness in Vijayawada. Field data was collected from over 300 women through surveys (2) and workshops (2) between November 2018 and June 2019, and Arc-GIS tools were used to generate vulnerability maps. Results show that women are more vulnerable than men, with a higher death rate during coastal disaster strikes. The current study also found that gender-specific traditional wear is one of the main factors for this specific vulnerability in this area. Furthermore, the majority of the women tend to be located at home to care for the elders and children, and this is associated with more fatalities during disaster events. Homes, particularly for the urban poor, are typically very small and located in narrow and restricted sites, which are a barrier for women to escape from unsafe residential areas during disasters. Overall, the research reveals that most of the coastal disaster events had a disproportionately negative impact on women. The results from this present study offer valuable information to aid evidence-based policy- and decision-makers to improve existing or generate innovative policies to save women’s lives and improve their livelihood in coastal areas.
Floods due to heavy rains or typhoons are frequent annual hazards in Japan. This study aims to reduce disaster fatalities and contribute to disaster risk reduction. This retrospective observational study analyzed fatalities caused by heavy rains or typhoons. In Japan, 578 fatalities, related to seven occurrences of heavy rains and 16 typhoons, occurred between 2016 and 2020. Moreover, 13,195 houses collapsed due to hazards. Furthermore, 334 (73.2%) of the 456 fatalities were > 60 years old. Heavy rains caused more local area destruction due to floods and landslides than typhoons although wind- and disaster-related mortalities were found to be caused by typhoons. Human damage was eminent in older people because of their vulnerabilities and possibly dangerous behavior. Many fatalities were due to floods (46.9%) and landslides (44.1%). Indoor and outdoor mortalities due to heavy rains or typhoons were 157 (55.9%) and 124 (44.1%), respectively, and 24 (21.8%) of 124 outdoor mortalities occurred in vehicles. The number of recent flood mortalities in Japan correlates with the number of destroyed houses. Analyzing the victim’s locations in the 2020 Kumamoto Heavy Rain using hazard and inundation maps suggested the difficulty of ensuring the safety of people living in dangerous areas. This study showed the characteristics of flood damage by heavy rains and typhoons in Japan and reports that flood damage is increasing because of the hazard size and community aging. Disaster risk reduction, disaster education, and evacuation safety plans for the elderly using hazard maps were important for strengthening disaster resilience.
Floods can be devastating in densely populated regions along rivers, so attaining a longer forecast lead time with high accuracy is essential for protecting people and property. Although many techniques are used to forecast floods, sufficient validation of the use of a forecast system for operational alert purposes is lacking. In this study, we validated the flooding locations and times of dike breaking that had occurred during Typhoon Hagibis, which caused severe flooding in Japan in 2019. To achieve the goal of the study, we combined a hydrodynamic model with statistical analysis under forcing by a 39-h prediction of the Japan Meteorological Agency’s Meso-scale model Grid Point Value (MSM-GPV) and obtained dike-break times for all flooded locations for validation. The results showed that this method was accurate in predicting floods at 130 locations, approximately 91.6% of the total of 142 flooded locations, with a lead time of approximately 32.75 h. In terms of precision, these successfully predicted locations accounted for 24.0% of the total of 542 locations under a flood warning, and on average, the predicted flood time was approximately 8.53 h earlier than a given dike-break time. More warnings were issued for major rivers with severe flooding, indicating that the system is sensitive to extreme flood events and can issue warnings for rivers subject to high risk of flooding.
Because of Taiwan’s specific geographical location, disastrous weather phenomena such as typhoons, extreme rainfall, flooding, and regional flooding occur frequently, resulting in devastating casualties and property loss. The losses caused by flooding are NT$5.5 billion per year. This study used insurance claims data on flood damage in Taiwan’s transportation construction projects (from 1996 to 2007) as a sample space. Statistical actuarial model analysis was performed to normalize the loss factors, thereby enabling loss model testing and quantitative analysis of the normalized loss factors. To evaluate the risk in transportation construction, two models were separately applied in the analysis: the value at risk and riskiness models. The results may aid in estimating flooding damage losses in transportation construction projects.
Floods are known to increase the level of allergens such as molds in the environments. Under climate change, the frequency of floods could be increased, which highlights the importance of understanding the impacts of floods on atopic diseases. However, there was a lack of studies. This study examines whether floods induce attacks of childhood atopic dermatitis (AD). A retrospective population-based study was conducted in Taiwan Island using Taiwan’s National Health Insurance Research Database. Emergency room (ER) visits for AD were identified among children aged 0-12 years. Weekly data of flood occurrence, number of flood sites, temperature, and air pollution were obtained for each township of the identified cases. A time-stratified case-crossover design was used. The relationship between ER visits for AD and floods was assessed by conditional logistic regression, adjusting for weekly mean temperature, PM(2.5) and NO(2). There were a total of 55,488 ER visits due to AD during the study period. Such visits increased when flood occurred, and then declined. The effects of floods at the week of flood remained robust, with OR of 1.14 (95% CI = 1.01-1.28) for flood occurrence and 1.31 (95% CI = 1.10-1.55) for the number of flood sites, after adjusting for covariates. Such effects were slightly higher in boys and children aged 1-12 years. This study demonstrated the impact of floods on flare-up of childhood AD, and the effect was most prominently at the week of flood. Healthcare workers should be alarmed for potential increase of AD flare ups after flood events.
OBJECTIVES: This study aimed to examine the effects of flooding due to Typhoon Hagibis on the incidence of cardiovascular/cerebrovascular events in Nagano City. METHODS: The SAVE trial retrospectively enrolled 2426 patients hospitalized for cardiovascular/cerebrovascular disease in 5 hospitals in Nagano City from October 1 to December 31 in 2017 and 2018 (pre-disaster period) and in 2019 (post-disaster period). From these, 280 patients who were hospitalized in a district flooded in 2019 were recruited for the same period (October 12 to December 31) over the 3 years. The baseline characteristics of and the incidence of cardiovascular/cerebrovascular disease in cases from the flooded district in 2019 were compared with those of cases in the flooded district in 2017 and 2018. RESULTS: The total number of patients with acute myocardial infarction did not differ significantly between the post- and pre-disaster periods. The incidence of unstable angina pectoris was significantly higher in 2019 (n = 4, 5.1%) than in 2017 and 2018 (n = 0, 0.0%) (P = 0.001). CONCLUSIONS: This study did not prove the impact of flood due to a typhoon on the incidence of cardiovascular/cerebrovascular events.
Background: Floods are the most common natural disaster which may have substantial impacts on the human health and life and the environment. In recent years, Iran have faced many floods and it seems that increasing impacts of floods in Iran are attributed to inadequate preparation and no well-established strategies and guidelines for response by health sector and other related response organizations. So, this study was conducted to review the current plans in the world to identify the required elements of the flood emergency response plan to prevent its consequences on the health sector in Iran. Methods: A comprehensive review was performed through search on electronic data bases, including, Medline, Scopus, ProQuest, and e-journals which were accessible during 2010-2020. The keywords were response plan, flood, requirements, guidelines, and health sector. Data were collected using data extraction form and analyzed through content analysis. Results: In the initial search, 960 possible sources of flood response were identified. After excluding duplicate papers and the documents that did not contribute to the flood response plan, 64 articles and programs or guidelines that all them has been reviewed, were obtained. The findings were divided into two groups, response prerequisites and response activities. Conclusion: This review provided a complete view of the flood consequences for the health sector and allows professionals to incorporate facets of the health effect of floods into a flood response plan. The flood response plan was divided into two general categories: Initial and specific, each of which plays an important role in preventing the negative effects of the floods.
Floods occur when a body of water overflows and submerges normally dry terrain. Tropical cyclones or tsunamis cause flooding. Health and safety are jeopardized during a flood. As a result, proactive flood mitigation measures are required. This study aimed to increase flood disaster preparedness among Selangor communities in Malaysia by implementing a Health Belief Model-Based Intervention (HEBI). Selangor’s six districts were involved in a single-blinded cluster randomized controlled trial Community-wide implementation of a Health Belief Model-Based Intervention (HEBI). A self-administered questionnaire was used. The intervention group received a HEBI module, while the control group received a health talk on non-communicable disease. The baseline variables were compared. Immediate and six-month post-intervention impacts on outcome indicators were assessed. 284 responses with a 100% response rate. At the baseline, there were no significant differences in ethnicity, monthly household income, or past disaster experience between groups (p>0.05). There were significant differences between-group for intervention on knowledge, skills, preparedness (p<0.001), Perceived Benefit Score (p = 0.02), Perceived Barrier Score (p = 0.03), and Cues to Action (p = 0.04). GEE analysis showed receiving the HEBI module had effectively improved knowledge, skills, preparedness, Perceived Benefit Score, Perceived Barrier Score, and Cues to Action in the intervention group after controlling the covariate. Finally, community flood preparedness ensured that every crisis decision had the least impact on humans. The HEBI module improved community flood preparedness by increasing knowledge, skill, preparedness, perceived benefit, perceived barrier, and action cues. As a result, the community should be aware of this module. Clinical trial registration: The trial registry name is Thai Clinical Trials Registry, trial number TCTR20200202002.
The evacuation of the population from flood-affected regions is a non-structural measure to mitigate flood hazards. Shelters used for this purpose usually accommodate a large number of flood evacuees for a temporary period. Floods during a pandemic result in a compound hazard. Evacuations under such situations are difficult to plan as social distancing is nearly impossible in the highly crowded shelters. This results in a multi-objective problem with conflicting objectives of maximizing the number of evacuees from flood-prone regions and minimizing the number of infections at the end of the shelter’s stay. To the best of our knowledge, such a problem is yet to be explored in literature. Here we develop a simulation-optimization framework, where multiple objectives are handled with a max-min approach. The simulation model consists of an extended Susceptible-Exposed-Infectious-Recovered-Susceptible model. We apply the proposed model to the flood-prone Jagatsinghpur district in the state of Odisha, India. We find that the proposed approach can provide an estimate of people required to be evacuated from individual flood-prone villages to reduce flood hazards during the pandemic. At the same time, this does not result in an uncontrolled number of new infections. The proposed approach can generalize to different regions and can provide a framework to stakeholders to manage conflicting objectives in disaster management planning and to handle compound hazards.
The elderly population is of utmost importance amongst vulnerable populations during disasters because they experience reduced functional abilities, cognitive disturbance, dementia, weak physical conditions and various degenerative diseases. This study aimed to assess the effect of disaster preparedness training on knowledge regarding flood disaster preparedness and management in families with older people. This study was conducted using a quasi-experimental pre-post design with 30 participants in natural hazard preparedness training using purposive sampling. The results of this study showed a significant change in general knowledge on disaster and flood (12.9 and 20 points, respectively). Disaster preparedness practice was good, as reflected in actions performed before, during and after disaster. Before a flood occurs, families prepare a disaster preparedness bag for important documents as well as logistics (e.g. food) for emergencies and equipment for evacuation whilst also storing valuable goods in a safe place. During floods, families prioritise older people’s evacuation whilst seeking information about the flood through neighbours, walkie-talkies, handphones, television and radio as well as ensuring that the necessary logistics are taken care of. After the disaster, families clean their properties, provide clean water and toilet facilities for the family, check the health of family members that may be impacted by the flood and make sure that all electrical panels are safe. It is concluded that disaster training affects the knowledge of flood management in families with older people.
The concept of resilience has been rapidly accepted across multiple disciplines and spheres of applied work, but operationalizing resilience poses several methodological challenges. Issues associated with complexity due to system dynamics, nonlinearity, and self-organization render traditional evaluation methods insufficient and often speculative. Focusing on system actors, processes and structures, and the scales of the system involved, we provide a framework and methodology to establish evidence and evaluate resilience. We take the case of two transboundary communities situated in the Gangetic plains of South Asia, i.e., Paklihawa (Nepal) and Shivpur (India), that are affected by annual monsoonal floods. Using an accessibility-based livelihood framework, we identified key indicators contributing to resilience and measured them in select households, pre- and post-monsoon, over three consecutive years. Focusing on the variation in well-being and coping capacity, we recommend two propositions that must simultaneously be satisfied for increased resilience. Over time, first, the well-being of the communities should increase, and second, the magnitude of recovery from shocks by the communities should decrease, approaching zero. We used a repeated measures analysis of variance to evaluate the significance of changes in well-being and recoveries over time. Our analysis shows that the resilience of Paklihawa increased significantly while Shivpur’s remained inconclusive. The two propositions and the methodology are robust to a wide range of shocks and social-ecological systems. This study contributes to the growing need for approaches toward measuring resilience and the monitoring and evaluation of resilience-focused interventions.
BACKGROUND: Armed forces hospitals are often called upon to provide medical aid to civilians during natural calamities. Though children are often the most vulnerable segment of population in these events, research that addresses their unique needs and the role of armed forces hospitals remains sparse. OBJECTIVES: We examined pediatric morbidity and mortality at a flooded armed forces hospital. Factors that affected outcomes were identified. METHODS: 158 patients were evacuated en masse from a children’s hospital in northern India that was submerged by flood to an adjacent partially inundated armed forces hospital specializing in military medicine and adult trauma. The children were provided case-based clinical care as per existing disaster management protocol. Geoclimatic vulnerability factors, morbidity/mortality, and medical and logistical challenges for future intervention were investigated. RESULTS: One pediatrician who provided initial triage was joined by two others after 48 hours. A limited load of adult patients permitted more resources for the children, majority (49 percent) of whom were neonates. Intensive care was necessitated for 32 (20.2 percent) cases, with half managed in adult ICU. Overall in-hospital mortality was 5.7 percent. Experienced staff, cross-specialty multitasking, and innovative and noncensorious leadership were identified as assets amidst resources compromised by flooding. Clear delineation of primary caregiver role of pediatrician at outset, pediatric emergency care training, pediatric triage, resource allocation for thermoregulation, oxygen therapy and ventilation, earmarking centers for transfer of cases, and safe transportation to the centers were identified as areas meriting further attention. CONCLUSION: Armed forces hospitals in vulnerable geoclimatic zones must address pediatric concerns in disaster management plans.
The upper Brahmaputra floodplain (UBF) is highly enriched with geogenic contaminants, mostly the Arsenic (As), owing to its sensitive geomorphology, aquifer groundwater (GW) dynamics, huge sediment deposition along with natural and anthropogenic disturbance significantly accelerate the As leaching rate into the groundwater, leading to an increase the health risk. Concerning the above active processes in the Lakhimpur district of UBF, current work aims to investigate seasonal dynamics of As contamination and associated health hazard for local community. To carry out this study, 51 GW samples analyzed which reveal the seasonal variation in As concentrations with the minimum average concentration in the monsoon season (4.7 μg.L(-1)) and the maximum in the post-monsoon season (18.5 μg.L(-1)) with 50% of the samples exceeding permissible limits. The differences in the local geological conditions and the GW flow may contribute to the spatial variations in mean As concentration in the study area. Also, the active GW recharge process identified in post-monsoon season accelerates the As leaching in the area’s aquifers. Further, results indicate higher As levels associated with a pH range of 6-7 favours As desorption from minerals under reducing conditions. The hazard index indicates that the children population has high carcinogenic risk compared to adult populations. Furthermore, the study highlights the social risk potential arising from public health crises due to As exposure. Overall, results indicate high As concentrations in region with moderate seasonal variability and demand a dire attention for long-term monitoring to provide sustainable water resources to safeguard the people at risk.
Recent years recorded an increasing number of short duration – high-intensity rainfall events in the Indian subcontinent consequent with urban and riverine flash floods. Rapid assessments of flooded areas are key for effective mitigation strategies and disaster risk plans, as well as to prepare operative policies for future events. Herein, we present an integrated methodology for rapidly mapping the flood extent, and depths based on Synthetic Aperture Radar (SAR) images and a digital elevation model (DEM). Incessant rain during August 2019 brought heavy riverine flooding in southern India, killed at least 280 people, and displaced about one million inhabitants from low-lying areas. We used SAR images by Sentinel-1 before, and during the flooding, and the MERIT DEM which enabled us to map the flood extent and flood depth of the inundation zones. Because the coverage of Sentinel-1 scene was limited to the Kabini river section during the flood period, flood extent and depth maps for the adjacent basin was generated by mapping the susceptibility for flooding using the training set obtained from the flood time Sentinel-1 images, and a set of predictive variables derived from DEM using random forest model. Qualitative analysis and cross-comparison with a numerical flood model proved the proposed approach is highly reliable with an accuracy value of 90% and 86% respectively for training and validation data, thus allowing a precise, simple, and fast flood mapping. The methodology presented here could be applied to other flooded areas having incomplete inventory in the context of flood risk assessment.
During the first half of 2019, many provinces of Iran were affected by floods, which claimed the lives of 82 people. The present study aimed to investigate the behavioral, health related and demographic risk factors associated with deaths due to floods. We measured the odds ratio and investigated the contribution and significance of the factors in relation to mortality. This case-control study was conducted in the cities affected by flood in Iran. Data were collected on the flood victims using a questionnaire. Survivors, a member of the flood victim’s family, were interviewed. In total, 77 subjects completed the survey in the case group, and 310 subjects completed the survey in the control group. The findings indicated that factors such as the age of less than 18 years, low literacy, being trapped in buildings/cars, and risky behaviors increased the risk of flood deaths. Regarding the behavioral factors, perceived/real swimming skills increased the risk of flood deaths although it may seem paradoxical. This increment is due to increased self confidence in time of flood. On the other hand, skills and abilities such as evacuation, requesting help, and escape decreased the risk of flood deaths. According to the results, the adoption of support strategies, protecting vulnerable groups, and improving the socioeconomic status of flood-prone areas could prevent and reduce the risk of flood deaths.
Event scenarios serve as the basis for emergency decision making after sudden disasters, and the accuracy of scenario deduction directly determines the effectiveness of emergency management implementation. On July 20, 2021, an exceptionally heavy rainstorm disaster occurred in Zhengzhou, Henan Province, China, causing serious urban waterlogging, river floods, flash floods and landslides and resulting in major casualties and property losses:14.79 million people affected, 398 people killed or missing (380 people in Zhengzhou) and a direct economic loss of 120.06 billion RMB. In order to investigate the complex evolution process of this disaster, a dynamic Bayesian network, evidence theory and emotion update mechanism are integrated to develop an efficient and effective scenario deduction model, with an emphasis on combining subjective and objective factors. In this model, more attention is given to subjective factors such as decision makers’ emotions. The elements of scenario deduction are classified into the situation status, meteorological factor, emergency activities, decision makers’ emotions and emergency goals, the coupling relationship between the elements are comprehensively analyzed, and the influence of these elements on the evolution mechanism of the rainstorm disaster is investigated, so as to facilitate targeted emergency management measures for the rescue operations. The empirical results show that the proposed dynamic Bayesian network can effectively simulate the dynamic change process of scenario deduction, the improved Dempster-Shafer evidence theory can reduce the subjectivity of the model in dealing with the uncertainty of the evolution process, and the emotion update mechanism can adequately quantify and decrease the influence caused by the emotional changes of decision makers. The model may better replicate actual events, and it may apply to the scenario deduction of other disasters, making an impact on the study of sudden catastrophes.
BACKGROUND: Adequate nutrition before and during pregnancy is necessary to maintain women’s reproductive health and to ensure healthy foetal outcome. Pregnant women are at high risk of acute malnutrition specifically during humanitarian crisis leading to adverse effects in foetal outcomes and women’s health. This study aimed to assess the factors associated with acute malnutrition among pregnant women visiting Antenatal Clinics in two hospitals and a Primary Health Care Centre of Siraha district in the south-eastern plains of Nepal immediately after 2017 flash flood. METHODS: A health-institution based cross-sectional study was conducted among 444 pregnant women of reproductive age (15-49 years) in second and third trimester in three health institutions. Data collection was done in the aftermath of 2017 flash floods through face to face interview. Multiple logistic regression analysis was used to identify the factors associated with acute malnutrition defined as Mid Upper Arm Circumference less than or equals to 21 centimetres. RESULTS: Out of 444 participants, 9.9% were found to be acutely malnourished. Participant’s education (AOR[Adjusted Odds Ratio]: 3.09, 95% CI[Confidence Interval]: 1.43-6.70), occupation (AOR: 3.16, 95% CI: 1.08-9.22), husband’s occupation (AOR: 6.61, 95% CI: 2.17-20.12), household food security (AOR: 3.39, 95% CI: 1.36-8.49) and participant’s dietary diversity (AOR:10.06, 95% CI: 3.35-30.27) were found to be statistically significant factors associated with acute malnutrition among pregnant women. CONCLUSIONS: Participants’ silliteracy, unemployment, husband not employed for cash, household food insecurity and low dietary diversity were found to be statistically significant predictors of acute malnutrition among pregnant women during flash floods.
The present work has been oriented to the qualitative and quantitative assessments of the aftermath effects of 2014 flood tragedy on the organic, inorganic and microbial contaminants in the floodwater, with a particular emphasis on their relative health risks and microbial infectious hazards to the flood-affected population, using average daily dose, hazard quotient, hazard index (HI), cancer risk (CR) and quantitative microbial risk assessment. Statistical comparison of the organic and inorganic contents was performed using the paired t-tests, while the predominant socio-demographic profiles and health attributes of the respondents to flood-induced health risks (HI) were verified by the chi-square test and binary logistic regression analysis. Among all, Fe, Cu, Pb, Ni, Zn, Cr, Cd, chlorpyrifos, diazinon, polycyclic aromatic hydrocarbons, estriol, 17α-ethinylestradiol, estrone, β-estradiol and bisphenol A were detected at the study area after flooding. The microbiological quality of the floodwater samples has been tracked positive for Escherichia coli, Salmonella typhimurium and Shigella flexneri, with the mean concentrations of 6500, 50 and 180 CFU/100 mL, respectively. Exposure and health risk assessments revealed that the overall HI value for organic and inorganic contaminants in the water samples was 1.19, exceeding the USEPA maximum limit of 1, after the flood incidence. The largest CR contributors were Ni, Cr and Cd, while the infection risks (P(inf,single)) associated with the exposure of E. coli, Salmonella spp. and Shigella spp. were identified to be 3.1 × 10(-2), 1.2 × 10(-4) and 3.2 × 10(-5) for incidental scenario; and 8.3 × 10(-1), 3.9 × 10(-1) and 1.9 × 10(-1) for intentional scenario, respectively. The findings of these integrated tools are critically important to provide a more reliable quantitative assessment of human health hazards and microbial risks for different environmental settings, to safeguard water resource, and preservation of public health and the overall river ecosystem.
The present study aimed to investigate the concentrations of potentially toxic metals (PTMs) in the drainages, rivers, and coast of Malacca in Peninsular Malaysia. The ranges of total PTM concentrations (mg/kg dry weight) were 1.88-7.01 for Cd, 18.9-1689 for Cu, 26.0-850 for Ni, 56.5-307 for Pb, and 75.4-312 for Zn. Based on an ecological risk assessment and geochemical fractions, it was concluded that heavy metals pollute the drainages and the Malacca River. The potential ecological risk index (PERI) categorised the drainage and river sites as a “very high ecological risk”. Therefore, it was shown that elevated levels of PTMs in the drainages near Malacca Industrial Area and in the Malacca River sediment were most probably attributed to untreated (or incomplete treatment of) industrial effluents. The drainage sediments were found to have higher hazard quotient (HQ) values for the three pathways of the PTMs for children and adults. Although in general, the non-carcinogenic risks of the PTMs for children and adults indicated no significant detrimental health effects, the hazard index (HI) for Pb in children at drainage locations surpassed 1.0, suggesting a non-carcinogenic risk (NCR), which is a cause for worry. Consequently, the ecological health risk assessments offered critical information for PTM pollution reduction and environmental management in future sustainable development initiatives in Peninsular Malaysia’s drainages and rivers. The present findings on the ecological health risks of PTMs based on 2006 samples can serve as an important baseline for future reference and comparison. This work should encourage future investigations on the direct impact of the risks to the residents during floods in Malaysia, as part of mitigation and risk assessments of the contaminated drainage and river sediments in an attempt to lower the hazards for the surrounding residents.
Assessments of vulnerability to flooding can generate useful data for planners and policy makers. To the best of the authors knowledge, no flood-vulnerability study has combined geophysical modelling of floods with socioeconomic assessments of vulnerability at finer municipal or household scale. In addition, the extent to which vulnerability assessments actually feed into flood adaptation policies remains largely unknown. A new flood vulnerability index, and associated methodology, is proposed, combining high-resolution hydrological-hydraulic modelling with built-environment and socio-economic indicators at the smallest spatial scale at which socio-economic data is available. The main advantage of the methodology is its ability to incorporate place-specific data, hence yielding more refined simulations of floods and the capacity to make projections into climate futures at local scale. The index is built and applied to the inter-city suburb of Marrickville in Sydney and used to assess the effects of future climate change on vulnerability mapping in the suburb. Finally, the results of the assessment are presented to, and discussed with, the local government authority responsible for implementing flood adaptation policies for Marrickville. Locally specific modelling of floods, combined with socio-economic and built-environment mapping, has yielded a rich set of information on flood vulnerability and significant variability within a single suburb. Flood duration is projected to increase by more than 100% under some climate change scenarios, as a result of reduced drainage caused by sea level rise. Feedback from municipal council has highlighted the potential usefulness of the knowledge generated by the assessment, especially for emergency services.
During flood events, warnings issued by emergency service agencies serve to communicate risk and guide community behavior. Yet research shows that while warnings convey operational details, they may not always be understood and appropriately actioned in a timely manner by the public. Such maladaptive behavior can place multiple parties at risk of injury and fatality. Few studies empirically consider and compare the effectiveness of traditional agency-designed oper-ational warnings with other designs such as behavior-oriented warnings. The former typically contain technical and operational detail while the latter provide immediate priority and greater emphasis on translating the situation into specific behavioral actions to be undertaken by the public. Using operational versus newly developed behavior-oriented warnings from New South Wales State Emergency Service in Australia, a total of 774 community members rated each type of scaled warning and their likelihood to engage in adaptive and maladaptive behaviors following exposure to warnings designed to convey one of five levels of an unfolding flooding scenario from its beginning to conclusion (‘Prepare for flooding’, ‘Be ready to evacuate’, ‘Evacuate’, ‘Too late to evacuate’ and ‘Safe to return’). Findings showed positive response to both types of warnings, with behavior-oriented warnings offering greater benefit for perception factors (e.g., risk and comprehension) and adaptive behavioral intentions.
BACKGROUND: Exposure to adverse experiences during pregnancy, such as a natural disaster, can modify development of the child with potential long-term consequences. Elemental hair analysis may provide useful indicators of cellular homeostasis and child health. The present study investigated (1) if flood-induced prenatal maternal stress is associated with altered hair elemental profiles in 4-year-old children, and (2) if hair elemental profiles are associated with behavioural outcomes in children. METHODS: Participants were 75 children (39 boys; 36 girls) whose mothers were exposed to varying levels of stress due to a natural disaster (2011 Queensland Flood, Australia) during pregnancy. At 4 years of age, language development, attention and internalizing and externalizing problems were assessed and scalp hair was collected. Hair was analyzed by inductively coupled plasma mass spectrometry (ICP-MS) for 28 chemical elements. RESULTS: A significant curvilinear association was found between maternal objective hardship and copper levels in boys, as low and high maternal objective hardship levels were associated with the highest hair copper levels. Mediation analysis revealed that low levels of maternal objective hardship and high levels of copper were associated with lower vocabulary scores. Higher levels of maternal objective hardship were associated with higher magnesium levels, which in turn were associated with attention problems and aggression in boys. In girls, high and low maternal objective hardship levels were associated with high calcium/potassium ratios. CONCLUSION: Elemental hair analysis may provide a sensitive biomonitoring tool for early identification of health risks in vulnerable children.
Research conducted in 2018 documented the disaster experiences of 56 women and men in Australia aged between 18 and 93 years. This paper draws out the gendered factors that affected their resilience, and in so doing, begins to address the dearth of research related to gendered aspects of long-term disaster resilience. It is unique in capturing the voices of survivors who spoke of events 9 years after the 2009 Black Saturday fires and of earlier fires and floods in Victoria more than 50 years ago, including the 1983 Ash Wednesday fires. Over decades, gendered expectations of men and women significantly hindered resilience. Men spoke of the long-term cost to them of demands to ‘be strong’ in the worst of disasters and reasons they were reluctant to seek help afterwards. Women spoke of their contributions holding a lesser value and of discrimination. Discussions of violence against women and children after disaster, and suicide ideation in anticipation of future disasters offered critical insights. Protective factors identified by informants were not wholly intrinsic to their character but were also physical, such as essential resources provided in the immediate aftermath, and psychological and community support offered in the long-term. Factors that helped resilience departed from the ‘masculine’ model of coping post-disaster by moving away from a refusal to admit trauma and suffering, to community-wide resilience bolstered by widespread emotional, social and psychological support. Genuine community planning for disasters before they strike builds trust and offers insights for emergency management planners.
OBJECTIVE: This study aimed to investigate the effects of disaster trauma, disaster conflict, and economic loss on posttraumatic stress disorder (PTSD), and to verify the moderating effect of personal and community resilience in these relationships. The data of 1914 people, aged 20 or above, who had experienced natural disasters (earthquake, typhoon, flooding) were used. METHODS: Hayes’s (2013) PROCESS macro (Model 1) was conducted to verify the moderation effect of personal and community resilience between PTSD and disaster trauma, disaster conflict, and economic loss. RESULTS: Disaster trauma, disaster conflict, and economic loss were found to be positively related to PTSD. Personal and community resilience were negatively related to PTSD. Resilience had a moderating effect on the relationship between disaster trauma, economic loss, and PTSD. However, there was no moderating effect on the relationship between disaster conflict and PTSD. Community resilience had a moderating effect on the relationship between economic loss and PTSD. However, there was no moderating effect on the relationship between disaster trauma, disaster conflict, and PTSD. CONCLUSIONS: The results suggest that personal and community resilience could be used for prevention and therapeutic interventions for disaster victims who experience PTSD.
By the 2050s, more than 120 million people are predicted to settle in the Pearl River Delta (PRD), which covers large coastal cities such as Guangzhou, Shenzhen and Hong Kong. Cities in the PRD are vitally important to China in relation to their socio-economic contributions. From recent evidence, this strongly urbanized area is vulnerable to, and currently facing bigger incidences of, coastal and urban flooding. Flood risk is growing in low-lying coastal areas due to rapid urbanization and increasing flood hazards exacerbated by climate change. Frequent intensive rainstorms, sea-level rise, typhoons and surges threaten large populations and their economic assets, causing severe socio-economic and ecological impacts in the PRD cities. Current flood risk management (FRM) in the delta is still predominately focused on using traditional techno-fixes and infrastructure paradigms, lacking sufficient strategic planning and flood protection to develop adequate flood resilience. Recent urban floods, enhanced by storm surges and intensive rainstorms, have affected multiple PRD cities and drawn attention to flood risk as a major challenge in the PRD’s coastal cities. This review encourages development of long-term FRM practices with provincial and municipal authorities working together more closely to develop better-integrated regional FRM strategies for the PRD.
OBJECTIVE: Typhoon Hagibis struck Japan on October 12, 2019. This study documents and characterizes deaths caused by Hagibis and helps identify strategies to reduce mortality in future disasters. METHODS: Japanese residents, who were killed by Typhoon Hagibis, as reported by Japan’s Fire and Disaster Management Agency, were considered for the study. Details were collected from mainstream Japanese media, and flooding data from hazard maps published by local municipalities. RESULTS: Out of the 99 total fatalities, 65 (73.0%) were aged 65 years or above. Among those who drowned indoors (20), 18 (90.0%) lived in high-risk areas of flooding, and their bodies were found on the first floor of their residences. A total of 10 (55.6%) out of the 18 fatalities lived in homes with 2 or more floors, indicating that they could have moved upstairs to avoid the floodwater. However, 6 (33.3%) could not do so due to existing health issues. CONCLUSIONS: Relatively elderly people, particularly those in areas at high risk of flooding, were most affected. Seeking higher ground is a standard safety measure in times of flooding, but this may not be possible for everyone depending on their health status, structure of their residence, and the depth of floodwaters.
This is a one-page summary of findings from EPA’s report Climate Change and Social Vulnerability in the United States: A Focus on Six Impacts related to disproportionate risks of climate change to Asian individuals and Pacific Islanders.
BACKGROUND: The intense interactions between people, animals and environmental systems in urban informal settlements compromise human and environmental health. Inadequate water and sanitation services, compounded by exposure to flooding and climate change risks, expose inhabitants to environmental contamination causing poor health and wellbeing and degrading ecosystems. However, the exact nature and full scope of risks and exposure pathways between human health and the environment in informal settlements are uncertain. Existing models are limited to microbiological linkages related to faecal-oral exposures at the individual level, and do not account for a broader range of human-environmental variables and interactions that affect population health and wellbeing. METHODS: We undertook a 12-month health and environmental assessment in 12 flood-prone informal settlements in Makassar, Indonesia. We obtained caregiver-reported health data, anthropometric measurements, stool and blood samples from children < 5 years, and health and wellbeing data for children 5-14 years and adult respondents. We collected environmental data including temperature, mosquito and rat species abundance, and water and sediment samples. Demographic, built environment and household asset data were also collected. We combined our data with existing literature to generate a novel planetary health model of health and environment in informal settlements. RESULTS: Across the 12 settlements, 593 households and 2764 participants were enrolled. Two-thirds (64·1%) of all houses (26·3-82·7% per settlement) had formal land tenure documentation. Cough, fever and diarrhoea in the week prior to the survey were reported among an average of 34.3%, 26.9% and 9.7% of children aged < 5 years, respectively; although proportions varied over time, prevalence among these youngest children was consistently higher than among children 5-14 years or adult respondents. Among children < 5 years, 44·3% experienced stunting, 41·1% underweight, 12.4% wasting, and 26.5% were anaemic. There was self- or carer-reported poor mental health among 16.6% of children aged 5-14 years and 13.9% of adult respondents. Rates of potential risky exposures from swimming in waterways, eating uncooked produce, and eating soil or dirt were high, as were exposures to flooding and livestock. Just over one third of households (35.3%) had access to municipal water, and contamination of well water with E. coli and nitrogen species was common. Most (79·5%) houses had an in-house toilet, but no houses were connected to a piped sewer network or safe, properly constructed septic tank. Median monthly settlement outdoor temperatures ranged from 26·2 °C to 29.3 °C, and were on average, 1·1 °C warmer inside houses than outside. Mosquito density varied over time, with Culex quinquefasciatus accounting for 94·7% of species. Framed by a planetary health lens, our model includes four thematic domains: (1) the physical/built environment; (2) the ecological environment; (3) human health; and (4) socio-economic wellbeing, and is structured at individual, household, settlement, and city/beyond spatial scales. CONCLUSIONS: Our planetary health model includes key risk factors and faecal-oral exposure pathways but extends beyond conventional microbiological faecal-oral enteropathogen exposure pathways to comprehensively account for a wider range of variables affecting health in urban informal settlements. It includes broader ecological interconnections and planetary health-related variables at the household, settlement and city levels. It proposes a composite framework of markers to assess water and sanitation challenges and flood risks in urban informal settlements for optimal design and monitoring of interventions.
OBJECTIVE: To determine the impact of the 2018 Japan Floods, one of the largest water disasters in Japan, on the number of prescriptions for triptans and ergotamine (acute treatment). BACKGROUND: Natural disasters frequently occur worldwide and may cause psychological stress-related diseases. Acute migraine attacks can be triggered by psychological stress. Disaster victims are likely to experience tremendous psychological stress; however, the relationship between natural disasters and migraine attacks is not well investigated. METHODS: A retrospective longitudinal cohort study was conducted using the National Database of Health Insurance Claims in the hardest-hit areas of the disaster 1 year before and after the disaster. We included people between the ages of 15 and 64 years. Those who had a victim code that was certificated by a local government were assigned to the victim group, and others to the nonvictim group. For those who were not prescribed acute treatment before the disaster (i.e., group without previous acute treatment), the cumulative incidence of new prescriptions for acute treatment at 12 months of follow-up was calculated and compared between victims and nonvictims with survival analysis. RESULTS: Of 3,475,515 people aged 15 to 64 years enrolled in the study, 16,103 (0.46%) were assigned to the victim group. In the group without previous acute treatment, 111 (0.70%) of 15,933 victims and 14,626 (0.43%) of 3,431,423 nonvictims were newly prescribed acute treatment after the disaster, and new prescriptions for acute treatment were significantly more likely to occur in victims than in nonvictims (adjusted hazard ratio, 1.68; 95% CI, 1.39-2.02). CONCLUSIONS: The 2018 Japan Floods increased the number of prescriptions for acute migraine medications among victims, suggesting that acute migraine attacks occurred more frequently after a natural disaster.
INTRODUCTION: Rainfall-induced floods and landslides accounted for 20.7% of all disaster events in Japan from 1985 through 2018 and caused a variety of health problems, both directly and indirectly, including injuries, infectious diseases, exacerbation of pre-existing medical conditions, and psychological issues. More evidence of health problems caused by floods or heavy rain is needed to improve preparedness and preventive measures; however, collecting health data surrounding disaster events is a major challenge due to environmental hazards, logistical constraints, political and economic issues, difficulties in communication among stakeholders, and cultural barriers. In response to the West Japan Heavy Rain in July 2018, Emergency Medical Teams (EMTs) used Japan – Surveillance in Post-Extreme Emergencies and Disasters (J-SPEED) as a daily reporting template, collecting data on the number and type of patients they treated and sending it to an EMT coordination cell (EMTCC) during the response. STUDY OBJECTIVE: The aim of the study was to conduct a descriptive epidemiology study using J-SPEED data to better understand the health problems during floods and heavy rain disasters. METHODS: The number and types of health problems treated by EMTs in accordance with the J-SPEED (Ver 1.0) form were reported daily by 85 EMTs to an EMTCC, where data were compiled during the West Japan Heavy Rain from July 8 through September 11, 2018. Reported items in the J-SPEED form were analyzed by age, gender, area (prefecture), and time period. RESULTS: The analysis of J-SPEED data from the West Japan Heavy Rain 2018 revealed the characteristics of a total of 3,617 consultations with the highest number of consultations (2,579; 71.3%) occurring between Day 5 and Day 12 of the 65-day EMT response. During the response period, skin disease was the most frequently reported health event (17.3%), followed by wounds (14.3%), disaster stress-related symptoms (10.0%), conjunctivitis (6.3%), and acute respiratory infections (ARI; 5.4%). CONCLUSION: During the response period, skin disease was the most frequently reported health event, followed by wounds, stress, conjunctivitis, and ARIs. The health impacts of a natural disaster are determined by a variety of factors, and the current study’s findings are highly context dependent; however, it is expected that as more data are gathered, the consistency of finding will increase.
BACKGROUND: The frequency and intensity of natural disasters are increasing worldwide, which makes our understanding of disaster-related diseases more important than ever. Natural disasters cause mental stress and infectious diarrhea, but the causal relationship between disasters and a potential consequence of these conditions, irritable bowel syndrome (IBS), is unreported. The 2018 Japan Floods, which took place in July 2018 was one of the largest water disasters in Japan’s recorded history. We investigate the change of drug prescriptions for IBS between disaster-suffers and non-sufferers throughout the disaster period to examine the relationship. METHODS: This is a retrospective cohort study based on the Japanese National Database of Health Insurance Claims and Specific Health Checkups in flood-stricken areas between July 2017 and June 2019. We included subjects older than 15 years of age who had visited a medical institution or been hospitalized in the hardest-hit areas of the disaster. Ramosetron, polycarbophil calcium, and mepenzolate bromide (IBS drugs) approved solely for the treatment of IBS in Japan were analyzed. The monthly rate of prescriptions for IBS drugs was compared between municipality-certified disaster victims and non-victims using a controlled interrupted time series analysis. For those who were not prescribed IBS drugs before the disaster (non-users), the occurrence of an IBS drug prescription after the disaster was evaluated using a multivariable logistic regression analysis adjusted for gender and age. RESULTS: Of 5,287,888 people enrolled, 32,499 (0.61%) were certified victims. The prescription rate for IBS drugs among victims increased significantly by 128% immediately after the disaster, while it was stable among non-victims. The trend for the post-disaster prescription rate among victims moved upward significantly when compared to non-victims (0.01% per month; 95% confidence interval (CI) 0.004-0.015; P = 0.001). Among non-users, the occurrence of an IBS drug prescription for victims was 0.71% and was significantly higher than non-victims (0.35%, adjusted odds ratio 2.05; 95% CI 1.81-2.32). CONCLUSIONS: The 2018 Japan Floods increased the rate of prescriptions for IBS drugs, suggesting that the disaster caused or worsened IBS among victims.
BACKGROUND: The July 2018 Japan Floods caused enormous damage to western Japan. Such disasters can especially impact elderly persons. Research has shown that natural disasters exacerbated a decline in cognitive function, but to date, there have been no studies examining the effects of this disaster on the elderly. The object of this study was to reveal the effect of this disaster in terms of cognitive decline among the elderly. METHODS: Study participants were certified users of the long-term care insurance (LTCI) system in Hiroshima, Okayama, and Ehime prefectures from May 2018 to June 2018. The observation period was from July 2018 to December 2018. Our primary outcome was cognitive decline after the disaster using a dementia symptomatology assessment. In addition to a crude model, a multivariate Cox proportional hazards model was used to assess the cognitive decline of victims, adjusting for age classification, gender, the level of dementia scale before the disaster occurred, residential environment, whether a participant used facilities shut down after the disaster, and population density. After we confirmed that the interaction term between victims and residential environment was statistically significant, we stratified them for the analysis. RESULTS: The total number of participants was 264,614. Victims accounted for 1.10% of the total participants (n = 2,908). For the Cox proportional hazards model, the hazard ratio of the victims was 1.18 (95% confidential interval (CI): 1.05-1.32) in the crude model and 1.12 (95% CI: 1.00-1.26) in the adjusted model. After being stratified by residential environment, the hazard ratio of home victims was 1.20 (95% CI: 1.06-1.36) and the hazard ratio of facility victims was 0.89 (95% CI: 0.67-1.17). CONCLUSIONS: This study showed that elderly living at home during the 2018 Japan Floods were at risk for cognitive decline. Medical providers, care providers, and local governments should establish a system to check on the cognitive function of elderly victims and provide necessary care support.
Managing information at city level has become increasingly important owing to the introduction of smart cities and the increasing severity of disasters due to climate change. A data collection framework, model construction, and information management must be established to systematically manage information at the city level. This study developed an urban model generation method using detailed attributes within the City Geography Markup Language (CityGML), a standard data schema for 3D representation of cities based on different types of publicly available information within Korea. The generated model was used to develop a method for simulating flooding status, degree of flooding, and level of building damage after heavy rainfall, in Korea. Furthermore, we developed a method to estimate the loss of human life and property damage by combining the results of the flood analysis with the city model. The proposed methodology supports the creation of standard-based models for flood analysis and exhibits strong interoperability for application to different areas of analysis.
Households living in the close vicinity of shoreline are constantly threatened by various climate change impacts. Community awareness towards climate change is a subject of considerable study as adequate knowledge is a preliminary step for adaptation decision making. An important question is how coastal communities perceive climatic variation, sea level rise and coastal hazard impacts and the socio-economic factors that affect their level of awareness. Thus, this research measures the level of awareness and the factors influencing it based on a household survey (n = 1016) that was conducted 10 critically eroded coastal areas in Selangor. Descriptive statistical analysis reveals that more than half of the households have high level of awareness about climatic variation and sea level, however, there is moderate awareness about the coastal hazard impacts such as human causalities and disease transmission. Even though households are more aware of direct coastal hazard impact such as damages to properties and disruption of daily activities. An independent sample T test indicates that respondents who are male, at working age, educated, involve in natural resource dependent occupations, and had prior exposure to extreme coastal hazards have higher levels of awareness. Research indicated about 55% of all sampled households reflected awareness of climate change, 60% households were aware of sea level rise and 47% households were aware of coastal hazard impact. This study recommends that households in Selangor coast need capacity building and climate change awareness initiatives which would assist household to build adaptive capacity, increase resilience and reduce vulnerability to climate change.
The east coast of Malaysia is frequently hit by monsoon floods every year that severely impact people, particularly those living close to the river bank, which is considered to be the most vulnerable and high-risk areas. We aim to determine the most vulnerable area and understand affected residents of this community who are living in the most sensitive areas caused by flooding events in districts of Temerloh, Pekan, and Kuantan, Pahang. This study involved collecting data for vulnerability index components. A field survey and face-to-face interviews with 602 respondents were conducted 6 months after the floods by using a questionnaire evaluation based on the livelihood vulnerability index (LVI). The findings show that residents in the Temerloh district are at higher risk of flooding damage compared to those living in Pekan and Kuantan. Meanwhile, the contribution factor of LVI-Intergovernmental Panel on Climate Change (IPCC) showed that Kuantan is more exposed to the impact of climate change, followed by Temerloh and Pekan. Among all the principal components shown, food components were considered to be the most vulnerable. Meanwhile, water components were categorised as the most invulnerable. Preventive planning involves preserving human life, minimising damage to household products, preserving crops and animals, adequate supply of clean water and food, good health and ensuring financial sustainability as an indication of changing livelihoods, sustainable food-storing systems, and other protective steps to curb damage and injury caused by annual flood strikes. Information generated on LVI assessment and adaptation procedures will help policymakers reduce people’s vulnerability in the face of floods and ensure proper plans are put in place in all relevant areas.
The need for an emergency disaster management related to dam has risen up in recent years. This is due to uncertainties in global weather predictions which also affect local Malaysian area. With unpredictable prolonged rainy weather, concerns on events that could lead to flooding has triggered the authority to review the evacuation strategies in critical locations. This paper describes an investigation on the effect of early warning system and people response delay to the rate of fatality in the event of flooding due to dam breach. The Life Safety Model is utilized as a tool for the simulation of people vehicle and building response to 2D hydraulic flow of the river originated from the dam. The study area is based on Kenyir Dam and its surrounding vicinity. A number of scenarios are simulated namely cases with and without early warning system. For the case with early warning system, different triggering time is also investigated. On top of that, the effect of people response delay to the warning system is simulated. It was found that early warning system plays a critical role in reducing the number of fatalities due to flooding. Equally important is the time taken for the community to start evacuating when triggered by the early warning system. From the result LSM, optimum evacuation parameters could be identified and used for the purpose of design, planning and implementation of local emergency evacuation plan in the event of dam-related flooding.
This research aimed at assessing flood hazard areas and flood literacy of the elderly population in Bangkok, Thailand and analyzing their flood preparedness through SWOT analysis. Expert interviews and a community survey were conducted. Using the analytic hierarchy process (AHP) and GIS technique, the results indicated that land-use, drainage density, and annual maximum rainfall were the most heavily weighted factors in flood hazard mapping in Bangkok. About half (50.32%) of Bangkok’s total area was defined as high flood hazard area. A total of 736 questionnaires were distributed in flood-prone areas and in the areas with the highest percentage of elderly population. The results of both SWOT and survey analysis found that many senior citizens have low digital and media literacy and limited experience in using information technology for flood preparedness. Lack of integration of disaster risk reduction and aging population policy, ineffective warning system, and lack of access to disaster preparedness training were the key barriers in reducing vulnerability to flood hazard. The survey revealed that the majority of elderly respondents (75%) have neither used online applications for their flood hazard management both before and during flood disaster nor shared/communicated information via online platforms. Some respondents (13%) used Facebook and Line applications to obtain information before a flood event. Very few of the elderly respondents (<2%) accessed the national/provincial web-based platform to find out flood-related information. Almost all respondents, especially who are living in high-risk flood zones, had never participated in the community training of flood preparedness and management. Therefore, effective strategies in enhancing social engagement of the elderly and their literacy skills in flood risk preparedness and management are urgently needed.
OBJECTIVE: This study explored the approaches for community-based flood disaster management for older adults in Southern Thailand. It sought to understand community culture for supporting older adults and promoting community strength in case of flood disaster. METHOD: This was a qualitative content analysis study using data from observation, in-depth interviews, secondary data, and focus group discussion. One hundred and twenty-seven people in total were selected specifically for the study, including Local Administration Organization (LAO), community leaders, public sector officers, civil groups, and older adult groups and family caregivers. RESULTS: The results of this study were two main themes, focusing on 1) approaches to community-based flood disaster management for older adults as follows: eight approaches in the phase of prevention and preparedness in flood disaster management for older adults, eight approaches in the phase of response in flood disaster management for older adults, and six approaches in the phase of recovery and rehabilitation in flood disaster management for older adults; and 2) factors contributing to success in flood disaster management for older adults has four factors, including the human factor, the work factor, the data factor, and the resource factor. CONCLUSION: The findings showed significant roles in improving the potential and strength in community-based flood disaster management for older adults and providing suggestions for community nurses and health practice personnel involving in flood disaster management to mitigate the potential influence on older adults in the community.
BACKGROUND: Floods cause not only damage but also public health issues. Developing an application to simulate public health problems during floods around the Loei River by implementing geographic information system (GIS) and structural equation model (SEM) techniques could help improve preparedness and aid plans in response to such problems in general and at the subdistrict level. As a result, the effects of public health problems would be physically and mentally less severe. METHODS: This research and development study examines cross-sectional survey data. Data on demographics, flood severity, preparedness, help, and public health problems during floods were collected using a five-part questionnaire. Calculated from the population proportion living within 300 m of the Loei River, the sample size was 560 people. The participants in each subdistrict were recruited proportionally in line with the course of the Loei River. Compared to the empirical data, the data analysis examined the causal model of public health problems during floods, flood severity, preparedness, and help. The standardized factor loadings obtained from the SEM analysis were substituted as the loadings in the equations for simulating public health problems during floods. RESULTS: The results revealed that the causal model of public health problems during floods, flood severity, preparation, and help agreed with the empirical data. Flood severity, preparedness, and aid (χ(2) = 479.757, df = 160, p value <.05, CFI = 0.985, RMSEA = 0.060, χ(2)/df = 2.998) could explain 7.7% of public health problems. The computed values were applied in a GIS environment to simulate public health problem situations at the province, district, and subdistrict levels. CONCLUSIONS: Flood severity and public health problems during floods were positively correlated; in contrast, preparedness and help showed an inverse relationship with public health problems. A total of 7.7% of the variance in public health problems during floods could be predicted. The analysed data were assigned in the GIS environment in the developed application to simulate public health problem situations during floods.
OBJECTIVE: To examine the relationship between flood severity and risk of hospitalisation in the Vietnam Mekong River Delta (MRD). METHODS: We obtained data on hospitalisations and hydro-meteorological factors during 2011-2014 for seven MRD provinces. We classified each day into a flood-season exposure period: the 2011 extreme annual flood (EAF); 2012-2014 routine annual floods (RAF); dry season and non-flood wet season (reference period). We used province-specific Poisson regression models to calculate hospitalisation incidence rate ratios (IRRs). We pooled IRRs across provinces using random-effects meta-analysis. RESULTS: During the EAF, non-external cause hospitalisations increased 7.2% (95% CI 3.2% to 11.4%); infectious disease hospitalisations increased 16.4% (4.3% to 29.8%) and respiratory disease hospitalisations increased 25.5% (15.5% to 36.4%). During the RAF, respiratory disease hospitalisations increased 8.2% (3.2% to 13.5%). During the dry season, hospitalisations decreased for non-external causes and for each specific cause except injuries. CONCLUSIONS: We observed a gradient of decreasing risk of hospitalisation from EAF to RAF/non-flood wet season to dry season. Adaptation measures should be strengthened to prepare for the increased probability of more frequent extreme floods in the future, driven by climate change.
This study develops and assesses the application of a livelihood vulnerability index (LVI), LVI-IPCC and livelihood effect index for the natural and agricultural resources in Northwestern Pakistan. By using structured questionnaire, primary data were collected from the targeted households in the study region. Data on socio-demographics, water security, health, social networks and climate variability were collected from the targeted respondents in this study area, and combined into indices. The IPCC framework was utilized that characterizes vulnerability into exposure, sensitivity and its adaptive capacity. Findings of our study showed that tehsil Shabqadar was more vulnerable among three studied tehsils particularly in natural disasters, health, water and land holding status. Tehsil Tangi was the second high vulnerable tehsil followed by tehsil Charsadda relative to other LVI components with the exclusion of livelihood strategies and financial constraints. Findings of this study provide a better understanding of the social and behavioral trends as well as an integrated and holistic view of the agriculture, climate change and livelihoods process in assessing the vulnerability. The findings and this pragmatic approach will be helpful in intending specific strategies and policy effectiveness to lessen susceptibility of households to climatic variations.
Emergency medical service (EMS) is important for rescuing victims suffering from life-threatening illnesses or accidents, and is highly time-sensitive by nature. Many uncertain contexts in the urban environment can prolong EMS response time and deteriorate its performance. Using the enhanced two-step floating catchment area (E2SFCA) method, this study measures EMS accessibility with the effect of a regular uncertain context (i.e., the city dynamics like time-varying population and traffic) and an irregular uncertain context (i.e., an extreme pluvial flood event which can cause extensive road closures). The results indicate that, in the central urban area of Shanghai, mid-west areas with denser populations have higher accessibility than eastern peripheral areas. Flooding can cause a remarkable decline of accessibility which falls to the lowest point slightly earlier than the time when the worst road connectivity emerges. The night time exhibits better accessibility than especially the peak hours during the daytime. The GWR results reveal that increasing facility richness and road density while decreasing flood-induced road closures have a positive effect on EMS accessibility. The study indicates that both regular and irregular uncertain contextual factors can influence EMS accessibility in a highly complex manner. Carefully taking these uncertainties into account would enable EMS planning in other contexts and regions to face the enormous challenges posed by the changing climate and increasingly complex urban environment.
In recent years, the rainstorm and flood disasters frequently happened in cities and posed increasingly wide challenges. Therefore, the whole development process of urban rainstorm and flood disaster should be carried out for the reasonable and quantitative assessment on cities’ ability to respond to rainstorm and flood disasters, and the index system of risk assessment on regional flood disaster is constructed based on the three attributes of vulnerability, adaptability and restorability. 3 first-class and 14 s-class indexes are set up accordingly. The weight of each index is calculated by weighting methods which are both subjective and objective based on entropy-weight order relation. Then, the theoretical model for risk assessment is established by weighted clustering assessment. Finally, the empirical analysis was conducted on the current situation of rainstorm and flood disaster in 8 regions of a city in China. The results show that among the risk grade of rainstorm and flood disaster in 8 regions, there are 2 regions with grade-II higher risk, 5 regions with grade-III general risk and 1 region with grade-IV low risk. The consistency between assessment results and actual operation of cities indicates this model can be applied and effective to some extent.
People are always susceptible to a loss of stability in urban floodwaters that leads to serious casualties. Thus, the safety criterion for the instability of people in floodwaters must be determined. In this study, the hydrodynamic criterion of the instability of people in floodwaters in terms of the incipient velocity and water depth is derived using the probability method based on Shannon entropy theory. The derived model can characterize variations in the incipient velocity of people in floodwaters with respect to the inundating water depth. Furthermore, a comparison with seven experimental datasets available in the literature shows the validity of the proposed entropy-based model considering data scattering. A sensitivity analysis of the derived model to some of the incorporated parameters was performed, and the qualitative results are in accordance with our understanding of the physical mechanism of the instability of people in floodwaters. Taking the physical parameters (height and mass) of Chinese adults and children as a representative example, this study also showed the vulnerability degree of Chinese adults and children subject to floodwaters. These findings could provide a reference for administrators and stakeholders for flood hazard mitigation and flood strategy management. This study shows that an entropy-based method could be a valuable addition to existing deterministic models for characterizing the instability criterion of people in an urban flooding event.
The evaluation of emergency response capability under different pluvial flooding scenarios is an essential approach to improve the emergency response capability of flood disasters. A new evaluation method of emergency response capacity of urban public services is proposed based on urban pluvial flooding scenario simulation. Firstly, inundation area and depth under different pluvial flooding scenarios are simulated based on the SCS-CN model. Following that, space densities of all indicators include inundation area and depth, road network and the emergency public service institutions. Then, the indicator weight is determined by the combined weighting method of entropy weight and coefficient of variation. Finally, the emergency response capacity index (of each pixel) is calculated based on the graph stacking method. Taking Erqi District, Zhengzhou City as an example, the emergency response capacity of public service under different urban flooding scenarios is evaluated. The results show that the spatial distribution difference of public service emergency response capacity in Erqi District, Zhengzhou City is obvious, and with the increase of the precipitation return period, the high value area of public service emergency response capability decreases gradually and the low value area increases gradually. This method takes into account the specific urban flooding scenario and the layout of public service institutions and road networks that have strong practicability. the results of the evaluation can provide a reference for the construction of urban flood emergency response capacity and provide support for emergency decision-making.
Billions of people live in urban poverty, with many forced to reside in disaster-prone areas. Research suggests that such disasters harm child nutrition and increase adult morbidity. However, little is known about impacts on mental health, particularly of people living in slums. In this paper we estimate the effects of flood disasters on the mental and physical health of poor adults and children in urban Indonesia. Our data come from the Indonesia Family Life Survey and new surveys of informal settlement residents. We find that urban poor populations experience increases in acute morbidities and depressive symptoms following floods, that the negative mental health effects last longer, and that the urban wealthy show no health effects from flood exposure. Further analysis suggests that worse economic outcomes may be partly responsible. Overall, the results provide a more nuanced understanding of the morbidities experienced by populations most vulnerable to increased disaster occurrence.
In Malaysia, floods are often considered a normal phenomenon in the lives of some communities, which can sometimes cause disasters to occur beyond expectations, as shown during the flood of 2014. The issue of flood disasters, which particularly impacts SDG 13 of the integrated Sustainable Development Goals (SDGs), still lacks widespread attention from sociology researchers in Malaysia. Similarly, questions related to the welfare of victims, especially in regards to aspects of disaster management from a humanitarian perspective, are still neglected. This study aims to identify the adaptive actions through a solution from a humanitarian perspective in managing flood disaster risks. For the purpose of obtaining data, this study used a qualitative approach with a case study design. Data were collected using in-depth interviews and non-participant observation methods. A total of ten experts, consisting of the flood management teams involved in managing the 2014 flood disaster in Hulu Dungun, Terengganu, Malaysia, were selected through a purposive random sampling method. The results showed that adaptive actions in managing flood disaster risks from a humanitarian point of view include the provision of social support, collective cooperation from the flood management teams, and adaptation efforts after the floods.
OBJECTIVES: In this paper, we explore the exposure to risk and experiences of people with disability and carers during a flooding event and the subsequent mental health impacts. DESIGN: A cross-sectional survey between September and November 2017. Binary logistic regression models were used to investigate associations between the mental health of people with disability and carers and their exposure to the flood. Inductive content analysis was used to analyse qualitative data. SETTING: Flood-affected communities in the rural area of Northern Rivers, New South Wales, Australia, 6 months after river flooding in 2017. PARTICIPANTS: People over 16 years and a resident in the Northern Rivers at the time of the flood were invited to participate. Using a purposive, snowballing sampling technique participants were drawn from a wide range of socioeconomic backgrounds and had experienced different degrees of flood exposure. RESULTS: Of 2252 respondents, there were 164 people with disability and 91 carers. Both groups had increased odds of having their home flooded (people with a disability: OR 2.41 95% CI 1.71 to 3.39; carers: OR 1.76 95% CI 1.10 to 2.84). On evacuation, respondents reported inaccessible, conflicting and confusing information regarding flood warnings. Essential services such as healthcare and social services were disrupted (people with a disability: OR 3.98 95% CI 2.82 to 5.60; carers 2.17 95% CI 1.33 to 3.54) and access to safe and mould free housing post flood event was limited. After taking sociodemographic factors into account, respondents with a disability and carers had greater odds of probable post-traumatic stress disorder compared with other respondents (people with a disability: 3.32 95% CI 2.22 to 4.96; carers: 1.87 95% CI 1.10 to 3.19). CONCLUSION: Our findings show the profound impact and systemic neglect experienced by people with disability and carers during and after the 2017 flood event in the Northern Rivers. As people with disability will take longer to recover, they will require longer-term tailored supports and purposeful inclusion in flood preparedness and recovery efforts.
Flood events can be dramatic and traumatic. People exposed to floods are liable to suffer from a variety of adverse mental health outcomes. The adverse effects of stressors during the recovery process (secondary stressors) can sometimes be just as severe as the initial trauma. Six months after extensive flooding in rural Australia, a survey of 2530 locals was conducted focusing on their flood experiences and mental health status. This mixed methods study analysed (a) quantitative data from 521 respondents (21% of total survey respondents) who had insurance coverage and whose household was inundated, 96 (18%) of whom reported an insurance dispute or denial; and (b) qualitative data on insurance-related topics in the survey’s open comments sections. The mental health outcomes were all significantly associated with the degree of flood inundation. The association was strong for probable PTSD and ongoing distress (Adjusted Odds Ratios (AORs) with 95% confidence intervals 2.67 (1.8-4.0) and 2.30 (1.6-3.3), respectively). The associations were less strong but still significant for anxiety and depression (AORs 1.79 (1.2-2.7) and 1.84 (1.2-2.9)). The secondary stressor of insurance dispute had stronger associations with ongoing distress and depression than the initial flood exposure (AORs 2.43 (1.5-3.9) and 2.34 (1.4-3.9), respectively). Insurance was frequently mentioned in the open comment sections of the survey. Most comments (78% of comments from all survey respondents) were negative, with common adverse trends including dispute/denial, large premium increases after a claim, inconsistencies in companies’ responses and delayed assessments preventing timely remediation.
There is substantial evidence that in the aftermath of a disaster, an individual’s sense of coherence (SOC) plays an important role in promoting one’s sense of well-being. The SOC is regarded as a core component of the salutogenic model of mental health. Disaster survivors are frequently subjected to traumatic experience and have higher psychological distress prevalence rates than people in the general population. The present study aimed to investigate possible socio-demographic differences (gender and age) on the sense of coherence (SOC) among disaster survivors in Indonesia. A total of 194 respondents (71 male and 123 females) from across the country participated in the online survey. A factorial ANOVA using JASP was conducted to investigate the main effects of gender and age groups and the interaction effect of these variables on the SOC level. The findings were two folds, age group variance was significantly associated with the SOC, while gender did not significantly associate with the SOC. The main effect of Age groups was F (2, 962.773) = 4.307, p = 0.005, indicating a significant difference of SOC between young adult, middle adult, and late adult groups.
OBJECTIVE: The impact of the 2018 Japan Floods on prescriptions of Yokukansan was evaluated. METHODS: This was a retrospective cohort study based on the National Database of Health Insurance Claims which covers all the prescriptions issued in Japan. Participants were patients aged 65 or older who received any medical care at medical institutions located in the three most-severely affected prefectures between 1 year before and after the disaster. We analyzed the number of new prescriptions of Yokukansan and other Kampo drugs among those who had not been prescribed any Kampo for 1 year before the disaster. Kaplan-Meier analysis and a Cox proportional hazards model were used to evaluate the risk of the disaster for a new prescription. RESULTS: Subjects comprised 1,372,417 people (including 12,787 victims, 0.93%). The hazard ratio (HR) of the disaster for Yokukansan prescriptions was 1.49 [95% confidence intervals (CI): 1.25-1.78], and 1.54 (95% CI: 1.29-1.84) in the crude and age-sex adjusted model, respectively. The HR of the disaster for prescription of other Kampo drugs in the crude and adjusted model was 1.33 (95% CI: 1.27-1.39), and 1.32 (95% CI: 1.27-1.38), respectively. The magnitude of increase of victims prescribed Yokukansan (31.4%) was statistically higher than for those prescribed other Kampo drugs (19.3%) (p < 0.001). CONCLUSION: The disaster increased prescriptions of both Yokukansan and other Kampo drugs among elderly victims. The increase was more remarkable in Yokukansan than other Kampo drugs. Clinicians and policymakers should be aware of the increased need for Yokukansan in times of natural disaster.
PURPOSE: Natural disaster has an impact on mental health. The 2018 Japan Floods, which took place in July 2018 were one of the largest water disasters in Japan’s recorded history. We aimed to evaluate the change in the number of benzodiazepine prescriptions by physicians before and after the disaster. METHODS: A retrospective cohort study based on the National Database of Health Insurance Claims was conducted in the flood-stricken areas between July 2017 and June 2019. The subjects were divided between victims and non-victims according to certification by local governments. Members of both groups were then categorized into three groups based on their pre-flood use of benzodiazepines: non-user, occasional user, and continuous user. Difference-in-differences (DID) analysis with a logistic regression model was conducted to estimate the effect of the disaster among victims by comparing the occurrence of benzodiazepine prescriptions before and after the disaster. RESULTS: Of 5,000,129 people enrolled, 31,235 were victims. Among all participants, the mean prescription rate for benzodiazepines in victims before the disaster (11.3%) increased to 11.8% after the disaster, while that in non-victims (8.3%) decreased to 7.9%. The DID analysis revealed that benzodiazepine prescription among victims significantly increased immediately after the disaster (adjusted ratio of odds ratios (ROR) 1.07: 95% confidence interval 1.05-1.11), and the effect of the disaster persisted even 1 year after the disaster (adjusted ROR 1.2: 95% confidence interval 1.16-1.24). CONCLUSION: The flood increased the number of benzodiazepines prescriptions among victims, and the effect persisted for at least 1 year.
Thailand has faced many flooding crises, especially in 2011, which caused widespread damage to indus-trial parks and community zones. However, the nega-tive consequences of flooding on the local people and workers in industrial zones have been little studied. This study focuses on the impacts of flooding after 2011 on the well-being of residents in industrial zones in terms of their work and livelihoods. Community -based research was used to explore the effects of floods on 647 respondents who worked in Rojana Indus-trial Park (N = 247) and those who lived around the park (N = 400). A questionnaire survey was con-ducted in February 2020. The results showed adverse impacts on the economy, accommodation, and well-being of both the local inhabitants and workers, whose monthly incomes and overtime jobs decreased signif-icantly compared to before the disaster. However, lo-cal people suffered more from low incomes than work-ers of the company, as the employees’ work status was maintained during the crisis. Japanese company cul-ture is investigated as a factor in the higher resilience and recovery levels of company employees than the Rojana community. In addition, the workers were evacuated to other accommodations until the com-pany recovered, while locals remained in their flooded homes. In addition, most respondents reported that mental health impacts were more likely to affect their mental health. For effective recovery and flood risk management, the government should follow up on em-ployment, accommodation, and livelihood after a sud-den flood, especially for the local people. A greater understanding of community risk, community engage-ment, and awareness-raising activities can enhance readiness, response, recovery, and resilience in disas-ter management by government, businesses, and local communities.
Developing countries are increasingly impacted by floods, especially in Asia. Traditional flood risk man-agement, using structural measures such as levees, can have negative impacts on the livelihoods of social groups that are more vulnerable. Ecosystem-based adaptation (EbA) provides a complementary approach that is potentially more inclusive of groups that are commonly described as more vulnerable, such as the poor and women. However, there is a lack of disaggregated and quantitative information on the potential of EbA to support vulnerable groups of society. This paper provides a quantitative analysis of the differ-ences in vulnerability to flooding as well as preferences for EbA benefits across income groups and gen -der. We use data collected through a survey of households in urban and rural Central Vietnam which included a discrete choice experiment on preferences for ecosystem services. A total of 1,010 households was surveyed during 2017 through a random sampling approach. Preferences are measured in monetary and non-monetary terms to avoid issues that may arise from financial constraints faced by respondents and especially the more vulnerable groups. Our results reveal that lower income households and women are overall more vulnerable than their counterparts and have stronger preferences for the majority of the EbA benefits, including flood protection, seafood abundance, tourism, and recreation suitability. These findings strongly indicate that EbA is indeed a promising tool to support groups of society that are espe-cially vulnerable to floods. These results provide crucial insights for future implementation of EbA pro-jects and for the integration of EbA with goals targeted at complying with the Sendai Framework and Sustainable Development Goals. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
The 2014 flood disaster has brought physical destruction, damage as well as social disruption that caused normal life to become less stable. A state of social equilibrium needs to be restored through effective restoration solutions to normalise life after the disaster. This qualitative research aims to identify two main issues, namely social disruption and social resilience, by utilising a case study of the 2014 flood disaster in Hulu Dungun, Terengganu. A total of 15 victims were selected using the purposive sampling method based on a set of defined criteria-the data collection method comprised of in-depth interviews and non-participant observation. The data were analysed through thematic analysis techniques. The results showed that the disruption suffered by the victims included disruption of social roles, the uncertainty of employment, instability of social routine, and collective trauma. However, the availability of social resilience had enabled the victims to rebuild their lives after flood disasters and restore the ‘normal’ or ‘stable’ situations of social equilibrium. The research is expected to contribute to environmental sociology that has yet to receive widespread attention from sociological researchers in Malaysia. This research is a meaningful effort towards promoting and increasing the environmental sociology study, which to date, remains disoriented.
Floods have become the most prevalent natural disaster in the world. Understanding the emotional impact of floods on people helps reduce negative mass incidents and contributes to the implementation of disaster prevention and mitigation. This study collected online discussions related to the great flood in the middle and lower reaches of the Yangtze River basin in China in 2020. Then, we obtained the sentiments of people and the deep thoughts behind their negative sentiment through the dictionary sentiment analysis and the LDA topic modeling, counting them according to the regions. The overall sentiment of Internet users during this flood was neutral, and the posts showing negative sentiment were mostly from the affected areas. People in the affected areas were highly concerned about personal safety and property, whose negative emotions were directed towards the flood prevention work and the relocation of affected people.
With extreme weather events on the rise, the question of how witnessing adverse weather events may affect individuals’ perception, and consequently their subjective well-being, gains in relevance. To identify events that have been witnessed, i.e., tangential exposure to a weather shock, satellite-based data on flooding is linked to an extensive household panel survey from rural Southeast Asia. Contrasting direct shock experience with tangential shock exposure, we find that mere proximity to a potentially adverse shock, without reporting any actual direct shock experience, could be sufficient to reduce subjective well-being. This effect is not only restricted to the present but can also impinge on expected future well-being dynamics. Eventually, such a persistent effect from witnessing a weather shock may have further politico-economic repercussions, for instance, by altering support for redistribution policies.
Since the outbreak of coronavirus disease 2019 (COVID-19), adolescents in 70 countries have suffered the COVID-19 pandemic and flood disasters simultaneously. Although antecedent cyberbullying variables have attracted significant research attention, the effects of psychological distress and the potential mechanisms of cyberbullying among adolescents under multiple disasters remains unclear. Based on social-ecological system theory, this study examines the moderating effects of parent-child relationships and the negotiable fate on the relationship between psychological distress and cyberbullying. A total of 1204 middle school students (52.4% boys) who suffered from floods and the COVID-19 pandemic from Zhengzhou City, China, are the participants. The results reveal that psychological distress was positively related to adolescent cyberbullying during a disaster. Parent-child relationships and negotiable fate significantly moderate the relationship between psychological distress and cyberbullying. Specifically, high parent-child relationships and a high negotiable fate could protect adolescents from the negative effects of psychological distress of cyberbullying. For adolescents with low or high parent-child relationships and low negotiable fate, the links between psychological distress and cyberbullying are stronger. These findings underline the significance of considering the interaction of psychological distress, parent-child relationships, and negotiable fate when examining adolescents’ cyberbullying during disasters.
Due to climate change and rapid urbanization, contemporary cities face the dual challenges of providing sufficient stormwater management and adequate park services, which potentially conflict over limited space and resources. To solve these problems, cities are increasingly combining stormwater infrastructure with park space in ways that create new efficiencies. To date, most research has focused on the stormwater management performance aspect of these combinations and not the techniques employed to achieve the combined goals. To fill this gap, 23 sponge city parks in Shanghai were investigated to examine the combination of stormwater and park services. Our findings show that stormwater techniques were primarily combined with the park facilities of water areas, paved open spaces, and pathways. Additionally, we found that larger parks employed a wider range of techniques for managing stormwater runoff and supported broader sets of park activities, while those at smaller scales prioritized infiltration, detention, and purification measures, as well as concentrated on social and economic activities. This study is the first to explore SPC parks that integrate stormwater management and park services, thereby providing implications for SPC development in China and insights into the ways that the two properties can be combined in other cities.
BACKGROUND: /Objective: Flooding risk is a global issue, and various approaches have been established to prevent flooding risk around the world. China is one of the heavily flood-affected countries and has been implementing the Sponge City program since 2015 to defend against flooding. Unfortunately, flooding has been common in China in recent years, causing severe health risks to citizens. This research mainly focuses on (a) evaluating the implementation of China’s Sponge City program and the associated impacts on human health and (b) exploring the future improvement of the Sponge City program in China. METHODS: The Interpretive Document Approach was used to explore an inclusive review of the Sponge City program and its implications on human health. RESULTS: /Findings: The Sponge City program in China is still insufficient to prevent flooding risks effectively. In the past eight years, 24/34 provinces have recorded flooding, which caused a total of 4701 deaths and over 525.5 billion RMB (around 72.9 billion US$) in economic loss. Till now, only 64/654 cities have promulgated local legislation to manage sponge city construction, although the Sponge City was implemented in 2015. Besides, the completed Sponge City program constructions cannot fully prevent flooding risks, the flood prevention capacity is limited. The Sponge City program is not granted priority, lacking national legislation hinders Sponge City program implementation in China. CONCLUSIONS: China needs to make national legislation on the Sponge City program and update the Sponge City program technology guidelines. Local governments should implement Sponge City construction according to local geographic environments.
Background: Children’s flood risk perceptions that include their awareness and behaviors, can be cultivated through disaster education, which is crucial for improving disaster resilience and adaptation to climate extremes. However, education’s co-influencing effect along with family and society was unclear. This study investigated a three-year disaster education program conducted in schools in Sichuan Province, China. Method: In three pilot counties, we used stratified duster sampling in 2016 and 2018 to separately survey the risk perceptions of 2,105 children (baseline) and 1710 children (post-intervention), respectively, aged 8-12, in 45 primary schools. The Ordinary Least Squares Regression and Propensity Score Matching Method (PSM) were used to assess the effectiveness of classroom education, propaganda poster, professional guidance, social education (television, radio, friends, and internet), and risk-related parent-child interactions. Interaction items and Structure Equation Model (SEM) were performed to identify their co-influencing mechanisms. Finally, the intervention effect was assessed by categorizing different levels of parent-child interactions and left-behind status. Result: The classroom education (Coeff = 0.040; P < 0.05), propaganda poster (Coeff = 0.024; P < 0.05), and professional guidance (Coeff = 0.016; P < 0.1) had significantly positive effects on children's flood risk perception. But these effects were found to be underestimated using PSM. Interaction effects between disaster education and parent-child interaction were statistically significant, and parent-child interaction was a moderating factor for improving risk perception (standardized indirect effect = 0.055, p < 0.001). Additionally, the mean score of risk perception increased by 118% in 2018 compared with the baseline. It was found that the higher the level of risk-related parent-child interaction, the higher the mean scores of risk perception (Coeff = 0.055; P < 0.001) irrespective whether they are left-behind children. Conclusion: To improve disaster resilience and climate change adaptation, risk-related parent-child interaction should be considered in disaster education, which is an effective way to promote children's risk perceptions. (C) 2020 Published by Elsevier B.V.
In this study, we investigated the flooding accident that occurred on Metro Line 5 in the capital city of Zhengzhou, Henan Province, China. On 20 July 2021, owing to an extreme rainstorm, serious inundation occurred in the Wulongkou parking lot of Zhengzhou Metro Line 5 and its surrounding area. Flooding forced a train to stop during operation, resulting in 14 deaths. Based on our preliminary investigation and analysis of this accident, we designed three main control measures to reduce the occurrence of similar accidents and mitigate the impact of similar accidents in the future, given the increasing number of extreme storm weather events in recent years: (1) to conduct subway flood risk assessments and to establish an early warning system, involving real-time monitoring of meteorological information during subway operation and construction; (2) to improve subway flood control emergency plans and to establish a response mechanism for subway flooding; and (3) to strengthen safety awareness training to ensure the orderly evacuation of people after accidents.
Drought and flood are two of the most destructive natural disasters with the most significant impact and greatest losses in the Dadu River basin (DRB). However, their impacts on people’s life have not attracted enough attention from scholars. In this study, the Standardized Precipitation Index (SPI) describing the drought/flood situation and the Composite Index of Human Well-being (CIHW) are calculated, and a framework is further constructed to assess the impacts of drought and flood disasters on human well-being in the DRB. The results show that the annual and seasonal SPI in the DRB generally exhibit an increasing trend in fluctuations during 2000-2009, indicating a wetting climate in this basin. Overall, the upper reaches of the DRB have experienced an evolution of flood-drought-flood state transition, where the variation amplitude of the SPI in the western sub-basin is greater than that in the eastern sub-basin. In addition, the lower reaches of the DRB have suffered more dramatic and periodic changes from the drought/flood disasters in terms of the SPI. For human well-being during 2000-2019, Maerkang City in the upper reaches, Kangding City in the middle reaches, and Shimian County in the lower reaches of the DRB are at a relatively higher level, with the CIHW decreasing from administrative centers to the around. Moreover, the CIHW over the whole basin increases gradually from 2000 to 2019. The SPI has significantly negative effects on different capitals, following a descending order of financial, social, physical, human and natural capitals. The counties of the basin are divided into four groups, namely the group with high disaster risks and high human well-being, the group with high disaster risks and low human well-being, the group with low disaster risks and high human well-being, and the group with low disaster risks and low human well-being. The panel regression results suggest that the construction of water conservancy facilities, the financial inputs in agriculture and meteorology, and the educational level have positive impacts on human well-being, but the impacts differ from different groups. The construction of water conservancy facilities has highly significant impacts on human well-being in all groups; the education level has no significant impact on the group with high disaster risk and high human well-being, which has not passed the significance test; while the financial inputs in agriculture and meteorology have relatively higher impacts on the whole basin and on the group with low disaster risk and low human well-being compared with other groups. Therefore, it is suggested that the negative impacts of drought and flood disasters can be mitigated through strengthening infrastructure construction, responding appropriately to climate change, avoiding disasters at the source of major projects and improving the disaster prevention and mitigation systems.
Hemorrhagic fever with renal syndrome (HFRS) continued to affect human health across Eurasia, which complicated by climate change has posed a challenge for the disease prevention measures. Nation-wide surveillance data of HFRS cases were collected during 2008-2020.The seasonality and epidemiological features were presented by combining the HFRS incidence and the endemic types data. Factors potentially involved in affecting incidence and shaping disease seasonality were investigated by generalized additive mixed model, distributed lag nonlinear model and multivariate meta-analysis. A total of 76 cities that reported totally 111,054 cases were analyzed. Three endemic types were determined, among them the Type I cities (Hantaan virus-dominant) were related to higher incidence level, showing one spike every year in Autumn-Winter season; Type II (Seoul virus-dominant) cities were related to lower incidence, showing one spike in Spring, while Type III (Hantaan/Seoul-mixed type) showed dual peaks with incidence lying between. Persistently heavy rainfall had significantly negative influence on HFRS incidence in Hantaan virus-dominant endemic area, while a significantly opposite effect was identified when continuously heavy rainfall induced floods, where temperature and relative humidity affected HFRS incidence via an approximately parabolic or linear manner, however few or no such effects was shown in Seoul virus-dominant endemic areas, which was more vulnerable to temperature variation. Dual seasonal pattern of HFRS was depended on the dominant genotypes of hantavirus, and impact of climate on HFRS was greater in Hantaan virus-dominant endemic areas, than in Seoul virus-dominant areas.
Climate change may contribute to the spatio-temporal occurrence of disasters. Long-term studies of either homogeneous or heterogeneous responses of historical disasters to climate change are, however, limited by the quality and quantity of the available proxy data. Here we reconstruct spatio-temporal patterns of five types of disasters in China during the period AD 1368-1911. Our analyses of these time series reveal that warmer temperatures decreased the occurrence of disasters in the monsoon-affected parts of central-east China, but it increased the frequency and intensity of disasters along the boundary of arid and humid conditions in parts of southwest and northeast China, probably driven by the interplay among monsoon, westerlies, polar vortex and variation of temperature. Moreover, we show that drought and flood events had cascading effects on the occurrences of locust outbreaks, famine and human epidemics. Our findings suggest that climate can contribute to the spatio-temporal occurrence of disasters, and therefore may contribute to an improvement of China’s regional to national risk management of future climate and environmental change.
BACKGROUND: Dengue is an endemic vector-borne disease influenced by environmental factors such as landscape and climate. Previous studies separately assessed the effects of landscape and climate factors on mosquito occurrence and dengue incidence. However, both factors concurrently coexist in time and space and can interact, affecting mosquito development and dengue disease transmission. For example, eggs laid in a suitable environment can hatch after being submerged in rain water. It has been difficult for conventional statistical modeling approaches to demonstrate these combined influences due to mathematical constraints. OBJECTIVES: To investigate the combined influences of landscape and climate factors on mosquito occurrence and dengue incidence. METHODS: Entomological, epidemiological, and landscape data from the rainy season (July-December) were obtained from respective government agencies in Metropolitan Manila, Philippines, from 2012 to 2014. Temperature, precipitation and vegetation data were obtained through remote sensing. A random forest algorithm was used to select the landscape and climate variables. Afterward, using the identified key variables, a model-based (MOB) recursive partitioning was implemented to test the combined influences of landscape and climate factors on ovitrap index (vector mosquito occurrence) and dengue incidence. RESULTS: The MOB recursive partitioning for ovitrap index indicated a high sensitivity of vector mosquito occurrence on environmental conditions generated by a combination of high residential density areas with low precipitation. Moreover, the MOB recursive partitioning indicated high sensitivity of dengue incidence to the effects of precipitation in areas with high proportions of residential density and commercial areas. CONCLUSIONS: Dengue dynamics are not solely influenced by individual effects of either climate or landscape, but rather by their synergistic or combined effects. The presented findings have the potential to target vector surveillance in areas identified as suitable for mosquito occurrence under specific climatic conditions and may be relevant as part of urban planning strategies to control dengue.
Dengue is a mosquito-borne viral infection, found in tropical and sub-tropical climates worldwide, mostly in urban and semi-urban areas. Countries like Pakistan receive heavy rains annually resulting in floods in urban cities due to poor drainage systems. Currently, different cities of Pakistan are at high risk of dengue outbreaks, as multiple dengue cases have been reported due to poor flood control and drainage systems. After heavy rain in urban areas, mosquitoes are provided with a favorable environment for their breeding and transmission through stagnant water due to poor maintenance of the drainage system. The history of the dengue virus in Pakistan shows that there is a closed relationship between dengue outbreaks and a rainfall. There is no specific treatment for dengue; however, the outbreak can be controlled through internet of medical things (IoMT). In this paper, we propose a novel privacy-preserved IoMT model to control dengue virus outbreaks by tracking dengue virus-infected patients based on bedding location extracted using call data record analysis (CDRA). Once the bedding location of the patient is identified, then the actual infected spot can be easily located by using geographic information system mapping. Once the targeted spots are identified, then it is very easy to eliminate the dengue by spraying the affected areas with the help of unmanned aerial vehicles (UAVs). The proposed model identifies the targeted spots up to 100%, based on the bedding location of the patient using CDRA.
Melioidosis is endemic in the remote Katherine region of northern Australia. In a population with high rates of chronic disease, social inequities, and extreme remoteness, the impact of melioidosis is exacerbated by severe weather events and disproportionately affects First Nations Australians. All culture-confirmed melioidosis cases in the Katherine region of the Australian Top End between 1989-2021 were included in the study, and the clinical features and epidemiology were described. The diversity of Burkholderia pseudomallei strains in the region was investigated using genomic sequencing. From 1989-2021 there were 128 patients with melioidosis in the Katherine region. 96/128 (75%) patients were First Nations Australians, 72/128 (56%) were from a very remote region, 68/128 (53%) had diabetes, 57/128 (44%) had a history of hazardous alcohol consumption, and 11/128 (9%) died from melioidosis. There were 9 melioidosis cases attributable to the flooding of the Katherine River in January 1998; 7/9 flood-associated cases had cutaneous melioidosis, five of whom recalled an inoculating event injury sustained wading through flood waters or cleaning up after the flood. The 126 first-episode clinical B. pseudomallei isolates that underwent genomic sequencing belonged to 107 different sequence types and were highly diverse, reflecting the vast geographic area of the study region. In conclusion, melioidosis in the Katherine region disproportionately affects First Nations Australians with risk factors and is exacerbated by severe weather events. Diabetes management, public health intervention for hazardous alcohol consumption, provision of housing to address homelessness, and patient education on melioidosis prevention in First Nations languages should be prioritised.
BACKGROUND: Although studies have provided the estimates of floods-diarrhoea associations, little is known about the lag effect, effect modification, and attributable risk. Based on Sichuan, China, an uneven socio-economic development province with plateau, basin, and mountain terrains spanning different climatic zones, we aimed to systematically examine the impacts of floods on diarrheal morbidity. METHODS: We retrieved information on daily diarrheal cases, floods, meteorological variables, and annual socio-economic characteristics for 21 cities in Sichuan from January 1, 2017 to December 31, 2019. We fitted time-series Poisson models to estimate the city-specific floods-diarrhoea relation over the lags of 0-14 days, and then pooled them using meta-analysis for cumulative and lag effects. We further employed meta-regression to explore potential effect modifiers and identify effect modification. We calculated the attributable diarrheal cases and fraction of attributable morbidity within the framework of the distributed lag model. RESULTS: Floods had a significant cumulative association with diarrhoea at the provincial level, but varied by regions and cities. The effects of the floods appeared on the second day after the floods and lasted for 5 days. Floods-diarrhoea relations were modified by three effect modifiers, with stronger flood effects on diarrhoea found in areas with higher air pressure, lower diurnal temperature range, or warmer temperature. Floods were responsible for advancing a fraction of diarrhoea, corresponding to 0.25% within the study period and 0.48% within the flood season. CONCLUSIONS: The impacts imposed by floods were mainly distributed within the first week. The floods-diarrhoea relations varied by geographic and climatic conditions. The diarrheal burden attributable to floods is currently low in Sichuan, but this figure could increase with the exposure more intensive and the effect modifiers more detrimental in the future. Our findings are expected to provide evidence for the formulation of temporal- and spatial-specific strategies to reduce potential risks of flood-related diarrhoea.
BACKGROUND: Schistosomiasis is a highly recurrent parasitic disease that affects a wide range of areas and a large number of people worldwide. In China, schistosomiasis has seriously affected the life and safety of the people and restricted the economic development. Schistosomiasis is mainly distributed along the Yangtze River and in southern China. Anhui Province is located in the Yangtze River Basin of China, with dense water system, frequent floods and widespread distribution of Oncomelania hupensis that is the only intermediate host of schistosomiasis, a large number of cattle, sheep and other livestock, which makes it difficult to control schistosomiasis. It is of great significance to monitor and analyze spatiotemporal risk of schistosomiasis in Anhui Province, China. We compared and analyzed the optimal spatiotemporal interpolation model based on the data of schistosomiasis in Anhui Province, China and the spatiotemporal pattern of schistosomiasis risk was analyzed. METHODS: In this study, the root-mean-square-error (RMSE) and absolute residual (AR) indicators were used to compare the accuracy of Bayesian maximum entropy (BME), spatiotemporal Kriging (STKriging) and geographical and temporal weighted regression (GTWR) models for predicting the spatiotemporal risk of schistosomiasis in Anhui Province, China. RESULTS: The results showed that (1) daytime land surface temperature, mean minimum temperature, normalized difference vegetation index, soil moisture, soil bulk density and urbanization were significant factors affecting the risk of schistosomiasis; (2) the spatiotemporal distribution trends of schistosomiasis predicted by the three methods were basically consistent with the actual trends, but the prediction accuracy of BME was higher than that of STKriging and GTWR, indicating that BME predicted the prevalence of schistosomiasis more accurately; and (3) schistosomiasis in Anhui Province had a spatial autocorrelation within 20 km and a temporal correlation within 10 years when applying the optimal model BME. CONCLUSIONS: This study suggests that BME exhibited the highest interpolation accuracy among the three spatiotemporal interpolation methods, which could enhance the risk prediction model of infectious diseases thereby providing scientific support for government decision making.
In Jambi province, Sumatra, Indonesia, flooding is a recurrent rainy season phenomenon. Historically considered manageable, recent political economic developments have changed this situation. Today, flooding is an environmental hazard and a threat to people’s livelihoods and health. Based on qualitative research and literature that has developed relational approaches to risk and water, we investigate past and present hydrosocial relations in Jambi province and reconstruct the changing meaning of flooding. We suggest that flooding as a hazard in Jambi was produced through the introduction of the plantation industry to the area and its prioritization of dry land for agm-industrial development. This development altered the materiality of water flows, reconfigured power relations and changed the socio-cultural dimensions of flooding. Together, these changes have led to a separation of flooding from its original social and geographic realm, producing new risks and vulnerabilities. This paper provides insights into the material and symbolic dimensions that influence how environmental processes come to be imagined, controlled and contested. It shows how tracing the socionatural production of hazards may help explain the increasingly systemic nature of risks and provide insights into the wider social meaning of environmental risks.
The epidemic of leptospirosis in humans occurs annually in Thailand. In this study, we have developed mathematical models to investigate transmission dynamics between humans, animals, and a contaminated environment. We compared different leptospire transmission models involving flooding and weather conditions, shedding and multiplication rate in a contaminated environment. We found that the model in which the transmission rate depends on both flooding and temperature, best-fits the reported human data on leptospirosis in Thailand. Our results indicate that flooding strongly contributes to disease transmission, where a high degree of flooding leads to a higher number of infected individuals. Sensitivity analysis showed that the transmission rate of leptospires from a contaminated environment was the most important parameter for the total number of human cases. Our results suggest that public education should target people who work in contaminated environments to prevent Leptospira infections.
Bacterial pathogens in surface waters threaten human health. The health risk is especially high in developing countries where sanitation systems are often lacking or deficient. Considering twelve flash-flood events sampled from 2011 to 2015 at the outlet of a 60-ha tropical montane headwater catchment in Northern Lao PDR, and using Escherichia coli as a fecal indicator bacteria, our objective was to quantify the contributions of both surface runoff and sub-surface flow to the in-stream concentration of E. coli during flood events, by (1) investigating E. coli dynamics during flood events and among flood events and (2) designing and comparing simple statistical and mixing models to predict E. coli concentration in stream flow during flood events. We found that in-stream E. coli concentration is high regardless of the contributions of both surface runoff and sub-surface flow to the flood event. However, we measured the highest concentration of E. coli during the flood events that are predominantly driven by surface runoff. This indicates that surface runoff, and causatively soil surface erosion, are the primary drivers of in-stream E. coli contamination. This was further confirmed by the step-wise regression applied to instantaneous E. coli concentration measured in individual water samples collected during the flood events, and by the three models applied to each flood event (linear model, partial least square model, and mixing model). The three models showed that the percentage of surface runoff in stream flow was the best predictor of the flood event mean E. coli concentration. The mixing model yielded a Nash-Sutcliffe efficiency of 0.65 and showed that on average, 89% of the in-stream concentration of E. coli resulted from surface runoff, while the overall contribution of surface runoff to the stream flow was 41%. We also showed that stream flow turbidity and E. coli concentration were positively correlated, but that turbidity was not a strong predictor of E. coli concentration during flood events. These findings will help building adequate catchment-scale models to predict E. coli fate and transport, and mapping the related risk of fecal contamination in a global changing context.
In this study, the adsorption-elution method was modified to concentrate viral particles in water samples and investigate the contamination of groundwater with norovirus genogroup II (NoV GII), rotavirus A (RVA), and Pepper mild mottle virus (PMMoV). The mean recovery rate of a murine norovirus strain, which was inoculated into groundwater samples collected from a deep well, was the highest (39%) when the viral RNA was directly extracted from the membrane instead of eluting the adsorbed viral particles. This adsorption-direct extraction method was applied to groundwater samples (20 liters) collected from deep wells used for the public drinking water supply (n = 22) and private wells (n = 9). RVA (85 copies/liter) and NoV GII (35 copies/liter) were detected in water samples from a deep well and a private well, respectively. PMMoV was detected in 95% and 89% of water samples from deep wells and private wells, respectively, at concentrations of up to 990 copies/liter. The modified method was also used to extract bacterial DNA from the membrane (recovery rate of inoculated Escherichia coli K-12 was 22%). The Bacteroidales genetic markers specific to ruminants (BacR) and pigs (Pig2Bac) were detected in samples from a deep well and a private well, respectively. The modified virus concentration method has important implications for the management of microbiological safety in the groundwater supply. IMPORTANCE We investigated the presence of enteric viruses and bacterial genetic markers to determine fecal contamination in groundwater samples from deep wells used for the public drinking water supply and private wells in Japan. Groundwater is often subjected to chlorination; malfunctions in chlorine treatment result in waterborne disease outbreaks. The modified method successfully concentrated both viruses and bacteria in 20-liter groundwater samples. Norovirus genogroup II (GII), rotavirus A, Pepper mild mottle virus, and Bacteroidales genetic markers specific to ruminants and pigs were detected. Frequent flooding caused by increased incidences of extreme rainfall events promotes the infiltration of surface runoff containing livestock wastes and untreated wastewater into wells, possibly increasing groundwater contamination risk. The practical and efficient method developed in this study will enable waterworks and the environmental health departments of municipal/prefectural governments to monitor water quality. Additionally, the modified method will contribute to improving the microbiological safety of groundwater.
Schistosomiasis is a water-borne parasitic disease distributed worldwide, while schistosomiasis japonica localizes in the People’s Republic of China, the Philippines, and a few regions of Indonesia. Although significant achievements have been obtained in these endemic countries, great challenges still exist to reach the elimination of schistosomiasis japonica, as the occurrence of flooding can lead to several adverse consequences on the prevalence of schistosomiasis. This review summarizes the influence of flooding on the transmission of schistosomiasis japonica and interventions responding to the adverse impacts from the One Health perspective in human beings, animals, and the environment. For human and animals, behavioral changes and the damage of water conservancy and sanitary facilities will increase the intensity of water contact. For the environment, the density of Oncomelania snails significantly increases from the third year after flooding, and the snail habitats can be enlarged due to active and passive diffusion. With more water contact of human and other reservoir hosts, and larger snail habitats with higher density of living snails, the transmission risk of schistosomiasis increases under the influence of flooding. With the agenda set for global schistosomiasis elimination, interventions from the One Health perspective are put forward to respond to the impacts of increased flooding. For human beings, conducting health education to increase the consciousness of self-protection, preventive chemotherapy for high-risk populations, supply of safe water, early case finding, timely reporting, and treating cases will protect people from infection and prevent the outbreak of schistosomiasis. For animals, culling susceptible domestic animals, herding livestock in snail-free areas, treating livestock with infection or at high risk of infection, harmless treatment of animal feces to avoid water contamination, and monitoring the infection status of wild animals in flooding areas are important to cut off the transmission chain from the resources. For the environment, early warning of flooding, setting up warning signs and killing cercaria in risk areas during and post flooding, reconstructing damaged water conservancy facilities, developing hygiene and sanitary facilities, conducting snail surveys, using molluscicide, and predicting areas with high risk of schistosomiasis transmission after flooding all contribute to reducing the transmission risk of schistosomiasis. These strategies need the cooperation of the ministry of health, meteorological administration, water resources, agriculture, and forestry to achieve the goal of minimizing the impact of flooding on the transmission of schistosomiasis. In conclusion, flooding is one of the important factors affecting the transmission of schistosomiasis japonica. Multi-sectoral cooperation is needed to effectively prevent and control the adverse impacts of flooding on human beings, animals, and the environment.
BACKGROUND: Flooding is considered to be one of the most important factors contributing to the rebound of Oncomelania hupensis, a small tropical freshwater snail and the only intermediate host of Schistosoma japonicum, in endemic foci. The aim of this study was to assess the risk of intestinal schistosomiasis transmission impacted by flooding in the region around Poyang Lake using multi-source remote sensing images. METHODS: Normalized Difference Vegetation Index (NDVI) data collected by the Landsat 8 satellite were used as an ecological and geographical suitability indicator of O. hupensis habitats in the Poyang Lake region. The expansion of the water body due to flooding was estimated using dual-polarized threshold calculations based on dual-polarized synthetic aperture radar (SAR). The image data were captured from the Sentinel-1B satellite in May 2020 before the flood and in July 2020 during the flood. A spatial database of the distribution of snail habitats was created using the 2016 snail survey in Jiangxi Province. The potential spread of O. hupensis snails after the flood was predicted by an overlay analysis of the NDVI maps in the flood-affected areas around Poyang Lake. The risk of schistosomiasis transmission was classified based on O. hupensis snail density data and the related NDVI. RESULTS: The surface area of Poyang Lake was approximately 2207 km(2) in May 2020 before the flood and 4403 km(2) in July 2020 during the period of peak flooding; this was estimated to be a 99.5% expansion of the water body due to flooding. After the flood, potential snail habitats were predicted to be concentrated in areas neighboring existing habitats in the marshlands of Poyang Lake. The areas with high risk of schistosomiasis transmission were predicted to be mainly distributed in Yongxiu, Xinjian, Yugan and Poyang (District) along the shores of Poyang Lake. By comparing the predictive results and actual snail distribution, we estimated the predictive accuracy of the model to be 87%, which meant the 87% of actual snail distribution was correctly identified as snail habitats in the model predictions. CONCLUSIONS: Data on water body expansion due to flooding and environmental factors pertaining to snail breeding may be rapidly extracted from Landsat 8 and Sentinel-1B remote sensing images. Applying multi-source remote sensing data for the timely and effective assessment of potential schistosomiasis transmission risk caused by snail spread during flooding is feasible and will be of great significance for more precision control of schistosomiasis.
INTRODUCTION: Skin and soft tissue infections have the potential to affect every patient admitted to a surgical service. Changes to the microbiota colonizing wounds during natural disasters, such as the Townsville floods of 2019, could impact empiric antibiotic choice and need for return to theatre. METHODS: This retrospective observational cohort study reviews culture data and demographics for patients undergoing surgical debridement of infected wounds over a six-month period starting in November 2018 to May 2019 at the Townsville Hospital. RESULTS: Of the 408 patients requiring operative intervention, only 61 patients met the inclusion criteria. The groups were comparative in terms of age and gender, but a greater proportion of patients (40.5% versus 29.1%, P = 0.368) in the post-flood group were diabetic. Common skin commensals, such as Staphylococcus aureus, were the most common pathogen in both groups, however the post-flood group had a higher proportion of atypical organisms (14 versus 8 patients), and an increased need for repeated debridement for infection control (24 versus 14 patients). CONCLUSION: Wound swabs and tissue culture are imperative during surgical debridement and may guide the use of more broad-spectrum coverage following a significant flooding event.
Surveillance programs are essential for the prevention and control of mosquito-borne arboviruses that cause serious human and animal diseases. Viral metatranscriptomic sequencing can enhance surveillance by enabling untargeted, high-throughput arbovirus detection. We used metatranscriptomic sequencing to screen field-collected mosquitoes for arboviruses to better understand how metatranscriptomics can be utilised in routine surveillance. Following a significant flood event in 2016, more than 56,000 mosquitoes were collected over seven weeks from field traps set up in Victoria, Australia. The traps were split into samples of 1000 mosquitoes or less and sequenced on the Illumina HiSeq. Five arboviruses relevant to public health (Ross River virus, Sindbis virus, Trubanaman virus, Umatilla virus, and Wongorr virus) were detected a total of 33 times in the metatranscriptomic data, with 94% confirmed using reverse transcription quantitative PCR (RT-qPCR). Analysis of metatranscriptomic cytochrome oxidase I (COI) sequences enabled the detection of 12 mosquito and two biting midge species. Screening of the same traps by an established public health arbovirus surveillance program corroborated the metatranscriptomic arbovirus and mosquito species detections. Assembly of genome sequences from the metatranscriptomic data also led to the detection of 51 insect-specific viruses, both known and previously undescribed, and allowed phylogenetic comparison to past strains. We have demonstrated how metatranscriptomics can enhance surveillance by enabling untargeted arbovirus detection, providing genomic epidemiological data, and simultaneously identifying vector species from large, unsorted mosquito traps.
Freshwater reservoirs are a crucial source of urban drinking water worldwide; thus, long-term evaluations of critical water quality determinants are essential. We conducted this study in a large drinking water reservoir for 11 years (2010-2020). The variabilities of ambient nutrients and total suspended solids (TSS) throughout the seasonal monsoon-mediated flow regime influenced algal chlorophyll (Chl-a) levels. The study determined the role of the monsoon-mediated flow regime on reservoir water chemistry. The reservoir conditions were mesotrophic to eutrophic based on nitrogen (N) and phosphorus (P) concentrations. An occasional total coliform bacteria (TCB) count of 16,000 MPN per 100 mL was recorded in the reservoir, presenting a significant risk of waterborne diseases among children. A Mann-Kendall test identified a consistent increase in water temperature, conductivity, and chemical oxygen demand (COD) over the study period, limiting a sustainable water supply. The drought and flood regime mediated by the monsoon resulted in large heterogeneities in Chl-a, TCB, TSS, and nutrients (N, P), indicating its role as a key regulator of the ecological functioning of the reservoir. The ambient N:P ratio is a reliable predictor of sestonic Chl-a productivity, and the reservoir was P-limited. Total phosphorus (TP) had a strong negative correlation (R(2) = 0.59, p < 0.05) with the outflow from the dam, while both the TSS (R(2) = 0.50) and Chl-a (R(2) = 0.32, p < 0.05) had a strong positive correlation with the outflow. A seasonal trophic state index revealed oligo-mesotrophic conditions, indicating a limited risk of eutrophication and a positive outcome for long-term management. In conclusion, the Asian monsoon largely controlled the flood and drought conditions and manipulated the flow regime. Exceedingly intensive crop farming in the basin may lead to oligotrophic nutrient enrichment. Although the reservoir water quality was good, we strongly recommend stringent action to alleviate sewage, nutrient, and pollutant inflows to the reservoir.
BACKGROUND: Typhoid fever is endemic in some Pacific Island Countries including Fiji and Samoa yet genomic surveillance is not routine in such settings. Previous studies suggested imports of the global H58 clade of Salmonella enterica var Typhi (Salmonella Typhi) contribute to disease in these countries which, given the MDR potential of H58, does not auger well for treatment. The objective of the study was to define the genomic epidemiology of Salmonella Typhi in Fiji. METHODS: Genomic sequencing approaches were implemented to study the distribution of 255 Salmonella Typhi isolates from the Central Division of Fiji. We augmented epidemiological surveillance and Bayesian phylogenomic approaches with a multi-year typhoid case-control study to define geospatial patterns among typhoid cases. FINDINGS: Genomic analyses showed Salmonella Typhi from Fiji resolved into 2 non-H58 genotypes with isolates from the two dominant ethnic groups, the Indigenous (iTaukei) and non-iTaukei genetically indistinguishable. Low rates of international importation of clones was observed and overall, there were very low levels an antibiotic resistance within the endemic Fijian typhoid genotypes. Genomic epidemiological investigations were able to identify previously unlinked case clusters. Bayesian phylodynamic analyses suggested that genomic variation within the larger endemic Salmonella Typhi genotype expanded at discreet times, then contracted. INTERPRETATION: Cyclones and flooding drove ‘waves’ of typhoid outbreaks in Fiji which, through population aggregation, poor sanitation and water safety, and then mobility of the population, spread clones more widely. Minimal international importations of new typhoid clones suggest that targeted local intervention strategies may be useful in controlling endemic typhoid infection. These findings add to our understanding of typhoid transmission networks in an endemic island country with broad implications, particularly across Pacific Island Countries. FUNDING: This work was supported by the Coalition Against Typhoid through the Bill and Melinda Gates Foundation [grant number OPP1017518], the Victorian Government, the National Health and Medical Research Council Australia, the Australian Research Council, and the Fiji Ministry of Health and Medical Services.
Henan Province in Central China was hit by unprecedented, rain-triggered floods in July 2021 and experienced a recurrence of the COVID-19 pandemic. The current study aims to identify the latent profiles of psychological status and acceptance of change among Henan residents who have been cumulatively exposed to these floods and the COVID-19 pandemic. A total of 977 participants were recruited. Latent profile analysis (LPA) was used to explore underlying patterns of psychological status (i.e., perceived risk of the COVID-19 pandemic, post-traumatic stress symptoms, anxiety and rumination) and acceptance of change. The predictors were evaluated with multinomial logistic regression. LPA identified four patterns of psychological status and acceptance of change: high distress/high acceptance (5.1%), moderate distress/moderate acceptance (20.1%), mild distress/mild acceptance (45.5%), and resilience (29.3%). The additive impact of the floods and COVID-19 pandemic and negative emotion during the floods were the risk factors, while flood coping efficacy, trust, and a closer psychological distance change were the protective factors. The present study therefore provides novel evidence on psychological status after both a natural disaster and a major public health event. The cumulative effects of the floods and the COVID-19 pandemic may have heightened the risk of post-disaster maladaptation. A complex relationship between psychological outcomes and acceptance of change was also found. The findings of this study thus provide a foundation for both disaster management and psychological assistance for particular groups.
Since the outbreak of COVID-19, wearing masks, vaccinations, and maintaining a safe distance has become social behaviors advocated by the government and widely adopted by the public. At the same time, unpredictable natural disaster risks brought by extreme climate change compound difficulties during epidemics and cause systemic risks that influence the existing pattern of epidemic prevention. Therefore, it is necessary to explore the effect of natural disaster risk caused by climate change on the response to outbreaks in the context of the COVID-19 epidemic. This study will focus on individual-level epidemic prevention behaviors, taking as an example the significant risk of severe destructive flooding caused by heavy rains in Henan, China, on July 20, 2021, which claimed 398 lives, to explore the effect of floods on the preventive behaviors of residents in the hardest hit areas against COVID-19. Through the multi-stage stratified random sampling of the affected residents in Zhengzhou, Xinxiang, Hebi, Luoyang, Anyang, and other cities in Henan Province, 2,744 affected people were surveyed via questionnaires. Through the linear regression model and moderating effect analysis, the study found that after floods, the individual’s flood risk perception and response behaviors significantly correlated with the individual’s prevention behaviors against COVID-19. Specifically, both flood risk perception and response behaviors strengthened the individual’s prevention behaviors. Furthermore, the study also found that community risk preparation behavior and social capital can moderate the above relationship to a certain extent. The research can guide risk communication under the compound risk scenario and prevent risky public behavior under the consistent presence of COVID-19 in the community.
This study introduces a new approach for the investigation of infections after an accidental ingestion of contaminated floodwater. The concept of Expected Annual Probability of Infection (EAPI) is introduced and implemented in an infection risk-model approach, by combining a Quantitative Microbial Risk Assessment (QMRA) with the four steps in flood risk assessment. Two groups and exposure paths are considered: adults wading in floodwater and small children swimming/playing in floodwater. The study area is located in Ghana, West Africa. Even though Ghana is one of the most urbanized countries in Africa it has significant problems with water resources management and public health. While cholera is classified as endemic in Accra, the natural and human-made characteristics of the capital makes it prone to flooding. The results of the EAPI approach show that on one hand the concentration of pathogens in floodwater, and thus the risk of infection, decreases with the increase of the flood magnitude. On the other hand, larger floods can spread the pathogens further from the point source, threatening populations previously not identified as at risk by small-scale floods. The concept of EAPI is demonstrated for cholera but it can be extended to other waterborne diseases and also different pathways of exposure, requiring minimal adaptations. For future applications, better estimation of EAPI key components and improvement points are discussed and recommendations given for all the assessment steps.
Prikazi podatkov hiroloških postaj in opozorila
Global food insecurity concerns due to climate change, emphasizes the need to focus on the sensitivity of sorghum to climate change and potential crop improvement strategies available, which is discussed in the current review to promote climate-smart agriculture. Climate change effects immensely disturb the global agricultural systems by reducing crop production. Changes in extreme weather and climate events such as high-temperature episodes and extreme rainfalls events, droughts, flooding adversely affect the production of staple food crops, posing threat to ecosystem resilience. The resulting crop losses lead to food insecurity and poverty and question the sustainable livelihoods of small farmer communities, particularly in developing countries. In view of this, it is essential to focus and adapt climate-resilient food crops which need lower inputs and produce sustainable yields through various biotic and abiotic stress-tolerant traits. Sorghum, “the camel of cereals”, is one such climate-resilient food crop that is less sensitive to climate change vulnerabilities and also an important staple food in many parts of Asia and Africa. It is a rainfed crop and provides many essential nutrients. Understanding sorghum’s sensitivity to climate change provides scope for improvement of the crop both in terms of quantity and quality and alleviates food and feed security in future climate change scenarios. Thus, the current review focused on understanding the sensitivity of sorghum crop to various stress events due to climate change and throws light on different crop improvement strategies available to pave the way for climate-smart agriculture.
Studies have shown that climatic factors can significantly influence transmission of many waterborne diseases. However, knowledge of the impact of climate variability on cryptosporidiosis is much less certain. Associations between the incidence of cryptosporidiosis and climatic variables have been reported in several countries. Given that the identified relationships were not consistently reported across studies, it is not known whether these were country-specific observations or can be considered more globally. Variation in the disease risk in both low- and middle-income countries and high-income countries presents new challenges and opportunities to enact responsive changes in research and public health policies. Available epidemiological evidence of the influence of weather and climate on cryptosporidiosis is reviewed. Fourteen studies met the inclusion criteria, and most studies showed that the incidence of cryptosporidiosis is highly sensitive to climatic conditions, especially temperature, rainfall and relative humidity. The identified associations varied across studies, with different conditions of importance and lag times across different locations. Therefore, there is a need for countries at risk to assess Cryptosporidium transmission routes based on the spatiotemporal patterns of the disease and what role climate and other socio-ecological changes play in the transmission. Information gathering will then allow us to provide information for evidence-based control strategies and mitigation of transmission. This review offers new perspectives on the role of climate variability on Cryptosporidium transmission. It highlights different epidemiological approaches adopted and provides the potential for future research and surveillance to reduce the disease burden. By evaluating the epidemiological transmission of this organism in high-income countries, all mitigation strategies, for example filtration and water catchment management, can be used as exemplars of preventing infection in low- to middle-income countries.
In Italy, human cases of West Nile virus (WNV) infection have been recorded since 2008, and seasonal outbreaks have occurred almost annually. In this study, we summarize available evidences on the epidemiology of WNV and West Nile neuro-invasive disease (WNND) in humans reported between 2012 and 2020. In total, 1145 WNV infection cases were diagnosed; of them 487 (42.5%) had WNND. A significant circulation of the pathogen was suggested by studies on blood donors, with annual incidence rates ranging from 1.353 (95% confidence intervals (95% CI) 0.279-3.953) to 19.069 cases per 100,000 specimens (95% CI 13.494-26.174). The annual incidence rates of WNND increased during the study period from 0.047 cases per 100,000 (95% CI 0.031-0.068) in 2012, to 0.074 cases per 100,000 (95% CI 0.054-0.099) in 2020, peaking to 0.377 cases per 100,000 (95% CI 0.330-0.429) in 2018. There were 60 deaths. Cases of WNND were clustered in Northern Italy, particularly in the Po River Valley, during the months of August (56.7%) and September (27.5%). Higher risk for WNND was reported in subjects of male sex (risk ratio (RR) 1.545, 95% CI 1.392-1.673 compared to females), and in older age groups (RR 24.46, 95% CI 15.61-38.32 for 65-74 y.o.; RR 43.7, 95% CI 28.33-67.41 for subjects older than 75 years), while main effectors were identified in average air temperatures (incidence rate ratio (IRR) 1.3219, 95% CI 1.0053-1.7383), population density (IRR 1.0004, 95% CI 1.0001-1.0008), and occurrence of cases in the nearby provinces (IRR 1.0442, 95% CI 1.0340-1.0545). In summary, an enhanced surveillance is vital for the early detection of human cases and the prompt implementation of response measures.
The coincidence of floods and coronavirus disease 2019 (COVID-19) is a genuine multihazard problem. Since the beginning of 2020, many regions around the World have been experiencing this double hazard of serious flooding and the pandemic. There have been 70 countries with flood events occurring after detection of the country’s first COVID-19 case and hundreds of thousands of people have been evacuated. The main objective of this article is to assess challenges that arise from complex intersections between the threat multipliers and to provide guidance on how to address them effectively. We consider the limitations of our knowledge including “unknown unknowns.” During emergency evacuation, practicing social distancing can be very difficult. However, people are going to take action to respond to rising waters, even if it means breaking quarantine. This is an emergency manager’s nightmare scenario: two potentially serious emergencies happening at once. During this unprecedented year (2020), we are experiencing one of the most challenging flood seasons we have seen in a while. Practical examples of issues and guides for managing floods and COVID-19 are presented. We feel that a new approach is needed in dealing with multiple hazards. Our main messages are: a resilience approach is needed whether in response to floods or a pandemic; preparation is vital, in addition to defense; the responsible actors must be prepared with actions plans and command structure, while the general population must be involved in the discussions so that they are aware of the risk and the reasons for the actions they must take. This article is categorized under:Engineering Water > Methods.
Climate change is negatively impacting the mental health of populations. This scoping review aims to assess the available literature related to climate change and mental health across the World Health Organisation’s (WHO) five global research priorities for protecting human health from climate change. We conducted a scoping review to identify original research studies related to mental health and climate change using online academic databases. We assessed the quality of studies where appropriate assessment tools were available. We identified 120 original studies published between 2001 and 2020. Most studies were quantitative (n = 67), cross-sectional (n = 42), conducted in high-income countries (n = 87), and concerned with the first of the WHO global research priorities-assessing the mental health risks associated with climate change (n = 101). Several climate-related exposures, including heat, humidity, rainfall, drought, wildfires, and floods were associated with psychological distress, worsened mental health, and higher mortality among people with pre-existing mental health conditions, increased psychiatric hospitalisations, and heightened suicide rates. Few studies (n = 19) addressed the other four global research priorities of protecting health from climate change (effective interventions (n = 8); mitigation and adaptation (n = 7); improving decision-support (n = 3); and cost estimations (n = 1)). While climate change and mental health represents a rapidly growing area of research, it needs to accelerate and broaden in scope to respond with evidence-based mitigation and adaptation strategies.
Europeans are not only exposed to direct effects from climate change, but also vulnerable to indirect effects from infectious disease, many of which are climate sensitive, which is of concern because of their epidemic potential. Climatic conditions have facilitated vector-borne disease outbreaks like chikungunya, dengue, and West Nile fever and have contributed to a geographic range expansion of tick vectors that transmit Lyme disease and tick-borne encephalitis. Extreme precipitation events have caused waterborne outbreaks and longer summer seasons have contributed to increases in foodborne diseases. Under the Green Deal, The European Union aims to support climate change health policy, in order to be better prepared for the next health security threat, particularly in the aftermath of the traumatic COVID-19 experience. To bolster this policy process we discuss climate change-related hazards, exposures and vulnerabilities to infectious disease and describe observed impacts, projected risks, with policy entry points for adaptation to reduce these risks or avoid them altogether.
Observed weather and projected climate change suggest an increase in the transmission of vector-borne diseases (VBDs) in the Hindu Kush Himalayan (HKH) region. In this study, we systematically explore the literature for empiric associations between the climate variables and specific VBDs and their vectors in the HKH region. We conducted a systematic synthesis of the published literature on climate variables, VBDs and vectors in the HKH region until the 8th of December 2020. The majority of studies show significant positive associations of VBDs with climatic factors, such as temperature, precipitation, relative humidity, etc. This systematic review allowed us to identify the most significant variables to be considered for evidence-based trend estimates of the effects of climate change on VBDs and their vectors in the HKH region. This evidence-based trend was set into the context of climate change as well as the observed expansion of VBDs and disease vectors in the HKH region. The geographic range of VBDs expanded into previously considered non-endemic areas of highlands (mountains) in the HKH region. Based on scarce, but clear evidence of a positive relationship of most climate variables and VBDs and the observed climatic changes, we strongly recommend an expansion of vector control and surveillance programmes in areas of the HKH region that were previously considered to be non-endemic.
Climate and weather directly impact plant phenology, affecting airborne pollen. The objective of this systematic review is to examine the impacts of meteorological variables on airborne pollen concentrations and pollen season timing. Using PRISMA methodology, we reviewed literature that assessed whether there was a relationship between local temperature and precipitation and measured airborne pollen. The search strategy included terms related to pollen, trends or measurements, and season timing. For inclusion, studies must have conducted a correlation analysis of at least 5 years of airborne pollen data to local meteorological data and report quantitative results. Data from peer-reviewed articles were extracted on the correlations between seven pollen indicators (main pollen season start date, end date, peak date, and length, annual pollen integral, average daily pollen concentration, and peak pollen concentration), and two meteorological variables (temperature and precipitation). Ninety-three articles were included in the analysis out of 9,679 articles screened. Overall, warmer temperatures correlated with earlier and longer pollen seasons and higher pollen concentrations. Precipitation had varying effects on pollen concentration and pollen season timing indicators. Increased precipitation may have a short-term effect causing low pollen concentrations potentially due to “wash out” effect. Long-term effects of precipitation varied for trees and weeds and had a positive correlation with grass pollen levels. With increases in temperature due to climate change, pollen seasons for some taxa in some regions may start earlier, last longer, and be more intense, which may be associated with adverse health impacts, as pollen exposure has well-known health effects in sensitized individuals.
A large-ensemble climate simulation database, which is known as the database for policy decision-making for future climate changes (d4PDF), was designed for climate change risk assessments. Since the completion of the first set of climate simulations in 2015, the database has been growing continuously. It contains the results of ensemble simulations conducted over a total of thousands years respectively for past and future climates using high-resolution global (60 km horizontal mesh) and regional (20 km mesh) atmospheric models. Several sets of future climate simulations are available, in which global mean surface air temperatures are forced to be higher by 4 K, 2 K, and 1.5 K relative to preindustrial levels. Nonwarming past climate simulations are incorporated in d4PDF along with the past climate simulations. The total data volume is approximately 2 petabytes. The atmospheric models satisfactorily simulate the past climate in terms of climatology, natural variations, and extreme events such as heavy precipitation and tropical cyclones. In addition, data users can obtain statistically significant changes in mean states or weather and climate extremes of interest between the past and future climates via a simple arithmetic computation without any statistical assumptions. The database is helpful in understanding future changes in climate states and in attributing past climate events to global warming. Impact assessment studies for climate changes have concurrently been performed in various research areas such as natural hazard, hydrology, civil engineering, agriculture, health, and insurance. The database has now become essential for promoting climate and risk assessment studies and for devising climate adaptation policies. Moreover, it has helped in establishing an interdisciplinary research community on global warming across Japan.
PURPOSE OF REVIEW: The purpose of this review is to summarize researchs that provide risk estimates for the historical and future impact that climate change has had upon dengue published from 2007 through 2019. RECENT FINDINGS: Findings from 30 studies on historical health estimates, with the majority of the studies conducted in Asia, emphasized the importance of temperature, precipitation, and relative humidity, as well as lag effects, when trying to understand how climate change can impact the risk of contracting dengue. Furthermore, 35 studies presented findings on future health risk based upon climate projection scenarios, with a third of them showcasing global level estimates and findings across the articles emphasizing the need to understand risk at a localized level as the impacts from climate change will be experienced inequitably across different geographies in the future. Dengue is one of the most rapidly spreading viral diseases in the world, with ~390 million people infected worldwide annually. Several factors have contributed towards its proliferation, including climate change. Multiple studies have previously been conducted examining the relationship between dengue and climate change, both from a historical and a future risk perspective. We searched the U.S. National Institute of Environmental Health (NIEHS) Climate Change and Health Portal for literature (spanning January 2007 to September 2019) providing historical and future health risk estimates of contracting dengue infection in relation to climate variables worldwide. With an overview of the evidence of the historical and future health risk posed by dengue from climate change across different regions of the world, this review article enables the research and policy community to understand where the knowledge gaps are and what areas need to be addressed in order to implement localized adaptation measures to mitigate the health risks posed by future dengue infection.
BACKGROUND: Projected increases in extreme weather may change relationships between rain-related climate exposures and diarrheal disease. Whether rainfall increases or decreases diarrhea rates is unclear based on prior literature. The concentration-dilution hypothesis suggests that these conflicting results are explained by the background level of rain: Rainfall following dry periods can flush pathogens into surface water, increasing diarrhea incidence, whereas rainfall following wet periods can dilute pathogen concentrations in surface water, thereby decreasing diarrhea incidence. OBJECTIVES: In this analysis, we explored the extent to which the concentration-dilution hypothesis is supported by published literature. METHODS: To this end, we conducted a systematic search for articles assessing the relationship between rain, extreme rain, flood, drought, and season (rainy vs. dry) and diarrheal illness. RESULTS: A total of 111 articles met our inclusion criteria. Overall, the literature largely supports the concentration-dilution hypothesis. In particular, extreme rain was associated with increased diarrhea when it followed a dry period [incidence rate ratio (IRR) = 1.26; 95% confidence interval (CI): 1.05, 1.51], with a tendency toward an inverse association for extreme rain following wet periods, albeit nonsignificant, with one of four relevant studies showing a significant inverse association (IRR = 0.911; 95% CI: 0.771, 1.08). Incidences of bacterial and parasitic diarrhea were more common during rainy seasons, providing pathogen-specific support for a concentration mechanism, but rotavirus diarrhea showed the opposite association. Information on timing of cases within the rainy season (e.g., early vs. late) was lacking, limiting further analysis. We did not find a linear association between nonextreme rain exposures and diarrheal disease, but several studies found a nonlinear association with low and high rain both being associated with diarrhea. DISCUSSION: Our meta-analysis suggests that the effect of rainfall depends on the antecedent conditions. Future studies should use standard, clearly defined exposure variables to strengthen understanding of the relationship between rainfall and diarrheal illness. https://doi.org/10.1289/EHP6181.
In the next century, global warming, due to changes in climatic factors, is expected to have an enormous influence on the interactions between pathogens and their hosts. Over the years, the rate at which vector-borne diseases and their transmission dynamics modify and develop has been shown to be highly dependent to a certain extent on changes in temperature and geographical distribution. Schistosomiasis has been recognized as a tropical and neglected vector-borne disease whose rate of infection has been predicted to be elevated worldwide, especially in sub-Saharan Africa; the region currently with the highest proportion of people at risk, due to changes in climate. This review not only suggests the need to develop an efficient and effective model that will predict Schistosoma spp. population dynamics but seeks to evaluate the effectiveness of several current control strategies. The design of a framework model to predict and accommodate the future incidence of schistosomiasis in human population dynamics in sub-Saharan Africa is proposed. The impact of climate change on schistosomiasis transmission as well as the distribution of several freshwater snails responsible for the transmission of Schistosoma parasites in the region is also reviewed. Lastly, this article advocates for modelling several control mechanisms for schistosomiasis in sub-Saharan Africa so as to tackle the re-infection of the disease, even after treating infected people with praziquantel, the first-line treatment drug for schistosomiasis.
The impact of climate change on the environment, biosphere, and biodiversity has become more evident in the recent years. Human activities have increased atmospheric concentrations of carbon dioxide (CO(2) ) and other greenhouse gases. Change in climate and the correlated global warming affects the quantity, intensity, and frequency of precipitation type as well as the frequency of extreme events such as heat waves, droughts, thunderstorms, floods, and hurricanes. Respiratory health can be particularly affected by climate change, which contributes to the development of allergic respiratory diseases and asthma. Pollen and mold allergens are able to trigger the release of pro-inflammatory and immunomodulatory mediators that accelerate the onset the IgE-mediated sensitization and of allergy. Allergy to pollen and pollen season at its beginning, in duration and intensity are altered by climate change. Studies showed that plants exhibit enhanced photosynthesis and reproductive effects and produce more pollen as a response to high atmospheric levels of carbon dioxide (CO(2) ). Mold proliferation is increased by floods and rainy storms are responsible for severe asthma. Pollen and mold allergy is generally used to evaluate the interrelation between air pollution and allergic respiratory diseases, such as rhinitis and asthma. Thunderstorms during pollen seasons can cause exacerbation of respiratory allergy and asthma in patients with hay fever. A similar phenomenon is observed for molds. Measures to reduce greenhouse gas emissions can have positive health benefits.
Despite being one of the continents with the least greenhouse gas emissions, no continent is being struck as severely by climate change (CC) as Africa. Mosquito-borne diseases (MBD) cause major human diseases in this continent. Current knowledge suggests that MBD range could expand dramatically in response to CC. This study aimed at assessing the relationship between CC and MBD in Africa. Methods For this purpose, a systematic peer review was carried out, considering all articles indexed in PubMed, Scopus, Embase and CENTRAL. Search terms referring to MBD, CC and environmental factors were screened in title, abstract and keywords.Results A total of twenty-nine studies were included, most of them on malaria (61%), being Anopheles spp. (61%) the most commonly analyzed vector, mainly in Eastern Africa (48%). Seventy-nine percent of these studies were based on predictive models. Seventy-two percent of the reviewed studies considered that CC impacts on MBD epidemiology. MBD prevalence will increase according to 69% of the studies while 17% predicted a decrease. MBD expansion throughout the continent was also predicted. Most studies showed a positive relationship between observed or predicted results and CC. However, there was a great heterogeneity in methodologies and a tendency to reductionism, not integrating other variables that interact with both the environment and MBD. In addition, most results have not yet been tested. A global health approach is desirable in this kind of research. Nevertheless, we cannot wait for science to approve something that needs to be addressed now to avoid greater effects in the future.
BACKGROUND: Mosquito-borne viral infections have in recent years, become a public health threat globally. This review aimed to provide an overview of the ecological and epidemiological profiles of mosquito-borne viral infections in the Democratic Republic of the Congo (DRC). METHODS: A search of literature was conducted using Google Scholar, PubMed and the WHO website using the following keywords: “Democratic Republic of the Congo”, “Zaire”, “Belgian Congo” and either of the following: “mosquito-borne virus”, “arbovirus”, “yellow fever”, “dengue”, “chikungunya”, “West Nile”, “Rift Valley fever”, “O’nyong’nyong”, “Zika”, “epidemiology”, “ecology”, “morbidity”, “mortality”. Published articles in English or French covering a period between 1912 and October 2018 were reviewed. RESULTS: A total of 37 articles were included in the review. The findings indicate that the burden of mosquito-borne viral infections in DRC is increasing over time and space. The north-western, north-eastern, western and central regions have the highest burden of mosquito-borne viral infections compared to south and eastern highland regions. Yellow fever, chikungunya, dengue, Zika, Rift Valley fever, West Nile and O’nyong’nyong have been reported in the country. These mosquito-borne viruses were found circulating in human, wildlife and domestic animals. Yellow fever and chikungunya outbreaks have been frequently reported. Aedes aegypti and Ae. simpsoni were documented as the main vectors of most of the mosquito-borne viral infections. Heavy rains, human movements, forest encroachment and deforestation were identified as drivers of mosquito-borne viruses occurrence in DRC. CONCLUSIONS: Mosquito-borne viral infections are becoming common and a serious public health problem in DRC. In the current context of climate change, there is urgent need to improve understanding on ecological and epidemiology of the diseases and strengthen surveillance systems for prompt response to epidemics in DRC.
Climate change is expanding the global at-risk population for vector-borne diseases (VBDs). The World Health Organization (WHO) health emergency and disaster risk management (health-EDRM) framework emphasises the importance of primary prevention of biological hazards and its value in protecting against VBDs. The framework encourages stakeholder coordination and information sharing, though there is still a need to reinforce prevention and recovery within disaster management. This keyword-search based narrative literature review searched databases PubMed, Google Scholar, Embase and Medline between January 2000 and May 2020, and identified 134 publications. In total, 10 health-EDRM primary prevention measures are summarised at three levels (personal, environmental and household). Enabling factor, limiting factors, co-benefits and strength of evidence were identified. Current studies on primary prevention measures for VBDs focus on health risk-reduction, with minimal evaluation of actual disease reduction. Although prevention against mosquito-borne diseases, notably malaria, has been well-studied, research on other vectors and VBDs remains limited. Other gaps included the limited evidence pertaining to prevention in resource-poor settings and the efficacy of alternatives, discrepancies amongst agencies’ recommendations, and limited studies on the impact of technological advancements and habitat change on VBD prevalence. Health-EDRM primary prevention measures for VBDs require high-priority research to facilitate multifaceted, multi-sectoral, coordinated responses that will enable effective risk mitigation.
East Africa is highly affected by neglected tropical diseases (NTDs), which are projected to be exacerbated by climate change. Consequently, understanding what research has been conducted and what knowledge gaps remain regarding NTDs and climate change is crucial to informing public health interventions and climate change adaptation. We conducted a systematic scoping review to describe the extent, range, and nature of publications examining relationships between NTDs and climatic factors in East Africa. We collated all relevant English and French publications indexed in PubMed(®), Web of Science™ Core Collection, and CAB Direct(©) databases published prior to 2019. Ninety-six publications were included for review. Kenya, Tanzania, and Ethiopia had high rates of publication, whereas countries in the Western Indian Ocean region were underrepresented. Most publications focused on schistosomiasis (n = 28, 29.2%), soil-transmitted helminthiases (n = 16, 16.7%), or human African trypanosomiasis (n = 14, 14.6%). Precipitation (n = 91, 94.8%) and temperature (n = 54, 56.3%) were frequently investigated climatic factors, whereas consideration of droughts (n = 10, 10.4%) and floods (n = 4, 4.2%) was not prominent. Publications reporting on associations between NTDs and changing climate were increasing over time. There was a decrease in the reporting of Indigenous identity and age factors over time. Overall, there were substantial knowledge gaps for several countries and for many NTDs. To better understand NTDs in the context of a changing climate, it would be helpful to increase research on underrepresented diseases and regions, consider demographic and social factors in research, and characterize how these factors modify the effects of climatic variables on NTDs in East Africa.
Oncomelania hupensis quadrasi is the snail intermediate host of Schistosoma japonicum in the Philippines. It was discovered by Dr. Marcos Tubangui in 1932 more than two decades after the discovery of the disease in the country in 1906. This review, the first for O. h. quadrasi, presents past and present works on the taxonomy, biology, ecology, control, possible paleogeographic origin of the snail intermediate host and future in research, control and surveillance of the snail. Extensive references are made of other subspecies of O. hupensis such as the subspecies in China for which majority of the advances has been accomplished. Contrasting views on whether the snail is to be considered an independent species of Oncomelania or as one of several subspecies of Oncomelania hupensis are presented. Snail control methods such as chemical methods using synthetic and botanical molluscicides, environmental manipulation and biological control are reviewed. Use of technologies such as Remote Sensing, Geographical Information System and landscape genetics is stressed for snail surveillance. Control and prevention efforts in the Philippines have consistently focused on mass drug administration which has proved inadequate in elimination of the disease. An integrated approach that includes snail control, environmental sanitation and health education has been proposed. Population movement such as migration for employment and economic opportunities and ecotourism and global climate change resulting in heavy rains and flooding challenge the gains of control and elimination efforts. Concern for possible migration of snails to non-endemic areas is expressed given the various changes both natural and mostly man-made favoring habitat expansion.
Changes to Australia’s climate and land-use patterns could result in expanded spatial and temporal distributions of endemic mosquito vectors including Aedes and Culex species that transmit medically important arboviruses. Climate and land-use changes greatly influence the suitability of habitats for mosquitoes and their behaviors such as mating, feeding and oviposition. Changes in these behaviors in turn determine future species-specific mosquito diversity, distribution and abundance. In this review, we discuss climate and land-use change factors that influence shifts in mosquito distribution ranges. We also discuss the predictive and epidemiological merits of incorporating these factors into a novel integrated statistical (SSDM) and mechanistic species distribution modelling (MSDM) framework. One potentially significant merit of integrated modelling is an improvement in the future surveillance and control of medically relevant endemic mosquito vectors such as Aedes vigilax and Culex annulirostris, implicated in the transmission of many arboviruses such as Ross River virus and Barmah Forest virus, and exotic mosquito vectors such as Aedes aegypti and Aedes albopictus. We conducted a focused literature search to explore the merits of integrating SSDMs and MSDMs with biotic and environmental variables to better predict the future range of endemic mosquito vectors. We show that an integrated framework utilising both SSDMs and MSDMs can improve future mosquito-vector species distribution projections in Australia. We recommend consideration of climate and environmental change projections in the process of developing land-use plans as this directly impacts mosquito-vector distribution and larvae abundance. We also urge laboratory, field-based researchers and modellers to combine these modelling approaches. Having many different variations of integrated (SDM) modelling frameworks could help to enhance the management of endemic mosquitoes in Australia. Enhanced mosquito management measures could in turn lead to lower arbovirus spread and disease notification rates.
PURPOSE OF REVIEW: To describe a collection of recent work published on thermal suitability for vector-borne diseases, in which mapping approaches illustrated the geographic shifts, and spatial approaches describe the demographic impact anticipated with a changing climate. RECENT FINDINGS: While climate change predictions of warming indicate an expansion in VBD suitability risk in some parts of the globe, while in others, optimal temperatures for transmission may be exceeded, as seen for malaria in Western Africa, resulting in declining risk. The thermal suitability of specific vector-pathogen pairs can have large impacts on geographic range of risk, and changes in human demography itself will intersect with this risk to create different vulnerability profiles over the coming century. Using a physiological approach to describe the thermal suitability of transmission for vector-borne diseases allows us to illustrate the future risk as mapped information. This in turn can be coupled with demographic projections to anticipate changing risk, and even changing vulnerability within that population change.
Melioidosis, caused by the facultative intracellular gram-negative pathogen Burkholderia pseudomallei, is an emerging cause of community-acquired pneumonia across the tropics. The majority of patients present with pneumonia with or without sepsis, but localized and asymptomatic infection is also well recognized. Recent modeling and epidemiological studies have demonstrated the widespread presence of B. pseudomallei in otherwise unrecognized regions with a predicted mortality of 90,000 deaths worldwide. Innovative environmental studies are also uncovering how hydrodynamic, pedology, fauna, and weather events influence geographic distribution and incidence of melioidosis cases. Of concern is the changes associated with global warming, which will be conducive to B. pseudomallei in combination with the global diabetes pandemic. In fact, over 80% of patient developing melioidosis have underlying comorbidities. For this great mimicker, culture remains the mainstay of diagnosis and despite availability of other assays, challenges still remain in reducing time to diagnosis and avoiding misdiagnosis. With institution of timely antimicrobials such as ceftazidime and supportive intensive care, overall mortality can be reduced to 10%, although this can still be as high as 50% in poorly resourced areas. Promise is on the horizon with the first human vaccine trials being planned for 2021. Meanwhile new multiomics techniques are giving us a better understanding of the role of virulence and host-pathogen interactions on patient outcomes.
Climate extremes threaten human health, economic stability, and the wellbeing of natural and built environments (e.g., 2003 European heat wave). As the world continues to warm, climate hazards are expected to increase in frequency and intensity. The impacts of extreme events will also be more severe due to the increased exposure (growing population and development) and vulnerability (aging infrastructure) of human settlements. Climate models attribute part of the projected increases in the intensity and frequency of natural disasters to anthropogenic emissions and changes in land use and land cover. Here, we review the impacts, historical and projected changes, and theoretical research gaps of key extreme events (heat waves, droughts, wildfires, precipitation, and flooding). We also highlight the need to improve our understanding of the dependence between individual and interrelated climate extremes because anthropogenic-induced warming increases the risk of not only individual climate extremes but also compound (co-occurring) and cascading hazards. Climate hazards are expected to increase in frequency and intensity in a warming world. Anthropogenic-induced warming increases the risk of compound and cascading hazards. We need to improve our understanding of causes and drivers of compound and cascading hazards.
BACKGROUND: Both the World Health Organization and the Intergovernmental Panel on Climate Change project that malnutrition will be the greatest contributor to climate change-associated morbidity and mortality. Although there have been several studies that have examined the potential effects of climate change on human health broadly, the effects on malnutrition are still not well understood. We conducted a systematic review investigating the role of three climate change proxies (droughts, floods, and climate variability) on malnutrition in children and adults. METHODS AND FINDINGS: We identified 22 studies examining the effects of droughts, floods, and climate variability on at least one malnutrition metric. We found that 17 out of 22 studies reported a significant relationship between climate change proxies and at least one malnutrition metric. In meta-analysis, drought conditions were significantly associated with both wasting (Odds Ratio [OR] 1.46, 95% Confidence Interval [CI] 1.05-2.04) and underweight prevalence (OR 1.46, 95% CI 1.01-2.11). CONCLUSIONS: Given the long-term consequences of malnutrition on individuals and society, adoption of climate change adaptation strategies such as sustainable agriculture and water irrigation practices, as well as improving nutritional interventions aimed at children aged 1-2 years and older adults, should be prioritised on global policy agendas in the coming years.
Efforts have been made to quantify the spatio-temporal malaria transmission intensity over India using the dynamical malaria model, namely, Vector-borne Disease Community Model of International Centre for Theoretical Physics Trieste (VECTRI). The likely effect of climate change in the variability of malaria transmission intensity over different parts of India is also investigated. The Historical data and future projection scenarios of the rainfall and temperature derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model output are used for this purpose. The Entomological Inoculation Rate (EIR) and Vector are taken as quantifiers of malaria transmission intensity. It is shown that the maximum number of malaria cases over India occur during the Sept-Oct months, whereas the minimum during the Feb-Apr months. The malaria transmission intensity as well as length of transmission season over India is likely to increase in the future climate as a result of global warming.
Environmental variables related to vegetation and weather are some of the most influential factors that impacting Aedes (Stegomya) aegypti, a mosquito vector of dengue, chikungunya and Zika viruses. In this paper, we aim to develop temporal predictive models for Ae. aegypti oviposition activity utilizing vegetation and meteorological variables as predictors in Córdoba city (Argentina). Eggs were collected using ovitraps placed throughout the city from 2009 to 2012 that were replaced weekly. Temporal generalized linear mixed models were developed with negative binomial distributions of errors that model average number of eggs collected weekly as a function of vegetation and meteorological variables with time lags. The best model included a vegetation index, vapor pressure of water, precipitation and photoperiod. With each unit of increment in vegetation index per week the average number of eggs increased by 1.71 in the third week. Furthermore, each millimeter increase of accumulated rain during 4 weeks was associated with a decrease of 0.668 in the average number of eggs found in the following week. This negative effect of precipitation could occur during abundant rainfalls that fill containers completely, thereby depriving females of oviposition sites and leading them to search for other suitable breeding sites. Furthermore, the average number of eggs increased with the photoperiod at low values of mean vapor pressure; however the average number of eggs decreased at high values of mean vapor pressure, and the positive relationship between the response variable and mean vapor pressure was stronger at low values of photoperiod. Additionally, minimum temperature was associated positively with oviposition activity and that low minimum temperatures could be a limiting factor in Ae. aegypti oviposition activity. Our results emphasize the important role that climatic variables such as temperature, precipitation, and vapor pressure play in Ae. aegypti oviposition activity and how these variables along with vegetation indices can be used to inform predictive temporal models of Ae. aegypti population dynamics that can be used for informing mosquito population control and arbovirus mitigation strategies.
The urban heat island is a representative urban climate characteristic, which can affect heat-stress conditions and extreme precipitation that are closely connected with human life. Better understanding of urban-climate interactions, therefore, is crucial to ultimately support better planning and adaptation in various application fields. This study assesses urban-climate interactions during summer for eastern North America using regional climate model simulations at 0.22° resolution. Two regional climate model experiments, with and without realistic representation of urban regions, are performed for the 1981–2010 period. Comparison of the two experiments shows higher mean temperatures and reduced mean precipitation in the simulation with realistic urban representation, which can be attributed primarily to reduced albedo and soil moisture for the urban regions in this simulation. Furthermore, the mean temperature and precipitation in the simulation with improved urban representation is also closer to that observed. Analysis of short-duration precipitation extremes for climatologically different sub-regions, however, suggests that, for higher temperatures, the magnitudes of precipitation extremes are generally higher in the simulation with realistic urban representation, particularly for coastal urban regions, and are collocated with higher values of convective available potential energy and cloud fraction. Enhanced sea and lake breezes associated with lower sea level pressure found around these regions, contribute additional water vapor and further enhance dynamic convective development, leading to higher precipitation intensities. Analysis of temperature extremes clearly demonstrates that urban regions experience aggravated heat-stress conditions due to relatively higher temperatures despite reduced relative humidity. Double the number of extreme heat spells lasting six or more days are noted for the coastal urban regions in the study domain. This study, in addition to demonstrating the differences in urban-climate interactions for climatologically different regions, also demonstrates the need for better representation of urban regions in climate models to generate realistic climate information.
Climate change and urbanization are converging to challenge the flood control in the Pearl River Delta (PRD) due to their adverse impacts on precipitation extremes and the urban areas environment. Previous studies have investigated temporal changes in flood risk with various single factor, few have considered the joint effects of climate change, urbanization and socio-economic development. Here, based on the representative concentration pathway (RCP) scenarios, we conducted a comprehensive assessment of future (2030-2050) flood risk over the PRD combined with a thorough investigation of climate change, urbanization and socio-economic development. Precipitation extremes were projected using the regional climate model RegCM4.6, and urbanization growth was projected based on the CA-Markov model. The economic and population development was estimated by the shared socio-economic pathways (SSPs). Flood risk mapping with different RCPs-urbanization-SSPs scenarios was developed for the PRD based on the set pair analyze theory. The results show that climate change and urbanization are expected to exacerbate flood risk in most parts of the PRD during the next few decades, concurrently with more intense extreme precipitation events. The high flood risk areas are projected mainly in the urban regions with unfavorable terrain and dense population. The highest flood risk areas are expected to increase by 8.72% and 19.80% under RCP4.5 and RCP8.5 scenarios, respectively. Reducing greenhouse gas emissions may effectively mitigate the flood risk over the PRD. This study highlight the links between flood risk and changing environment, suggesting that flood risk management and preventative actions should be included in regional adaptation strategies.
BACKGROUND: Ross River virus (RRV) disease is Australia’s most widespread vector-borne disease causing significant public health concern. The aim of this study was to identify the ecological covariates of RRV risk and to develop epidemic forecasting models in a disease hotspot region of South Australia. METHODS: Seasonal autoregressive integrated moving average models were used to predict the incidence of RRV disease in the Riverland region of South Australia, an area known to have a high incidence of the disease. The model was developed using data from January 2000 to December 2012 then validated using disease notification data on reported cases for the following year. RESULTS: Monthly numbers of the mosquito Culex annulirostris (?=0.033, p<0.001) and total rainfall (?=0.263, p=0.002) were significant predictors of RRV transmission in the study region. The forecasted RRV incidence in the predictive model was generally consistent with the actual number of cases in the study area. CONCLUSIONS: A predictive model has been shown to be useful in forecasting the occurrence of RRV disease, with increased vector populations and rainfall being important factors associated with transmission. This approach may be useful in a public health context by providing early warning of vector-borne diseases in other settings.
The present study describes the development of a web-based flood risk information system ‘WebFRIS’ for Jagatsinghpur district, a severely flood-prone region in Eastern India. The WebFRIS is designed by using various readily available open-source web tools and packages such as Google Map, PHP, MySQL, and JSON. Special emphasis is directed towards designing the layout and architecture, to be easily accessible by any end-user irrespective of any technical know-how. The WebFRIS illustrates spatial maps of flood hazard, socio-economic vulnerability, and flood risk at the village level for two-time scenarios. While analyzing a set of graphical statistics depicting the changes in flood risk components, a significant increase in high and very-high categories of both flood hazard (~140%) and socio-economically vulnerable villages (~68%) is noticed during Scenario-I. The number of villages facing compound risk (contributed equally by flood hazard and socio-economic vulnerability) nearly doubled in Scenario-I. A spatial analysis of diametric changes in flood risk shows that a large proportion of villages in Balikuda, Ersama, and Tirtol tehsils have undergone radical changes. Following these observations, a set of possible engineering, social, and policy measures are proposed, whose implementation in the near future is expected to reinforce flood management in the study area. The WebFRIS architecture is flexible, easy-to-use; it is expected to provide crucial lessons to the local bodies, town-planners, water professionals, flood experts, and also the citizens, a precious knowledge on flood risk management. The WebFRIS may be considered as a precious cartographic product for environmental management. The proposed web platform is generic, as it can be applied to study other inter-related systems such as environmental protection, land-use planning, coastal habitat restoration, and community resilience building.
The association between meteorological factors and infectious diarrhea has been widely studied in many countries. However, investigation among children under 5 years old in Jiangsu, China remains quite limited. Data including infectious diarrhea cases among children under five years old and daily meteorological indexes in Jiangsu, China from 2015 to 2019 were collected. The lag-effects up to 21 days of daily maximum temperature (Tmax) on infectious diarrhea were explored using a quasi-Poisson regression with a distributed lag non-linear model (DLNM) approach. The cases number of infectious diarrhea was significantly associated with seasonal variation of meteorological factors, and the burden of disease mainly occurred among children aged 0-2 years old. Moreover, when the reference value was set at 16.7°C, Tmax had a significant lag-effect on cases of infectious diarrhea among children under 5 years old in Jiangsu Province, which was increased remarkably in cold weather with the highest risk at 8°C. The results of DLNM analysis implicated that the lag-effect of Tmax varied among the 13 cities in Jiangsu and had significant differences in 8 cities. The highest risk of Tmax was presented at 5 lag days in Huaian with a maximum RR of 1.18 (95% CI: 1.09, 1.29). Suzhou which had the highest number of diarrhea cases (15830 cases), had a maximum RR of 1.04 (95% CI:1.03, 1.05) on lag 15 days. Tmax is a considerable indicator to predict the epidemic of infectious diarrhea among 13 cities in Jiangsu, which reminds us that in cold seasons, more preventive strategies and measures should be done to prevent infectious diarrhea.
PURPOSE: Salmonella is one of the main causes of gastroenteritis, and its incidence may be affected by meteorological variables. This is the first study about the effect of climatic factors on salmonella incidence in Kermanshah, Iran. METHODS: Data about salmonellosis cases in Kermanshah were inquired from Center for Communicable Disease Control, at the Ministry of Health and Medical Education of Iran, for the 2008 to 2018 time-frame. Meteorological variables including maximum, minimum and mean of temperature and humidity, sunshine hours and rainfall were inquired for the same time frame. Negative binomial generalized linear models (GLM) were used to assess the effect of meteorological variables on the weekly incidence of salmonellosis. RESULTS: During the years under study, 569 confirmed cases were registered in Kermanshah province. Study results showed a 3?% increase in salmonellosis incidence, after 1?% increase in minimum humidity in the week before (incidence rate ratio (IRR): 1.03; 95?% confidence interval (CI):1.02-1.05) and also a 4?% increase in incidence for 1 °C increase in mean temperature in the same week (IRR: 1.04; 95?% CI:1.02-1.06). CONCLUSIONS: Increase in minimum humidity and mean temperature may have a role in increasing the incidence of salmonellosis in Iran.
Spontaneous pneumothorax (SP) is defined as the presence of free air inside the pleural space. Many studies have reported that meteorological variables may trigger SP, but the mechanism is unknown. The aim of this study was to compare the effects of meteorological variables on the development of SP in two regions with different altitudes. The study was conducted in the Çanakkale (2 m above sea level) and the Erzurum region (1758 m). A total of 494 patients with SP who presented to the hospitals of the two regions between January 2011 and December 2016 were included in the study. The meteorological variables used included ambient temperature, atmospheric pressure, relative humidity, precipitation amount, wind speed, and wind direction (as north and south). The total 2192 days were divided into two as days with and without an SP case presentation. A 4-day period prior to the day a case presented was compared with the other days without any cases to investigate the presence of any lagged effect. Statistical significance was accepted at p?<?0.05. Comparison of these two regions showed a significant difference between them. The meteorological variables of the regions that affect SP development were found to be low mean minimum temperature, high daily temperature change, low precipitation, low wind speed and north winds for Erzurum, and only rainy days for Çanakkale. The results have demonstrated that cold weather, sudden temperature changes, north winds, and low wind speed are risk factors for the development of SP at high altitudes.
OBJECTIVE: The objective of the study was to explore the influences of seasonality, meteorological conditions, and air pollution exposure on the number of patients who visit the hospital due to seizures. METHODS: Outpatient and inpatient data from the National Health Insurance Database of Taiwan from 2009 to 2013, meteorological data from the Meteorological Bureau, and air pollution exposure data from the Taiwan Air Quality Monitoring Stations were collected and integrated into daily time series data. The following data processing and analysis results are based on the mean of the 7?days’ lag data of the 18 meteorological condition/air pollution exploratory factors to identify the critical meteorological conditions and air pollution exposure factors by executing univariate analysis. The average hospital visits for seizure per day by month were used as an index of observation. The effect of seasonality has also been examined. RESULTS: The average visits per day by month had a significant association with 10 variables. Overall, the number of visits due to these factors has been estimated to be 71.529 (13.7%). The most obvious factors affecting the estimated number of visits include ambient temperature, CH(4), and NO. Six air pollutants, namely CH(4), NO, CO, NO(2), PM2.5, and NMHC had a significantly positive correlation with hospital visits due to seizures. Moreover, the average daily number of hospital visits was significantly high in January and February (winter season in Taiwan) than in other months (R(2)?=?0.422). CONCLUSION: The prediction model obtained in this study indicates the necessity of rigorous monitoring and early warning of these air pollutants and climate changes by governments. Additionally, the study provided a firm basis for establishing prediction models to be used by other countries or for other diseases.
The human population is increasing. The ongoing urbanization process, in conjunction with climate change, is causing larger environmental footprints. Consequently, quality of life in urban systems worldwide is under immense pressure. Here, the seasonal characteristics of Maribor’s urban thermal environment were studied from the perspectives of surface urban heat island (SUHI) and urban heat island (UHI) A remote sensing thermal imagery time series and in-situ measurements (stationary and mobile) were combined with select geospatial predictor variables to model this atmospheric phenomenon in its most intensive season (summer). Finally, CMIP6 climate change scenarios and models were considered, to predict future UHI intensity. Results indicate that Maribor’s UHI intensity maximum shifted from winter to spring and summer. The implemented generalized additive model (GAM) underestimates UHI intensity in some built-up parts of the study area and overestimates UHI intensity in green vegetated areas. However, by the end of the century, UHI magnitude could increase by more than 60% in the southern industrial part of the city. Such studies are of particular concern, in regards to the increasing frequency of heat waves due to climate change, which further increases the (already present) heat stress in cities across the globe.
Some studies have demonstrated that precipitation is an important risk factor of dengue epidemics. However, current studies mostly focused on a single precipitation variable, and few studies focused on the impact of precipitation patterns on dengue epidemics. This study aims to explore optimal precipitation patterns for dengue epidemics. Weekly dengue case counts and meteorological data from 2006 to 2018 in Guangzhou of China were collected. A generalized additive model with Poisson distribution was used to investigate the association between precipitation patterns and dengue. Precipitation patterns were defined as the combinations of three weekly precipitation variables: accumulative precipitation (Pre_A), the number of days with light or moderate precipitation (Pre_LMD), and the coefficient of precipitation variation (Pre_CV). We explored to identify optimal precipitation patterns for dengue epidemics. With a lead time of 10 weeks, minimum temperature, relative humidity, Pre_A, and Pre_LMD were positively associated with dengue, while Pre_CV was negatively associated with dengue. A precipitation pattern with Pre_A of 20.67-55.50 mm per week, Pre_LMD of 3-4 days per week, and Pre_CV less than 1.41 per week might be an optimal precipitation pattern for dengue epidemics in Guangzhou. The finding may be used for climate-smart early warning and decision-making of dengue prevention and control.
Culex mosquitoes are important vectors of West Nile Virus (WNV), St. Louis Encephalitis Virus (SLEV) and Japanese Encephalitis Virus (JEV). Climate change is expected to alter their ability to spread diseases in human populations. Studies examining the influence of climate variability on Culex mosquitoes in South East Asia are scarce. We examined the influence of climate variability on reported Culex mosquito larval habitats from 2009 to 2018 in Singapore. We analysed the non-linear immediate and lagged weather dependence of Culex habitats over 5 weeks in negative binomial regression models using nationally representative data. We adjusted for the effects of long-term trend, seasonality, public holidays and autocorrelation. There were 41,170 reported Culex larval habitats over the study period. Non-residential premises were associated with more reports of habitats compared to residential premises [Rate Ratio (RR): 113.9, 95% CI: 110.9, 116.9]. Larvae in more than 90% of these habitats were entomologically identified as Culex quinquefasciatus. In residences, every 10 mm increase in rainfall above a 90 mm threshold was associated with a 10.1% [Incidence Rate Ratio (IRR): 0.899, 95% CI: 0.836, 0.968] cumulative decline in larval habitats. Public holidays were not significantly included in the model analysing larval habitats in residences. In non-residences, a 1 °C increase in the ambient air temperature with respect to the mean was associated with a 36.0% (IRR: 1.360, 95% CI: 1.057, 1.749) cumulative increase in Culex larval habitats. Public holidays were associated with a decline in Culex larval habitats in the same week. Our study provides evidence of how ambient air temperature and rainfall variability influences the abundance of Culex mosquito larval habitats. Our findings support the utility of using weather data in predictive models to inform the timing of vector control measures aimed at reducing the risk of WNV and other Culex-borne flavivirus transmission in urban areas.
Previous studies found non-linear mutual interactions among hydrometeorological factors on diarrheal disease. However, the complex interactions of the hydrometeorological, topographical and human activity factors need to be further explored. This study aimed to reveal how hydrological and other factors jointly influence bacillary dysentery in different geographical regions. Using Anhui Province in China, consisted of Huaibei plain, Jianghuai hilly and Wannan mountainous regions, we integrated multi-source data (6 meteorological, 3 hydrological, 2 topographic, and 9 socioeconomic variables) to explore the direct and interactive relationship between hydrological factors (quick flow, baseflow and local recharge) and other factors by combining the ecosystem model InVEST with spatial statistical analysis. The results showed hydrological factors had significant impact powers (q = 0.444 (Huaibei plain) for local recharge, 0.412 (Jianghuai hilly region) and 0.891 (Wannan mountainous region) for quick flow, respectively) on bacillary dysentery in different regions, but lost powers at provincial level. Land use and soil properties have created significant interactions with hydrological factors across Anhui province. Particularly, percentage of farmland in Anhui province can influence quick flow across Jianghuai, Wannan regions and the whole province, and it also has significant interactions with the baseflow and local recharge across the plain as well as the whole province. Percentage of urban areas had interactions with baseflow and local recharge in Jianghuai and Wannan regions. Additionally, baseflow and local recharge could be interacted with meteorological factors (e.g. temperature and wind speed), while these interactions varied in different regions. In conclusion, it was evident that hydrological factors had significant impacts on bacillary dysentery, and also interacted significantly with meteorological and socioeconomic factors. This study applying ecosystem model and spatial analysis help reveal the complex and nonlinear transmission of bacillary dysentery in different geographical regions, supporting the development of precise public health interventions with consideration of hydrological factors.
In recent years, there have been considerable changes in the distribution of diseases that are potentially tied to ongoing climate variability. The aim of this study was to investigate the association between the incidence of cutaneous leishmaniasis (CL) and climatic factors in an Iranian city (Isfahan), which had the highest incidence of CL in the country. CL incidence and meteorological data were acquired from April 2010 to March 2017 (108 months) for Isfahan City. Univariate and multivariate seasonal autoregressive integrated moving average (SARIMA), generalized additive models (GAM), and generalized additive mixed models (GAMM) were used to identify the association between CL cases and meteorological variables, and forecast CL incidence. AIC, BIC, and residual tests were used to test the goodness of fit of SARIMA models; and R(2) was used for GAM/GAMM. 6798 CL cases were recorded during this time. The incidence had a seasonal pattern and the highest number of cases was recorded from August to October. In univariate SARIMA, (1,0,1) (0,1,1)(12) was the best fit for predicting CL incidence (AIC=8.09, BIC=8.32). Time series regression (1,0,1) (0,1,1)(12) showed that monthly mean humidity after 4-month lag was inversely related to CL incidence (AIC=8.53, BIC=8.66). GAMM results showed that average temperature with 2-month lag, average relative humidity with 3-month lag, monthly cumulative rainfall with 1-month lag, and monthly sunshine hours with 1-month lag were related to CL incidence (R(2)=0.94). The impact of meteorological variables on the incidence of CL is not linear and GAM models that include non-linear structures are a better fit for prediction. In Isfahan, Iran, meteorological variables can greatly predict the incidence of CL, and these variables can be used for predicting outbreaks.
Urbanization models that do not comply with the planning criteria are affecting human lives. In urban areas, street trees have positive contributions to the ecosystem and human thermal comfort. In this study, the thermal comfort of the main streets that connect people to each other and provide access and transportation has been thermally explored. Cumhuriyet Street, which is one of the vibrant streets in Erzurum, was selected as a case study scenario in the winter and summer periods in 2018 by using the ENVI-met V. 4.4.2 winter model. A different green scenario is proposed, and the best thermal comfort scenario in both seasons is determined. The results show that, in the summer period, the air temperature of the greener street scenario is about 1.0 °C cooler than the existing condition and about 2.0 °C warmer in the winter period. Physiological equivalent temperature (PET) value was better in narrow canyon streets in winter months, but in wide canyon streets in summer months. The green scenarios of wide canyon streets positively affect the outdoor thermal comfort in both seasons. These results clearly imply that green streets are an appropriate strategy for city streets that suffer from discomfort levels in cold winter and hot summer periods. It has been concluded that it is possible to increase thermal comfort through improvement in the open space in street and more suitable plant preferences for livable urbanization. Planning streets in a new city characterized by summer and winter seasons should take into consideration an accurate decision for providing a thermal comfort level and healthy urbanization.
We herein report a 56-year-old woman who developed allergic bronchopulmonary aspergillosis (ABPA) possibly due to fungal exposure after disastrous heavy rainfall in Western Japan in 2018. She was diagnosed with ABPA complicated with asthma, increased peripheral blood eosinophil count, elevation of specific immunoglobulin E for Aspergillus fumigatus, positive Aspergillus fumigatus precipitation antibody reaction test results, and notable chest computed tomography findings. After treatment with benralizumab, her symptoms, peripheral blood eosinophil count, radiological findings, and respiratory function dramatically improved. The administration of benralizumab appears to be an effective treatment strategy for ABPA.
Objective: Numerous epidemiological studies have reported relevance of morbidity and mortality from cardiovascular diseases with short-term exposure to environmental temperature. In this study, we examined the hypothesis between temperature indices and hospital admission because of cardiovascular diseases. Methods: The daily number of CVDs was obtained from all hospitals of the Sabzevar city. A semi-parametric generalized additive model (GAM) following a quasi-Poisson distribution with distributed lag non-linear model (dlnm) was selected as a modeling framework for time-series analysis. Results: The overall CVD risk comparing the 1st percentile and the 99th percentile relative to the mean temperature (at lag 0) was 1.33 (95% CI, 1.11: 1.61), and 1.34 (95% CI, 1.10: 1.64), respectively. For all indicators, the extremely cold effects persisted for the initial 7 days. Conclusions: Our results suggest that extremely cold and extremely hot temperatures increase the relative risk of cardiovascular diseases.
INTRODUCTION: Enteric Fever (EF) affects over 14.5 million people every year globally, with India accounting for the largest share of this burden. The water-borne nature of the disease makes it prone to be influenced as much by unsanitary living conditions as by climatic factors. The detection and quantification of the climatic effect can lead to improved public health measures which would in turn reduce this burden. METHODOLOGY: We obtained a list of monthly Widal positive EF cases from 1995 to 2017 from Ahmedabad and Surat Municipalities. We obtained population data, daily weather data, and Oceanic Niño Index values from appropriate sources. We quantified the association between extreme weather events, phases of El Niño Southern Oscillations (ENSO) and incidence of EF. RESULTS: Both cities showed a seasonal pattern of EF, with cases peaking in early monsoon. Risk of EF was affected equally in both cities by the monsoon season — Ahmedabad (35%) and Surat (34%). Extreme precipitation was associated with 5% increase in EF in Ahmedabad but not in Surat. Similarly, phases of ENSO had opposite effects on EF across the two cities. In Ahmedabad, strong El Niño months were associated with 64% increase in EF risk while strong La Niña months with a 41% reduction in risk. In Surat, strong El Niño was associated with 25% reduction in risk while moderate La Niña with 21% increase in risk. CONCLUSIONS: Our results show that the risk of EF incidence in Gujarat is highly variable, even between the two cities only 260 kms apart. In addition to improvements in water supply and sewage systems, preventive public health measures should incorporate variability in risk across season and phases of ENSO. Further studies are needed to characterize nationwide heterogeneity in climate-mediated risk, and to identify most vulnerable populations that can benefit through early warning systems.
The surface water is a significant feature in the hydrological system and is a vital compound for life growth. Assessment of trace elements in the water bodies is essential since it poses huge threats to aquatic organisms and humans if present in high concentrations. This study was carried out to assess the seasonal changes in the dissolved trace elements concentration in Bhavani river, which is one of the major rivers of Tamil Nadu, southern India and also to assess the human health risk due to its consumption. A total of 46 surface water samples were collected along the river during pre-monsoon and post-monsoon of 2018 and were analyzed for various trace elements such as Zn, Cu, Fe, Ni, and Pb. The variation in trace element concentration is observed spatially, where higher concentration is found in samples from agricultural and urban areas than the samples from the undisturbed natural-mountain terrains. The results highlighted that the concentrations of trace elements differ temporally where the concentration is greater during the monsoon due to increased discharge of sewage and agricultural run off to the river. Multivariate statistical analysis indicates stronger relationship between trace elements and other physio-chemical parameters hinting that natural and anthropogenic sources alters the riverine chemistry. Thus, the rainfall-runoff characteristics along with lithology, topography, and landuse of the basin plays a dominant role in the seasonal variation of dissolved trace elements. The water quality index value shows “good/excellent” during pre-monsoon and “marginal/fair” during monsoon season and the Heavy Metal Pollution Index values were also low during both the seasons. The river water samples which defy these indices were found to be either from urban or agricultural lands. The oral and dermal ingestion health risk to adults was assessed, which indicates that the risks posed to humans by consumption of water were minimal. The trace metal concentration of the river was then compared with the other rivers of world and India, where it shows that Zn, Cu, and Ni concentration was higher in Bhavani than in most of the rivers. Thus, the study highlighted that the urban settlements and agricultural lands have a considerable influence on river quality thereby triggering the increase in trace element concentrations. Therefore, the study necessitates on the continuous monitoring of river along with adoption of stringent discharge protocols.
Enteric infections and water-related illnesses are more frequent during times of relative water abundance, especially in regions that experience bimodal rainfall patterns. However, it is unclear how seasonal changes in water availability and drinking water source types affect enteric infections in young children. This study investigated seasonal shifts in primary drinking water source type and the effect of water source type on enteric pathogen prevalence in stool samples from 404 children below age 5 in rural communities in Limpopo Province, South Africa. From wet to dry season, 4.6% (n = 16) of households switched from a source with a higher risk of contamination to a source with lower risk, with the majority switching to municipal water during the dry season. In contrast, 2.6% (n = 9) of households switched from a source with a lower risk of contamination to a source with higher risk. 74.5% (n = 301) of the total households experienced interruptions in their water supply, regardless of source type. There were no significant differences in enteric pathogen prevalence between drinking water sources. Intermittent municipal water distribution and household water use and storage practices may have a larger impact on enteric infections than water source type. The limited differences in enteric pathogen prevalence in children by water source could also be due to other exposure pathways in addition to drinking water, for example through direct contact and food-borne transmission.
Secure potable water is indispensable to life. The presence of salinity in potable water has become a serious problem worldwide and it is essential to ensure secure potable water, particularly in the coastal areas of Bangladesh. In this work, 48 (forty-eight) harvested rainwater samples were assessed from Upazila (sub-district) of Mongla and Sarankhola, Bagerhat district, Bangladesh during the monsoon (May) and post-monsoon (October) periods. The objective was to examine the effect of seasonal variations on the quality of harvested rainwater. The harvested rainwater was analyzed for fecal coliform, total coliform, lead (Pb), zinc (Zn), pH, and turbidity. The mean pH in monsoon and post-monsoon periods was 6.93 and 7.24, respectively, which was within both the WHO guideline and Bangladesh Drinking Standard. In the monsoon season, turbidity levels in samples met the Bangladesh water quality standard but 10% of the harvested rainfall samples had Pb levels that exceeded the WHO drinking water limit. The turbidity of harvested rainwater in post-monsoon exceeded the WHO and Bangladesh Drinking Standard by 21% (10 out of 48) and 6% (3 out of 48), respectively. The fecal coliform of harvested rainwater exceeded both WHO and Bangladesh Drinking Standard by 56% (27 out of 48) and 67% (32 out of 48) in the monsoon and post-monsoon, correspondingly. Conversely, total coliform of harvested rainwater exceeded both the WHO and Bangladesh Drinking Standard by 67% (32 out of 48) and 79% (38 out of 48), accordingly in the monsoon and post-monsoon seasons. The Zn was below the WHO and Bangladesh Drinking Standard but Pb exceeded the WHO guideline in the monsoon and post-monsoon by 15% (7 out of 48) and 17% (8 out of 48), respectively. Pb is toxic to humans and children are especially vulnerable. The harvested rainwater should be treated effectively to reduce the toxicity and danger posed by Pb, fecal coliform, and total coliform before it is fit for drinking purposes.
Amazonian populations are increasingly exposed to climatic shocks, yet knowledge of related health impacts is limited. Understanding how health risks are coproduced by local climatic variability, place and social inequities is vital for improving decision-making, particularly in decentralized contexts. We assess the impacts of rainfall variability and multiscale vulnerabilities on birth weight, which has lifelong health consequences. We focus on highly river-dependent areas in Amazonia, using urban and rural birth registrations during 2006-2017. We find a strong but spatially differentiated relationship between local rainfall and subsequent river-level anomalies. Using Bayesian models, we disentangle the impacts of rainfall shocks of different magnitudes, municipal characteristics, social inequities and seasonality. Prenatal exposure to extremely intense rainfall is associated with preterm birth, restricted intra-uterine growth and lower mean birth weight (<=-183 g). Adverse birth outcomes also follow non-extreme intense rainfall (40% higher odds of low birth weight), drier conditions than seasonal averages (-39 g mean birth weight) and conception in the rising-water season (-13 g mean birth weight). Babies experience penalties totalling 646 g when born to adolescent, Amerindian, unmarried mothers that received no formal education or antenatal or obstetric health care. Rainfall variability confers intergenerational disadvantage, especially for socially marginalized Amazonians in forgotten places. Structural changes are required to reduce inequities, foster citizen empowerment and improve the social accountability of public institutions. Amazonians are subject to climate shocks, but the associated health outcomes are still unclear. This study finds that rainfall variability is associated with adverse birth outcomes, especially for those most isolated and marginalized.
Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113?years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi-day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10?days) are missed at ranks at shorter duration (e.g., 2–3?days), thereby highlighting the importance to multi-day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction.
BACKGROUND: Accurate and timely forecasts of bacillary dysentery (BD) incidence can be used to inform public health decision-making and response preparedness. However, our ability to detect BD dynamics and outbreaks remains limited in China. OBJECTIVES: This study aims to explore the impacts of meteorological factors on BD transmission in four representative regions in China and to forecast weekly number of BD cases and outbreaks. METHODS: Weekly BD and meteorological data from 2014 to 2016 were collected for Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China). A boosted regression tree (BRT) model was conducted to assess the impacts of meteorological factors on BD transmission. Then a real-time forecast and early warning model based on BRT was developed to track the dynamics of BD and detect the outbreaks. The forecasting methodology was compared with generalized additive model (GAM) and seasonal autoregressive integrated moving average model (SARIMA) that have been used to model the BD case data previously. RESULTS: Ambient temperature was the most important meteorological factor contributing to the transmission of BD (80.81%-92.60%). A positive effect of temperature was observed when weekly mean temperature exceeded 4 °C, -3 °C, 9 °C and 16 °C in Beijing (Northern China), Shenyang (Northeast China), Chongqing (Southwest China) and Shenzhen (Southern China), respectively. BD incidence (Beijing and Shenyang) in temperate cities was more sensitive to high temperature than that in subtropical cities (Chongqing and Shenzhen). The dynamics and outbreaks of BD can be accurately forecasted and detected by the BRT model. Compared to GAM and SARIMA, BRT model showed more accurate forecasting for 1-, 2-, 3-weeks ahead forecasts in Beijing, Shenyang and Shenzhen. CONCLUSIONS: Temperature plays the most important role in weather-attributable BD transmission. The BRT model achieved a better performance in comparison with GAM and SARIMA in most study cities, which could be used as a more accurate tool for forecasting and outbreak alert of BD in China.
Climate risks and vulnerability continue to disproportionately affect the urban poor given their constrained adaptive capacity. This paper examines the urban poor’s perceptions and vulnerability to climate change in Kampala. Data was collected from a proportionate sample of 534 respondents drawn from households that were randomly selected from the city’s informal settlements and interviewed using a structured questionnaire. Six focus group discussions and 15 key informant interviews were conducted whose participants were purposively selected because of their knowledge and experiences. Quantitative data was analyzed using chi-square tests while content analysis was used to analyze qualitative data from key informant interviews and focus group discussions. A total of 96.6% of the households were aware of climate change, mainly perceived as rising temperatures and reduction in rainfall. Floods (53.4%) and droughts (27%) were the most commonly experienced climate risks, with the former considered more frequent and severe. Perceptions and vulnerability to climate risk varied with incomes, education level, marital status, main occupation, housing conditions and length of stay. Individuals with less wealth and education, employed in informal business and having insecure housing tenure were most vulnerable to flooding than they are to drought. The sensitivity of the urban poor communities is heightened by ecosystem degradation, poor access to urban infrastructure, utilities and services. With socio-economic attributes highly associated to climate change vulnerabilities, incorporating social dimensions and exchange of information between the vulnerable communities, planners and decision makers is necessary to inform the city’s adaptation policy and building long-term urban resilience. Partnerships are necessary between the urban authorities, communities, civil society and donors/financiers to improve housing and livelihoods in slums settlements. At the same time, strengthening co-production of climate information services, building climate change awareness, restoration of critical ecosystems and a broader inclusive adaptation planning are avenues for building resilient urban poor communities.
Because of climate change and rapid urbanization, urban impervious underlying surfaces have expanded, causing Chinese cities to become strongly affected by flood disasters. Therefore, research on urban flood risks has greatly increased over the past decade, with studies focusing on reducing the risk of flood disaster. From 2012 to 2020, the impervious underlying surface has increased, and the permeable underlying surface has decreased annually in Kunming City. This study was conducted to investigate the impact of continuous changes in the urban underlying surface on flood disasters in the Runcheng area south of Kunming City from 2012 to 2020. We constructed a two-dimensional flood model to conduct flood simulations and flood risk analysis for this area. The relationship between the permeability of the underlying surface and urban flood risk was simulated and analyzed by varying the urban underlying surface permeability (0-60%). The simulation results show that the model can accurately simulate urban waterlogging, and the increase in urban waterlogging risk is related to the underlying surface permeability. Urban flood risk decreases with the increase in permeable underlying surface. The increase rate of flood risk in the part with permeability of 0-35% is greater than that the part with permeability of 35-60%, that is, when the permeability of underlying surface is lower than 35%, the flood risk rate will be higher. We demonstrated the impact of the urban underlying surface permeability on the risk of urban flood disasters, which is useful for urban planning decisions and urban flooding risk controls.
Climate change is expected to increase the prevalence of water-borne diseases especially in developing countries. Climate-resilient drinking water supplies are critical to protect communities from faecal contamination and thus against increasing disease risks. However, no quantitative assessment exists for the impacts of short-term climate variability on faecal contamination at different drinking water sources in developing countries, while existing understanding remains largely conceptual. This critical gap limits the ability to predict drinking water quality under climate change or to recommend climate-resilient water sources for vulnerable communities. This study aims to provide such quantitative understanding by investigating the relationships between faecal contamination and short-term climate variability across different types of water sources. We collected a novel dataset with over 20 months’ monitoring of weather, Escherichia coli (E. coli) and total coliforms, at 233 different water sources in three climatically different regions in Tanzania. We then took a rigorous statistical analysis with Bayesian hierarchical models, to relate both contamination occurrence and amount to climate variability. The model results explained the temporal variability in drinking water faecal contamination using climate predictors, and also revealed the climate sensitivity of faecal contamination for individual water sources. We found that: a) short-term climate variability and baseline contamination levels can explain about half the observed variability in faecal contamination (R(2) ? 0.44); b) increased contamination was most consistently related to recent heavy rainfall and high temperature across different water sources; c) unimproved water sources such as the unprotected dug wells have substantially higher climate sensitivity. Based on these results, we can expect substantial increases in drinking water contamination risks across tropical Sub-Saharan Africa and South-East Asian developing countries under a warmer climate, which highlight the urgent need of protecting vulnerable communities from the severe climate impacts.
Rivers are important for drinking water supply worldwide. However, they are often impacted by pathogen discharges via wastewater treatment plants (WWTP) and combined sewer overflows (CSO). To date, accurate predictions of the effects of future changes and pollution control measures on the microbiological water quality of rivers considering safe drinking water production are hindered due to the uncertainty of the pathogen source and transport variables. The aim of this study was to test an integrative approach for an improved understanding of these effects, i.e. climate change and population growth as well as enhanced treatment at WWTPs and/or prevention of CSOs. We applied a significantly extended version of QMRAcatch (v1.0 Python), a probabilistic-deterministic model that combines fate and transport modelling with quantitative microbial infection risk assessment. The impact of climatic changes until the period 2035-2049 was investigated by a conceptual semi-distributed hydrological model, based on regional climate model outputs. QMRAcatch was calibrated and validated using site- and source-specific data (human-associated genetic microbial source tracking marker and enterovirus). The study showed that the degree to which future changes affect drinking water safety strongly depends on the type and magnitude of faecal pollution sources and are thus highly site- and scenario-specific. For example, if the load of pathogens from WWTPs is reduced through enhanced treatment, climate-change driven increases in CSOs had a considerable impact. Preventing CSOs and installing enhanced treatment at the WWTPs together had the most significant positive effect. The simultaneous consideration of source apportionment and concentrations of reference pathogens, focusing on human-specific viruses (enterovirus, norovirus) and cross-comparison with bacterial and protozoan pathogens (Campylobacter, Cryptosporidium), was found crucial to quantify these effects. While demonstrated here for a large, wastewater-impacted river, the approach is applicable at other catchments and pollution sources. It allows assessing future changes and selecting suitable pollution control measures for long-term water safety planning.
The Middle Paranapanema region in the state of São Paulo, Brazil, is an area with high diversity for Biomphalaria species, with municipalities historically marked by cases of schistosomiasis transmission. The objectives of the study were to evaluate the current distribuition and predict the future distribution of habitats of Biomphalaria species at a high spatial resolution along 114 freshwater sites in the Middle Paranapanema watershed. The modelling encompassed 55 municipalities of the Middle Paranapanema region, which were analyzed through the maximum entropy algorithm. All geographic coordinates of the Biomphalaria species collected from 2015-2018 and environmental data were obtained through WorldClim, HydroSHEDS, TOPODATA and Secretaria do Meio Ambiente for the 1970-2017 period. For the 2041-2060 period we used the HadGEM2-ES climate model. Due to climate change, MaxEnt showed that there was a high probability for the maintenance of B. glabrata habitats near Ourinhos and Assis, an expansion of scattered spots, and a 50% probability that the species will spread throughout new suitable areas. The results showed that the geographical range of B. straminea will most likely expand in the future along the Middle Paranapanema hydrographic basin, especially in the municipalities near Ourinhos. For B. glabrata and B. straminea, the geographic expansion was related to the predicted increase in the annual temperature range. The habitats suitable for B. tenagophila and B. peregrina seemed to slightly expand around the west border of the Middle Paranapanema region. Biomphalaria occidentalis may have a small reduction in its distribution due to climate change. The variables that contributed the most to the future modelling for these three species were precipitation and temperature. Identifying the sites with intermediate hosts for schistosomiasis may guide public health measures to avoid or reduce future transmissions in this region.
Climate risk is a consequence of climate hazards, exposure, and the vulnerability (IPCC 2014). Here, we assess future (2040-2049) climate risk for the entire contiguous US at the county level with a novel climate risk index integrating multiple hazards, exposures and vulnerabilities. Future, weather and climate hazards are characterized as frequency of heat wave, cold spells, dryer, and heavy precipitation events along with anomalies of temperature and precipitation using high resolution (4 km) downscaled climate projections. Exposure is characterized by projections of population, infrastructure, and built surfaces prone to multiple hazards including sea level rise and storm surges. Vulnerability is characterized by projections of demographic groups most sensitive to climate hazards. We found Florida, California, the central Gulf Coast, and North Atlantic at high climate risk in the future. However, the contributions to this risk vary regionally. Florida is projected to be equally hard hit by the three components of climate risk. The coastal counties in the Gulf states of Louisiana, Texas, Mississippi and Alabama are at high climate risk due to high exposure and hazard. High exposure and vulnerability drive high climate risk in California counties. This approach can guide planners in targeting counties at most risk and where adaptation strategies to reduce exposure or protect vulnerable populations might be best applied.
Bangladesh stands out as a climate change hot spot due to its unique geography, climate, high population density, and limited adaptation capacity. Mounting evidence suggests that the country is already suffering from the effects of climate change which may get worse without aggressive action. Here, we use an ensemble of high-resolution (10 km) regional climate model simulations to project near-term change in climate extremes, mainly heat waves and intense rainfall, for the period (2021–2050). Near-term climate projections represent a valuable input for designing sound adaptation policies. Our climate projections suggest that heatwaves will become more frequent and severe in Bangladesh under the business-as-usual scenario (RCP8.5). In particular, extremes of wet-bulb temperature (a temperature and humidity metric important in evaluating humid heat stress) in the western part of Bangladesh including Bogra, Ishurdi, and Jessore are likely to exceed the extreme danger threshold (according to U.S. National Weather Service criterion), which has rarely been observed in the current climate. The return periods of extreme heat waves are also significantly shortened across the country. In addition, country-averaged rainfall is projected to increase by about 6% during the summer months, with the largest increases (above 10%) in the eastern mountainous areas, such as Sylhet and Chittagong. Meanwhile, insignificant changes in extreme rainfall are simulated. Our results suggest that Bangladesh is particularly susceptible to climate extremes in the near future, in the form of extreme heat waves over the western part of the country.
Currently, the correlation between ambient temperature and systemic lupus erythematosus (SLE) hospital admissions remains not determined. The aim of this study was to explore the correlation between ambient temperature and SLE hospital admissions in Hefei City, China. An ecological study design was adopted. Daily data on SLE hospital admissions in Hefei City, from January 1, 2007, to December 31, 2017, were obtained from the two largest tertiary hospitals in Hefei, and the daily meteorological data at the same period were retrieved from China Meteorological Data Network. The generalized additive model (GAM) combined with distributed lag nonlinear model (DLNM) with Poisson link was applied to evaluate the influence of ambient temperature on SLE hospital admissions after controlling for potential confounding factors, including seasonality, relative humidity, day of week, and long-term trend. There were 1658 SLE hospital admissions from 2007 to 2017, including 370 first admissions and 1192 re-admissions (there were 96 admissions with admission status not stated). No correlation was observed between ambient temperature and SLE first admissions, but a correlation was found between low ambient temperature and SLE re-admissions (RR: 2.53, 95% CI: 1.11, 5.77) (3.5 °C vs 21 °C). The effect of ambient temperature on SLE re-admissions remained for 2 weeks but disappeared in 3 weeks. Exposure to low ambient temperature may increase hospital re-admissions for SLE, and thus it is important for SLE patients to maintain a warm living environment and avoid exposure to lower ambient temperature.
The present work investigates the increase of confirmed cases of West Nile virus and the relationship between weather-related patterns and the geographical expansion of West Nile virus in Greece, with a special focus on West Attica, Central Greece, a semi-arid, ecologically fragile Mediterranean area. Using data from the European Environment Agency, European Drought Observatory of Joint Research Centre, the pairwise relationship between surface air temperature anomalies, precipitation anomalies, soil moisture index anomalies, and the fraction of absorbed photosynthetically active radiation anomalies (fAPAR) was evaluated during summer time of 2018, a particularly intense virus outbreak. The empirical results of this study indicate that total precipitation during 2018 was extremely high, nearly 500% above the average. These conditions contributed to the increase of soil moisture index anomaly and fAPAR, creating an ideal microenvironment (wet soils and green pastures) for mosquito breeding. This phenomenon was directly associated with a drastic outbreak of West Nile virus cases in the area, compared with earlier years. Our results indicate how unusually high values of summer precipitation may have contributed (both through direct and indirect ecological channels) to the rapid spread of the West Nile virus in West Attica, causing a significant number of confirmed cases and fatalities. Climate change may bring forth other issues aside from natural disasters, including-but not limited to-virus expansion.
Most of the recent epidemic outbreaks in the world have as a trigger, a strong migratory component as has been evident in the recent Covid-19 pandemic. In this work we address the problem of migration of human populations and its effect on pathogen reinfections in the case of Dengue, using a Markov-chain susceptible-infected-susceptible (SIS) metapopulation model over a network. Our model postulates a general contact rate that represents a local measure of several factors: the population size of infected hosts that arrive at a given location as a function of total population size, the current incidence at neighboring locations, and the connectivity of the network where the disease spreads. This parameter can be interpreted as an indicator of outbreak risk at a given location. This parameter is tied to the fraction of individuals that move across boundaries (migration). To illustrate our model capabilities, we estimate from epidemic Dengue data in Mexico the dynamics of migration at a regional scale incorporating climate variability represented by an index based on precipitation data.
Foodborne diseases (FBDs) remain a global public health concern. Climatic factors such as wind-chill temperature, rainfall, and relative humidity affect the incidence of several FBDs. This study was performed to analyze how the various factors of the climate influence the incidence and severity of FBDs. This study retrospectively analyzed the results of multiplex polymerase chain reaction (mPCR) tests for diarrhea-causing bacteria performed on 2300 fecal samples obtained from patients at Dankook University Hospital, Cheonan, from June 2010 to December 2019. The Clostridioides difficile toxin B infection rate positively correlated with the intensity of sunshine, and the content of particulate matter. The Campylobacter spp. infection rate positively correlated with wind-chill temperature and the content of particulate matter. The Escherichia coli O157:H7 infection rate positively correlated with relative humidity. These findings may explain the dynamics and risks of Clostridioides difficile toxin B, Clostridium perfringens, Campylobacter spp., and Escherichia coli O157:H7 infection. They may help predict interrelationships among climatic factors and standardize national environmental health policies. However, in-depth research with large-scale data, molecular biology, and epidemiology would be required going forward. Future research would also require objective indicators of the changes in the prevalence of FBD-causing microbial pathogens for the effective prevention and management of these bacterial infections.
Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB.
From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of 11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging (GN) and spectral nudging (SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting (WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface (NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes, and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.
Urban resilience is a major indicator of a city’s sustainability. Climate change increases the frequency and intensity of extreme weather events, thereby increasing uncertainty and disaster risk. A city’s capacity to cope with climatic risks can be improved by developing resilience. In China, heavy rainfall is the most frequent and costly extreme weather event. We conducted a comparative case study on Beijing’s extraordinary 7.21 rainstorm disaster in 2012 and the 7.20 rainstorm in 2016. Taken generic resilience and specific resilience as the analytical framework, we found that generic resilience is mainly determined by the socio-economic development level and geography of each district; while the combination of engineering and non-engineering adaptive measures after 2012 disaster has improved the specific resilience to rainstorm disaster, which contributed a good performance in the 2016 rainstorm. As a megacity in China, Beijing is a representative case that provides guidance for other cities to improve their urban resilience to rainstorm disasters.
Rift Valley Fever (RVF) is a zoonotic disease whose outbreak results in heavy economic and public health burdens. In East Africa, RVF is mainly experienced in arid and semi-arid areas predominantly inhabited by the pastoralists. These areas experience sudden, dramatic epidemics of the disease at intervals of approximately 10 years, associated with widespread flooding and the resultant swarms of mosquitoes. Pastoralists’ indigenous knowledge and experience of RVF is critical for public health interventions targeting prevention and control of RVF. The study adopted a descriptive cross-sectional design combining both quantitative and qualitative methods of data collection. A total of 204 respondents participated in questionnaire survey and 15 key informants and 4 focus group discussions were interviewed and conducted respectively. In addition, secondary data mainly journal publications, books, policy documents and research reports from conferences and government departments were reviewed. Findings indicated that the Somali pastoralists possess immense knowledge of RVF including signs and symptoms, risk factors, and risk pathways associated with RVF. Ninety eight percent (98%) of respondents identified signs and symptoms such as bloody nose, diarrhea, foul smell and discharge of blood from the orifices which are consistent with RVF. Heavy rains and floods (85%) and sudden emergence of mosquito swarms (91%) were also cited as the major RVF risk factors while mosquito bites (85%), drinking raw milk and blood (78%) and contact with animal fluids during mobility, slaughter and obstetric procedures (77%) were mentioned as the RVF entry risk pathways. Despite this immense knowledge, the study found that the pastoralists did not translate the knowledge into safer health practices because of the deep-seated socio-cultural practices associated with pastoralist production system and religious beliefs. On top of these practices, food preparation and consumption practices such as drinking raw blood and milk and animal ritual sacrifices continue to account for most of the mortality and morbidity cases experienced in humans and animals during RVF outbreaks. This article concludes that pastoralists’ indigenous knowledge on RVF has implications on public health delivery approaches. Since the pastoralists’ knowledge on RVF was definitive, integrating the community into early warning systems through training on reporting mechanisms and empowering the nomads to use their mobile phone devices to report observable changes in their livestock and environment could prove very effective in providing information for timely mobilization of public health responses. Public health advocacy based on targeted and contextually appropriate health messaging and disseminated through popular communication channels in the community such as the religious leaders and local radio stations would also be needed to reverse the drivers of RVF occurrence in the study area.
Natural hazards like floods and droughts affect many aspects of life. The study in particular examined the impacts of droughts on under-five mortality rate in Southern Africa, adjusting for gross domestic product (GDP) and literacy rate. Despite drought and child mortality being key public health concerns in Southern Africa over the past few decades, there have hardly been any studies examining the relationships between them. The study used publicly available data from 1980 to 2012. The Standard Precipitation Index (SPI) was calculated for 3-, 6-, 9-, and 12-monthly time scales for ten southern African countries. The wetter and drier states are represented by positive and negative SPI values, respectively. SPI, GDP, and literacy rate were considered for predicting child mortality rate using both Multiple Linear Regression techniques and nonlinear methods (Generalized Additive Model), on a leave-one-year-out cross validation approach for model evaluation. Child mortality increased as the drought worsened for five countries in this region, namely Angola, Malawi, Mozambique, Namibia, and Zambia. We found that child mortality can be predicted with a high degree of accuracy using three predictor variables-drought index, GDP and literacy rate. Statistical modelling based on early warning system can complement regional capacities for drought response systems to increase child survival rate in drought-prone areas
Understanding the regional impact of future climate change is one of the major global challenges of this century. This study investigated possible effects of climate change on malaria in West Africa in the near future (2006-2035) and the far future (2036-2065) under two representative concentration pathway (RCP) scenarios (RCP4.5 and RCP8.5), compared to an observed evaluation period (1981-2010). Projected rainfall and temperature were obtained from the coordinated regional downscaling experiment (CORDEX) simulations of the Rossby Centre Regional Atmospheric regional climate model (RCA4). The malaria model used is the Liverpool malaria model (LMM), a dynamical malaria model driven by daily time series of rainfall and temperature obtained from the CORDEX data. Our results highlight the unimodal shape of the malaria prevalence distribution, and the seasonal malaria transmission contrast is closely linked to the latitudinal variation of the rainfall. Projections showed that the mean annual malaria prevalence would decrease in both climatological periods under both RCPs but with a larger magnitude of decreasing under the RCP8.5. We found that the mean malaria prevalence for the reference period is greater than the projected prevalence for 6 of the 8 downscaled GCMs. The study enhances understanding of how malaria is impacted under RCP4.5 and RCP8.5 emission scenarios. These results indicate that the southern area of West Africa is at most risk of epidemics, and the malaria control programs need extra effort and help to make the best use of available resources by stakeholders.
Lyme disease is the most common vector-borne disease in temperate zones and a growing public health threat in the United States (US). The life cycles of the tick vectors and spirochete pathogen are highly sensitive to climate, but determining the impact of climate change on Lyme disease burden has been challenging due to the complex ecology of the disease and the presence of multiple, interacting drivers of transmission. Here we incorporated 18 years of annual, county-level Lyme disease case data in a panel data statistical model to investigate prior effects of climate variation on disease incidence while controlling for other putative drivers. We then used these climate-disease relationships to project Lyme disease cases using CMIP5 global climate models and two potential climate scenarios (RCP4.5 and RCP8.5). We find that interannual variation in Lyme disease incidence is associated with climate variation in all US regions encompassing the range of the primary vector species. In all regions, the climate predictors explained less of the variation in Lyme disease incidence than unobserved county-level heterogeneity, but the strongest climate-disease association detected was between warming annual temperatures and increasing incidence in the Northeast. Lyme disease projections indicate that cases in the Northeast will increase significantly by 2050 (23,619 ± 21,607 additional cases), but only under RCP8.5, and with large uncertainty around this projected increase. Significant case changes are not projected for any other region under either climate scenario. The results demonstrate a regionally variable and nuanced relationship between climate change and Lyme disease, indicating possible nonlinear responses of vector ticks and transmission dynamics to projected climate change. Moreover, our results highlight the need for improved preparedness and public health interventions in endemic regions to minimize the impact of further climate change-induced increases in Lyme disease burden.
Climate change and variability influence temperature and rainfall, which impact vector abundance and the dynamics of vector-borne disease transmission. Climate change is projected to increase the frequency and intensity of extreme climate events. Mosquito-borne diseases, such as dengue fever, are primarily transmitted by Aedes aegypti mosquitoes. Freshwater availability and temperature affect dengue vector populations via a variety of biological processes and thus influence the ability of mosquitoes to effectively transmit disease. However, the effect of droughts, floods, heat waves, and cold waves is not well understood. Using vector, climate, and dengue disease data collected between 2013 and 2019 in Kenya, this retrospective cohort study aims to elucidate the impact of extreme rainfall and temperature on mosquito abundance and the risk of arboviral infections. To define extreme periods of rainfall and land surface temperature (LST), we calculated monthly anomalies as deviations from long-term means (1983-2019 for rainfall, 2000-2019 for LST) across four study locations in Kenya. We classified extreme climate events as the upper and lower 10% of these calculated LST or rainfall deviations. Monthly Ae. aegypti abundance was recorded in Kenya using four trapping methods. Blood samples were also collected from children with febrile illness presenting to four field sites and tested for dengue virus using an IgG enzyme-linked immunosorbent assay (ELISA) and polymerase chain reaction (PCR). We found that mosquito eggs and adults were significantly more abundant one month following an abnormally wet month. The relationship between mosquito abundance and dengue risk follows a non-linear association. Our findings suggest that early warnings and targeted interventions during periods of abnormal rainfall and temperature, especially flooding, can potentially contribute to reductions in risk of viral transmission.
Changes in ambient temperature have been reported as an important risk factor for respiratory diseases among pre-school children. However, there have been few studies so far on the effects of temperature on children respiratory health in developing countries including Vietnam. This study examined the impact of short-term changes in ambient temperature on hospital admissions for acute lower respiratory infection (ALRI) among children aged less than 5 years old in Ho Chi Minh City (HCMC), Vietnam. Data on daily hospital admissions from 2013 to 2017 were collected from two large paediatric hospitals of the city. Daily meteorological data of the same period were also collected. Time series analysis was performed to evaluate the association between risk of hospitalisations and temperatures categorised by seasons, age, and causes. We found that a 1 °C increase in maximum temperature was associated with 4.2 and 3.4% increase in hospital admission for ALRI among children 3-5 years old during the dry season and the rainy season, respectively. Surprisingly, in the rainy season, a rise of 1°C diurnal temperature range (DTR) was significantly associated with a decrease from 2.0 to 2.5% risk of hospitalisation for ALRI among children <3 years old. These findings suggested that although high temperature is a risk factor for hospital admissions among children in general, other modifiable factors such as age, exposure time, air conditioning usage, wearing protective clothing, socioeconomic status, and behaviour may influence the overall effect of high temperature on hospital admissions of children <5 years old in HCMC. The findings of this study have provided evidence for building public health policies aimed at preventing and minimizing the adverse health effects of temperature on children in HCMC.
As the world’s population is expected to be over 2/3rd urban by 2050, climate action in cities is a growing area of interest in the inter-disciplines of development policy, disaster mitigation and environmental governance. The climate impacts are expected to be quite severe in the developing world, given its urban societies are densely packed, vastly exposed to natural elements while possessing limited capabilities. There is a notable ambiguity and complexity that inhibits a methodical approach in identifying urban resilience measures. The complexity is due to intersection of large number of distinct variables in climate geoscience (precipitation and temperature anomalies at different locations, RCPs, timeline), adaptation alternatives (approach, priority, intervention level) and urban governance (functional mandate, institutional capacity, and plans & policies). This research examines how disparate and complex knowledge and information in these inter-disciplines can be processed for systematic ‘negotiation’ to situate, ground and operationalize resilience in cities. With India as a case, we test this by simulating mid-term and long-run climate scenarios (2050 & 2080) to map regional climate impacts that shows escalation in the intensity of climate events like heat waves, urban flooding, landslides and sea level rise. We draw on suitable adaptation measures for five key urban sectors- water, infrastructure (including energy), building, urban planning, health and conclude a sleuth of climate resilience building measures for policy application through national/ state policies, local urban plans and preparation of city resilience strategy, as well as advance the research on ‘negotiated resilience’ in urban areas.
BACKGROUND: People working in agriculture, fishing, and forestry have elevated risks of suicide. The suicide rates for the occupations of “agriculture, fishing, and forestry” are significantly higher than any other occupation. AIMS OF STUDY: This study evaluates whether the variability in socioeconomic and demographic factors and in climate as well as the support from mental health providers and social associations affected the suicide rates of farmers in the US. METHODS: We estimate Poisson count data regression and county level-fixed effects regressions using data from the National Center for Health Statistics complemented with relevant socio-economic, climate data and data on mental health providers from a variety of sources. RESULTS: The results show more suicides in counties with more farms and with higher share of population without health insurance, lower agricultural wages and, in non-rural counties higher poverty rate. Surprisingly, we find more suicides in counties with more social associations, while the availability of mental health providers is associated with fewer suicides in non-rural counties, and lower suicide rate in southern counties. DISCUSSION: These results highlight the need for innovative targeted policy interventions instead of relying on one-size-fits-all approach. Farmers and farm workers are yet to be reached with modern and effective tools to improve mental health and prevent suicide. At the same time, factors such as the weather and climate as well as some more traditional factors such as social associations or religious participation play a limited role. IMPLICATIONS FOR HEALTH POLICIES: Support mechanisms have a differential effect in rural and urban areas. It is important to identify the specific demographic, climate, and policy changes that serve as external stressors and affect farm workers’ suicide and accidental death from on-farm injury. IMPLICATION FOR FURTHER RESEARCH: Ideally, individual level data on farmers would be best in a study that evaluates what factors cause suicides.
Under climate change, compound flooding has resulted in severe disasters in coastal areas around the world. In this study, an integrated framework is proposed to determine the range of compound flood risk without the requirement of joint probability analysis between storm surge and rainfall. In the framework, the flood risks are analyzed under four extreme scenarios with/without the compound effect of storm surge and rainfall in the past and the future. From the end of the 20th century to the middle of the 21st century, the worst scenario shows that the flood area significantly increases by 92% for the low-lying coastal areas in southwest Taiwan under the compound effect of storm surge and rainfall if they are fully correlated. In the most optimistic scenario, the flood area slightly increases by 15% without compound effect (only storm surge is considered). To coastal flooding, the synchronization of storm surge and rainfall contributes much more than the climate-induced amplification of individual factors. When storm surge and rainfall happen at the same time, the extent and duration of flooding increase simultaneously under the influence of pluvial and surge-induced flooding. Risk analysis shows an obvious increase of risk level for villages originally at low risks, which require integrated countermeasures against the consequence brought by compound flooding in the future. The framework can be applied in other low-lying coastal areas to quantify the potential impacts on human and environment caused by compound flooding under climate change.
Climate change-induced extreme weather events have been at their worst increase in the past decade (2010-2020) across Africa and globally. This has proved disruptive to global socio-economic activities. One of the challenges that has been faced in this regard is the increased coastal flooding of cities. This study examined the trends and impacts of coastal flooding in the Western Cape province of South Africa. Making use of archival climate data and primary data from key informants and field observations, it emerged that there is a statistically significant increase in the frequency of flooding and consequent human and economic losses from such in the coastal cities of the province. Flooding in urban areas of the Western Cape is a factor of human and natural factors ranging from extreme rainfall, usually caused by persistent cut off-lows, midlatitude cyclones, cold fronts and intense storms. Such floods become compounded by poor drainage caused by vegetative overgrowth on waterways and land pollution that can be traced to poor drainage maintenance. Clogging of waterways and drainage systems enhances the risk of flooding. Increased urbanisation, overpopulation in some areas and non-adherence to environmental laws results in both the affluent and poor settling on vulnerable ecosystems. These include coastal areas, estuaries, and waterways, and this worsens the risk of flooding. The study recommends a comprehensive approach to deal with factors that increase the risk of flooding as informed by the provisions of both the Sustainable Development Goals framework and the Sendai Framework for Disaster Risk Reduction 2015-2030 in a bid to de-risking human settlement in South Africa.
This study investigates the impact of future changes in climatic variables on dengue incidence in the region of the Tucurui dam in the Amazon. Tucurui dam is the one of the largest hydroelectric power stations in the Amazon. Correlations and regression analysis through least squares fitting between dengue cases and temperature, precipitation, and humidity are obtained. Positive correlations between dengue incidence and temperature are found for lags from 4 to 5 months (higher correlation for lag 5), dengue and precipitation for lags 0 up to 1, and dengue and humidity for lag 0. The positive correlations between dengue and precipitation and between dengue and humidity are higher for the simultaneous correlation. To investigate the impact of the future changes in these climatic variables in the region, projections of RegCM4 model simulations under the RCP 8.5 scenario are obtained. The model projections indicate a warming and moisture increase in the region near the dam at the end of the twenty-first century. Regression analysis using the model projections indicates that the dengue incidence may increase substantially in future climate scenarios in this region (more than fivefold compared with the present climate). This increase is between two and three times higher than the global estimates of dengue incidence in the future. It is suggested that the incidence of dengue cases is more sensitive to changes in temperature. Vector parameters increase with temperature in the future, indicating that the temperature conditions are highly favorable for the spread of the disease in the region. The results indicate that cities in the area surrounding the Tucurui hydroelectric dam are areas of potential dengue incidence in the future. These findings may be applied to hydroelectric dams in other areas of the world. However, future studies involving additional dams are necessary. The results suggest an increase in climate-driven risk of transmission from Aedes aegypti throughout the entire Amazon, and especially the eastern and southern parts.
Longevity research is a hot topic in the health field. Considerable research focuses on longevity phenomenon in Bama Yao Autonomous County, which has a typical karst landform and is located in Southwest China. This study aims to illustrate the spatial feature of longevity indicators in other Yao areas, to analyze the correlation between climatic factors and longevity indicators, and to provide new clues and targets for further longevity studies. We collect and integrate population, climate, and terrain data into a spatial database. The main analysis methods include spatial autocorrelation, high/low clustering, and multiscale geographically weighted regression (MGWR). Two longevity clusters are identified in Guijiang River Basin (longevity index (LI%): 2.49?±?0.63) and Liujiang River Basin (LI%: 2.13?±?0.60). The spatial distribution of longevity indicators is autocorrelative (Moran’s I?=?0.652, p?
Global warming is likely to cause a progressive drought increase in some regions, but how population and natural resources will be affected is still underexplored. This study focuses on global population and land-use (forests, croplands, pastures) exposure to meteorological drought hazard in the 21st century, expressed as frequency and severity of drought events. As input, we use a large ensemble of climate simulations from the Coordinated Regional Climate Downscaling Experiment, population projections from the NASA-SEDAC dataset, and land-use projections from the Land-Use Harmonization 2 project for 1981-2100. The exposure to drought hazard is presented for five SSPs (SSP1-SSP5) at four Global Warming Levels (GWLs, from 1.5 to 4 degrees C). Results show that considering only Standardized Precipitation Index (SPI; based on precipitation), the combination SSP3-GWL4 projects the largest fraction of the global population (14%) to experience an increase in drought frequency and severity (vs. 1981-2010), with this value increasing to 60% if temperature is considered (indirectly included in the Standardized Precipitation-Evapotranspiration Index, SPEI). With SPEI, considering the highest GWL for each SSP, 8 (for SSP2, SSP4, and SSP5) and 11 (SSP3) billion people, that is, more than 90%, will be affected by at least one unprecedented drought. For SSP5 (fossil-fuelled development) at GWL 4 degrees C, approximately 2 center dot 10(6) km(2) of forests and croplands (respectively, 6 and 11%) and 1.5 center dot 10(6) km(2) of pastures (19%) will be exposed to increased drought frequency and severity according to SPI, but for SPEI, this extent will rise to 17 center dot 10(6) km(2) of forests (49%), 6 center dot 10(6) km(2) of pastures (78%), and 12 center dot 10(6) km(2) of croplands (67%), with mid-latitudes being the most affected areas. The projected likely increase of drought frequency and severity significantly increases population and land-use exposure to drought, even at low GWLs, thus extensive mitigation and adaptation efforts are needed to avoid the most severe impacts of climate change.
The world’s most important mosquito vector of viruses, Aedes aegypti, is found around the world in tropical, subtropical and even some temperate locations. While climate change may limit populations of Ae. aegypti in some regions, increasing temperatures will likely expand its territory thus increasing risk of human exposure to arboviruses in places like Europe, Northern Australia and North America, among many others. Most studies of Ae. aegypti biology and virus transmission focus on locations with high endemicity or severe outbreaks of human amplified urban arboviruses, such as dengue, Zika, and chikungunya viruses, but rarely on areas at the margins of endemicity. The objective in this study is to explore previously published global patterns in the environmental suitability for Ae. aegypti and dengue virus to reveal deviations in the probability of the vector and human disease occurring. We developed a map showing one end of the gradient being higher suitability of Ae. aegypti with low suitability of dengue and the other end of the spectrum being equal and higher environmental suitability for both Ae. aegypti and dengue. The regions of the world with Ae. aegypti environmental suitability and no endemic dengue transmission exhibits a phenomenon we term ‘aegyptism without arbovirus’. We then tested what environmental and socioeconomic variables influence this deviation map revealing a significant association with human population density, suggesting that locations with lower human population density were more likely to have a higher probability of aegyptism without arbovirus. Characterizing regions of the world with established populations of Ae. aegypti but little to no autochthonous transmission of human-amplified arboviruses is an important step in understanding and achieving aegyptism without arbovirus.
Climate change driven increases in the frequency of extreme heat events (EHE) and extreme precipitation events (EPE) are contributing to both infectious and non-infectious disease burden, particularly in urban city centers. While the share of urban populations continues to grow, a comprehensive assessment of populations impacted by these threats is lacking. Using data from weather stations, climate models, and urban population growth during 1980-2017, here, we show that the concurrent rise in the frequency of EHE, EPE, and urban populations has resulted in over 500% increases in individuals exposed to EHE and EPE in the 150 most populated cities of the world. Since most of the population increases over the next several decades are projected to take place in city centers within low- and middle-income countries, skillful early warnings and community specific response strategies are urgently needed to minimize public health impacts and associated costs to the global economy.
Dengue transmission is climate-sensitive and permissive conditions regularly cause large outbreaks in Asia-Pacific area. As climate change progresses, extreme weather events such as heatwaves and unusually high rainfall are predicted more intense and frequent, but their impacts on dengue outbreaks remain unclear so far. This paper aimed to investigate the relationship between extreme weather events (i.e., heatwaves, extremely high rainfall and extremely high humidity) and dengue outbreaks in China. We obtained daily number of locally acquired dengue cases and weather factors for Guangzhou, China, for the period 2006-2015. The definition of dengue outbreaks was based on daily number of locally acquired cases above the threshold (i.e., mean + 2SD of daily distribution of dengue cases during peaking period). Heatwave was defined as ?2 days with temperature ? 95th percentile, and extreme rainfall and humidity defined as daily values ?95th percentile during 2006-2015. A generalized additive model was used to examine the associations between extreme weather events and dengue outbreaks. Results showed that all three extreme weather events were associated with increased risk of dengue outbreaks, with a risk increase of 115-251% around 6 weeks after heatwaves, 173-258% around 6-13 weeks after extremely high rainfall, and 572-587% around 6-13 weeks after extremely high humidity. Each extreme weather event also had good capacity in predicting dengue outbreaks, with the model’s sensitivity, specificity, accuracy, and area under the receiver operating characteristics curve all exceeding 86%. This study found that heatwaves, extremely high rainfall, and extremely high humidity could act as potential drivers of dengue outbreaks.
This study’s purpose is to analyze the degree of risk and vulnerability involved in landslide and flash flood prone community areas in Thepparat sub-district, Sichon district, Nakhon Si Thammarat province, Thailand. It also aims to analyze and understand the socio-economic impacts on the community at the household level, and assess the community’s risk and vulnerability by examining its risk perception. The risk perception was done using focus group discussions and a questionnaire survey with key stakeholders. It mainly focused on how the risk of landslides and flash floods influences the community’s risk perceptions, which was tested in two parts: at the organizational and community levels by focusing on government officials and households, respectively. A correlation matrix was used to understand the relationship of the indicators selected. The Pearson correlation result has shown that the degree of risk awareness positively correlates with the income level, education level, and controllability, signifying that the risk of landslides and flash floods influences household risk perceptions. The qualitative assessment recommends community-level preparedness as being paramount to reduce the risk for a resilient community.
Severe fever with thrombocytopenia syndrome (SFTS) was firstly identified in mainland China in 2009 and the geographic distribution has expanded in recent years. In this study, we constructed ecological niche models (ENM) of SFTS with meteorological factors, environmental factor, and density of domestic animals using MaxEnt. We found four significant associated factors including altitude, yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity which accounted for 94.1% percent contribution. SFTS occurrence probability was high when altitude was between -100 m and 100 m, and the probability was nearly 0 when altitude was beyond 3000 m. Response curves of SFTS to the yearly average temperature, yearly accumulated precipitation, and yearly average relative humidity were all reversed V-shape. SFTS occurrence probability was high where the yearly average temperature, yearly accumulated precipitation, and yearly relative humidity were 12.5-17.5 °C, 700-2250 mm and 63-82%, respectively. ENMs predicted that the potential high-risk areas were mainly distributed in eastern areas and central areas of China. But there were some predicted potential high-risk areas where no SFTS case was reported up to date. More researches should be done to make clear whether SFTS case had occurred in these areas.
This study focuses on Guizhou Province, a region with difficult geographical conditions and poor economic development, to examine the effect of rainfall shocks on contemporaneous infant health and long-run socioeconomic outcomes in China. The study results indicate that negative rainfall shocks are robustly correlated with higher infant mortality and lower birth weight. In the long run, early life rainfall shortages limit an individual’s income and housing conditions. The study findings indicate a significant interaction of rainfall shock with the severity of water scarcity. This result implies that drinking water safety is an essential channel through which early life rainfall shocks influence individual health endowments. However, agriculture production is not a likely channel for rainfall effects despite its association with infant mortality. Accordingly, our empirical results suggest that improving public facility coverage will reduce the vulnerability of infant health to adverse rainfall shocks in Guizhou and other developing areas.
Under the global climate warming, extreme weather events occur more and more frequently. Epidemiological studies have proved that extreme temperature is strongly correlated with respiratory diseases. We evaluated extreme-temperature effect on respiratory emergency room (ER) visits for 5 years in Lanzhou, a northwest temperate climate city of China from January 1st, 2013, to August 31st, 2017. We built a distributed lag non-linear model (DLNM) to evaluate the lag effect up to 30 days. Results showed the relative risk (RR) of respiratory disease always reached the maximum at lag 0 day and decreased to 1.0 at lag 5 days. Extremely low temperature showed the lag effect of 22 days and the maximum RR was 1.415 (95% CI 1.295-1.546) at lag 0 day. Extremely high temperature showed the lag effect of 7 days and the maximum RR was 1.091 (95% CI 1.069-1.114) at lag 0 day. The elders (age > 65 years) were at the greatest risk to extreme temperatures and the response were very acute. Children (age ? 15 years) were at the lowest risk but the lag effect lasted the longest lag days than other subgroups. Males showed longer-term lag effect and higher RR than females. Our study indicated that the extremely low temperature has a significantly greater effect on respiratory diseases than extremely high temperature.
Leptospirosis is a disease usually acquired by humans through water contaminated with the urine of rodents that comes into direct contact with the cutaneous lesions, eyes, or mucous membranes. The disease has an important environmental component associated with climatic conditions and natural disasters, such as floods. We analyzed the relationship between rainfall and temperature and the incidence of leptospirosis in the top 30 municipalities with the highest numbers of cases of the disease in the period of 2007 to 2016. It was an ecological study of the time series of cases of leptospirosis, rainfall, and temperature with lags of 0, 1, 2, 3, and 4 weeks. A multilevel negative binomial regression model was implemented to evaluate the relationship between leptospirosis and both meteorological factors. In the 30 evaluated municipalities during the study period, a total of 5136 cases of leptospirosis were reported. According to the implemented statistical model, there was a positive association between the incidence of leptospirosis and rainfall with a lag of 1 week and a negative association with temperature with a lag of 4 weeks. Our results show the importance of short-term lags in rainfall and temperature for the occurrence of new cases of leptospirosis in Colombia.
Climate change could intensify extreme weather events, such as flooding, which amplifies the public health threat of waterborne diseases. Thus, assessing health vulnerability and adaptation (V&A) could facilitate nationally effective responses to extreme climate events. However, related studies are still negligible, and the assessment urgently needs to be validated with actual health data after extreme weather events. We established health V&A indices through literature review and factor analyses. Then, we separately mapped the spatial distribution of flood exposure, social and public health sensitivity, and adaptive capacity before the 2016 flood in Anhui province and compared it with post-flood diarrhea risks by using the geographic information system method to assess health vulnerability. Finally, we validated the indices by exploring the relationship between health V&A indices and post-flood diarrhea risks by using the quantile regression model. Results revealed that health V&A can be framed and categorized as key components of exposure, sensitivity, and adaptive capacity. The remarkable differences in the spatial distribution of health vulnerability were generally consistent with the demographic sensitivity, geographic flooding exposure, and post-flood diarrhea risks in Anhui. In addition, health V&A indices exerted significant positive impacts on infectious diarrhea post-flooding at all quantiles and were significant across different percentiles. Moreover, the impacts of flood exposure on total infectious diarrhea were high and continuous, whereas the impacts of sensitivity were not obvious in the flood’s early stage (Coeff = 0.643; p < 0.001) but high in the flood's middle (Coeff = 0.997; p < 0.001) and late stages (Coeff = 0.975; p < 0.001). However, the impacts of adaptive capacity were heterogeneous and high in the flood's early stage (Coeff = 0.665; p < 0.001 at the 25th percentile) and late stage (Coeff = 1.296; p < 0.001 at the 75th percentile) but were insignificant at the 50th percentile. This study contributed validated three-layered health V&A indices with 30 indicators and identified that the impacts of the key components on post-flood waterborne-disease risks are heterogeneous. For instance, local public health sensitivity and adaptive capacity are insufficient to reduce these risks in the long run. This study could be used to project population health risks after extreme weather events and thereby contributes to local government planning of health adaptation.
Malaria is a climate-sensitive infectious disease. Many ecological studies have investigated the independent impacts of ambient temperature on malaria. However, the optimal temperature measures of malaria and its interaction with other meteorological factors on malaria transmission are less understood. This study aims to investigate the effect of ambient temperature and its interactions with relative humidity and rainfall on malaria in Suzhou, a temperate climate city in Anhui Province, China. Weekly malaria and meteorological data from 2005 to 2012 were obtained for Suzhou. A distributed lag nonlinear model was conducted to quantify the effect of different temperature measures on malaria. The best measure was defined as that with the minimum quasi-Akaike information criterion. GeoDetector and Poisson regression models were employed to quantify the interactions of temperature, relative humidity, and rainfall on malaria transmission. A total of 13,382 malaria cases were notified in Suzhou from 2005 to 2012. Each 5 °C rise in average temperature over 10 °C resulted in a 22% (95% CI: 17%, 28%) increase in malaria cases at lag of 4 weeks. In terms of cumulative effects from lag 1 to 8 weeks, each 5 °C increase over 10 °C caused a 175% growth in malaria cases (95% CI: 139%, 216%). Average temperature achieved the best performance in terms of model fitting, followed by minimum temperature, most frequent temperature, and maximum temperature. Temperature had an interactive effect on malaria with relative humidity and rainfall. High temperature together with high relative humidity and high rainfall could accelerate the transmission of malaria. Meteorological factors may affect malaria transmission interactively. The research findings could be helpful in the development of weather-based malaria early warning system, especially in the context of climate change for the prevention of possible malaria resurgence.
Despite the significant economic cost of falls and injuries to individuals and communities, little is known about the impact of meteorological factors on the incidence of fall-related injuries (FRIs). Therefore, a time-series study was conducted to explore the effects of meteorological factors on FRIs in Ma’anshan City, East China. Injury data from 2011 to 2017 were collected from the National Injury Monitoring Station in Ma’anshan City. A distributed lag nonlinear model was used in this study to evaluate the correlation between ambient temperature and fall injuries. The results showed a significant exposure-response relationship between temperature and FRIs in Ma’anshan City. The high temperatures increased the risk of FRIs (RR = 1.110; 95% CI, 1.005-1.225; lag 0). The lag effect appeared at lag 10 (RR = 1.032; 95% CI, 1.003-1.063), and then gradually remained stable after lag 25 (RR = 1.077; 95% CI, 1.045-1.110). The effect of ambient temperature varied with age and gender. The lag effect of high temperature appeared in the male group after lag 15 (RR = 1.042; 95% CI, 1.006-1.079). In contrast, the effect of the female group appeared for the first time at lag 0 (RR = 1.187; 95% CI, 1.042-1.352). And the ? 60 years subgroup seemed to be more sensitive in low temperature (RR = 1.017; 95% CI, 1.004-1.031; lag 0; RR = 1.003; 95% CI, 1.000-1.007; lag 25). The cumulative result is similar to the single-day effect. From the results, this study would help the establishment of fall-related injury prediction and provide evidence for the formulation and implementation of preventive strategies and measures in the future.
Cardiovascular disease (CVD), reported to relate with climate change, is the leading cause of global mortality and morbidity. Since the relevant information is quite limited from suburbs and countryside in developing and underdeveloped countries, there are no studies that focused on morbidity through diurnal temperature range (DTR) for these regions. This is the first study to evaluate the short-term effect of DTR on CVD hospital admission in suburban farmers, as well as to identify vulnerable subpopulations. Daily time series data of CVD hospital admissions on suburban farmers of Qingyang, China, and meteorological data from 2011 to 2015 were collected, and a distributed lag non-linear model (DLNM) combined with a quasi-Poisson generalized additive regression model (GAM) was used to examine the exposure-response relationship and delayed effect between DTR and CVD hospital admissions. Stratified analyses by age and gender were performed and extreme DTR effects were examined. Non-linear relation between DTR and CVD hospital admissions was observed, and whether DTR lower or higher than the reference (13 °C, 50(th) percentile) had adverse effect while lower DTR have slightly higher impact. Also, both extreme low and extreme high DTR had adverse effect. Besides, adults (age < 65) and males were more vulnerable to the effects of DTR compared with the old (age ? 65) and females, respectively. This study provides evidence that not only high DTR but also low DTR had adverse effects on CVD which should be paid attention to. Adults and males were more vulnerable among suburban farmers. The results are inconsistent with the studies from urban and indicate differences between urban and suburban residents. Multiple factors such as occupations, risk awareness, and lifestyles could have a significant influence on CVD morbidity, and further study is needed to explore more evidence.
Since the early twentieth century, the intensity of malaria transmission has decreased sharply worldwide, although it is still an infectious disease with a yearly estimate of 228 million cases. The aim of this study was to expand our knowledge on the main drivers of malaria in Spain. In the case of autochthonous malaria, these drivers were linked to socioeconomic and hygienic and sanitary conditions, especially in rural areas due to their close proximity to the wetlands that provide an important habitat for anopheline reproduction. In the case of imported malaria, the main drivers were associated with urban areas, a high population density and international communication nodes (e.g. airports). Another relevant aspect is that the major epidemic episodes of the twentieth century were strongly influenced by war and military conflicts and overcrowding of the healthcare system due to the temporal overlap with the pandemic flu of 1918. Therefore, military conflicts and overlap with other epidemics or pandemics are considered to be drivers of malaria that can-in a temporary manner-exponentially intensify transmission of the disease. Climatic factors did not play a relevant role as drivers of malaria in Spain (at least directly). However, they did influence the seasonality of the disease and, during the epidemic outbreak of 1940-1944, the climate conditions favored or coadjuvated its spread. The results of this study provide additional knowledge on the seasonal and interannual variability of malaria that can help to develop and implement health risk control measures. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s41207-021-00245-8.
Aedes aegypti is the main vector of dengue globally. The variables that influence the abundance of dengue vectors are numerous and complex. This has generated a need to focus on areas at risk of disease transmission, the spatial-temporal distribution of vectors, and the factors that modulate vector abundance. To help guide and improve vector-control efforts, this study identified the ecological, social, and other environmental risk factors that affect the abundance of adult female and immature Ae. aegypti in households in urban and rural areas of northeastern Thailand. A one-year entomological study was conducted in four villages of northeastern Thailand between January and December 2019. Socio-demographic; self-reported prior dengue infections; housing conditions; durable asset ownership; water management; characteristics of water containers; knowledge, attitudes, and practices (KAP) regarding climate change and dengue; and climate data were collected. Household crowding index (HCI), premise condition index (PCI), socio-economic status (SES), and entomological indices (HI, CI, BI, and PI) were calculated. Negative binomial generalized linear models (GLMs) were fitted to identify the risk factors associated with the abundance of adult females and immature Ae. aegypti. Urban sites had higher entomological indices and numbers of adult Ae. aegypti mosquitoes than rural sites. Overall, participants’ KAP about climate change and dengue were low in both settings. The fitted GLM showed that a higher abundance of adult female Ae. aegypti was significantly (p < 0.05) associated with many factors, such as a low education level of household respondents, crowded households, poor premise conditions, surrounding house density, bathrooms located indoors, unscreened windows, high numbers of wet containers, a lack of adult control, prior dengue infections, poor climate change adaptation, dengue, and vector-related practices. Many of the above were also significantly associated with a high abundance of immature mosquito stages. The GLM model also showed that maximum and mean temperature with four-and one-to-two weeks of lag were significant predictors (p < 0.05) of the abundance of adult and immature mosquitoes, respectively, in northeastern Thailand. The low KAP regarding climate change and dengue highlights the engagement needs for vector-borne disease prevention in this region. The identified risk factors are important for the critical first step toward developing routine Aedes surveillance and reliable early warning systems for effective dengue and other mosquito-borne disease prevention and control strategies at the household and community levels in this region and similar settings elsewhere.
Climate change affects the reproductive life cycles of plants, including pollen production, which has consequences for allergic respiratory diseases. We examined climatic trends at eight locations in Bavaria, Southern Germany, with pollen time series of at least 10 years (up to 30 years in Munich). Climate change in Bavaria was characterized by a rise in temperature, but not during the winter. There is also a trend towards a more continental climate in Bavaria, which is significant in the Alps in the south of the territory. The influence of climate change depended on pollen type. Wind-pollinated arboreal species (e.g. Alnus, Betula and Cupressaceae/Taxaceae) showed advances in the start and end dates of pollen seasons and an increase in pollen load. These changes correlated negatively with late-winter (February) and spring temperatures (April). For herbaceous species, like Poaceae and Urticaceae, an earlier season was observed. Although precipitation is not a limiting factor in Southern Germany, water availability in the spring did influence the magnitude of grass pollen seasons. The effect of climatic change on the characteristics of pollen seasons was also more pronounced at higher altitudes, significant at > 800 m above sea level. Our results show that trends for start, end dates and intensity were similar at all locations, but only statistically significant at some. If we assume that earlier and more intense pollen seasons result in increases in prevalence and severity of allergic diseases, then the effect of climate change on public health in Bavaria may be significant.
Food poisoning is caused by pathogenic bacteria in water and aquatic products, especially bivalves (e.g., oysters, clams), which can bioaccumulate pathogenic bacteria. Polluted water and aquatic products thus pose a serious threat to human health and safety. In this study, the types of pathogenic bacteria in water samples and shellfish collected from the Dadeng offshore area in Xiamen were examined. We also analyzed the relationships between dominant pathogens and major climate and water quality parameters. Our objective was to provide reference data that may be used to help prevent bacterial infections and to improve aquatic food hygiene in Xiamen and its surrounding areas to safe levels, thus ensuring the health of Xiamen residents. We found that the main pathogenic bacteria were Vibrio and Bacillus, with the dominant pathogen being Vibrio parahaemolyticus. Physical and chemical indexes (water temperature, salinity, pH, dissolved oxygen, and turbidity) of water bodies and the 3-day accumulated rainfall were found to be important factors affecting the occurrence and abundance of V. parahaemolyticus.
Constant environmental degradation and increased frequency and severity of natural disasters have been evident over the past few decades worldwide. As such, scientific tools to predict and assess risks keep being developed. Assessing disaster risk is an important task in supporting the transition to a sustainable society. However, as disasters and systems become more complex, disaster models combining diverse aspects including climatic, social, economic, and environmental factors are necessary. For this study, we set a model using the concept of risk by identifying hazards, exposure, and vulnerability. Here, the vulnerability was classified into two domains, sensitivity and adaptive capacity, and two spheres, natural/built environment and human environment. Also, we stressed that controllable geo-spatial indicators should be included in risk assessments to effectively reduce risk and implement adequate spatio-temporal actions. The approach of this study was applied to Kazakhstan and South Korea as a pilot study to develop Agricultural Drought Risk Index (ADRI) and maps. As a result, the agricultural drought risk could be analyzed for South Korea and Kazakhstan. In addition, we performed additional spatial analyses at a reasonable scale for practical use. It was concluded that prioritizing risk areas at administrative and site level could contribute in decision and policy-making for risk reduction. Furthermore, spatial data availability and quality were found to be significant in assessing disaster risk.
Egypt is one Arab country that is vulnerable to flash floods caused by heavy and intensive rainfall. Different locations in Egypt are vulnerable to the hazards of flash floods, especially in Upper Egypt. Throughout history, Egypt witnessed a series of events of flash floods that lead to mortality, damages, and economic losses. The intensity and frequency of flash floods in Egypt vary from year to year according to a number of hydrological and climatological variables. Although several previous flash floods studies have been conducted in Egypt, studies on the governorate of Asyut are still limited. This study integrates the physical and social parameters in order to assess the vulnerability to flash floods. The objectives of this study are to shed light on flash floods in the study area, develop a vulnerability model to determine the regions vulnerable to the impacts of flash floods, and propose a flash flood alert system in the governorate of Asyut in Egypt to mitigate the impacts of flash floods and to avoid the loss of life and property. The AHP (analytical hierarchy process) is used for assigning the optimal criterion weight of the considered vulnerability parameters based on the responses of eight expert respondents to an online Google forms questionnaire. The highest weighted flash floods causative parameters are population density (27.4%), precipitation (22.1%), total population (16.4%), and elevation (10.2%), respectively. The results reveal that Asyut is one of the Egyptian governorates prone to flash floods’ impacts, especially in Dayrut, Al-Qusiyah, and Abnub, urban districts. The findings of this study are expected to be useful to policymakers and responsible authorities for better disaster risk management and for dealing with the flash floods events in the future.
Extreme climate change is posing an increasing threat to human welfare across countries. Specifically, the devastating floods coupled with the looming spectre of drought are argued to explain cross-country differences in food security. While the debate continues and uncertainties about the precise influence of climate change on food security linger, the question of whether climate change plays a pivotal role in increased hunger and food insecurity across countries remains unanswered. This study presented new evidence of the role of climate change in Africa’s food security. We utilised the Mann-Kendall test and Sen’s slope estimator to analyse climate change trends. We also employed the pooled mean group technique and the Dumitrescu-Hurlin panel causality test to investigate the effect of climate change on food security in 15 African countries between 1970 and 2016. Our empirical findings revealed three things. First, rainfall plays a decisive role in Africa’s food security when examined broadly. However, the significance of the effect of rainfall varied substantially across the 15 countries. Second, we find no robust impact of temperature on food security in the long run. However, the short-run results showed that extreme temperatures impede food security, with varying magnitudes across countries. Third, except for rainfall, a bidirectional causality exists between food security and temperature in Africa. Given the risks associated with rain-fed agriculture, we argue that African countries need to limit their dependence on rain-fed agriculture to boost food production.
Climate drives population dynamics through multiple mechanisms, which can lead to seemingly context-dependent effects of climate on natural populations. For climate-sensitive diseases, such as dengue, chikungunya, and Zika, climate appears to have opposing effects in different contexts. Here we show that a model, parameterized with laboratory measured climate-driven mosquito physiology, captures three key epidemic characteristics across ecologically and culturally distinct settings in Ecuador and Kenya: the number, timing, and duration of outbreaks. The model generates a range of disease dynamics consistent with observed Aedes aegypti abundances and laboratory-confirmed arboviral incidence with variable accuracy (28-85% for vectors, 44-88% for incidence). The model predicted vector dynamics better in sites with a smaller proportion of young children in the population, lower mean temperature, and homes with piped water and made of cement. Models with limited calibration that robustly capture climate-virus relationships can help guide intervention efforts and climate change disease projections.
BACKGROUND: Dengue is one of the most rapidly spreading vector-borne diseases, which is considered to be a major health concern in tropical and sub-tropical countries. It is strongly believed that the spread and abundance of vectors are related to climate. Construction of climate-based mathematical model that integrates meteorological factors into disease infection model becomes compelling challenge since the climate is positively associated with both incidence and vector existence. METHODS: A host-vector model is constructed to simulate the dynamic of transmission. The infection rate parameter is replaced with the time-dependent coefficient obtained by optimization to approximate the daily dengue data. Further, the optimized infection rate is denoted as a function of climate variables using the Autoregressive Distributed Lag (ARDL) model. RESULTS: The infection parameter can be extended when updated daily climates are known, and it can be useful to forecast dengue incidence. This approach provides proper prediction, even when tested in increasing or decreasing prediction windows. In addition, associations between climate and dengue are presented as a reversed slide-shaped curve for dengue-humidity and a reversed U-shaped curves for dengue-temperature and dengue-precipitation. The range of optimal temperature for infection is 24.3-30.5 °C. Humidity and precipitation are positively associated with dengue upper the threshold 70% at lag 38 days and below 50 mm at lag 50 days, respectively. CONCLUSION: Identification of association between climate and dengue is potentially useful to counter the high risk of dengue and strengthen the public health system and reduce the increase of the dengue burden.
We examine the relationships between climatic conditions, breastfeeding behavior, and maternal time use in Ethiopia. Infant feeding practices are important predictors of child nutrition that may be affected by a number of factors including mother’s time engaging in agricultural labor, food security, cultural beliefs, and antenatal care. We use panel data from the Living Standards Measurement Study to investigate linkages between climatic conditions during a child’s first year of life and year prior to birth and duration of exclusive breastfeeding. We then explore one potential mechanism: women’s agricultural labor. Results indicate that rainfall during the primary agricultural season-kiremt-in a child’s first year of life plays an important role in duration of exclusive breastfeeding. Experiencing 25 cm of average monthly kiremt rainfall, versus 5 cm, is associated with a 20-percentage-point decrease in the likelihood of being exclusively breastfed for the recommended six months. More kiremt rainfall is associated with a greater number of days that women spend planting and harvesting, and at high levels of rainfall women with infants do not engage in significantly fewer days of agricultural labor than those without infants. Lastly, we find that during the year before birth, greater rainfall during kiremt as well as the dry season is associated with a lower likelihood of six months of exclusive breastfeeding, potentially due to the early introduction of complementary foods. Our findings indicate that agricultural labor demands may in part drive breastfeeding behaviors, leading to “sub-optimal” feeding practices in the short-term, but resulting in improved household food security in the longer-term.
In 2016, an outbreak of anthrax killing thousands of reindeer and affecting dozens of humans occurred on the Yamal peninsula, Northwest Siberia, after 70 years of epidemiological situation without outbreaks. The trigger of the outbreak has been ascribed to the activation of spores due to permafrost thaw that was accelerated during the summer heat wave. The focus of our study is on the dynamics of local environmental factors in connection with the observed anthrax revival. We show that permafrost was thawing rapidly for already 6 years before the outbreak. During 2011-2016, relatively warm years were followed by cold years with a thick snow cover, preventing freezing of the soil. Furthermore, the spread of anthrax was likely intensified by an extremely dry summer of 2016. Concurrent with the long-term decreasing trend in the regional annual precipitation, the rainfall in July 2016 was less than 10% of its 30-year mean value. We conclude that epidemiological situation of anthrax in the previously contaminated Arctic regions requires monitoring of climatic factors such as warming and precipitation extremes.
The persistence of high values of relative humidity for several hours to a few days has wide-ranging implications for natural and human systems. Among its many impacts, persistent high relative humidity contributes to reduced atmospheric visibility, fog frequency and duration, road and powerline icing, the occurrence of foliar plant disease and the temperature at which heat-related morbidity and mortality can occur. Despite this, the characteristics of humidity spells-including shifts with climate change-are rarely investigated and consequently poorly understood. Hourly relative humidity, precipitation and temperature for 35 locations in the Lower Peninsula (LP) of Michigan during 2003-2017, and for seven locations during 1973-2017, were used to assess, by biweekly periods, spatial, intra-annual and inter-annual variations in the characteristics of relative humidity spells. Two humidity thresholds that accommodate a wide range of applications were used: (1) high relative humidity (HRH), defined as hourly values >= 60%, and extremely high relative humidity (EHRH), defined as hourly values >= 85%. Extended HRH and EHRH spells are frequent across the LP, with HRH spells often spanning 36 hr or longer and EHRH spells commonly persisting more than 12 hr. The probability of HRH and EHRH spells generally decreased with time during 1973-2017, particularly later in the period. Although most spells initiate in the late afternoon and early evening hours, this diurnal preference is less evident as spell length increases, especially for EHRH spells. Furthermore, precipitation is more likely to occur with EHRH spells compared to HRH spells. The orientation and strength of spatial gradients in average annual spell frequency are highly dependent on the choice of humidity and duration thresholds and the temperatures accompanying the spells. This study represents the first comprehensive analysis of the persistence of humidity spells and illustrates the potential usefulness of temporally-flexible climatological summaries relevant for a wide range of applications.
BACKGROUND: The impact of simultaneous adverse climate conditions in the risk of myocardial infarction (MI) was not tested before. The aim of the present study was to investigate the impact of the combination of climate and air pollution features in the number of admissions and mortality due to acute myocardial infarction in 39 municipalities of São Paulo from 2012 to 2015. METHODS: Data about MI admissions were obtained from the Brazilian public health system (DataSUS). Daily information on weather were accessed from the Meteorological Database for Teaching and Research. Additionally, daily information on air pollution were obtained from the Environmental Company of the State of São Paulo. A hierarchical cluster analysis was applied for temperature, rainfall patterns, relative air humidity, nitrogen dioxide, particulate matter 2.5 and particulate matter 10. MI admissions and in-hospital mortality were compared among the clusters. RESULTS: Data analysis produced 3 clusters: High temperature variation-Low humidity-high pollution (n=218 days); Intermediate temperature variation/high humidity/intermediate pollution (n=751 days) and low temperature variation/intermediate humidity-low pollution (n=123 days). All environmental variables were significantly different among clusters. The combination of high temperature variation, dry weather and high pollution resulted in a significant 9% increase in hospital admissions for MI [30.5 (IQR 25.0-36.0)]; patients/day; P<0.01). The differences in weather and pollution did not have impact on in-hospital mortality (P=0.88). CONCLUSION: The combination of atmospheric conditions with high temperature variation, lower temperature, dryer weather and increased inhalable particles was associated with a marked increase of hospital admissions due to MI.
Urbanization, livestock activities, and rainfall are factors that contribute to the contamination of inland water. This study aimed to determine the spatial and temporal variability of total coliforms (TCs) and fecal coliforms (FCs) in the surface water of San Pedro Lake as well as the gills and skin of Nile tilapia (Oreochromis niloticus) cultivated in the lake. The study consisted of seasonal sampling during an annual cycle. Using the multiple-tube fermentation technique, we quantified the microbial load of TCs in the lake and fish. The median of the TC and FC groups in surface water showed differences during the seasonal cycle, in which a significant correlation was observed between rainfall and bacterial load in the lake surface water. There was a significant seasonal difference between FCs and TCs in the gills as well as in skin FCs. Anthropogenic activities in the watershed combined with rainfall influence the bacterial load of San Pedro Lake. However, the water quality is still classified as excellent and uncontaminated according to Mexican regulations with lower FC values acceptable for higher FC values. In addition, the bacterial load in tilapia from San Pedro Lake does not pose a risk to human health. PRACTITIONER POINTS: Watershed livestock activities combined with rainfall increase fecal matter pollution in specific areas of the lake. San Pedro Lake displays satisfactory quality for aquatic life. The median fecal coliform population in lake fish (gills and skin) differs by season.
Global warming is already having a negative impact on vital sectors on which human development depends, such as water resource availability. In this study, the changes and abrupt change timing of climatic extreme indices, aridity and drought over the Region of South Aegean are captured using the Mann-Kendall and Pettitt tests, while the latter variables are correlated with the water volume transported by ships to the region as well as the relevant costs. The region’s climate is shifting to warmer conditions with less precipitation, since significantly positive trends were noted with regard to the number of tropical nights, warm nights, warm days, the warm spell duration index and the diurnal temperature range; significant negative trends were observed in relation to the number of cool nights, cool days and the cold spell duration index, with the change-point year for the latter variables being 2006. Inaddition, 7/11 precipitation related indices exhibited a downward trend, while significantly negative trends were observed with regard to the number of consecutive dry days, with the timing of the abrupt change being 2001. The Aridity Index (AI) reveals that the region’s climate characterization is changing from dry and sub-humid to semi-arid conditions, whilst the Reconnaissance Drought Index standardized (RDI(st)) and the Standardized Precipitation Index (SPI) indices suggests an amplification of drought phenomena over the Region. The tourism variables illustrated a significant positive trend, with the timing of the abrupt change being registered during 2006-2009, whilst the correlation analysis between tourism variables and water transfers implies that the surge on water transfer by ships to the Region occurred between 1998 and 2008. This can be mainly attributed to the changes in climate patterns. The correlation analysis documents a strong positive correlation between the water transfer dataset and the diurnal temperature range, and a moderately negative association with the precipitation related indices, annual precipitation, drought phenomena and aridity with 7/11.
This paper describes spatial distribution of Visceral Leishmaniasis (VL) and determines its correlation with climatic factors in an endemic focus in northern and central Tunisia. Data on VL cases in children under five years of age were obtained by consulting medical reports from all Tunisian Pediatric Departments (TPD) during 2006-2016. Three key climatic factors, namely precipitation, continentality index and pluviometric coefficient of Emberger were used as predictor variables to model the VL geographical distribution. Data handling and statistical analysis were performed using R and Arcview GIS software systems. Bayesian local spatial model was employed to analyse the data. The results show a progressive increase in the VL incidence rates in regions with high levels of precipitation, but with low values of both continentality index and pluviometric coefficient of Emberger. A likely explanation of these findings arises from the opposite local effects of climatic factors which tend to cancel each other out in the calculation of the mean parameter estimate over the whole study area. We conclude that using non-local spatial analysis approach leads to misleading epidemiological interpretations, which in turn are of relevance for more efficient and cost-effective resource allocation for control and well manage the spread of VL in the study region and elsewhere in Tunisia.
Climate change has been linked to poor childhood growth and development through maternal stress, nutritional insults related to lean harvests, and exposure to infectious diseases. Vulnerable populations are often most susceptible to these stressors. This study tested whether susceptibility to linear growth faltering is higher among Peruvian children from indigenous, rural, low-education, and low-income households. High-resolution weather and household survey data from Demographic and Health Survey 1996-2012 were used to explore height-for-age z-scores (HAZ) at each year of life from 0 to 5. Rural, indigenous children at age 0-1 experience a HAZ reduction of 0.35 units associated with prenatal excess rainfall which is also observed at age 4-5. Urban, non-indigenous children at age 4-5 experience a HAZ increase of 0.07 units associated with postnatal excess rainfall, but this advantage is not seen among rural, indigenous children. These findings highlight the need to consider developmental stage and social predictors as key components in public health interventions targeting increased climate change resilience.
Many zoonotic diseases are weather sensitive, raising concern how their distribution and outbreaks will be affected by climate change. At northern high latitudes, the effect of global warming on especially winter conditions is strong. By using long term monitoring data (1980-1986 and 2003-2013) from Northern Europe on temperature, precipitation, an endemic zoonotic pathogen (Puumala orthohantavirus, PUUV) and its reservoir host (the bank vole, Myodes glareolus), we show that early winters have become increasingly wet, with a knock-on effect on pathogen transmission in its reservoir host population. Further, our study is the first to show a climate change effect on an endemic northern zoonosis, that is not induced by increased host abundance or distribution, demonstrating that climate change can also alter transmission intensity within host populations. Our results suggest that rainy early winters accelerate PUUV transmission in bank voles in winter, likely increasing the human zoonotic risk in the North.
Arboviral diseases are a theme of high interest in the field of public and collective health worldwide. Dengue, Zika, and Chikungunya, in particular, have shown significant expansion in terms of morbidity and mortality in different portions of the ecumene. These diseases are of great interest in geographic studies due to the characteristics of their vector (Aedes aegypti), adapted to the environmental and unequal context of the urbanization process. Given this background, this study assesses the relationship between global climate change and the risk of arboviral diseases for the state of Rio de Janeiro. To this end, the characteristics of future climate susceptibility to vector proliferation in the scenarios RCP 4.5 and 8.5 (2011-2040 and 2041-2070) were assessed using two models: Eta HadGEM2-ES and Eta MIROC5, as well as the vulnerability conditions that favor the spread of arboviruses. The results indicate that the tendency of thermal and hygrometric elevation, in association with vulnerability, may have repercussions on the intensification and spatial expansion of the risk of arboviral diseases in the state of Rio de Janeiro, since there is a spatial and temporal expansion of the optimal environmental conditions for the development of the vector.
Climate change is predicted to adversely affect agricultural yields, particularly in African countries such as Ethiopia, where crop production relies heavily on environmental factors such as rainfall and temperature. However, there have only been a limited number of studies on the effects of climate change dynamics on food security in Africa, particularly at the household level. We therefore analyzed local climatic changes, the status of household food security, climate-related causes of food insecurity, food security determinants, and the adaptation strategies of local farmers. Three decades meteorological data were analyzed. A total of 185 farmers were selected using simple random sampling and interviewed, together with focus groups. Data were analyzed using the descriptive and inferential statistics were used together with the logit regression model. Climate change over the last three decades was found to have a negative impact the food security status of households. Crop production was constrained by poor rainfall, severe erosion, and increases in temperature. The unpredictability of rainfall, pests, and diseases were also contributing factors. Using the calorie intake approach, 60.5% of sampled respondents were found to be food insecure. Analysis using the logistic regression model showed that age and family size, as well as the amount of cultivated land and rainfall, were the significant (p < .05) factors influencing household food security status. A large proportion (69.8%) of farmers were incorporating adapting strategies into farm management including improved use of crop varieties and livestock production, in addition to income diversification. Taken together, these findings show that improving climate change awareness, facilitating the participation of female-led households in income generation, and strengthening existing adaptation measures have positive impacts on food security.
A warmer climate has caused more extreme climate events like the heatwave or extreme precipitation, which has led to a large number of lives and economic losses. In this study, we adopt historical daily precipitation from rainfall estimates on a gridded network (REGEN) and future daily projections from 10 general circulation models (GCMs) to analyze the potential risks of extreme precipitation due to changes in the magnitude and frequency. We calculate the 10-year and 100-year return levels by fitting the partial duration series (PDS) data with the generalized Pareto (GP) distribution. The potential risks are quantified in two terms: by the ratio of the magnitude to the threshold and by the exceedance frequency comparing to the theoretical value. The results show that in the future, about 46% of the world may suffer from mid or high risk of change in extreme precipitation. Most regions show higher risk due to the increased frequency of extreme precipitation events under the RCP8.5 scenario. The high risk of humid regions mainly appears under the RCP8.5 scenario and is mainly driven by frequency change, while that of arid regions appears under both the scenarios and is driven by both the frequency and magnitude change. The tropical rainforest climate areas of South America (SA (N)), the tropical savanna or tropical wet monsoon and tropical dry areas of South Asia (SA), and the subarctic climate areas of Northern Asia (NOA) may suffer more risks from the view of both magnitude and frequency changes of extreme precipitation.
The present study aims to assess the recent changes and trends in the extreme climate indices in the Kashmir basin using the observational records from 1980 to 2016. The extreme climate indices were computed using the ClimPACT2 software and a total of 39 indices were selected for the analysis having particular utility to various sectors like agriculture, water resources, energy consumption, and human health. Besides adopting the station scale analysis, regional averages were computed for each index. In terms of the mean climatology, an increase has been observed in the annual mean temperature with a magnitude of 0.024 °C/year. Further, differential warming patterns have been observed in the mean maximum and minimum temperatures with mean maximum temperature revealing higher increases than mean minimum temperature. On the other hand, the annual precipitation shows a decrease over most of the region, and the decreases are more pronouncing in the higher altitudes. The trend analysis of the extreme indices reveals that in consonance with the rising temperature there has been an increase in the warm temperatures and decrease in the cold temperatures across the Kashmir basin. Furthermore, our analysis suggests a decrease in the extreme precipitation events. The drought indices viz., Standardised Precipitation Index (SPI), and Standardised Precipitation Evapotranspiration Index (SPEI) manifest decreasing trends with the tendency towards drier regimes implying the need for better water resource management in the region under changing climate.
Many studies have explored the association between temperature and atopic dermatitis (AD); however, the results are inconsistent. We used a quasi-Poisson function fitted to a distributed lag nonlinear model (DLNM) to evaluate the association between daily average temperature and AD outpatient visits from January 1, 2013, to December 31, 2019, in Lanzhou, China. We found that the exposure-response association curve was inversely “s-shaped,” low-temperature effects occurred at a lag of 11 days and then lasted for 10 days, and high-temperature effects occurred on the current day and then significantly decreased. Both low and high ambient temperatures can increase the risk of outpatient visits. Compared with median temperature (12.89°C), the cumulative relative risk (RR) of extreme high temperature and moderate-high temperature were 1.847 (95% confidence interval [CI]: 1.613, 2.114) and 1.447 (95% CI: 1.298, 1.614), respectively, at lag0-7 days, and the cumulative RRs of extremely low temperature and moderate-low temperature were 1.004 (95% CI: 0.904, 1.115) and 1.056 (95% CI: 0.925, 1.205), respectively, at lag0-21 days. Females were more sensitive to high temperatures than males, and high or low temperatures had significant effects on children ?14 years of age. Graphical abstract.
BACKGROUND: There is growing evidence suggesting that extreme temperatures have an impact on mental disorders. We aimed to explore the effect of extreme temperatures on emergency room (ER) visits for mental health disorders using 2.8 million records from New York State, USA (2009-2016), and to examine potential effect modifications by individuals’ age, sex, and race/ethnicity through a stratified analysis to determine if certain populations are more susceptible. METHOD: To assess the short-term impact of daily average temperature on ER visits related to mental disorders, we applied a quasi-Poisson generalized linear model combined with a distributed lag non-linear model (DLNM). The model was adjusted for day of the week, precipitation, as well as long-term and seasonal time trends. We also conducted a meta-analysis to pool the region-specific risk estimates and construct the overall cumulative exposure-response curves for all regions. RESULTS: We found positive associations between short-term exposure to extreme heat (27.07 (?)C) and increased ER visits for total mental disorders, as well as substance abuse, mood and anxiety disorders, schizophrenia, and dementia. We did not find any statistically significant difference among any subgroups of the population being more susceptible to extreme heat than any other. CONCLUSIONS: Our findings suggest that there is a positive association between short-term exposure to extreme heat and increased ER visits for total mental disorders. This extreme effect was also found across all sub-categories of mental disease, although further research is needed to confirm our finding for specific mental disorders, such as dementia, which accounted for less than 1% of the total mental disorders in this sample.
Prevalence of allergic diseases has been increasing due to multiple factors, among which climate change has had the most impact. Climate factors increase production of pollen, which also exhibits increased allergenicity. Also, as a result of climate change, there has been a shift in flowering phenology and pollen initiation causing prolonged pollen exposure. Various numerical models have been developed to understand the effect of climate change on pollen emission and transport and the impact on allergic airway diseases.
With the rising trends in elderly populations around the world, there is a growing interest in understanding how climate variability is related to the health of this population group. Therefore, we analyzed the associations between mortality in the elderly due to cardiovascular (CVD) and respiratory diseases (RD) and meteorological variables, for three cities in the State of Sao Paulo, Brazil: Campos do Jordao, Ribeirao Preto, and Santos, all in different subtropical regions, from 1996 to 2017. The main objective was to verify how these distinct subtropical climates impact elderly mortality differently. We applied the autoregressive model integrated with moving average (ARIMA) and the principal component analysis (PCA), in order to evaluate statistical associations. Results showed CVD as a major cause of mortality, particularly in the cold period, when a high mortality rate is also observed due to RD. The mortality rate was higher in Campos do Jordao and lower in Santos. In Campos do Jordao, results indicate an increased probability of mortality from CVD and RD due to lower temperatures. In Ribeirao Preto, the lower relative humidity may be related to the increase in CVD and RD deaths. This study emphasizes that, even among subtropical climates, there are significant differences on how climate impacts human health, which can assist decision-makers in the implementation of mitigating and adaptive measures.
INTRODUCTION: In 2016-18, the Democratic Republic of São Tomé and Príncipe suffered a necrotic skin infection epidemic. METHODS: A surveillance system was established after increased hospitalisations for this infection. Microbiology results were available for samples analysed in December 2016 and March 2017 using whole genome sequencing and metagenomics. Negative binomial regression was used to study the association of weather conditions with monthly case counts in a time-series analysis. RESULTS: From October 2016 to October 2018, the epidemic cumulative attack rate was 1.5%. The first peak lasted 5 months, accounting for one-third of total cases. We could not conclusively identify the aetiological agent(s) due to the country’s lack of microbiology capacity. Increased relative humidity was associated with increased monthly cases (incidence rate ratio (IRR) 1.05, 95% CI 1.02-1.09), and higher precipitation in the previous month with a higher number of cases in the following month (months with 0-49 mm rainfall compared with months with 50-149 mm and ?150 mm: IRR 1.44, 95 % CI 1.13-1.78 and 1.50, 95% CI 1.12-1.99, respectively). DISCUSSION: This epidemic was favoured by increased relative humidity and precipitation, potentially contributing to community-based transmission of ubiquitous bacterial strains superinfecting skin wounds. FUNDING: World Health Organization Regional Office for Africa, Ministry of Health.
BACKGROUND: Extreme weather events happen more frequently along with global warming and they constitute a challenge for public health preparedness. For example, many investigations showed heavy rainfall was associated with an increased risk of acute gastroenteritis. In this study, we examined the associations between different meteorological factors and paediatric acute gastroenteritis in an affluent setting in China controlling for pollutant effects. METHODS: Aggregated total weekly number of intestinal infection-related hospital admissions, and meteorological and air pollution data during 1998-2018 in Hong Kong were collected and analysed by a combination of quasi-Poisson generalized additive model and distributed lag nonlinear model. Study population was restricted to children under 5 years of age at the time of admission. RESULTS: While heavy rainfall did not exhibit a statistically significant association with the risk of paediatric admission due to intestinal infections, low temperature and humidity extremes (both relative humidity and vapour pressure) did. Compared with the temperature at which the lowest risk was detected (i.e. 22.5 °C), the risk was 6.4% higher (95% confidence interval: 0.0% to 13.0% at 15.1 °C (i.e. the 5th percentile)). We also found the risk of paediatric admission was statistically significantly associated with an increase in the number of extreme cold days in a week over the study period. CONCLUSION: Cold condition may have greater impact on disease transmission through increased stability and infectivity of enteric viruses in affluent settings like Hong Kong and thus resulted in an increased risk for paediatric acute gastroenteritis. On the contrary, an insignificant impact from heavy rainfall and high temperature may indicate a minor effect on disease transmission through bacterial growth in contaminated food and water. With the identified impacts of weather factors, extreme weather events are likely to distort the prevalence and seasonal pattern of diarrhoeal diseases in the future.
Gender-sensitive and gender-responsive approaches are important to increase adaptive capacity in a changing climate given the gendered nature of exposure levels to climate shocks. Nonetheless, knowledge and perception of the public to climate change influence behavioural intention to adapt. While literature is replete with public perception and adaptation strategies to climate change, there is a dearth of information exploring the influence of gender on climate change knowledge. This paper employs quantitative and qualitative data to examine the influence of gender on knowledge in climate trends in Beitbridge Rural District, Zimbabwe, using questionnaire surveys. This survey tool consisted of demographic questions on gender and other variables. Our results indicate that compared to women, actual knowledge of trends in selected variables of climate change was higher among men. Furthermore, male respondents had higher self-evaluated knowledge on climate trends compared to female participants. We recommend gender disaggregated data in the vulnerability and adaptation assessments and the education, training and awareness sections of the National Communications to the United Nations Convention on Climate Change.
Rain, snow, or ice may discourage older adults from leaving their homes with potential consequences for social isolation, decreased physical activity, and cognitive decline. This study is the first to examine potential links between annual precipitation exposure and cognitive function in a large population-based cohort of older Americans. We examined the association between precipitation (percent of days with snow or rain in the past year) and cognitive function in 25,320 individuals aged 45+ from the Reasons for Geographic and Racial Differences in Stroke Study. Linear mixed models assessed the relationship between precipitation and cognitive function, as well as rates of change in cognitive function with age. We found a non-linear relationship between precipitation and cognitive function. Compared to those exposed to infrequent precipitation (less than 20% of days with rain/snow in the past year), cognitive function was higher among older adults experiencing moderately frequent precipitation (20-40% of annual days with precipitation). However, beyond more than about 45% of days with precipitation in the past year, there was a negative association between precipitation and cognitive function, with faster rates of cognitive decline with age. These exploratory findings motivate further research to better understand the complex role of precipitation for late-life cognitive function.
Since the first report in December 2019, the novel coronavirus (COVID-19) has spread to most parts of the world, with over 21.5 million people infected and nearly 768,000 deaths to date. Evidence suggests that transmission of the virus is primarily through respiratory droplets and contact routes, and airborne carriers such as atmospheric particulates and aerosols have also been proposed as important vectors for the environmental transmission of COVID-19. Sewage and human excreta have long been recognized as potential routes for transmitting human pathogens. The causative agent of the COVID-19 pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been detected in human feces and urine, where it could remain viable for days and show infectivity. Urban flooding, a common threat in summer caused by heavy rainfalls, is frequently reported in urban communities along with sewage overflows. With summer already underway and economy re-opening in many parts of the world, urban flooding and the often-accompanied sewage overflows could jeopardize previous mitigation efforts by posing renewed risks of virus spread in affected areas and communities. In this article, we present the up-to-date evidence and discussions on sewage-associated transmission of COVID-19, and highlighted the roles of sewage overflow and sewage-contaminated aerosols in two publicized events of community outbreaks. Further, we collected evidence in real-life environments to demonstrate the shortcuts of exposure to overflowed sewage and non-dispersed human excreta during a local urban flooding event. Given that communities serviced by combined sewer systems are particularly prone to such risks, local municipalities could prioritize wastewater infrastructure upgrades and consider combined sewer separations to minimize the risks of pathogen transmission via sewage overflows during epidemics.
The scarlet fever incidence has increased drastically in recent years in China. However, the long-term relationship between climate variation and scarlet fever remains contradictory, and an early detection system is lacking. In this study, we aim to explore the potential long-term effects of variations in monthly climatic parameters on scarlet fever and to develop an early scarlet-fever detection tool. Data comprising monthly scarlet fever cases and monthly average climatic variables from 2004 to 2017 were retrieved from the Notifiable Infectious Disease Surveillance System and National Meteorological Science Center, respectively. We used a negative binomial multivariable regression to assess the long-term impacts of weather parameters on scarlet fever and then built a novel forecasting technique by integrating an autoregressive distributed lag (ARDL) method with a nonlinear autoregressive neural network (NARNN) based on the significant meteorological drivers. Scarlet fever was a seasonal disease that predominantly peaked in spring and winter. The regression results indicated that a 1 °C increment in the monthly average temperature and a 1-h increment in the monthly aggregate sunshine hours were associated with 17.578% (95% CI 7.674 to 28.393%) and 0.529% (95% CI 0.035 to 1.025%) increases in scarlet fever cases, respectively; a 1-hPa increase in the average atmospheric pressure at a 1-month lag was associated with 12.996% (95% CI 9.972 to 15.919%) decrements in scarlet fever cases. Based on the model evaluation criteria, the best-performing basic and combined approaches were ARDL(1,0,0,1) and ARDL(1,0,0,1)-NARNN(5, 22), respectively, and this hybrid approach comprised smaller performance measures in both the training and testing stages than those of the basic model. Climate variability has a significant long-term influence on scarlet fever. The ARDL-NARNN technique with the incorporation of meteorological drivers can be used to forecast the future epidemic trends of scarlet fever. These findings may be of great help for the prevention and control of scarlet fever.
We used monthly precipitation and temperature data to give early warning of years with higher West Nile Virus (WNV) risk in Nebraska. We used generalized additive models with a negative binomial distribution and smoothing curves to identify combinations of extremes and timing that had the most influence, experimenting with all combinations of temperature and drought data, lagged by 12, 18, 24, 30, and 36 months. We fit models on data from 2002 through 2011, used Akaike’s Information Criterion (AIC) to select the best-fitting model, and used 2012 as out-of-sample data for prediction, and repeated this process for each successive year, ending with fitting models on 2002-2017 data and using 2018 for out-of-sample prediction. We found that warm temperatures and a dry year preceded by a wet year were the strongest predictors of cases of WNV. Our models did significantly better than random chance and better than an annual persistence naïve model at predicting which counties would have cases. Exploring different scenarios, the model predicted that without drought, there would have been 26% fewer cases of WNV in Nebraska through 2018; without warm temperatures, 29% fewer; and with neither drought nor warmth, 45% fewer. This method for assessing the influence of different combinations of extremes at different time intervals is likely applicable to diseases other than West Nile, and to other annual outcome variables such as crop yield.
The global monsoon is characterised by transitions between pronounced dry and wet seasons, affecting food security for two-thirds of the world’s population. Rising atmospheric CO(2) influences the terrestrial hydrological cycle through climate-radiative and vegetation-physiological forcings. How these two forcings affect the seasonal intensity and characteristics of monsoonal precipitation and runoff is poorly understood. Here we use four Earth System Models to show that in a CO(2)-enriched climate, radiative forcing changes drive annual precipitation increases for most monsoon regions. Further, vegetation feedbacks substantially affect annual precipitation in North and South America and Australia monsoon regions. In the dry season, runoff increases over most monsoon regions, due to stomatal closure-driven evapotranspiration reductions and associated atmospheric circulation change. Our results imply that flood risks may amplify in the wet season. However, the lengthening of the monsoon rainfall season and reduced evapotranspiration will shorten the water resources scarcity period for most monsoon regions.
INTRODUCTION: To investigate total annual precipitation, precipitation anomaly and aridity index in relation to linear growth in children under 5 in Uganda and quantify the mediating role of crop yield. METHODS: We analysed data of 5219 children under 5 years of age who participated in the 2016 Uganda Demographic and Health Survey. Annual crop yield in kilograms per hectare for 42 crops at a 0.1° (~10 km at the equator) spatial resolution square grid was obtained from the International Food Policy Research Institute. Normalised rainfall anomaly and total precipitation were derived from the African Rainfall Estimation Algorithm Version 2 product. Linear regression models were used to associate total annual precipitation and anomalies with height-for-age z-scores and to explore the mediating role of crop yield qualitatively. The intervening effects were quantitatively estimated by causal mediation models. RESULTS: Twenty-nine per cent of children were stunted (95% CI 28% to 31%). After adjusting for major covariates, higher total annual precipitation was significantly associated with increasing height-for-age z-scores. At the mean, an increase of 1 standard deviation in local annual rainfall was associated with a 0.07-point higher z-score. Aridity index and precipitation anomaly were not associated with height-for-age z scores in altitude-adjusted models. Crop yields of nuts, seeds, cereals and pulses were significant mediating factors. For instance, 38% of the association between total annual precipitation with height-for-age z-scores can be attributed to the yield of sesame seeds. CONCLUSIONS: Higher total annual precipitation at the village-level was significantly associated with higher height-for-age z-scores among children in Uganda. This association can be partially explained by higher crop yield, especially from seeds and nuts. This study suggests that more attention should be paid to villages with lower annual rainfall amounts to improve water availability for agriculture.
BACKGROUND: Although visceral leishmaniasis (VL), a disease caused by parasites, is controlled in most provinces in China, it is still a serious public health problem and remains fundamentally uncontrolled in some northwest provinces and autonomous regions. The objective of this study is to explore the spatial and temporal characteristics of VL in Sichuan Province, Gansu Province and Xinjiang Uygur Autonomous Region in China from 2004 to 2018 and to identify the risk areas for VL transmission. METHODS: Spatiotemporal models were applied to explore the spatio-temporal distribution characteristics of VL and the association between VL and meteorological factors in western China from 2004 to 2018. Geographic information of patients from the National Diseases Reporting Information System operated by the Chinese Center for Disease Control and Prevention was defined according to the address code from the surveillance data. RESULTS: During our study period, nearly 90% of cases occurred in some counties in three western regions (Sichuan Province, Gansu Province and Xinjiang Uygur Autonomous Region), and a significant spatial clustering pattern was observed. With our spatiotemporal model, the transmission risk, autoregressive risk and epidemic risk of these counties during our study period were also well predicted. The number of VL cases in three regions of western China concentrated on a few of counties. VL in Kashi Prefecture, Xinjiang Uygur Autonomous Region is still serious prevalent, and integrated control measures must be taken in different endemic areas. CONCLUSIONS: The number of VL cases in three regions of western China concentrated on a few of counties. VL in Kashi Prefecture, Xinjiang Uygur Autonomous Region is still serious prevalent, and integrated control measures must be taken in different endemic areas. Our findings will strengthen the VL control programme in China.
BACKGROUND: The public health impacts of tropical cyclones (TCs) are expected to increase due to the continued growth of coastal populations and the increasing severity of these events. However, the impact of TCs on pregnant women, a vulnerable population, remains largely unknown. We aimed to estimate the association between prenatal exposure to TCs and risk of preterm birth in the eastern United States (US) and to assess whether the association varies by individual- and area-level characteristics. METHODS: We included data on 19,529,748 spontaneous singleton births from 1989 to 2002 across 378 US counties. In each county, we classified days as exposed to a TC when TC-associated peak sustained winds at the county’s population-weighted center were >17.2 m/s (gale-force winds or greater). We defined preterm birth as births delivered prior to 37 completed weeks of gestation. We used distributed lag log-linear mixed-effects models to estimate the relative risk (RR) and absolute risk difference (ARD) for TC exposure by comparing preterm births occurring in TC-periods (from 2 days before to 30 days after the TC’s closest approach to the county’s population center) to matched non-TC periods. We conducted secondary analyses using other wind thresholds (12 m/s and 22 m/s) and other exposure metrics: county distance to storm track (30 km, 60 km, and 100 km) and cumulative rainfall within the county (75 mm, 100 mm, and 125 mm). RESULTS: During the study period, there were 1,981,797 (10.1%) preterm births and 58 TCs that affected at least one US county on which we had birth data. The risk of preterm birth was positively associated with TC exposure defined as peak sustained wind speed >17.2 m/s (gale-force winds or greater) [RR: 1.01 (95% CI: 0.99, 1.03); ARD: 9 (95% CI: -7, 25) per 10,000 pregnancies], distance to storm track <60 km [RR: 1.02 (95% CI: 1.01, 1.04); ARD: 23 (95% CI: 9, 38) per 10,000 pregnancies], and cumulative rainfall >100 mm [RR: 1.04 (95% CI: 1.02, 1.06); ARD: 36 (95% CI: 16, 56) per 10,000 pregnancies]. Results were comparable when considering other wind, distance, or rain thresholds. The association was more pronounced among early preterm births and mothers living in more socially vulnerable counties but did not vary across strata of other hypothesized risk factors. CONCLUSIONS: Maternal exposure to TC was associated with a higher risk of preterm birth. Our findings provide initial evidence that severe storms may trigger preterm birth.
Malaria is a vector-borne disease of significant public health concern. Despite widespread success of many elimination initiatives, elimination efforts in some regions of the world have stalled. Barriers to malaria elimination include climate and land use changes, such as warming temperatures and urbanization, which can alter mosquito habitats. Socioeconomic factors, such as political instability and regional migration, also threaten elimination goals. This is particularly relevant in areas where local elimination has been achieved and consequently surveillance and control efforts are dwindling and are no longer a priority. Understanding how environmental change, impacts malaria elimination has important practical implications for vector control and disease surveillance strategies. It is important to consider climate change when monitoring the threat of malaria resurgence due to socioeconomic influences. However, there is limited assessment of how the combination of climate variation, interventions and socioeconomic pressures influence long-term trends in malaria transmission and elimination efforts. In this study, we used Bayesian hierarchical mixed models and malaria case data for a 29-year period to disentangle the impacts of climate variation and malaria control efforts on malaria risk in the Ecuadorian province of El Oro, which achieved local elimination in 2011. We found shifting patterns of malaria between rural and urban areas, with a relative increase ofPlasmodium vivaxin urbanized areas. Minimum temperature was an important driver of malaria seasonality and the association between warmer minimum temperatures and malaria incidence was greater forPlasmodium falciparumcompared toP. vivaxmalaria. There was considerable heterogeneity in the impact of three chemical vector control measures on bothP. falciparumandP. vivaxmalaria. We found statistically significant associations between two of the three measures [indoor residual spraying (IRS) and space spraying] and a reduction in malaria incidence, which varied between malaria type. We also found environmental suitability for malaria transmission is increasing in El Oro, which could limit future elimination efforts if malaria is allowed to re-establish. Our findings have important implications for understanding environmental obstacles to malaria elimination and highlights the importance of designing and sustaining elimination efforts in areas that remain vulnerable to resurgence.
BACKGROUND: In Thailand, dengue fever is one of the most well-known public health problems. The objective of this study was to examine the epidemiology of dengue and determine the seasonal pattern of dengue and its associate to climate factors in Bangkok, Thailand, from 2003 to 2017. METHODS: The dengue cases in Bangkok were collected monthly during the study period. The time-series data were extracted into the trend, seasonal, and random components using the seasonal decomposition procedure based on loess. The Spearman correlation analysis and artificial neuron network (ANN) were used to determine the association between climate variables (humidity, temperature, and rainfall) and dengue cases in Bangkok. RESULTS: The seasonal-decomposition procedure showed that the seasonal component was weaker than the trend component for dengue cases during the study period. The Spearman correlation analysis showed that rainfall and humidity played a role in dengue transmission with correlation efficiency equal to 0.396 and 0.388, respectively. ANN showed that precipitation was the most crucial factor. The time series multivariate Poisson regression model revealed that increasing 1% of rainfall corresponded to an increase of 3.3% in the dengue cases in Bangkok. There were three models employed to forecast the dengue case, multivariate Poisson regression, ANN, and ARIMA. Each model displayed different accuracy, and multivariate Poisson regression was the most accurate approach in this study. CONCLUSION: This work demonstrates the significance of weather in dengue transmission in Bangkok and compares the accuracy of the different mathematical approaches to predict the dengue case. A single model may insufficient to forecast precisely a dengue outbreak, and climate factor may not only indicator of dengue transmissibility.
Limited research exists on the influence of climatic conditions on the risk of hospital admission for asthma in Minas Gerais, Brazil. The objectives of this article are: a) to evaluate the influence of climatic conditions on hospital admissions for asthma and lower respiratory tract infections (LRTIs) among children and adolescents living in Belo Horizonte during the period 2002 to 2012 and identify epidemic peaks of admissions for asthma; b) to compare local seasonal patterns of admissions for asthma and LRTIs. Using hospital admission data stratified by aged group, regression analysis was performed to determine the relationship between the variables. Epidemic peaks were identified using an ARIMA model. There was an increase in admissions for asthma with an increase in relative humidity after rainy periods; admissions for bronchiolitis were associated with low levels of maximum temperature and rainfall. Rainy periods can lead to an increase in indoor and outdoor humidity, facilitating fungal proliferation, while cold periods can lead to an increase in the spread of viruses.
A yellow fever epidemic occurred in Cadiz and other areas of southern Spain during the last months of 1800. An anonymous author attributed this disease to the contrast between the cold and rainy winter and spring, and the subsequent very hot summer. However, the physician J.M. Arejula published a report in 1806 where he refuted this conclusion after a detailed analysis of the meteorological conditions in the area. This controversy is a good example of the discussion about the relationships between meteorological conditions and public health. In this work, this “scientific” controversy is studied. Although the arguments of both authors were inspired by the neo-Hippocratic medical paradigm, the anonymous author put forth a simple cause effect hypothesis, while Arejula recognized the complexity of the problem, introducing the concept of “concause” to explain the confluence of environmental and contagious effects.
Evidence on the long-term influence of climatic variables on pertussis is limited. This study aims to explore the long-term quantitative relationship between weather variability and pertussis. Data on the monthly number of pertussis cases and weather parameters in Chongqing in the period of 2004-2018 were collected. Then, we used a negative binomial multivariable regression model and cointegration testing to examine the association of variations in monthly meteorological parameters and pertussis. Descriptive statistics exhibited that the pertussis incidence rose from 0.251 per 100,000 people in 2004 to 3.661 per 100,000 persons in 2018, and pertussis was a seasonal illness, peaked in spring and summer. The results from the regression model that allowed for the long-term trends, seasonality, autoregression, and delayed effects after correcting for overdispersion showed that a 1 hPa increment in the delayed one-month air pressure contributed to a 3.559% (95% CI 0.746-6.293%) reduction in the monthly number of pertussis cases; a 10 mm increment in the monthly aggregate precipitation, a 1 °C increment in the monthly average temperature, and a 1 m/s increment in the monthly average wind velocity resulted in 3.641% (95% CI 0.960-6.330%), 19.496% (95% CI 2.368-39.490%), and 3.812 (95% CI 1.243-11.690)-fold increases in the monthly number of pertussis cases, respectively. The roles of the mentioned weather parameters in the transmission of pertussis were also evidenced by a sensitivity analysis. The cointegration testing suggested a significant value among variables. Climatic factors, particularly monthly temperature, precipitation, air pressure, and wind velocity, play a role in the transmission of pertussis. This finding will be of great help in understanding the epidemic trends of pertussis in the future, and weather variability should be taken into account in the prevention and control of pertussis.
The 2018 outbreak of dengue in the French overseas department of Réunion was unprecedented in size and spread across the island. This research focuses on the cause of the outbreak, asserting that climate played a large role in the proliferation of the Aedes albopictus mosquitoes, which transmitted the disease, and led to the dengue outbreak in early 2018. A stage-structured model was run using observed temperature and rainfall data to simulate the life cycle and abundance of the Ae. albopictus mosquito. Further, the model was forced with bias-corrected subseasonal forecasts to determine if the event could have been forecast up to 4 weeks in advance. With unseasonably warm temperatures remaining above 25°C, along with large tropical-cyclone-related rainfall events accumulating 10-15 mm per event, the modeled Ae. albopictus mosquito abundance did not decrease during the second half of 2017, contrary to the normal behavior, likely contributing to the large dengue outbreak in early 2018. Although subseasonal forecasts of rainfall for the December-January period in Réunion are skillful up to 4 weeks in advance, the outbreak could only have been forecast 2 weeks in advance, which along with seasonal forecast information could have provided enough time to enhance preparedness measures. Our research demonstrates the potential of using state-of-the-art subseasonal climate forecasts to produce actionable subseasonal dengue predictions. To the best of the authors’ knowledge, this is the first time subseasonal forecasts have been used this way.
BACKGROUND: Intense studies have been carried out on the effects of climate change on vector-borne diseases and vectors. Culex pipiens pallens and Culex pipiens quinquefasciatus are two medically concerned mosquito species in temperate and tropical areas, which serve as important disease-transmitting pests of a variety of diseases. The ongoing geographical expansion of these mosquitoes has brought an increasing threat to public health. RESULTS: Based on mosquito occurrence records and high-resolution environmental layers, an ecological niche model was established to model their current and future potential distribution in China. Our model showed that the current suitable area for Cx. p. pallens is distributed in the central, eastern and northern parts of China, while Cx. p. quinquefasciatus is distributed in vast areas in southern China. Under future climate change scenarios, both species are predicted to expand their range to varying degrees and RCP 8.5 provides the largest expansion. Northward core shifts will occur in ranges of both species. Environmental variables which have significant impact on the distribution of mosquitoes were also revealed by our model. CONCLUSION: Severe habitat expansion of vectors is likely to occur in the future 21st century. Our models mapped the high-risk areas and risk factors which needs to be paid attention. The results of our study can be referenced in further ecological surveys and will guide the development of strategies for the prevention and control of vector-borne diseases. © 2020 Society of Chemical Industry.
Previous studies that observed the fact that Middle Palaeolithic sites mainly were concentrated in arid and semi-arid areas in Africa and Southwest Asia, concluded that climate factors determined the distribution patterns. We argue that biological factors could have been equally important. In present-day sub-Saharan Africa, mosquito borne diseases and especially falciparum malaria have a serious impact on human populations. This study was aimed to investigate the possible former effect of falciparum malaria on Middle Palaeolithic site distribution patterns and explain why ancient humans avoided the humid areas in the tropical and subtropical regions. It was found that the early human settlements situated in those regions of Africa and Southwest Asia where the potential annual development period of falciparum parasites was short in the mosquitoes, the area was not too humid, and the potential falciparum malaria incidence values were low or moderate. In the Indian Peninsula, precipitation played a less significant role in determining human settlements. The number of the months when the extrinsic development of Plasmodium falciparum parasites was possible showed the strongest structural overlap with the modelled malaria incidences according to the spatial occurrence of the Middle Paleolithic archaeological sites in the case of Africa and in Southwest Asia. In the Indian Peninsula, climatic factors showed the strongest structural overlap with the modelled malaria incidences according to the occurrence patterns of the Middle Palaeolithic archaeological sites.
The H1N1 “Spanish influenza” pandemic of 1918-1919 caused the highest known number of deaths recorded for a single pandemic in human history. Several theories have been offered to explain the virulence and spread of the disease, but the environmental context remains underexamined. In this study, we present a new environmental record from a European, Alpine ice core, showing a significant climate anomaly that affected the continent from 1914 to 1919. Incessant torrential rain and declining temperatures increased casualties in the battlefields of World War I (WWI), setting the stage for the spread of the pandemic at the end of the conflict. Multiple independent records of temperature, precipitation, and mortality corroborate these findings.
Arid and semi-arid climates, including that of Iran, are more susceptible to environmental changes due to their special ecological structure than other climates. Therefore, climate change in these areas appears to have significant effects on agricultural and food production systems. The present study explores the effect of climatic changes on total horticultural production and food security in agro-ecological zones of Iran. The study was conducted in two steps. In the first step, the effects of climatic parameters on total horticultural production were investigated using time series data (1985-2017) and a regression model. In the second step, due to the important role of horticultural products in per capita food consumption in Iran, the effect of climate parameters on food security was also examined. Results revealed that total horticultural production was influenced by temperature, evapotranspiration, and wind speed at the 0.05 level. With the increase in temperature (at a rate of one unit), total horticultural production is reduced to 0.01 million tons. Evapotranspiration and wind speed have had a negative effect on total horticultural production, and with increasing evapotranspiration and wind speed, total horticultural production was 0.029 and 0.008 million, respectively, tons decreased. Also, food security was influenced by temperature, precipitation, and wind speed.
Objective: To determine the significance of temperature, rainfall and humidity in the seasonal abundance of Anopheles stephensi in southern Iran. Methods: Data on the monthly abundance of Anopheles stephensi larvae and adults were gathered from earlier studies conducted between 2002 and 2019 in malaria prone areas of southeastern Iran. Climatic data for the studied counties were obtained from climatology stations. Generalized estimating equations method was used for cluster correlation of data for each study site in different years. Results: A significant relationship was found between monthly density of adult and larvae of Anopheles stephensi and precipitation, max temperature and mean temperature, both with simple and multiple generalized estimating equations analysis (P<0.05). But when analysis was done with one month lag, only relationship between monthly density of adults and larvae of Anopheles stephensi and max temperature was significant (P<0.05). Conclusions: This study provides a basis for developing multivariate time series models, which can be used to develop improved appropriate epidemic prediction systems for these areas. Long-term entomological study in the studied sites by expert teams is recommended to compare the abundance of malaria vectors in the different areas and their association with climatic variables.
Recent literature provides evidence that income shocks early in life can have long-run consequences on adult welfare. Rural Brazil frequently suffers from rainfall variations that negatively impact vulnerable households, who often lack the means for coping with these events. This paper evaluates how early-life rainfall shocks influence adult health and socioeconomic outcomes in Brazil. We find evidence that several critical periods can produce long-run consequences. Using rainfall deviations, our two most robust results are that greater rainfall in utero negatively impacts adult incomes (finding that a one standard deviation increase in rainfall causes adult incomes to fall by 7-10 percent) and that greater rainfall in the second and third years of life improve adult health (increasing body mass index by 0.16). However, our results depend crucially on our choices regarding two features. First, our results differ across two common measures of critical periods, which are used to define shocks relative to the timing of one’s birth. Second, the way rainfall variation is measured also matters, with use of an extreme weather indicator suggesting heterogeneous effects by gender, with extreme weather negatively impacting women’s health (both before and after birth) but positively affecting several men’s outcomes (both before and after birth). We find some evidence that mortality selection may drive some of these results. This paper provides further evidence that early-life shocks (from in utero through the third year of life) can cause long-run consequences, but also suggests that more attention should be paid to the specific measurement and timing of rainfall shocks.
In recent years, dengue has been rapidly spreading and growing in the tropics and subtropics. Located in southern China, Hong Kong’s subtropical monsoon climate may favour dengue vector populations and increase the chance of disease transmissions during the rainy summer season. An increase in local dengue incidence has been observed in Hong Kong ever since the first case in 2002, with an outbreak reaching historically high case numbers in 2018. However, the effects of seasonal climate variability on recent outbreaks are unknown. As the local cases were found to be spatially clustered, we developed a Poisson generalized linear mixed model using pre-summer monthly total rainfall and mean temperature to predict annual dengue incidence (the majority of local cases occur during or after the summer months), over the period 2002-2018 in three pre-defined areas of Hong Kong. Using leave-one-out cross-validation, 5 out of 6 observations of area-specific outbreaks during the major outbreak years 2002 and 2018 were able to be predicted. 42 out of a total of 51 observations (82.4%) were within the 95% confidence interval of the annual incidence predicted by our model. Our study found that the rainfall before and during the East Asian monsoon (pre-summer) rainy season is negatively correlated with the annual incidence in Hong Kong while the temperature is positively correlated. Hence, as mosquito control measures in Hong Kong are intensified mainly when heavy rainfalls occur during or close to summer, our study suggests that a lower-than-average intensity of pre-summer rainfall should also be taken into account as an indicator of increased dengue risk.
Numerous studies have examined the effects of weather on emergency ambulance service (EAS) demand. Given Taipei’s unique physical and social environments, empirical evidence collected from other regions may not be applicable. Collecting more information about the characteristics of vulnerable groups and the effects of weather could help the EAS managing authority in formulating cost-effective EAS policies. This study aims to look at the effects of weather on EAS demand in Taipei and to make a comparison with Hong Kong, which is also an Asian city and has a similar cultural context. The study analyzed over 370,000 EAS usage records from the Taipei City Fire Department. These records were aggregated into time series data according to patients’ characteristics and then regressed on meteorological data via multivariate forward regression. The effect size differences of the variance explained by different groups of EAS users’ regression models were compared. Afterward, the results of the regression analysis from Taipei were compared with those from a Hong Kong study. Elderly and critical patients in both cities showed significantly more sensitivity to weather than other patients. Further analysis showed that non-trauma cases were related to weather in Taipei. Although both cities had similar results, the Taipei study clearly showed that elderly and critical patients were more sensitive to weather than other patient subgroups. Health education programs should focus on the vulnerable groups identified in this study in order to increase their awareness and help them protect themselves before the onset of adverse weather conditions. By generating results that are directly applicable to Taipei, the formulation of inappropriate EAS policies can be prevented.
INTRODUCTION: Bacterial meningitis still constitutes an important threat in Africa. In the meningitis belt, a clear seasonal pattern in the incidence of meningococcal disease during the dry season has been previously correlated with several environmental parameters like dust and sand particles as well as the Harmattan winds. In parallel, the evidence of seasonality in meningitis dynamics and its environmental variables remain poorly studied outside the meningitis belt. This study explores several environmental factors associated with meningitis cases in the Democratic Republic of Congo (DRC), central Africa, outside the meningitis belt area. METHODS: Non-parametric Kruskal-Wallis’ tests were used to establish the difference between the different health zones, climate and vegetation types in relation to both the number of cases and attack rates for the period 2000-2018. The relationships between the number of meningitis cases for the different health zones and environmental and socio-economical parameters collected were modeled using different generalized linear (GLMs) and generalized linear mixed models (GLMMs), and different error structure in the different models, i.e., Poisson, binomial negative, zero-inflated binomial negative and more elaborated multi-hierarchical zero-inflated binomial negative models, with randomization of certain parameters or factors (health zones, vegetation and climate types). Comparing the different statistical models, the model with the smallest Akaike’s information criterion (AIC) were selected as the best ones. 515 different health zones from 26 distinct provinces were considered for the construction of the different GLM and GLMM models. RESULTS: Non-parametric bivariate statistics showed that there were more meningitis cases in urban health zones than in rural conditions (?2 = 6.910, p-value = 0.009), in areas dominated by savannah landscape than in areas with dense forest or forest in mountainous areas (?2 = 15.185, p-value = 0.001), and with no significant difference between climate types (?2 = 1.211, p-value = 0,449). Additionally, no significant difference was observed for attack rate between the two types of heath zones (?2 = 0.982, p-value = 0.322). Conversely, strong differences in attack rate values were obtained for vegetation types (?2 = 13.627, p-value = 0,001) and climate types (?2 = 13.627, p-value = 0,001). This work demonstrates that, all other parameters kept constant, an urban health zone located at high latitude and longitude eastwards, located at low-altitude like in valley ecosystems predominantly covered by savannah biome, with a humid tropical climate are at higher risk for the development of meningitis. In addition, the regions with mean range temperature and a population with a low index of economic well-being (IEW) constitute the perfect conditions for the development of meningitis in DRC. CONCLUSION: In a context of global environmental change, particularly climate change, our findings tend to show that an interplay of different environmental and socio-economic drivers are important to consider in the epidemiology of bacterial meningitis epidemics in DRC. This information is important to help improving meningitis control strategies in a large country located outside of the so-called meningitis belt.
BACKGROUND: Scrub typhus is a major cause of acute febrile illness in the tropics and is endemic over large areas of the Asia Pacific region. The national and global burden of scrub typhus remains unclear due to limited data and difficulties surrounding diagnosis. METHODOLOGY/PRINCIPAL FINDINGS: Scrub typhus reporting data from 2003-2018 were collected from the Thai national disease surveillance system. Additional information including the district, sub-district and village of residence, population, geographical, meteorological and satellite imagery data were also collected for Chiangrai, the province with the highest number of reported cases from 2003-2018. From 2003-2018, 103,345 cases of scrub typhus were reported with the number of reported cases increasing substantially over the observed period. There were more men than women, with agricultural workers the main occupational group affected. The majority of cases occurred in the 15-64 year old age group (72,144/99,543, 72%). Disease burden was greatest in the northern region, accounting for 53% of the total reported cases per year (mean). In the northern region, five provinces-Chiangrai, Chiangmai, Tak, Nan and Mae Hong Son-accounted for 84% (46,927/55,872) of the total cases from the northern region or 45% (46,927/103,345) of cases nationally. The majority of cases occurred from June to November but seasonality was less marked in the southern region. In Chiangrai province, elevation, rainfall, temperature, population size, habitat complexity and diversity of land cover contributed to scrub typhus incidence. INTERPRETATION: The burden of scrub typhus in Thailand is high with disease incidence rising significantly over the last two decades. However, disease burden is not uniform with northern provinces particularly affected. Agricultural activity along with geographical, meteorological and land cover factors are likely to contribute to disease incidence. Our report, along with existing epidemiological data, suggests that scrub typhus is the most clinically important rickettsial disease globally.
Yellow Fever (YF) is an arbovirus endemic in tropical regions of South America and Africa and it is estimated to cause 78,000 deaths a year in Africa alone. Climate change may have substantial effects on the transmission of YF and we present the first analysis of the potential impact on disease burden. We extend an existing model of YF transmission to account for rainfall and a temperature suitability index and project transmission intensity across the African endemic region in the context of four climate change scenarios. We use these transmission projections to assess the change in burden in 2050 and 2070. We find disease burden changes heterogeneously across the region. In the least severe scenario, we find a 93.0%[95%CI(92.7, 93.2%)] chance that annual deaths will increase in 2050. This change in epidemiology will complicate future control efforts. Thus, we may need to consider the effect of changing climatic variables on future intervention strategies.
BACKGROUND: The Crimean-Congo Hemorrhagic fever (CCHF) is endemic in Iran and has a high fatality rate. The aim of this study was to investigate the association between CCHF incidence and meteorological variables in Zahedan district, which has a high incidence of this disease. METHODS: Data about meteorological variables and CCHF incidence was inquired from 2010 to 2017 for Zahedan district. The analysis was performed using univariate and multivariate Seasonal Autoregressive Integrated Moving Average (SARIMA) models and Generalized Additive Models (GAM) using R software. AIC, BIC and residual tests were used to test the goodness of fit of SARIMA models, and R(2) was used to select the best model in GAM/GAMM. RESULTS: During the years under study, 190 confirmed cases of CCHF were identified in Zahedan district. The fatality rate of the disease was 8.42%. The disease trend followed a seasonal pattern. The results of multivariate SARIMA showed the (0,1,1) (0,1,1)(12) model with maximum monthly temperature lagged 5?months, forecasted the disease better than other models. In the GAM, monthly average temperature lagged 5?months, and the monthly minimum of relative humidity and total monthly rainfall without lag, had a nonlinear relation with the incidence of CCHF. CONCLUSIONS: Meteorological variables can affect CCHF occurrence.
Flooding displaces large populations each season, which potentially increases the exposure of the vulnerable societies. Having failed to curve down the number of people infected with COVID-19 in the first wave of the pandemic, many states in the United States (U.S.) are now at high risk of the concurrence of the two disasters. Assessing this compound risk before the country enters the flood season is of vital importance. Therefore, we provide a prompt tool to assess the compound risk of COVID-19 at the county level over the U.S. We find that (1) the number of flood insurance house claims can proxy the displaced population accurately with more spatiotemporal detail, and (2) the high-risk areas of both flooding and COVID-19 are concentrated along the southern and eastern coasts and some parts of the Mississippi River. Our findings may trigger the interest of further exploring the topics related to the concurrence of COVID-19 and flooding.
From 2011 through 2018, there was a notable increase in sporadic Legionnaires’ disease in the state of Minnesota. Sporadic cases are those not associated with a documented outbreak. Outbreak-related cases are typically associated with a common identified contaminated water system; sporadic cases typically do not have a common source that has been identified. Because of this, it is hypothesised that weather and environmental factors can be used as predictors of sporadic Legionnaires’ disease. An ecological design was used with case report surveillance data from the state of Minnesota during 2011 through 2018. Over this 8-year period, there were 374 confirmed Legionnaires’ disease cases included in the analysis. Precipitation, temperature and relative humidity (RH) data were collected from weather stations across the state. A Poisson regression analysis examined the risk of Legionnaires’ disease associated with precipitation, temperature, RH, land-use and age. A lagged average 14-day precipitation had the strongest association with Legionnaires’ disease (RR 2.5, CI 2.1-2.9), when accounting for temperature, RH, land-use and age. Temperature, RH and land-use also had statistically significant associations to Legionnaires’ disease, but with smaller risk ratios. This study adds to the body of evidence that weather and environmental factors play an important role in the risk of sporadic Legionnaires’ disease. This is an area that can be used to target additional research and prevention strategies.
In this study, the spatial pattern and temporal evolution of PM(2.5) over North China Plain (NCP) and Northeast China (NEC) during 2014-2018 was investigated. The annual mean PM(2.5) shows clear decreasing trends over time, but the seasonal mean PM(2.5) as well as the seasonal total duration and frequency of haze days shows large inter-annual fluctuation. Based on the atmospheric stagnation index (ASI), this study examined the correlation between ASI and haze events over NCP and NEC. Detailed analysis indicates that location dependency exists of ASI in the capability of capturing the haze events, and the ability is limited in NCP. Therefore, we first propose two alternative methods in defining the ASI to either account for the lag effect or enlarge the threshold value of wind speed at 500 hPa. The new methods can improve the ability of ASI to explain the haze events over NEC, though marginal improvement was achieved in NCP. Furthermore, this study constructed the equation based on the boundary layer height and wind speed at 10-meter, apparently improving the ability in haze capture rate (HCR), a ratio of haze days during the stagnation to the total haze days. Based on a multi-model ensemble analyses under Representative Concentration Pathway (RCP) 8.5, we found that by the end of this century, climate change may lead to increases in both the duration and frequency of wintertime stagnation events over NCP. In contrast, the models predict a decrease in stagnant events and the total duration of stagnation in winter over NEC.
This study established the correlation between respiratory syncytial virus (RSV) bronchiolitis and climate factors in the area of Sousse, Tunisia, during 13 years (2003-2015), from neonates and children <=?5 years old and hospitalized in Farhat Hached University-Hospital of Sousse. The meteorological data of Sousse including temperature, rainfall, and humidity were obtained. RSV detection was carried out with the direct immunofluorescence assay. The impact of climate factors on viral circulation was statistically analyzed. From 2003 to 2015, the total rate of RSV bronchiolitis accounted for 34.5% and peaked in 2007 and 2013. RSV infection was higher in male cases and pediatric environment (p<0.001) and was detected in 47.3% of hospitalizations in intensive care units. The epidemic of this pathogen started in October and peaked in January (41.6%). When the infectivity of RSV was at its maximum, the monthly average rainfall was high (31 mm) and the monthly average temperature and the monthly average humidity were at their minimum (11 °C and 66%, respectively). RSV activity was negatively correlated with temperature (r?=?-?0.78, p?=?0.003) and humidity (r?=?-?0.62, p?=?0.03). Regression analysis showed that the monthly average temperature fits into a linear model (R(2)?=?61%, p?
This paper examines the relationship between weather conditions and child nutrition in Ethiopia. We link data from four rounds of the Ethiopia Demographic and Health Survey to high-resolution climate data to measure exposure to rainfall and temperature in utero and during early life. We then estimate a set of multivariate regression models to understand how weather conditions impact child stunting, an indicator of sustained early life undernutrition. We find that greater rainfall during the rainy seasons in early life is associated with greater height for age. In addition, higher temperatures in utero, particularly during the first and third trimesters, and more rainfall during the third trimester, are positively associated with severe stunting, though stunting decreases with temperature in early life. We find potential evidence for a number of pathways underlying the weather-child nutrition relationship including agricultural livelihoods, heat stress, infectious disease transmission, and women’s time use during pregnancy. These findings illuminate the complex pathways through which climate change may influence child health and should motivate additional research focused on identifying the causal mechanisms underlying these links.
BACKGROUND: Between 2014 and 2017, successive cholera epidemics occurred in South Sudan within the context of civil war, population displacement, flooding, and drought. We aim to describe the spatiotemporal and molecular features of the three distinct epidemic waves and explore the role of vaccination campaigns, precipitation, and population movement in shaping cholera spread in this complex setting. METHODS: In this descriptive epidemiological study, we analysed cholera linelist data to describe the spatiotemporal progression of the epidemics. We placed whole-genome sequence data from pandemic Vibrio cholerae collected throughout these epidemics into the global phylogenetic context. Using whole-genome sequence data in combination with other molecular attributes, we characterise the relatedness of strains circulating in each wave and the region. We investigated the association of rainfall and the instantaneous basic reproduction number using distributed lag non-linear models, compared county-level attack rates between those with early and late reactive vaccination campaigns, and explored the consistency of the spatial patterns of displacement and suspected cholera case reports. FINDINGS: The 2014 (6389 cases) and 2015 (1818 cases) cholera epidemics in South Sudan remained spatially limited whereas the 2016-17 epidemic (20?438 cases) spread among settlements along the Nile river. Initial cases of each epidemic were reported in or around Juba soon after the start of the rainy season, but we found no evidence that rainfall modulated transmission during each epidemic. All isolates analysed had similar genotypic and phenotypic characteristics, closely related to sequences from Uganda and Democratic Republic of the Congo. Large-scale population movements between counties of South Sudan with cholera outbreaks were consistent with the spatial distribution of cases. 21 of 26 vaccination campaigns occurred during or after the county-level epidemic peak. Counties vaccinated on or after the peak incidence week had 2·2 times (95% CI 2·1-2·3) higher attack rates than those where vaccination occurred before the peak. INTERPRETATION: Pandemic V cholerae of the same clonal origin was isolated throughout the study period despite interepidemic periods of no reported cases. Although the complex emergency in South Sudan probably shaped some of the observed spatial and temporal patterns of cases, the full scope of transmission determinants remains unclear. Timely and well targeted use of vaccines can reduce the burden of cholera; however, rapid vaccine deployment in complex emergencies remains challenging. FUNDING: The Bill & Melinda Gates Foundation.
BACKGROUND: Suicidal behavior is determined by the consequence of an interaction between biological, psychological and sociological factors, as well as between individual and environmental effects. Fluctuations in meteorological factors can modify human behavior and affect suicidal rates. We hypothesize that high temperatures can be associated with an increase rate of suicidal attempts. METHODS: We included all the patients admitted to Soroka University Medical Center (SUMC) due to suicide attempts between the years 2002-2017 and were residents of Southern Israel. We computed two sets of regression models: first, a time stratified case-crossover design to control for seasonality and individual differences. Results are presented as odds ratio (OR) with confidence interval (CI); and then, time-series analyses to calculate the incidence rate ratio (IRR) and the cumulative effect of temperature on the daily incidences of emergency department (ED) admissions after suicide attempts. We stratified the analyses by demographic variables to identify significant individual differences. RESULTS: We identified 3100 attempts, by 2338 patients who lived in Be’er Sheva between 16 and 90 years of age; 421 patients made 2+ attempts. Suicide attempts were associated with a 5 °C increase during the summer season (OR 1.59, 95% CI 1.22-2.08) and a 5 °C increase in all seasons was associated with those who have made multiple attempts (OR 1.18, 95% CI 1.0005-1.38). The cumulative effect of 5 °C increment is associated with more suicide attempts over 2 days (IRR 1.10, 95% CI 0.98; 1.24) and 5 days (IRR 1.04, 95% CI 1.00; 1.08). The associations were greater for patients with psychiatric diagnosis and patients with multiple attempts. In a stratified analysis by individual characteristics we didn’t find significant association. CONCLUSION: High temperatures and low amount of precipitations are evidently of great impact on people’s susceptibility to suicidal behavior, especially for individuals who have had a prior suicide attempt. Our findings indicate the need for public health attention in the summer when temperature increases precipitously over days, especially for those who have made a prior suicide attempt.
BACKGROUND: This study aimed to describe the changing distribution of human brucellosis between 2004 and 2017 in mainland China and seek scientific evidence of the relationship between socio-economic, environmental, and ecological factors and human brucellosis incidence. METHODS: The annual numbers of brucellosis cases and incidence rates from 31 provinces in mainland China between 2004 and 2017 were obtained from the Data-Center for China Public Health Science. The number of monthly brucellosis cases in 2018 was obtained from the Chinese Center for Disease Control and Prevention. The electronic map of the People’s Republic of China was downloaded from the National Earth System Science Data Sharing Platform. Human population density, gross domestic product (GDP), and an inventory of cattle and sheep at the end of each year from 2004 to 2017 were obtained from the National Bureau of Statistics of China. Annual rainfall data from 31 provinces in the People’s Republic of China from 2004 to 2017 were collected from the China Meteorological Data Service Center. The risk distribution and changing trends of human brucellosis were mapped with ArcGIS. A cluster analysis was employed to identify geographical areas and periods with statistically significant incidence rates. Multivariate linear regression was used to determine possible factors that were significantly correlated with the presence of human brucellosis cases. RESULTS: Human brucellosis cases have spread throughout the whole country. Human brucellosis cases occurred mostly from March to August and were concentrated from April to July. The inventory of sheep, GDP, and climate were significantly correlated with the presence of brucellosis cases in mainland China. CONCLUSIONS: The geographical expansion of human brucellosis in mainland China was observed, so did the high-incidence clusters between 2004 and 2017. Most of the cases were reported during the early spring to early summer (February-August). Results from the multivariate linear regression suggested that the inventory of sheep, GDP, and climate were significantly associated with the incidence of human brucellosis in mainland China.
BACKGROUND: As global progress to reduce malaria transmission continues, it is increasingly important to track changes in malaria incidence rather than prevalence. Risk estimates for Africa have largely underutilized available health management information systems (HMIS) data to monitor trends. This study uses national HMIS data, together with environmental and geographical data, to assess spatial-temporal patterns of malaria incidence at facility catchment level in Uganda, over a recent 5-year period. METHODS: Data reported by 3446 health facilities in Uganda, between July 2015 and September 2019, was analysed. To assess the geographic accessibility of the health facilities network, AccessMod was employed to determine a three-hour cost-distance catchment around each facility. Using confirmed malaria cases and total catchment population by facility, an ecological Bayesian conditional autoregressive spatial-temporal Poisson model was fitted to generate monthly posterior incidence rate estimates, adjusted for caregiver education, rainfall, land surface temperature, night-time light (an indicator of urbanicity), and vegetation index. RESULTS: An estimated 38.8 million (95% Credible Interval [CI]: 37.9-40.9) confirmed cases of malaria occurred over the period, with a national mean monthly incidence rate of 20.4 (95% CI: 19.9-21.5) cases per 1000, ranging from 8.9 (95% CI: 8.7-9.4) to 36.6 (95% CI: 35.7-38.5) across the study period. Strong seasonality was observed, with June-July experiencing highest peaks and February-March the lowest peaks. There was also considerable geographic heterogeneity in incidence, with health facility catchment relative risk during peak transmission months ranging from 0 to 50.5 (95% CI: 49.0-50.8) times higher than national average. Both districts and health facility catchments showed significant positive spatial autocorrelation; health facility catchments had global Moran’s I?=?0.3 (p <?0.001) and districts Moran’s I?=?0.4 (p <?0.001). Notably, significant clusters of high-risk health facility catchments were concentrated in Acholi, West Nile, Karamoja, and East Central – Busoga regions. CONCLUSION: Findings showed clear countrywide spatial-temporal patterns with clustering of malaria risk across districts and health facility catchments within high risk regions, which can facilitate targeting of interventions to those areas at highest risk. Moreover, despite high and perennial transmission, seasonality for malaria incidence highlights the potential for optimal and timely implementation of targeted interventions.
Natural environmental disasters in the developing countries of West Africa are at alarming rate which necessitate the investigation of long-term trend of rainfall and temperature. Current variation, trends of temperature, and rainfall across Nigeria were investigated using parametric and non-parametric statistical tools. Meteorological data obtained from the Nigeria Meteorological Agency in Lagos, Nigeria, from 1970 to 2010 were used for this analysis. Seasonal and annual trends of maximum temperature, minimum temperature, and rainfall were carried out using Mann-Kendall and Sen’s slope methods. Long-term linear regression of these meteorological variables was analyzed across eighteen locations in the country. Spatial distribution of seasonal trends of these variables was also estimated for the four seasons in Nigeria. The result of the linear regression on temperatures and rainfall showed increasing trends in most of the locations across the country. Similarly, Mann-Kendall and Sen’s slope analysis showed a significant increasing trend in most areas across the country. Consequently, recent phenomena of environmental hazard such as an outbreak of airborne diseases and flooding leading to the collapse of buildings and various environmental disasters can be linked to the observed result.
BACKGROUND: In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal and to identify the meteorological, environmental, and preventive factors that influence this variation. METHODS: This study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central Senegal (total population approximately 500,000) as part of a trial of seasonal malaria chemoprevention (SMC). Data on weekly rainfall and annual vegetation types were obtained for each village through remote sensing. The time series of weekly malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. Malaria hotspots were detected during each transmission period with the SaTScan method. The effects of rainfall, vegetation type, and SMC intervention on the spatio-temporal variation of malaria hotspots were assessed using a General Additive Mixed Model. RESULTS: The malaria incidence for the entire area varied between 0 and 115.34 cases/100,000 person weeks during the study period. During high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. During low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. Villages with SMC were less likely to be hotspots (OR?=?0.48, IC95%: 0.33-0.68). The association between rainfall and hotspot status was non-linear and depended on both vegetation type and amount of rainfall. The association between village location in the study area and hotspot status was also shown. CONCLUSION: In our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. By taking into consideration the environmental and meteorological characteristics common to all hotspots, monitoring of these factors could lead targeted public health interventions at the local level. Moreover, spatial hotspots and foci of malaria persisting during LTPs need to be further addressed. TRIAL REGISTRATION: The data used in this work were obtained from a clinical trial registered on July 10, 2008 at www.clinicaltrials.gov under NCT00712374.
Hand, Foot, and Mouth Disease (HFMD) is a common and widespread infectious disease. Previous studies have presented evidence that climate factors, including the monthly averages of temperature, relative humidity, air pressure, wind speed and Cumulative Risk (CR) all have a strong influence on the transmission of HFMD. In this paper, the monthly time-lag geographically- weighted regression model was constructed to investigate the spatiotemporal variations of effect of climate factors on HFMD occurrence in Inner Mongolia Autonomous Region, China. From the spatial and temporal perspectives, the spatial and temporal variations of effect of climate factors on HFMD incidence are described respectively. The results indicate that the effect of climate factors on HFMD incidence shows very different spatial patterns and time trends. The findings may provide not only an indepth understanding of spatiotemporal variation patterns of the effect of climate factors on HFMD occurrence, but also provide helpful evidence for making measures of HFMD prevention and control and implementing appropriate public health interventions at the county level in different seasons.
BACKGROUND: Human brucellosis imposes a heavy burden on the health and economy of endemic regions. Since 2011, China has reported at least 35,000 human brucellosis cases annually, with more than 90% of these cases reported in the northern. Given the alarmingly high incidence and variation in the geographical distribution of human brucellosis cases, there is an urgent need to decipher the causes of such variation in geographical distribution. METHOD: We conducted a retrospective epidemiological study in Shaanxi Province from January 1, 2005 to December 31, 2018 to investigate the association between meteorological factors and transmission of human brucellosis according to differences in geographical distribution and seasonal fluctuation in northwestern China for the first time. RESULTS: Human brucellosis cases were mainly distributed in the Shaanbei upland plateau before 2008 and then slowly extended towards the southern region with significant seasonal fluctuation. The results of quasi-Poisson generalized additive mixed model (GAMM) indicated that air temperature, sunshine duration, rainfall, relative humidity, and evaporation with maximum lag time within 7 months played crucial roles in the transmission of human brucellosis with seasonal fluctuation. Compared with the Shaanbei upland plateau, Guanzhong basin had more obvious fluctuations in the occurrence of human brucellosis due to changes in meteorological factors. Additionally, the established GAMM model showed high accuracy in predicting the occurrence of human brucellosis based on the meteorological factors. CONCLUSION: These findings may be used to predict the seasonal fluctuations of human brucellosis and to develop reliable and cost-effective prevention strategies in Shaanxi Province and other areas with similar environmental conditions.
Fecal coliform bacteria are a key indicator of human health risks; however, the spatiotemporal variability and key influencing factors of river fecal coliform have yet to be explored in a rural-suburban-urban watershed with multiple land uses. In this study, the fecal coliform concentrations in 21 river sections were monitored for 20 months, and 441 samples were analyzed. Multivariable regressions were used to evaluate the spatiotemporal dynamics of fecal coliform. The results showed that spatial differences were mainly dominated by urbanization level, and environmental factors could explain the temporal dynamics of fecal coliform in different urban patterns except in areas with high urbanization levels. Reducing suspended solids is a direct way to manage fecal coliform in the Beiyun River when the natural factors are difficulty to change, such as temperature and solar radiation. The export of fecal coliform from urban areas showed a quick and sensitive response to rainfall events and increased dozens of times in the short term. Landscape patterns, such as the fragmentation of impervious surfaces and the overall landscape, were identified as key factors influencing urban non-point source bacteria. The results obtained from this study will provide insight into the management of river fecal pollution.
Background: despite the increase in malaria control and elimination efforts, weather patterns and ecological factors continue to serve as important drivers of malaria transmission dynamics. This study examined the statistical relationship between weather variables and malaria incidence in Abuja, Nigeria. Methodology/Principal Findings: monthly data on malaria incidence and weather variables were collected in Abuja from the year 2000 to 2013. The analysis of count outcomes was based on generalized linear models, while Pearson correlation analysis was undertaken at the bivariate level. The results showed more malaria incidence in the months with the highest rainfall recorded (June-August). Based on the negative binomial model, every unit increase in humidity corresponds to about 1.010 (95% confidence interval (CI), 1.005-1.015) times increase in malaria cases while the odds of having malaria decreases by 5.8% for every extra unit increase in temperature: 0.942 (95% CI, 0.928-0.956). At lag 1 month, there was a significant positive effect of rainfall on malaria incidence while at lag 4, temperature and humidity had significant influences. Conclusions: malaria remains a widespread infectious disease among the local subjects in the study area. Relative humidity was identified as one of the factors that influence a malaria epidemic at lag 0 while the biggest significant influence of temperature was observed at lag 4. Therefore, emphasis should be given to vector control activities and to create public health awareness on the proper usage of intervention measures such as indoor residual sprays to reduce the epidemic especially during peak periods with suitable weather conditions.
Previous research has associated snowfall with risk of myocardial infarction (MI). Most studies have been conducted in regions with harsh winters; it remains unclear whether snowfall is associated with risk of MI in regions with milder or more varied climates. A case-crossover design was used to investigate the association between snowfall and death from MI in British Columbia, Canada. Deaths from MI among British Columbia residents between October 15 and March 31 from 2009 to 2017 were identified. The day of each death from MI was treated as the case day, and each case day was matched to control days drawn from the same day of the week during the same month. Daily snowfall amount was assigned to case and control days at the residential address, using weather stations within 15 km of the residence and 100 m in elevation. In total, 3,300 MI case days were matched to 10,441 control days. Compared with days that had no snowfall, odds of death from MI increased 34% (95% confidence interval: 0%, 80%) on days with heavy snowfall (?5 cm). In stratified analysis of deaths from MI as a function of both maximum temperature and snowfall, risk was significantly increased on snowfall days when the temperature was warmer.
Wildfires constitute a serious threat for both the environment and human well-being. The US fire policy aims to tackle this problem, devoting a sizeable amount of resources and resorting extensively to fire suppression strategies. The theoretical literature has established a link between climate conditions and wildfire incidence. Using state-level data from 2002 to 2013 for the USA, this work proposes a wildfire incidence indicator and runs a generalized spatial ordered probit model in order to test the findings of the previous literature empirically. Moreover, this article investigates the extent of spatial spillovers in the climatic covariates. The results highlight a significant impact of precipitation and temperature on fire incidence and provide some evidence of the role of spatial spillovers. In particular, transitions from lower to higher wildfire incidence levels are significantly encouraged by increases in local temperature and significantly discouraged by increases in both local precipitation and lagged precipitation. The present analysis complements the recent literature, confirming the previous findings with a solid empirical investigation and offering a policy-oriented picture of wildfire risks all over the USA.
Dengue is an important emerging vector-borne disease in Bhutan. This study aimed to quantify the spatial and temporal patterns of dengue and their relationship to environmental factors in dengue-affected areas at the sub-district level. A multivariate zero-inflated Poisson regression model was developed using a Bayesian framework with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure. The posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. A total of 708 dengue cases were notified through national surveillance between January 2016 and June 2019. Individuals aged ?14 years were found to be 53% (95% CrI: 42%, 62%) less likely to have dengue infection than those aged >14 years. Dengue cases increased by 63% (95% CrI: 49%, 77%) for a 1°C increase in maximum temperature, and decreased by 48% (95% CrI: 25%, 64%) for a one-unit increase in normalized difference vegetation index (NDVI). There was significant residual spatial clustering after accounting for climate and environmental variables. The temporal trend was significantly higher than the national average in eastern sub-districts. The findings highlight the impact of climate and environmental variables on dengue transmission and suggests prioritizing high-risk areas for control strategies.
Optimise control strategies of infectious diseases, identify factors that favour the circulation of pathogens, and propose risk maps are crucial challenges for global health. Ecological niche modelling, once relying on an adequate framework and environmental descriptors can be a helpful tool for such purposes. Despite the existence of a vaccine, yellow fever (YF) is still a public health issue. Brazil faced massive sylvatic YF outbreaks from the end of 2016 up to mid-2018, but cases in human and non-human primates have been recorded until the beginning of 2020. Here we used both human and monkey confirmed YF cases from two epidemic periods (2016/2017 and 2017/2018) to describe the spatial distribution of the cases and explore how biotic and abiotic factors drive their occurrence. The distribution of YF cases largely overlaps for humans and monkeys, and a contraction of the spatial extent associated with a southward displacement is observed during the second period of the epidemics. More contributive variables to the spatiotemporal heterogeneity of cases were related to biotic factors (mammal richness), abiotic factors (temperature and precipitation), and some human-related variables (population density, human footprint, and human vaccination coverage). Both projections of the most favourable conditions showed similar trends with a contraction of the more at-risk areas. Once extrapolated at a large scale, the Amazon basin remains at lower risk, although surrounding forest regions and notably the North-West region, would face a higher risk. Spatial projections of infectious diseases often relied on climatic variables only; here for both models, we instead highlighted the importance of considering local biotic conditions, hosts vulnerability, social and epidemiological factors to run the spatial risk analysis correctly: all YF cases occurring later on, in 2019 and 2020, were observed in the predicted at-risk areas.
The lower Brahmaputra River in Bangladesh and Northeast India often floods during the monsoon season, with catastrophic consequences for people throughout the region. While most climate models predict an intensified monsoon and increase in flood risk with warming, robust baseline estimates of natural climate variability in the basin are limited by the short observational record. Here we use a new seven-century (1309-2004 C.E) tree-ring reconstruction of monsoon season Brahmaputra discharge to demonstrate that the early instrumental period (1956-1986 C.E.) ranks amongst the driest of the past seven centuries (13(th) percentile). Further, flood hazard inferred from the recurrence frequency of high discharge years is severely underestimated by 24-38% in the instrumental record compared to previous centuries and climate model projections. A focus on only recent observations will therefore be insufficient to accurately characterise flood hazard risk in the region, both in the context of natural variability and climate change.
BACKGROUND: Numerous studies have demonstrated the potential association between rainfall and hand, foot and mouth disease (HFMD), but the results are inconsistent. This study aimed to quantify the relationship between rainfall and HFMD based on a multicity study and explore the potential sources of spatial heterogeneity. METHODS: We retrieved the daily counts of childhood HFMD and the meteorological variables of the 143 cities in mainland China between 2009 and 2014. A common time series regression model was applied to quantify the association between rainfall and HFMD for each of the 143 cities. Then, we adopted the meta-regression model to pool the city-specific estimates and explore the sources of heterogeneity by incorporating city-specific characteristics. RESULTS: The overall pooled estimation suggested a nonlinear exposure-response relationship between rainfall and HFMD. Once rainfall exceeded 15?mm, the HFMD risk stopped increasing linearly and began to plateau with the excessive risk ratio (ERR) peaking at 21?mm of rainfall (ERR?=?3.46, 95% CI: 2.05, 4.88). We also found significant heterogeneity in the rainfall-HFMD relationships (I(2) =?52.75%, P
BACKGROUND: Acute appendicitis represents an extremely common surgical emergency, yet its aetiology remains uncertain. A multifactorial understanding of its causation has emerged along with increasing evidence of seasonal variation. This study seeks to find evidence for such a circannual trend within the United Kingdom (UK), and further assess key meteorological indicators which may be causative of any such variation. METHODS: The patient records of a region health body in the North East of England were retrospectively assessed over a 7-year period. The incident cases of acute appendicitis were recorded and averaged by month before undergoing statistical analysis for variation and correlation with average temperature, sunlight hours, and rainfall. RESULTS: The incidence of acute appendicitis revealed significant seasonal variation with only 38 incident cases in the months of January compared to 73 in July, a 92.1% increase. Only a weak correlation was seen between incidence and average sunlight hours/rainfall, however a significant, positive correlation was found between incidence and average temperature (r?=?0.58, p?=?0.048). CONCLUSION: Compelling evidence is found to support the existence of a circannual trend for acute appendicitis. Data suggests a seasonal peak in the month of July, accompanied by a low in January, a finding that develops the understanding of this trend from previously equivocal research in the UK. A clear correlation is also established between the incidence of acute appendicitis and average temperature. The 92.1% increase between the coolest and warmest months suggests a greater magnitude for this as a risk factor than has previously been shown.
Hand, foot, and mouth disease (HFMD) is a common infectious disease in the Asia-Pacific region that primarily affects children younger than 5 years. Previous studies have confirmed that the seasonal transmission of this disease is strongly related to meteorological factors, but the results are not consistent. In addition, the associations between weather conditions and HFMD in northwestern China have not been investigated. Therefore, we aimed to examine this issue in Xi’an, the largest city of northwestern China that has been suffering from serious HFMD epidemics. In the current study, data for HFMD and six meteorological factors were collected from 2009 to 2018. Using cross-correlation analysis, the Granger causality test, and the distributed lag nonlinear model, we estimated the quantitative relationships and exposure-lag-response effects between weekly meteorological factors and HFMD incidence among children. We found that the seasonal distribution of HFMD in Xi’an has two peaks each year and is significantly impacted by the weekly temperature, precipitation, and evaporation over an 8-week period. Higher values of temperature and evaporation had positive associations with disease transmission, whereas the association between precipitation and HFMD showed an inverted-U shape. The maximum relative risks (RRs) of HFMD for the weekly mean temperature (approximately 31.1°C), weekly cumulative evaporation (57.9 mm), and weekly cumulative precipitation (30.0 mm) were 1.56 (95% CI: 1.35-1.81), 1.40 (95% CI: 1.05-1.88), and 1.16 (95% CI: 1.11-1.70), respectively. The identified risk determinants and lag effects could provide important information for early interventions to reduce the local disease burden.
BACKGROUND: Influenza is a disease under surveillance worldwide with different seasonal patterns in temperate and tropical regions. Previous studies have conducted modeling of influenza seasonality using climate variables. This study aimed to identify potential meteorological factors that are associated with influenza seasonality in Jinan, China. METHODS: Data from three influenza sentinel hospitals and respective climate factors (average temperature, relatively humidity (RH), absolute humidity (AH), sunshine duration, accumulated rainfall and speed of wind), from 2013 to 2016, were collected. Statistical and wavelet analyses were used to explore the epidemiological characteristics of influenza virus and its potential association with climate factors. RESULTS: The dynamic of influenza was characterized by annual cycle, with remarkable winter epidemic peaks from December to February. Spearman’s correlation and wavelet coherence analysis illuminated that temperature, AH and atmospheric pressure were main influencing factors. Multiple wavelet coherence analysis showed that temperature and atmospheric pressure might be the main influencing factors of influenza virus A(H3N2) and influenza virus B, whereas temperature and AH might best shape the seasonality of influenza virus A(H1N1)pdm09. During the epidemic season, the prevalence of influenza virus lagged behind the change of temperature by 1-8 weeks and atmospheric pressure by 0.5-3 weeks for different influenza viruses. CONCLUSION: Climate factors were significantly associated with influenza seasonality in Jinan during the influenza epidemic season and the optional time for influenza vaccination is before November. These finding should be considered in influenza planning of control and prevention.
INTRODUCTION: Malaria is an infectious disease of high transmission in the Amazon region, but its dynamics and spatial distribution may vary depending on the interaction of environmental, socio-cultural, economic, political and health services factors. OBJECTIVE: To verify the existence of malaria case patterns in consonance with the fluviometric regimes in Amazon basin. METHOD: Methods of descriptive and inferential statistics were used in malaria and water level data for 35 municipalities in the Amazonas State, in the period from 2003 to 2014. RESULTS: The existence of a tendency to modulate the seasonality of malaria cases due to distinct periods of rivers flooding has been demonstrated. Differences were observed in the annual hydrological variability accompanied by different patterns of malaria cases, showing a trend of remodeling of the epidemiological profile as a function of the flood pulse. CONCLUSION: The study suggests the implementation of regional and local strategies considering the hydrological regimes of the Amazon basin, enabling municipal actions to attenuate the malaria in the Amazonas State.
BACKGROUND: Southeast Brazil has recently experienced a Yellow Fever virus (YFV) outbreak where the mosquito Haemagogus leucocelaenus was a primary vector. Climatic factors influence the abundance of mosquito vectors and arbovirus transmission. OBJECTIVES: We aimed at describing the population dynamics of Hg. leucocelaenus in a county touched by the recent YFV outbreak. METHODS: Fortnightly egg collections with ovitraps were performed from November 2012 to February 2017 in a forest in Nova Iguaçu, Rio de Janeiro, Brazil. The effects of mean temperature and rainfall on the Hg. leucocelaenus population dynamics were explored. FINDINGS: Hg. leucocelaenus eggs were continuously collected throughout the study, with a peak in the warmer months (December-March). The climatic variables had a time-lagged effect and four weeks before sampling was the best predictor for the positivity of ovitraps and total number of eggs collected. The probability of finding > 50% positive ovitraps increased when the mean temperature was above 24ºC. The number of Hg. leucocelaenus eggs expressively increase when the mean temperature and accumulated precipitation surpassed 27ºC and 100 mm, respectively, although the effect of rainfall was less pronounced. MAIN CONCLUSIONS: Monitoring population dynamics of Hg. leucocelaenus and climatic factors in YFV risk areas, especially mean temperature, may assist in developing climate-based surveillance procedures to timely strengthening prophylaxis and control.
More than 40% of the human population reside in global tropical zones despite the extreme climates that frequently approach the upper thermotolerance levels for human physical activity and societal flourishing. Many of these regions also regularly subject resident populations to extreme weather events. Australia’s tropical regions experience exceptionally high climatic variability, making it one of the world’s most challenging for human settlements. Adaptation planning, project management and health protection agencies working at local scales require localized analysis on long-term climatic trends and projections. Utility of existing large-scale analyses is constrained by climatic heterogeneity across expansive national scales. Here we track historical changes in seasonal climatic extremes for seven key population centres across Australia’s north between the periods 1911-1940 and 1988-2017 as measured against the 1961-1990 period. Shifts in daily minimum temperature (20 degrees C or more), maximum temperature (10th, 90th and 95th percentiles), trends in heatwaves (5 days or longer) and in 1- and 3-day heavy rainfall events (95th and 98th percentiles) are provided. Results indicate the greatest warming has occurred during the Dry season and in coastal locations. Rainfall extremes demonstrate a pattern of marked spatial non-uniformity. This location-centred approach to identifying shifts in climatic extremes has wide applicability for adaptation planning across diverse global climatic regions.
Vector control is one of the main aspects to reach the target of eliminating visceral leishmaniasis from Indian sub-continent as set by the World Health Organisation. Data on different aspects of vector like ecology, behaviour, population dynamics and their association with environmental factors are very important for formulating an effective vector control strategy. The present work was designed to study the species abundance and impact of environmental factors on population dynamics of vector P. argentipes in a visceral leishmaniasis endemic area of Malda district, West Bengal. Adult sand flies were collected using light traps and mouth aspirators from twelve kala-azar affected villages of Habibpur block of Malda district, on a monthly basis from January to December, 2018. Morphological and molecular methods were used for species identification. Population dynamics were assessed by man hour density and per night per trap collection. Data were analysed using SPSS software to determine the impact of environmental factors on vector population P. argentipes was found to the predominant species and prevalent throughout the year. A significantly higher number of sand flies were collected from cattle sheds than human dwellings and peri-domestic vegetation. A portion of the P. argentipes population was exophilic and exophagic as evidenced by their collection from peri-domestic vegetation. The highest population density was recorded during April to September. Population dynamics were mostly influenced by average temperature along humidity and rain fall. Resting behaviour of sand flies was not restricted to the lower portion of the wall but equally distributed throughout the wall and ceiling. Programme officials should consider management of outdoor populations of the sand flies and timings of indoor residual spray for chemical control purpose.
PURPOSE: To delineate the seasonality of acute primary angle-closure (APAC) admission in a coastal city of southern China and its association with climatic factors. METHODS: A total of 1155 Chinese subjects with principal diagnosis of APAC attack were recruited from 2012 to 2016, and their medical records were retrieved. Monthly climatic factors were obtained from the Meteorological Bureau of Shantou. Monthly and seasonal APAC admissions were compared, and its correlation with climatic factors was evaluated. RESULTS: APAC admission was higher in female subjects (75.9%) with an overall mean age of 64.7 ± 9.3 years. APAC admission was highest in summer with the peak onset in June. The peak of APAC admission for female subjects aged ? 65 years was in June, and that for> 65 years was in July. The peak of APAC admission for male subjects aged > 65 years was in August. Precipitation was positively correlated with APAC admission rate for both aged ? 65 (? = 0.415, p = 0.001) and > 65 years old (? = 0.364, p = 0.004) female subjects. In contrast, surface temperature was positively correlated with APAC admission rate for male subjects aged > 65 years (? = 0.441, p < 0.001). No climatic factor was correlated with APAC admission rate for male subjects ? 65 years. CONCLUSIONS: This study revealed the peak season of APAC admission in summer, and surface temperature and precipitation are the associated factors. Close monitoring of climate changes could help to reduce the incidence of APAC attack.
AIMS: To determine whether the neonatal and delivery outcomes of gestational diabetes vary seasonally in the context of a relatively cool temperate climate. METHODS: A retrospect cohort of 23 735 women consecutively delivering singleton, live-born term infants in a single tertiary obstetrics centre in the UK (2004-2008) was identified. A total of 985 (4.1%) met the diagnostic criteria for gestational diabetes. Additive dynamic regression models, adjusted for maternal age, BMI, parity and ethnicity, were used to compare gestational diabetes incidence and outcomes over annual cycles. Outcomes included: random plasma glucose at booking; gestational diabetes diagnosis; birth weight centile; and delivery mode. RESULTS: The incidence of gestational diabetes varied by 30% from peak incidence (October births) to lowest incidence (March births; P=0.031). Ambient temperature at time of testing (28 weeks) was strongly positively associated with diagnosis (P<0.001). Significant seasonal variation was evident in birth weight in gestational diabetes-affected pregnancies (average 54(th) centile June to September; average 60(th) centile December to March; P=0.027). Emergency Caesarean rates also showed significant seasonal variation of up to 50% (P=0.038), which was closely temporally correlated with increased birth weights. CONCLUSIONS: There is substantial seasonal variation in gestational diabetes incidence and maternal-fetal outcomes, even in a relatively cool temperate climate. The highest average birth weight and greatest risk of emergency Caesarean delivery occurs in women delivering during the spring months. Recognizing seasonal variation in neonatal and delivery outcomes provides new opportunity for individualizing approaches to managing gestational diabetes.
Background: Benign paroxysmal positional vertigo (BPPV) is the most common cause of vertigo, especially in the elderly. Several studies have revealed a possible seasonality to BPPV. However, whether the seasonality of BPPV also exists in China is unclear. The characteristics of cardio-cerebrovascular risk factors for BPPV in the cold season have not yet been investigated. Objectives: (1) To investigate the seasonality of BPPV; (2) To explore the relationship between cardio-cerebrovascular risk factors and seasonality of BPPV. Methods: A retrospective observational study was performed in Beijing Tiantan Hospital from Jan 2016 to Dec 2018. The study included 1,409 new-onset BPPV patients aged 18-88 years. The demographic data, onset time, and medical history of BPPV were collected. The meteorological data, including temperature, atmospheric pressure, rainfall, and insolation, was obtained from Beijing Meteorological service. The x (2) goodness of fit test was used to evaluate whether BPPV patients’ numbers were significantly different among different months of the year. The Spearman correlation was used to detect the correlation between numbers of BPPV patients diagnosed monthly with each climatic parameter. The chi-square test for linear-by-linear association were used to investigate the relationship between cardio-cerebrovascular risk factor and seasonality of BPPV. Results: November to next March is the top 5 months with higher BPPV patient numbers (P < 0.001). The numbers of BPPV diagnosed monthly were conversely correlated with temperature and rainfall (r = -0.736, P = 0.010; r = -0.650, P = 0.022, respectively), positively correlated with atmospheric pressure (r = 0.708, P = 0.010), but no significant correlated with insolation. BPPV in the cold season (including January, February, March, November, and December) had a higher proportion, accounting for 54.2% of all BPPV patients. Among BPPV patients with ?2, 1, and none cardio-cerebrovascular risk factors, the cold season accounted for 57.0, 56.0, 49.8%, respectively. As the number of cardio-cerebrovascular risk factors increased, the proportion of patients in the cold season of BPPV increased (P = 0.025). Conclusions: BPPV patients are seen more in the months with low temperature, low rainfall, and high atmospheric pressure. Compared with the non-cold season, BPPV patients have more risk factors for cardio-cerebrovascular diseases in the cold season.
Respiratory syncytial virus (RSV) infects young children and causes influenza-like illness. RSV circulation and prevalence differ among countries and climates. To better understand whether climate factors influence the seasonality of RSV in Thailand, we examined RSV data from children???5 years-old who presented with respiratory symptoms from January 2012-December 2018. From a total of 8,209 nasopharyngeal samples, 13.2% (1,082/8,209) was RSV-positive, of which 37.5% (406/1,082) were RSV-A and 36.4% (394/1,082) were RSV-B. The annual unimodal RSV activity from July-November overlaps with the rainy season. Association between meteorological data including monthly average temperature, relative humidity, rainfall, and wind speed for central Thailand and the incidence of RSV over 7-years was analyzed using Spearman’s rank and partial correlation. Multivariate time-series analysis with an autoregressive integrated moving average (ARIMA) model showed that RSV activity correlated positively with rainfall (r?=?0.41) and relative humidity (r?=?0.25), but negatively with mean temperature (r?=?-?0.27). The best-fitting ARIMA (1,0,0)(2,1,0)(12) model suggests that peak RSV activity lags the hottest month of the year by 4 months. Our results enable possible prediction of RSV activity based on the climate and could help to anticipate the yearly upsurge of RSV in this region.
BACKGROUND: Between 1999 and 2008 Russia experienced a flare-up of transmission of vivax malaria following its massive importation with more than 500 autochthonous cases in European Russia, the Moscow region being the most affected. The outbreak waned soon after a decrease in importation in mid-2000s and strengthening the control measures. Compared with other post-eradication epidemics in Europe this one was unprecedented by its extension and duration. METHODS: The aim of this study is to identify geographical determinants of transmission. The degree of favourability of climate for vivax malaria was assessed by measuring the sum of effective temperatures and duration of season of effective infectivity using data from 22 weather stations. For geospatial analysis, the locations of each of 405 autochthonous cases detected in Moscow region have been ascertained. A MaxEnt method was used for modelling the territorial differentiation of Moscow region according to the suitability of infection re-emergence based on the statistically valid relationships between the distribution of autochthonous cases and environmental and climatic factors. RESULTS: In 1999-2004, in the beginning of the outbreak, meteorological conditions were extremely favourable for malaria in 1999, 2001 and 2002, especially within the borders of the city of Moscow and its immediate surroundings. The greatest number of cases occurred at the northwestern periphery of the city and in the adjoining rural areas. A significant role was played by rural construction activities attracting migrant labour, vegetation density and landscape division. A cut-off altitude of 200 m was observed, though the factor of altitude did not play a significant role at lower altitudes. Most likely, the urban heat island additionally amplified malaria re-introduction. CONCLUSION: The malariogenic potential in relation to vivax malaria was high in Moscow region, albeit heterogeneous. It is in Moscow that the most favourable conditions exist for vivax malaria re-introduction in the case of a renewed importation. This recent event of large-scale re-introduction of vivax malaria in a temperate area can serve as a case study for further research.
The first documented Rift Valley hemorrhagic fever outbreak in the Arabian Peninsula occurred in northwestern Yemen and southwestern Saudi Arabia from August 2000 to September 2001. This Rift Valley fever outbreak is unique because the virus was introduced into Arabia during or after the 1997-1998 East African outbreak and before August 2000, either by wind-blown infected mosquitos or by infected animals, both from East Africa. A wet period from August 2000 into 2001 resulted in a large number of amplification vector mosquitoes, these mosquitos fed on infected animals, and the outbreak occurred. More than 1,500 people were diagnosed with the disease, at least 215 died, and widespread losses of domestic animals were reported. Using a combination of satellite data products, including 2 x 2 m digital elevation images derived from commercial satellite data, we show rainfall and potential areas of inundation or water impoundment were favorable for the 2000 outbreak. However, favorable conditions for subsequent outbreaks were present in 2007 and 2013, and very favorable conditions were also present in 2016-2018. The lack of subsequent Rift Valley fever outbreaks in this area suggests that Rift Valley fever has not been established in mosquito species in Southwest Arabia, or that strict animal import inspection and quarantine procedures, medical and veterinary surveillance, and mosquito control efforts put in place in Saudi Arabia following the 2000 outbreak have been successful. Any area with Rift Valley fever amplification vector mosquitos present is a potential outbreak area unless strict animal import inspection and quarantine proceedures are in place.
Non-point stormwater runoff is a major contamination source of receiving waterbodies. Heightened incidence of waterborne disease outbreaks related to recreational use and source water contamination is associated with extreme rainfall events. Such extreme events are predicted to increase in some regions due to climate change. Consequently, municipal separate storm sewer systems (MS4s) conveying pathogens to receiving waters are a growing public health concern. In addition, the spread of antibiotic resistance genes (ARGs) and antibiotic resistant bacteria in various environmental matrices, including urban runoff, is an emerging threat. The resistome and microbiota profile of MS4 discharges has yet to be fully characterized. To address this knowledge gap, we first analyzed the relationship between rainfall depth and intensity and E. coli densities (fecal indicator) in stormwater from four MS4 outflows in Columbus, Ohio, USA during the spring and summer of 2017. Microbial source tracking (MST) was conducted to examine major fecal contamination sources in the study sewersheds. A subset of samples was analyzed for microbial and resistome profiles using a metagenomic approach. The results showed a significant positive relationship between outflow E. coli density and rainfall intensity. MST results indicate prevalent fecal contamination from ruminant populations in the study sites (91% positive among the samples tested). Protobacteria and Actinobacteria were two dominant bacteria at a phylum level. A diverse array of ARGs and potentially pathogenic bacteria (e.g. Salmonella enterica Typhimurium), fungi (e.g. Scedosporium apiospermum), and protists (e.g. Acanthamoeba palestinensis) were found in urban stormwater outflows that discharge into adjacent streams. The most prevalent ARGs among samples were ?-lactam resistance genes and the most predominant virulence genes within bacterial community were related with Staphylococcus aureus. A comprehensive contamination profile indicates a need for sustainable strategies to manage urban stormwater runoff amid increasingly intense rainfall events to protect public and environmental health.
Aedes aegypti is the main vector of dengue, Zika, chikungunya, and yellow fever viruses. Controlling populations of vector mosquito species in urban environments is a major challenge and being able to determine what aquatic habitats should be prioritized for controlling Ae. aegypti populations is key to the development of more effective mosquito control strategies. Therefore, our objective was to leverage on the Miami-Dade County, Florida immature mosquito surveillance system based on requested by citizen complaints through 311 calls to determine what are the most important aquatic habitats in the proliferation of Ae. aegypti in Miami. We used a tobit model for Ae. aegypti larvae and pupae count data, type and count of aquatic habitats, and daily rainfall. Our results revealed that storm drains had 45% lower percentage of Ae. aegypti larvae over the total of larvae and pupae adjusted for daily rainfall when compared to tires, followed by bromeliads with 33% and garbage cans with 17%. These results are indicating that storm drains, bromeliads and garbage cans had significantly more pupae in relation to larvae when compared to tires, traditionally know as productive aquatic habitats for Ae. aegypti. Ultimately, the methodology and results from this study can be used by mosquito control agencies to identify habitats that should be prioritized in mosquito management and control actions, as well as to guide and improve policies and increase community awareness and engagement. Moreover, by targeting the most productive aquatic habitats this approach will allow the development of critical emergency outbreak responses by directing the control response efforts to the most productive aquatic habitats.
We combine data from the 2006 and 2011 Uganda Demographic and Health Surveys (UDHS) with rainfall data and two waves of the Ugandan National Household Survey (UNHS) to study patterns in child weight, as measured by weight-for-height z scores (WHZ), among 3492 rural children below age 5 in Uganda. We focus on rainfall as a nutrition driver along agriculture and disease pathways. We find a positive and significant association between crop yield and WHZ, but the magnitude of this association diminishes as we control for covariates, especially the use of productivity-enhancing agricultural inputs. We find diarrheal disease to have a negative and significant association with WHZ, and modifying effects of social and environmental factors along the disease pathway. Contemporaneous rainfall is associated with a lower likelihood of diarrheal disease in areas with excess rainfall and a higher likelihood of diarrheal disease in rainfall deficit areas. Our findings reinforce calls for targeted and situation-sensitive policies to promote child nutrition.
Global climate change makes extreme precipitation events likely to become more frequent and intense in large parts of Africa. We study the effect of rainfall shocks on intimate partner violence in sub-Saharan Africa. The analysis shows the presence of spatial autocorrelation in rainfall shocks, which compromises the exogeneity of rainfall shocks in many applications. We correct for the autocorrelation using spatial polynomials. In particular, we use three different estimation strategies. We first use the complete cross-sectional sample to analyze whether recent droughts are correlated with respondents’ experience with intimate partner violence during the last year. We then use the nine countries with repeated surveys to construct a repeated cross-section analysis at the grid level. Finally, we use event history analysis on a time series constructed from the information provided by the abused women about when the violence first took place. We find no robust evidence that droughts increase intimate partner violence. Potential explanations are that the rainfall shocks do not affect spouses’ power, or that the slow onset of the droughts allows for a calmer response to the crisis. We contribute to the wider literature on climate and conflict as many of the mechanisms, economic and psychological, that link climate to violence apply to both intimate partner violence and organized violence.
The number of dengue fever incidence and its distribution has increased considerably in recent years in Africa. However, due to inadequate research at the continental level, there is a limited understanding regarding the current and future spatial distribution of the main vector, the mosquitoAedes aegypti, and the associated dengue risk due to climate change. To fill this gap we used reported dengue fever incidences, the presence of Ae. aegypti, and bioclimatic variables in a species distribution model to assess the current and future (2050 and 2070) climatically suitable areas. High temperatures and with high moisture levels are climatically suitable for the distribution of Ae. aegypti related to dengue fever. Under the current climate scenario indicated that 15.2% of the continent is highly suitable for dengue fever outbreaks. We predict that climatically suitable areas for Ae. aegypti related to dengue fever incidences in eastern, central and western part of Africa will increase in the future and will expand further towards higher elevations. Our projections provide evidence for the changing continental threat of vector-borne diseases and can guide public health policy decisions in Africa to better prepare for and respond to future changes in dengue fever risk.
BACKGROUND: The prevalence of Acute Myocardial Infarction (AMI) varies from region to region caused by seasonal climate changes and temperature variation. This study aimed to assess the relationship between changing meteorological conditions and incidence of AMI in Iran. METHODS: This retrospective prevalence study was based on medical records of the heart center of Mazandaran Province on all patients diagnosed with AMI in Mazandaran, northern Iran between 2013 and 2015. Patients’ sex and the day, month, year and time of hospital admission were extracted from patients’ records. Moreover, the meteorological reports were gathered. RESULTS: A statistically significant difference was found between the distributions of AMI cases across 12 months of the year (P < 0.01). Fuzzy clustering analysis using 16 different climatic variables showed that March, April, and May were in the same cluster together. The other 9 months were in different clusters. CONCLUSION: Significant increase in AMI was seen in March, April and May (cold to hot weather).
Severe fever with thrombocytopenia syndrome (SFTS), a tick-borne infectious disease, is difficult to differentiate from other common febrile diseases. Clinically distinctive features and climate variates associated with tick growth can be useful predictors for SFTS. This retrospective study (2013-2019) demonstrated the role of climatic factors as predictors of SFTS and developed a clinical scoring system for SFTS using climate variables and clinical characteristics. The presence of the SFTS virus was confirmed using reverse transcription polymerase chain reaction (RT-PCR) tests. In the univariate analysis, the SFTS-positive group was significantly associated with higher mean ambient temperature and humidity compared with the SFTS-negative group (22.5 °C vs. 18.9 °C; 77.9% vs. 70.7%, all p < 0.001). In the multivariate analysis, poor oral intake (Odds ratio [OR] 5.87, 95% CI: 2.42-8.25), lymphadenopathy (OR 7.20, 95% CI: 6.24-11.76), mean ambient temperature ? 20 °C (OR 4.62, 95% CI: 1.46-10.28), absolute neutrophil count ? 2000 cells/?L (OR 8.95, 95% CI: 2.30-21.25), C-reactive protein level ? 1.2 mg/dL (OR 6.42, 95% CI: 4.02-24.21), and creatinine kinase level ? 200 IU/L (OR 5.94, 95% CI: 1.42-24.92) were significantly associated with the SFTS-positive group. This study presents the risk factors, including ambient temperature and clinical characteristics, that physicians should consider when suspecting SFTS.
Climate change is postulated to alter the distribution and abundance of species which serve as vectors for pathogens and is thus expected to affect the transmission of infectious, vector-borne diseases such as malaria. The ability to project and therefore, to mitigate the risk of potential expansion of infectious diseases requires an understanding of how vectors respond to environmental change. Here, we used an extensive dataset on the distribution of the mosquito Anopheles sacharovi, a vector of malaria parasites in Greece, southeast Europe, to build a modeling framework that allowed us to project the potential species range within the next decades. In order to account for model uncertainty, we employed a multi-model approach, combining an ensemble of diverse correlative niche models and a mechanistic model to project the potential expansion of species distribution and to delineate hotspots of potential malaria risk areas. The performance of the models was evaluated using official records on autochthonous malaria incidents. Our projections demonstrated a gradual increase in the potential range of the vector distribution and thus, in the malaria receptive areas over time. Linking the model outputs with human population inhabiting the study region, we found that population at risk increases, relative to the baseline period. The methodological framework proposed and applied here, offers a solid basis for a climate change impact assessment on malaria risk, facilitating informed decision making at national and regional scales.
Identifying Aedes aegypti breeding hotspots in urban areas is crucial for the design of effective vector control strategies. Remote sensing techniques offer valuable tools for mapping habitat suitability. In this study, we evaluated the association between urban landscape, thermal features, and mosquito infestations. Entomological surveys were conducted between 2016 and 2019 in Vila Toninho, a neighborhood of São José do Rio Preto, São Paulo, Brazil, in which the numbers of adult female Ae. aegypti were recorded monthly and grouped by season for three years. We used data from 2016 to 2018 to build the model and data from summer of 2019 to validate it. WorldView-3 satellite images were used to extract land cover classes, and land surface temperature data were obtained using the Landsat-8 Thermal Infrared Sensor (TIRS). A multilevel negative binomial model was fitted to the data, which showed that the winter season has the greatest influence on decreases in mosquito abundance. Green areas and pavements were negatively associated, and a higher cover of asbestos roofs and exposed soil was positively associated with the presence of adult females. These features are related to socio-economic factors but also provide favorable breeding conditions for mosquitos. The application of remote sensing technologies has significant potential for optimizing vector control strategies, future mosquito suppression, and outbreak prediction.
Rivers are representative of the overall contamination found in their catchment area. Contaminant concentrations in watercourses depend on numerous factors including land use and rainfall events. Globally, in Mediterranean regions, rainstorms are at the origin of fluvial multipollution phenomena as a result of Combined Sewer Overflows (CSOs) and floods. Large loads of urban-associated microorganisms, including faecal bacteria, are released from CSOs which place public health – as well as ecosystems – at risk. The impacts of freshwater contamination on river ecosystems have not yet been adequately addressed, as is the case for the release of pollutant mixtures linked to extreme weather events. In this context, microbial communities provide critical ecosystem services as they are the only biological compartment capable of degrading or transforming pollutants. Through the use of 16S rRNA gene metabarcoding of environmental DNA at different seasons and during a flood event in a typical Mediterranean coastal river, we show that the impacts of multipollution phenomena on structural shifts in the particle-attached riverine bacteriome were greater than those of seasonality. Key players were identified via multivariate statistical modelling combined with network module eigengene analysis. These included species highly resistant to pollutants as well as pathogens. Their rapid response to contaminant mixtures makes them ideal candidates as potential early biosignatures of multipollution stress. Multiple resistance gene transfer is likely enhanced with drastic consequences for the environment and human-health, particularly in a scenario of intensification of extreme hydrological events.
Over the years, Jamaica has experienced sporadic cases of dengue fever. Even though the island is vulnerable to dengue, there is paucity in the spatio-temporal analysis of the disease using Geographic Information Systems (GIS) and remote sensing tools. Further, access to time series dengue data at the community level is a major challenge on the island. This study therefore applies the Water-Associated Disease Index (WADI) framework to analyze vulnerability to dengue in Jamaica based on past, current and future climate change conditions using three scenarios: (1) WorldClim rainfall and temperature dataset from 1970 to 2000; (2) Climate Hazard Group InfraRed Precipitation with Station data (CHIRPS) rainfall and land surface temperature (LST) as proxy for air temperature from the Moderate Resolution Imaging Spectroradiometer (MODIS) for the period 2002 to 2016, and (3) maximum temperature and rainfall under the Representative Concentration Pathway (RCP) 8.5 climate change scenario for 2030 downscaled at 25 km based on the Regional Climate Model, RegCM4.3.5. Although vulnerability to dengue varies spatially and temporally, a higher vulnerability was depicted in urban areas in comparison to rural areas. The results also demonstrate the possibility for expansion in the geographical range of dengue in higher altitudes under climate change conditions based on scenario 3. This study provides an insight into the use of data with different temporal and spatial resolution in the analysis of dengue vulnerability.
Extreme floods pose multiple direct and indirect health risks. These risks include contamination of water, food, and the environment, often causing outbreaks of diarrheal disease. Evidence regarding the effects of flooding on individual diarrhea-causing pathogens is limited, but is urgently needed in order to plan and implement interventions and prioritize resources before climate-related disasters strike. This study applied a causal inference approach to data from a multisite study that deployed broadly inclusive diagnostics for numerous high-burden common enteropathogens. Relative risks (RRs) of infection with each pathogen during a flooding disaster that occurred at one of the sites-Loreto, Peru-were calculated from generalized linear models using a comparative interrupted time series framework with the other sites as a comparison group and adjusting for background seasonality. During the early period of the flood, increased risk of heat-stable enterotoxigenic E. coli (ST-ETEC) was identified (RR = 1.73 [1.10, 2.71]) along with a decreased risk of enteric adenovirus (RR = 0.36 [0.23, 0.58]). During the later period of the flood, sharp increases in the risk of rotavirus (RR = 5.30 [2.70, 10.40]) and sapovirus (RR = 2.47 [1.79, 3.41]) were observed, in addition to increases in transmission of Shigella spp. (RR = 2.86 [1.81, 4.52]) and Campylobacter spp. (RR = 1.41 (1.01, 1.07). Genotype-specific exploratory analysis reveals that the rise in rotavirus transmission during the flood was likely due to the introduction of a locally atypical, non-vaccine (G2P[4]) strain of the virus. Policy-makers should target interventions towards these pathogens-including vaccines as they become available-in settings where vulnerability to flooding is high as part of disaster preparedness strategies, while investments in radical, transformative, community-wide, and locally-tailored water and sanitation interventions are also needed.
The Phyllosoma complex is a Triatominae (Hemiptera: Reduviidae) group of medical importance involved in Trypanosoma cruzi (Kinetoplastida: Trypanosomatidae) transmission. Most of the members of this group are endemic and sympatric species with distribution in Mexico and the southern U.S.A. We employed MaxEnt to construct ecological niche models of nine species of Triatominae to test three hypothesis: (a) whether species with a broad climatic niche breadth occupy a broader geographical range than species with a narrow climatic breadth, (b) whether species with broad distribution present high degree of climatic fragmentation/isolation, which was tested through landscape metrics; and (c) whether the species share the same climatic niche space (niche conservatism) considered through an equivalence test implemented in ENMtools. Overall, our results suggest that the geographical distribution of this complex is influenced mainly by temperature seasonality where all suitable areas are places of current and potential transmission of T. cruzi. Niche breadth in the Phyllosoma complex is associated with the geographical distribution range, and the geographical range affects the climatic connectivity. We found no strong evidence of niche climatic divergence in members of this complex. We discuss the epidemiological implications of these results.
This study aims to assess the physical and social vulnerability of floods, which occurred in the year 2015 in Adyar Basin of Chennai, Tamil Nadu. Thematic layers, such as rainfall, land use land cover (LULC), drainage density, slope, soil, and roads per watershed, were prepared and assigned the ranks using rank sum method. The knowledge based weighted indexed overlay analysis was employed based on causative factors, to prepare vulnerability map of the Adyar Basin. This research would help the community to find the vulnerability based on multi criteria analysis, by considering certain indicators like household, residential properties of the people living in Adyar basin. This engineering geological study, can play a vital role in comparing the physical and social vulnerability along with the real time vulnerability to ensure public safety, cost-effective solution for planning mitigation measures and preparedness in flood prone areas.
Background: Toxoplasma gondii is a parasite of worldwide importance but its burden in indigenous communities remains unclear. In French Guiana, atypical strains of T. gondii originating from a complex rainforest cycle involving wild felids have been linked to severe infections in humans. These cases of Amazonian toxoplasmosis are sporadic and outbreaks are rarely described. We report on the investigation of an outbreak of acute toxoplasmosis in a remote Amerindian village. We discuss the causes and consequences of this emergence. Methods: In May 2017, during the rainy season and following an episode of flooding, four simultaneous cases of acute toxoplasmosis were serologically confirmed in two families living the village. Other non-diagnosed cases were then actively screened by a medical team along with epidemiological investigations. Inhabitants from nine households were tested for T. gondii antibodies and parasite DNA by PCR when appropriate. Samples of water, cat feces and cat rectal swabs, soil, and meat were tested for T. gondii DNA by PCR. Positive PCR samples with sufficient DNA amounts were genotyped using 15 microsatellite markers. Results: Between early May and early July 2017, out of 54 tested inhabitants, 20 cases were serologically confirmed. A fetus infected at gestational week 10 died but other cases were mild. Four patients tested positive for parasite DNA and two identical strains belonging to an atypical genotype could be isolated from unrelated patients. While domestic cats had recently appeared in the vicinity, most families drank water from unsafe sources. Parasite DNA was recovered from one water sample and nine soil samples. Three meat samples tested positive, including wild and industrial meat. Conclusions: The emergence of toxoplasmosis in such a community living in close contact with the Amazon rainforest is probably multifactorial. Sedentary settlements have been built in the last few decades without providing safe water sources, increasing the risk of parasite circulation in cases of dangerous new habits such as cat domestication. Public health actions should be implemented in these communities such as safe water supply, health recommendations, and epidemiological surveillance of acute toxoplasmosis. A “One Health” strategy of research involving medical anthropology, veterinary medicine, and public health needs to be pursued for a better understanding of the transmission routes and the emergence of this zoonosis.
Global climate change is an environmental hazard with significant public health impacts. High-impact weather events including periods of extreme temperature or extreme precipitation are frequently associated with adverse effects on human health. This study evaluates the impact of extreme weather events on injuries across New Hampshire. A set of five daily extreme weather metrics (EWMs) was analyzed: daily maximum temperature <= 32 degrees F (0 degrees C), daily maximum temperature >= 90 degrees F (32 degrees C), daily maximum temperature >= 95 degrees F (35 degrees C), daily precipitation >= 1 ”, and daily precipitation >= 2 ”. Exposure to these EWMs was defined by linking the population within 10 miles of nine weather stations distributed across the state. Injuries were defined as hospitalizations categorized as: all-cause injury, vehicle accidents, accidental falls, accidents due to natural and environmental causes (including excessive heat, excessive cold, exposure due to weather conditions, lightning, and storms and floods), accidental drowning, and carbon monoxide poisoning. The associations between all injury categories and all EWMs as well as daily maximum temperature and daily precipitation were explored. A quasi-Poisson regression model was used to evaluate the relationship between the four strongest exposure-outcome pairs linking maximum temperature to all-cause injury-, vehicle accident-, accidental fall-, and heat-related hospital visits. Results indicate that daily maximum temperature (>90 degrees F) was most strongly associated with heat-related hospital visits and was also associated with all-cause injury-related hospital visits. Future work should include further analysis of cold weather metrics and incorporate these findings into public health planning and response efforts.
Mountains are characterized by their specificities such as fragility, marginality and remoteness. They are prone to various hazards such as drought, flood, forest fire, landslide and therefore physical, ecological and social systems of the mountains are at risk. Climate change adds to intensifying the magnitude of multi-hazard risk in mountains. The present study attempts to evaluate risk induced by multi-hazard and climate change in the Indian Himalayan Region (IHR) using the Intergovernmental Panel on Climate Change (IPCC) framework. The proposed multi-hazard risk index was based on indicators from a broader domain and applied on 109 administrative districts of IHR. Exposure, sensitivity, adaptive capacity, and coping capacity were defined using comprehensive and sub-regional indicators identified through inductive and deductive approaches. The result showed that the differential risks among the districts of IHR were governed by the multiplicity of the factor such as demography, amenities, natural capital, partnership, technology and spatial specificities of the districts. The result highlighted the need of inclusion of spatial specificities for the risk mitigation in the IHR and therefore a Mountain Specific Risk Management Framework (MSMRMF) was proposed for sustaining the mountainous communities. The proposed MSMRMF contained two broad components as risk assessment and risk addressal. The framework detailed the risk mitigation and coping strategies (based on adjustment of internal and external strengths) for addressing risks. Risk mitigation was proposed to achieved through habitation resilience, natural capital enhancement, external partnerships, climate change adaptation, and technological interventions. The framework would provide an insight of risk and risk management strategies for the multi-hazard prone mountain regions for the sustainable development under the global change.
In this study, we examine the concepts of spatial dependence and spatial heterogeneity in the effect of macro-level and micro-level factors on stunting among children aged under five in Uganda. We conducted a cross-sectional analysis of 3624 Ugandan children aged under five, using data from the 2016 Ugandan Demographic and Health Survey. Multilevel mixed-effect analysis, spatial regression methods and multi-scale geographically weight regression (MGWR) analysis were employed to examine the association between our predictors and stunting as well as to analyse spatial dependence and variability in the association. Approximately 28% of children were stunted. In the multilevel analysis, the effect of drought, diurnal temperature and livestock per km(2) on stunting was modified by child, parent and household factors. Likewise, the contextual factors had a modifiable effect on the association between child’s sex, mother’s education and stunting. The results of the spatial regression models indicate a significant spatial error dependence in the residuals. The MGWR suggests rainfall and diurnal temperature had spatial varying associations with stunting. The spatial heterogeneity of rainfall and diurnal temperature as predictors of stunting suggest some areas in Uganda might be more sensitive to variability in these climatic conditions in relation to stunting than others.
Reported dengue fever cases are increasing day by day in the world as well as in Sri Lanka. Model, Prediction and Control are three major parts of the process of analysis of the dengue incidence which leads to reduce the burden of the dengue. There is an increasing trend in the applications and developments in interval-valued data analysis over recent years. Particularly, under regressions there have being developed various techniques to handle interval-valued dependent and independent variables. Representation of data as intervals is very much useful to capture uncertainty and missing details associated with variables. Further, the predictions in intervals suit well when the situations of exact forecasts may not necessary. In this study interval-valued dengue data with interval-valued minimum temperature, maximum temperature and rainfall from 2009 to 2015 in the Colombo district, Sri Lanka were model using three interval valued regression procedures, namely, Center Method (CM), Center and Range Method (CRM) and Constrained Center and Range Method (CCRM). Predicted dengue cases in a range is particularly important because actions taking towards controlling the dengue do not depend on exact number but on magnitude of the values represent in the interval. Data in the year 2016 used for the validation of the models which is developed under three methods. Root of the mean square error, coefficient of determination as well as square root of variance of the models were used to select the best procedure to predict dengue cases. Among the three regression procedures both CRM and CCRM perform well in predicting monthly dengue cases in Colombo.
Although previous studies have reported that meteorological factors might affect the risk of Japanese encephalitis (JE), the relationship between meteorological factors and JE remains unclear. This study aimed to evaluate the relationship between meteorological factors and JE and identify the threshold temperature. Daily meteorological data and JE surveillance data in Dazhou, Sichuan, were collected for the study period from 2005 to 2012 (restricting to May-October because of the seasonal distribution of JE). A distributed lag nonlinear model was used to analyze the lagged and cumulative effect of daily average temperature and daily rainfall on JE transmission. A total of 622 JE cases were reported over the study period. We found JE was positively associated with daily average temperature and daily rainfall with a 25-day lag and 30-day lag, respectively. The threshold value of the daily average temperature is 20°C. Each 5°C increase over the threshold would lead to a 13% (95% CI: 1-17.3%) increase in JE. Using 0 mm as the reference, a daily rainfall of 100 mm would lead to a 132% (95% CI: 73-311%) increase in the risk of JE. Japanese encephalitis is climate-sensitive; meteorological factors should be taken into account for the future prevention and control measure making, especially in a warm and rainy weather condition.
To examine the effects of temperature on the daily cases of hand, foot, and mouth disease (HFMD).Data on the daily cases of HFMD in Lanzhou from 2008 to 2015 were obtained, and meteorological data from the same period were collected. A distributed lag nonlinear model was fitted to reveal the relationship between the daily mean temperature and the daily cases of HFMD.From 2008 to 2015, 25,644 cases were reported, of which children under 5 years of age accounted for 78.68% of cases. The highest peak of HFMD cases was usually reported between April to July each year. An inverse V-shaped relationship was observed between daily mean temperature and HFMD cases; a temperature of 18°C was associated with a maximum risk of HFMD. The relative risk (RR) was 1.57 (95% confidence interval: 1.23-1.23), and boys and children aged 3 to 5 years were populations with the highest risk. The cumulative risks of high temperature (20.2°C and 25.2°C) in the total, age-specific, and gender-specific groups peaked on lag 14 days; RR was higher in girls than in boys and in children aged 1 to 2 years than in other age groups. However, the effects of low temperature (-5.3°C, 2.0°C, and 12.8°C) were not significant for both gender-specific and age-specific patients.High temperature may increase the risk of HFMD, and boys and children aged 3 to 5 years were at higher risks on lag 0 day; however, the cumulative risks in girls and children aged 1 to 2 years increased with the increasing number of lag days.
Influenza usually breaks out seasonally in temperate regions, especially in winter, infection rates and mortality rates of influenza increase significantly, which means that dry air and cold temperatures accelerate the spread of influenza viruses. However, the meteorological factors that lead to seasonal influenza outbreaks and how these meteorological factors play a decisive role in influenza transmission remain unclear. During the epidemic of infectious diseases, the neglect of unreported cases leads to an underestimation of infection rates and basic reproduction number. In this paper, we propose a new non-autonomous periodic differential equation model with meteorological factors including unreported cases. First, the basic reproduction number is obtained and the global asymptotic stability of the disease-free periodic solution is proved. Furthermore, the existence of periodic solutions and the uniformly persistence of the model are demonstrated. Second, the best-fit parameter values in our model are identified by the MCMC algorithm on the basis of the influenza data in Gansu province, China. We also estimate that the basic reproduction number is 1.2288 (95% CI:(1.2287, 1.2289)). Then, to determine the key parameters of the model, uncertainty and sensitivity analysis are explored. Finally, our results show that influenza is more likely to spread in low temperature, low humidity and low precipitation environments. Temperature is a more important factor than relative humidity and precipitation during the influenza epidemic. In addition, our results also show that there are far more unreported cases than reported cases.
BACKGROUND: More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission. METHODS: We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1?km?×?1?km spatial resolution and a weekly temporal resolution. RESULTS: Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions. CONCLUSIONS: Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.
This study statistically identified the association of remotely sensed environmental factors, such as Land Surface Temperature (LST), Night Time Light (NTL), rainfall, the Normalised Difference Vegetation Index (NDVI) and elevation with the incidence of leptospirosis in Thailand based on the nationwide 7,495 confirmed cases reported during 2013-2015. This work also established prediction models based on empirical findings. Panel regression models with random-effect and fixed-effect specifications were used to investigate the association between the remotely sensed environmental factors and the leptospirosis incidence. The Local Indicators of Spatial Association (LISA) statistics were also applied to detect the spatial patterns of leptospirosis and similar results were found (the R2 values of the random-effect and fixed-effect models were 0.3686 and 0.3684, respectively). The outcome thus indicates that remotely sensed environmental factors possess statistically significant contribution in predicting this disease. The highest association in 3 years was observed in LST (random- effect coefficient = -9.787, P<0.001; fixed-effect coefficient = -10.340, P=0.005) followed by rainfall (random-effect coefficient = 1.353, P<0.001; fixed-effect coefficient = 1.347, P<0.001) and NTL density (random-effect coefficient = -0.569, P=0.004; fixed-effect coefficient = -0.564, P=0.001). All results obtained from the bivariate LISA statistics indicated the localised associations between remotely sensed environmental factors and the incidence of leptospirosis. Particularly, LISA’s results showed that the border provinces in the northeast, the northern and the southern regions displayed clusters of high leptospirosis incidence. All obtained outcomes thus show that remotely sensed environmental factors can be applied to panel regression models for incidence prediction, and these indicators can also identify the spatial concentration of leptospirosis in Thailand.
BACKGROUND: India is expected to experience an increase in the frequency and intensity of extreme weather events in the coming decades, which poses serious risks to human health and wellbeing in the country. OBJECTIVE: This paper aims to shed light on the possible detrimental effects of monsoon weather shocks on childhood undernutrition in India using the Demographic and Health Survey 2015-16, in combination with geo-referenced climate data. METHODS: Undernutrition is captured through measures of height-for-age, weight-for-height, stunting and wasting among children aged 0-59 months. The standardised precipitation and evapotranspiration index (SPEI) is used to measure climatic conditions during critical periods of child development. RESULTS: The results of a multivariate logistic regression model show that climate anomalies experienced in utero and during infancy are associated with an increased risk of child undernutrition; exposure to excessive monsoon precipitation during these early periods of life elevates the risk of stunting, particularly for children in the tropical wet and humid sub-tropical regions. In contrast, the risk of stunting is reduced for children residing in the mountainous areas who have experienced excessive monsoon precipitation during infancy. The evidence on the short-term effects of climate shocks on wasting is inconclusive. We additionally show that excessive precipitation, particularly during the monsoon season, is associated with an increased risk of contracting diarrhoea among children under five. Diseases transmitted through water, such as diarrhoea, could be one important channel through which excessive rainfall increases the risk of stunting. CONCLUSIONS: We find a positive association between childhood undernutrition and exposure to excessive monsoon precipitation in India. Pronounced differences across climate zones are found. The findings of the present analysis warn of the urgent need to provide health assistance to children in flood-prone areas.
Purpose The purpose of this paper is to examine the role of high intensity precipitation events in increasing the vulnerability to floods in Mediterranean Spain. Precipitation intensity in this area appears to have augmented in the last two decades in association with warming trends of the Mediterranean Sea. At the same time, intense urbanization processes, occupying and transforming flood prone land, have produced an important increase in exposure. The main objective is to assess whether higher intensity precipitation and changing patterns in exposure aggravate vulnerability to floods. Design/methodology/approach In this paper, vulnerability is understood as the result of the interrelationships between exposure, sensitivity, impacts and adaptive capacity. Consequently, methods used involved the compilation and analysis of published and unpublished precipitation data, population and land use data, data on insurance claims, and media sources related to those variables. Findings Changes toward episodes of more intense precipitation in the expanding urban areas of Mediterranean Spain increase exposure but not necessarily vulnerability, at least in terms of human deaths. However, adaptative capacity needs to be formulated. Actions that attempt to absorb and eventually reuse flood flows (as the flood park in Alicante) appear to be more effective than traditional hydraulic solutions (as in Majorca). Originality/value The paper provides a systematic and coherent approach to vulnerability analysis taking into account the changing dynamics of its components. Especially, it signals the limits of current adaptive approaches to flooding and advocates for changes toward a more circular and less linear approach to urban drainage.
Heat waves are extreme climate events that have the potential to cause immense stress on human health, agriculture, and energy systems, so understanding the processes leading to their onset is crucial. There is no single accepted definition for heat waves, but they are generally described as a sustained amount of time over which temperature exceeds a local threshold. Multiple different temperature variables are potentially relevant, because high values of both daily maximum and minimum temperatures can be detrimental to human health. In this study, we focus explicitly on the different mechanisms associated with summertime heat waves manifested during daytime hours versus nighttime hours over the contiguous United States. Heat waves are examined using the National Aeronautics and Space Administration Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2). Over 1980-2018, the increase in the number of heat-wave days per summer was generally stronger for nighttime heat-wave days than for daytime heat-wave days, with localized regions of significant positive trends. Processes linked with daytime and nighttime heat waves are identified through composite analysis of precipitation, soil moisture, clouds, humidity, and fluxes of heat and moisture. Daytime heat waves are associated with dry conditions, reduced cloud cover, and increased sensible heating. Mechanisms leading to nighttime heat waves differ regionally across the United States, but they are typically associated with increased clouds, humidity, and/or low-level temperature advection. In the midwestern United States, enhanced moisture is transported from the Gulf of Mexico during nighttime heat waves.
Meteorological drivers are known to affect transmissibility of respiratory viruses including respiratory syncytial virus (RSV), but there are few studies quantifying the role of these drivers. We used daily RSV hospitalization data to estimate the daily effective reproduction number (R(t)), a real-time measure of transmissibility, and examined its relationship with environmental drivers in Singapore from 2005 through 2015. We used multivariable regression models to quantify the proportion of the variance in R(t) explained by each meteorological driver. After constructing a basic model for RSV seasonality, we found that by adding meteorological variables into this model we were able to explain a further 15% of the variance in RSV transmissibility. Lower and higher value of mean temperature, diurnal temperature range (DTR), precipitation and relative humidity were associated with increased RSV transmissibility, while higher value of maximum wind speed was correlated with decreased RSV transmissibility. We found that a number of meteorological drivers were associated with RSV transmissibility. While indoor conditions may differ from ambient outdoor conditions, our findings are indicative of a role of ambient temperature, humidity and wind speed in affecting RSV transmission that could be biological or could reflect indirect effects via the consequences on time spent indoors.
INTRODUCTION: Respiratory syncytial virus (RSV) infection is a major cause of hospitalization in children. Meteorological factors are known to influence seasonal RSV epidemics, but the relationship between meteorological factors and RSV infection in children is not well understood. We aimed to explore the relationship between meteorological factors and RSV infections among hospitalized children, using different statistical models. METHODS: We conducted a retrospective review concerning children with RSV infections admitted to a tertiary pediatric hospital in Wenzhou, China, between January 2008 and December 2017. The relationship between meteorological factors (average daily temperatures, average daily relative humidity, rainfall, rainfall days, and wind speed) and the incidence of RSV in hospitalized children was analyzed using three time-series models, namely an autoregressive integrated moving average (ARIMA) model, a generalized additive model (GAM), and a least absolute shrinkage and selection operator (LASSO)-based model. RESULTS: In total, 15?858 (17.6%) children tested positive for RSV infection. The ARIMA model revealed a marked seasonal pattern in the RSV detection rate, which peaked in winter and spring. The model was a good predictor of RSV incidence (R(2) : 83.5%). The GAM revealed that a lower temperature and higher wind speed preceded increases in RSV detection. The LASSO-based model revealed that temperature and relative humidity were negatively correlated with RSV detection. CONCLUSIONS: Seasonality of RSV infection in hospitalized children correlated strongly with temperature. The LASSO-based model can be used to predict annual RSV epidemics using weather forecast data.
Malaria, a vector-borne disease, is a significant public health problem in Keonjhar district of Odisha (the malaria capital of India). Prediction of malaria, in advance, is an urgent need for reporting rolling cases of disease throughout the year. The climate condition do play an essential role in the transmission of malaria. Hence, the current study aims to develop and assess a simple and straightforward statistical model of an association between malaria cases and climate variates. It may help in accurate predictions of malaria cases given future climate conditions. For this purpose, a Bayesian Gaussian time series regression model is adopted to fit a relationship of the square root of malaria cases with climate variables with practical lag effects. The model fitting is assessed using a Bayesian version of R(2) (RsqB). Whereas, the predictive ability of the model is measured using a cross-validation technique. As a result, it is found that the square root of malaria cases with lag 1, maximum temperature, and relative humidity with lag 3 and 0 (respectively), are significantly positively associated with the square root of the cases. However, the minimum and average temperatures with lag 2, respectively, are observed as negatively (significantly) related. The considered model accounts for moderate amount of variation in the square root of malaria cases as received through the results for RsqB. We also present Absolute Percentage Errors (APE) for each of the 12 months (January-December) for a better understanding of the seasonal pattern of the predicted (square root of) malaria cases. Most of the APEs obtained corresponding to test data points is reasonably low. Further, the analysis shows that the considered model closely predicted the actual (square root of) malaria cases, except for some peak cases during the particular months. The output of the current research might help the district to develop and strengthen early warning prediction of malaria cases for proper mitigation, eradication, and prevention in similar settings.
Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.
The first long-term monitoring to document both activity and density of questing ixodid ticks in Vienna, Austria, is introduced. It was started in 2017 and is planned to run over decades. Such long-term monitorings are needed to quantify possible effects of climate change or to develop tick density forecast models. The monthly questing tick density at three sites has been observed by using a standardized sampling method by dragging an area of [Formula: see text] at each occasion. Popular recreational areas were chosen as study sites. These are the Prater public park, the wooded Kahlenberg, and a wildlife garden in Klosterneuburg. First results show a 3-year time series of nymphs and adults of the Ixodes ricinus species complex and Haemaphysalis concinna for the period 2017-2019. Whereas questing nymphs of the I. ricinus species complex were collected from February to November, H. concinna nymphs were only dragged from May to October. The peak of nymphal activity of the I. ricinus species complex was in May, that of H. concinna in August. In addition, a brief overview is given about ticks and tick-borne pathogens occurring in urban and suburban areas of Vienna.
The robust estimate and forecast capability of random forests (RF) has been widely recognized, however this ensemble machine learning method has not been widely used in mosquito-borne disease forecasting. In this study, two sets of RF models were developed at the national (pooled department-level data) and department level in Colombia to predict weekly dengue cases for 12-weeks ahead. A pooled national model based on artificial neural networks (ANN) was also developed and used as a comparator to the RF models. The various predictors included historic dengue cases, satellite-derived estimates for vegetation, precipitation, and air temperature, as well as population counts, income inequality, and education. Our RF model trained on the pooled national data was more accurate for department-specific weekly dengue cases estimation compared to a local model trained only on the department’s data. Additionally, the forecast errors of the national RF model were smaller to those of the national pooled ANN model and were increased with the forecast horizon increasing from one-week-ahead (mean absolute error, MAE: 9.32) to 12-weeks ahead (MAE: 24.56). There was considerable variation in the relative importance of predictors dependent on forecast horizon. The environmental and meteorological predictors were relatively important for short-term dengue forecast horizons while socio-demographic predictors were relevant for longer-term forecast horizons. This study demonstrates the potential of RF in dengue forecasting with a feasible approach of using a national pooled model to forecast at finer spatial scales. Furthermore, including sociodemographic predictors is likely to be helpful in capturing longer-term dengue trends.
It is often difficult to define the relationship and the influence of climate on the occurrence and distribution of disease. To examine this issue, the effects of climate indices on the distributions of malaria and meningitis in Nigeria were assessed over space and time. The main purpose of the study was to evaluate the relationships between climatic variables and the prevalence of malaria and meningitis, and develop an early warning system for predicting the prevalence of malaria and meningitis as the climate varies. An early warning system was developed to predetermine the months in a year that people are vulnerable to malaria and meningitis. The results revealed a significant positive relationship between rainfall and malaria, especially during the wet season with correlation coefficient R-2 >= 60.0 in almost all the ecological zones. In the Sahel, Sudan and Guinea, there appears to be a strong relationship between temperature and meningitis with R-2 > 60.0. In all, the results further reveal that temperatures and aerosols have a strong relationship with meningitis. The assessment of these initial data seems to support the finding that the occurrence of meningitis is higher in the northern region, especially the Sahel and Sudan. In contrast, malaria occurrence is higher in the southern part of the study area. We suggest that a thorough investigation of climate parameters is critical for the reallocation of clinical resources and infrastructures in economically underprivileged regions.
BACKGROUND AND OBJECTIVE: Malaria is an arthropod-borne infectious disease transmitted by the mosquito Anopheles and claims millions of lives globally every year. Reasons for failure to eradicate this disease are multifactorial. The seasonality of the malaria is principally determined by climatic factors conducive for breeding of the vector. We aimed to study the relationship between climatic variability and the seasonality of malaria over an eight-year duration. METHODS: This was a retrospective medical chart review of 8,844 confirmed cases of malaria which presented to The Indus Hospital, Karachi from January 2008 to November 2015. Cases were plotted against meteorological data for Karachi to elicit monthly variation. RESULTS: A secular incline and seasonality in malaria cases over the duration of eight years was seen. More cases were reported in the summer, rainy season compared with the other three seasons in each year. There was significant association with specific climate variables such as temperature, moisture, and humidity. CONCLUSION: There is a marked seasonal variation of malaria in Karachi, influenced by various environmental factors. Identification of the ‘the concentrated period’ of malaria can be helpful for policymakers to deploy malaria control interventions.
BACKGROUND: Malaria remains a major tropical vector-borne disease of immense public health concern owing to its debilitating effects in sub-Saharan Africa. Over the past 30?years, the high altitude areas in Eastern Africa have been reported to experience increased cases of malaria. Governments including that of the Republic of Uganda have responded through intensifying programs that can potentially minimize malaria transmission while reducing associated fatalities. However, malaria patterns following these intensified control and prevention interventions in the changing climate remains widely unexplored in East African highland regions. This study thus analyzed malaria patterns across altitudinal zones of Mount Elgon, Uganda. METHODS: Times-series data on malaria cases (2011-2017) from five level III local health centers occurring across three altitudinal zones; low, mid and high altitude was utilized. Inverse Distance Weighted (IDW) interpolation regression and Mann Kendall trend test were used to analyze malaria patterns. Vegetation attributes from the three altitudinal zones were analyzed using Normalized Difference Vegetation Index (NDVI) was used to determine the Autoregressive Integrated Moving Average (ARIMA) model was used to project malaria patterns for a 7 year period. RESULTS: Malaria across the three zones declined over the study period. The hotspots for malaria were highly variable over time in all the three zones. Rainfall played a significant role in influencing malaria burdens across the three zones. Vegetation had a significant influence on malaria in the higher altitudes. Meanwhile, in the lower altitude, human population had a significant positive correlation with malaria cases. CONCLUSIONS: Despite observed decline in malaria cases across the three altitudinal zones, the high altitude zone became a malaria hotspot as cases variably occurred in the zone. Rainfall played the biggest role in malaria trends. Human population appeared to influence malaria incidences in the low altitude areas partly due to population concentration in this zone. Malaria control interventions ought to be strengthened and strategically designed to achieve no malaria cases across all the altitudinal zones. Integration of climate information within malaria interventions can also strengthen eradication strategies of malaria in such differentiated altitudinal zones.
Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with increasing spread. Currently SFTS transmission has expanded beyond Asian countries, however, with definitive global extents and risk patterns remained obscure. Here we established an exhaustive database that included globally reported locations of human SFTS cases and the competent vector, Haemaphysalis longicornis (H. longicornis), as well as the explanatory environmental variables, based on which, the potential geographic range of H. longicornis and risk areas for SFTS were mapped by applying two machine learning methods. Ten predictors were identified contributing to global distribution for H. longicornis with relative contribution >= 1%. Outside contemporary known distribution, we predict high receptivity to H. longicornis across two continents, including northeastern USA, New Zealand, parts of Australia, and several Pacific islands. Eight key drivers of SFTS cases occurrence were identified, including elevation, predicted probability of H. longicornis presence, two temperature-related factors, two precipitation-related factors, the richness of mammals and percentage coverage of water bodies. The globally model-predicted risk map of human SFTS occurrence was created and validated effective for discriminating the actual affected and unaffected areas (median predictive probability 0.74 vs. 0.04, P < 0.001) in three countries with reported cases outside China. The high-risk areas (probability >= 50%) were predicted mainly in east-central China, most parts of the Korean peninsula and southern Japan, and northern New Zealand. Our findings highlight areas where an intensive vigilance for potential SFTS spread or invasion events should be advocated, owing to their high receptibility to H. longicornis distribution.
On 6 June 2019, the Norwegian Institute of Public Health was notified of?more than?50 cases of gastroenteritis in Askøy. A reservoir in a water supply system was suspected as the source of the outbreak because of the acute onset and geographical distribution of cases. We investigated the outbreak to confirm the source, extent of the outbreak and effect of control measures. A case was defined as a person in a household served by Water Supply System A (WSS-A) who had gastroenteritis for more than?24 h between 1 and 19 June 2019. We conducted pilot interviews, a telephone survey and an SMS-based cohort study of residents served by WSS-A. System information of WSS-A was collected. Whole genome sequencing on human and environmental isolates was performed. Among 6,108 individuals, 1,573 fulfilled the case definition. Residents served by the reservoir had a 4.6× higher risk of illness than others. Campylobacter jejuni isolated from cases (n?=?24) and water samples (n?=?4) had identical core genome MLST profiles. Contamination through cracks in the reservoir most probably occurred during heavy rainfall. Water supply systems are susceptible to contamination, particularly to certain weather conditions. This highlights the importance of water safety planning and risk-based surveillance to mitigate risks.
Lassa fever (LF) is increasingly recognised as an important rodent-borne viral haemorrhagic fever presenting a severe public health threat to sub-Saharan West Africa. In 2017-18, LF caused an unprecedented epidemic in Nigeria and the situation was worsening in 2018-19. This work aims to study the epidemiological features of epidemics in different Nigerian regions and quantify the association between reproduction number (R) and state rainfall. We quantify the infectivity of LF by the reproduction numbers estimated from four different growth models: the Richards, three-parameter logistic, Gompertz and Weibull growth models. LF surveillance data are used to fit the growth models and estimate the Rs and epidemic turning points (?) in different regions at different time periods. Cochran’s Q test is further applied to test the spatial heterogeneity of the LF epidemics. A linear random-effect regression model is adopted to quantify the association between R and state rainfall with various lag terms. Our estimated Rs for 2017-18 (1.33 with 95% CI 1.29-1.37) was significantly higher than those for 2016-17 (1.23 with 95% CI: (1.22, 1.24)) and 2018-19 (ranged from 1.08 to 1.36). We report spatial heterogeneity in the Rs for epidemics in different Nigerian regions. We find that a one-unit (mm) increase in average monthly rainfall over the past 7 months could cause a 0.62% (95% CI 0.20%-1.05%)) rise in R. There is significant spatial heterogeneity in the LF epidemics in different Nigerian regions. We report clear evidence of rainfall impacts on LF epidemics in Nigeria and quantify the impact.
Leptospirosis is one of the most common and neglected tropical waterborne diseases in China, causing serious economic losses, and constituting a significant public health threat. Leptospirosis has recently received increased attention and is considered a re-emerging infectious disease in many countries. The incidence of leptospirosis among people suggests that occupation, age, season, sex and water recreational activities are significant risk factors. The aim of this study was to describe the epidemiological profiles of leptospirosis in China during the 2007-2018 period. The morbidity data of leptospirosis by age, season (month), gender, occupation and geographic location (different provinces) were obtained from the public health science data centre of China for subsequent epidemiological analysis. The results indicate that the incidence of leptospirosis has shown a slow downward trend from 2007 to 2018, but morbidity rates were still relatively high (0.0660-0.0113). The incidence of leptospirosis varied in different provinces of China; cases localized mainly to the Southern and Central provinces, areas with warm weather and ample rainfall. Older people (aged 60-75), males, farmers, students and field workers were high-risk populations. During the 2007-2018 observation period, morbidity rates increased beginning in May, remained at high levels in August and September and decreased after November. The present investigation highlights the re-emergence of leptospirosis in some provinces of China (especially in Yunnan and Fujian) and shows that leptospirosis remains a serious public health threat. The results of this study should enhance measures taken for the prevention, control, and surveillance of leptospirosis in China.
The impacts of climate change and human activities are challenging water sustainability in many cities around the world. Advanced understanding of the future long-term coevolution of coupled urban human-water systems is of considerable interest in this context. This study uses a previously developed sociohydrologic model to explore the coevolutionary trajectories of Beijing City’s human-water system over the 2015-2099 period under possible climate changes. The effects of multiple human adaptive actions under alternative climate scenarios are investigated in particular. Results show that there might be a recurrent competition for water between humans and the natural environment (e.g., groundwater aquifer) in the long-term future, indicating that effective water management needs to ensure that this competition remains within a safe operating space. Three regimes of the human-environment competition are revealed, including a sustainable development regime in which human society and groundwater aquifer are both safe throughout their coevolutionary trajectories, a regime that may lead to severe population loss due to overaggressive population control actions, and a regime that may cause aquifer depletion due to under-perception of the drawdown of groundwater table. Results also show that relying too much on interbasin water diversion project might slacken human water conservation measures and eventually cause more severe aquifer depletion in the long run. Maintaining a high community sensitivity to drawdown of groundwater table and moderate measures to control population growth are keys to avoid unintended, negative consequences.
BACKGROUND: Haemorrhagic fever with renal syndrome (HFRS) is climate sensitive. HFRS-weather associations have been investigated by previous studies, but few of them looked into the interaction of meteorological factors on HFRS in different climate zones. OBJECTIVE: We aim to explore the interactions and marginal effects of meteorological factors on HFRS in China. METHODS: HFRS surveillance data and meteorological data were collected from 254 cities during 2006-2016. A monthly time-series study design and generalized estimating equation models were adopted to estimate the interactions and marginal effects of meteorological factors on HFRS in different climate zones of China. RESULTS: Monthly meteorological variables and the number of HFRS cases showed seasonal fluctuations and the patterns varied by climate zone. We found that maximum lagged effects of temperature on HFRS were 1-month in temperate zone, 2-month in warm temperate zone, 3-month in subtropical zone, respectively. There is an interaction effect between mean temperature and precipitation in temperate zone, while in warm temperate zone the interaction effect was found between mean temperature and relative humidity. CONCLUSION: The interaction effects and marginal effects of meteorological factors on HFRS varied from region to region in China. Findings of this study may be helpful for better understanding the roles of meteorological variables in the transmission of HFRS in different climate zones, and provide implications for the development of weather-based HFRS early warning systems.
The weather is arguably one of the most common topics in daily conversation. However, it is also a well-known factor in psychiatric problems worldwide such as depression, where particularly elders and females are prone to the condition. Previous studies have mostly focused on the association between long-term climate/season change and depressive symptoms to test the belief that people feel depressed when the weather is bad. Yet, little is known about the relationship between intraday weather conditions and depressive symptoms. This study aimed to decompose this association and explore age and gender differences in depressive symptoms’ report under different intraday weather conditions. We analyzed data with a total sample size of 20,987 individuals aged 15-96 years obtained via the China Labor-force Dynamic Survey (CLDS) project in 2016. The surveyors filled in the intraday weather conditions (i.e., sunny, cloudy, overcast, light rain, moderate rain, and heavy rain) in the questionnaire with depression being self-reported using the Center for Epidemiologic Studies Depression (CES-D) Scale. In the survey, 17.3% [95% confidence interval (CI) = 16.8%, 17.8%] individuals were assessed to have depressive symptoms (CES-D scores >15). Overcast day was the peak weather condition for depressive symptoms, while gender and age differences of depressive symptoms were biggest in the weather condition of moderate rain. Multivariate logistic regression revealed that female and middle-old age individuals were more likely to report having depressive symptoms, and people under overcast day were more likely to report having depressive symptoms compared to under sunny day [odds ratio (OR) = 1.25, 95%CI = 1.11, 1.39]. This intraday weather conditions-depression link was significant in males and middle-old age individuals but not in females and youngsters.
Measles is a major cause of child mortality in sub-Saharan Africa. Current immunization strategies achieve low coverage in areas where transmission drivers differ substantially from those in high-income countries. A better understanding of measles transmission in areas with measles persistence will increase vaccination coverage and reduce ongoing transmission. We analysed weekly reported measles cases at the district level in Niger from 1995 to 2004 to identify underlying transmission mechanisms. We identified dominant periodicities and the associated spatial clustering patterns. We also investigated associations between reported measles cases and environmental drivers associated with human activities, particularly rainfall. The annual and 2-3-year periodicities dominated the reporting data spectrum. The annual periodicity was strong with contiguous spatial clustering, consistent with the latitudinal gradient of population density, and stable over time. The 2-3-year periodicities were weaker, unstable over time and had spatially fragmented clustering. The rainy season was associated with a lower risk of measles case reporting. The annual periodicity likely reflects seasonal agricultural labour migration, whereas the 2-3-year periodicity potentially results from multiple mechanisms such as reintroductions and vaccine coverage heterogeneity. Our findings suggest that improving vaccine coverage in seasonally mobile populations could reduce strong measles seasonality in Niger and across similar settings.
SARS CoV-2 (COVID-19) Coronavirus cases are confirmed throughout the world and millions of people are being put into quarantine. A better understanding of the effective parameters in infection spreading can bring about a logical measurement toward COVID-19. The effect of climatic factors on spreading of COVID-19 can play an important role in the new Coronavirus outbreak. In this study, the main parameters, including the number of infected people with COVID-19, population density, intra-provincial movement, and infection days to end of the study period, average temperature, average precipitation, humidity, wind speed, and average solar radiation investigated to understand how can these parameters effects on COVID-19 spreading in Iran? The Partial correlation coefficient (PCC) and Sobol’-Jansen methods are used for analyzing the effect and correlation of variables with the COVID-19 spreading rate. The result of sensitivity analysis shows that the population density, intra-provincial movement have a direct relationship with the infection outbreak. Conversely, areas with low values of wind speed, humidity, and solar radiation exposure to a high rate of infection that support the virus’s survival. The provinces such as Tehran, Mazandaran, Alborz, Gilan, and Qom are more susceptible to infection because of high population density, intra-provincial movements and high humidity rate in comparison with Southern provinces.
The transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the severity of the related disease (COVID-19) are influenced by a large number of factors. This study aimed to investigate the correlation of COVID-19 case and death rates with possible causal climatological and sociodemographic factors for the March to May 2020 (first wave) period in a worldwide scale by statistically processing data for over one hundred countries. The weather parameters considered herein were air temperature, relative humidity, cumulative precipitation, and cloud cover, while sociodemographic factors included population density, median age, and government measures in response to the pandemic. The results of this study indicate that there is a statistically significant correlation between average atmospheric temperature and the COVID-19 case and death rates, with chi-square test p-values in the 0.001-0.02 range. Regarding sociodemographic factors, there is an even stronger dependence of the case and death rates on the population median age (p = 0.0006-0.0012). Multivariate linear regression analysis using Lasso and the forward stepwise approach revealed that the median age ranks first in importance among the examined variables, followed by the temperature and the delays in taking first governmental measures or issuing stay-at-home orders.
Estimating the epidemic potential of vector-borne diseases, along with the relative contribution of underlying mechanisms, is crucial for animal and human health worldwide. In West African Sahel, several outbreaks of Rift Valley fever (RVF) have occurred over the last decades, but uncertainty remains about the conditions necessary to trigger these outbreaks. We use the basic reproduction number (R(0)) as a measure of RVF epidemic potential in northern Senegal, and map its value in two distinct ecosystems, namely the Ferlo and the Senegal River delta and valley. We consider three consecutive rainy seasons (July-November 2014, 2015 and 2016) and account for several vector and animal species. We parametrize our model with estimates of Aedes vexans arabiensis, Culex poicilipes, Culex tritaeniorhynchus, cattle, sheep and goat abundances. The impact of RVF virus introduction is assessed every week over northern Senegal. We highlight September as the period of highest epidemic potential in northern Senegal, resulting from distinct dynamics in the two study areas. Spatially, in the seasonal environment of the Ferlo, we observe that high-risk locations vary between years. We show that decreased vector densities do not greatly reduce R(0) and that cattle immunity has a greater impact on reducing transmission than small ruminant immunity. The host preferences of vectors and the temperature-dependent time interval between their blood meals are crucial parameters needing further biological investigations.
India and other Southeast Asian countries are severely affected by Japanese encephalitis (JE), one of the deadliest vector-borne disease threat to human health. Several epidemiological observations suggest climate variables play a role in providing a favorable environment for mosquito development and virus transmission. In this study, generalized additive models were used to determine the association of JE admissions and mortality with climate variables in Gorakhpur district, India, from 2001-2016. The model predicted that every 1 unit increase in mean (Tmean;°C), and minimum (Tmin;°C) temperature, rainfall (RF; mm) and relative humidity (RH; %) would on average increase the JE admissions by 22.23 %, 17.83 %, 0.66 %, and 5.22 % respectively and JE mortality by 13.27 %, 11.77 %, 0.94 %, and 3.27 % respectively Conversely, every unit decrease in solar radiation (Srad; MJ/m(2)/day) and wind speed (WS; Kmph) caused an increase in JE admission by 17% and 11.42% and in JE mortality by 9.37% and 4.88% respectively suggesting a protective effect at higher levels. The seasonal analysis shows that temperature was significantly associated with JE in pre-monsoon and post-monsoon while RF, RH, Srad, and WS are associated with the monsoon. Effect modification due to age and gender showed an equal risk for both genders and increased risk for adults above 15 years of age, however, males and age groups under 15 years outnumbered females and adults. Sensitivity analysis results to explore lag effects in climate variables showed that climate variables show the strongest association at lag 1 to 1.5 months with significant lag effect up tp lag 0-60 days. The exposure-response curve for climate variables showed a more or less linear relationship, with an increase in JE admissions and mortality after a certain threshold and decrease were reported at extreme levels of exposure. The study concludes that climate variables could influence the JE vector development and multiplication and parasite maturation and transmission in the Gorakhpur region whose indirect impact was noted for JE admission and mortality. In response to the changing climate, public health interventions, public awareness, and early warning systems would play an unprecedented role to compensate for future risk.
Kerteszia cruzii is a sylvatic mosquito and the primary vector of Plasmodium spp., which can cause malaria in humans in areas outside the Amazon River basin in Brazil. Anthropic changes in the natural environments are the major drivers of massive deforestation and local climate change, with serious impacts on the dynamics of mosquito communities and on the risk of acquiring malaria. Considering the lack of information on the dynamics of malaria transmission in areas across the Atlantic Forest biome, where Ke. cruzii is the dominant vector, and the impact of climate drivers of malaria, the present study aimed to: (i) investigate the occurrence and survival rate of Ke. cruzii based on the distinct vegetation profiles found in areas across the coastal region of the Brazilian Atlantic Forest biome; (ii) estimate the extrinsic incubation period (EIP) and survival rates of P. vivax and P. falciparum parasites in Ke. cruzii under current and future scenarios. The potential distribution of Plasmodium spp. was estimated using simulation analyses under distinct scenarios of average temperature increases from 1 °C to 3.7 °C. Our results showed that two conditions are necessary to explain the occurrence and survival of Ke. cruzii: warm temperature and presence of the Atlantic Forest biome. Moreover, both Plasmodium species showed a tendency to decrease their EIP and increase their estimated survival rates in a scenario of higher temperature. Our findings support that the high-risk malaria areas may include the southern region of the distribution range of the Atlantic Forest biome in the coming years. Despite its limitations and assumptions, the present study provides robust evidence of areas with potential to be impacted by malaria incidence in a future scenario. These areas should be monitored in the next decades regarding the occurrence of the mosquito vector and the potential for malaria persistence and increased occurrence.
The incidence of hospitalized leptospirosis patients was positively associated with increased precipitation in Salvador, Brazil. However, Leptospira infection risk among a cohort of city residents was inversely associated with rainfall. These findings indicate that, although heavy rainfall may increase severe illness, Leptospira exposures can occur year-round.
BACKGROUND: Due to variations in climatic conditions, the effects of meteorological factors and PM(2.5) on influenza activity, particularly in subtropical regions, vary in existing literature. In this study, we examined the relationship between influenza activity, meteorological parameters, and PM(2.5) . METHODS: A total of 20 165 laboratory-confirmed influenza cases in Hangzhou, Zhejiang province, were documented in our dataset and aggregated into weekly counts for downstream analysis. We employed a combination of the quasi-Poisson-generalized additive model and the distributed lag non-linear model to examine the relationship of interest, controlling for long-term trends, seasonal trends, and holidays. RESULTS: A hockey-stick association was found between absolute humidity and the risk of influenza infections. The overall cumulative adjusted relative risk (ARR) was statistically significant when weekly mean absolute humidity was low (<10 µg/m(3) ) and high (>17.5 µg/m(3) ). A slightly higher ARR was observed when weekly mean temperature reached over 30.5°C. A statistically significantly higher ARR was observed when weekly mean relative humidity dropped below 67%. ARR increased statistically significantly with increasing rainfall. For PM(2.5) , the ARR was marginally statistically insignificant. In brief, high temperature, wet and dry conditions, and heavy rainfall were the major risk factors associated with a higher risk of influenza infections. CONCLUSIONS: The present study contributes additional knowledge to the understanding of the effects of various environmental factors on influenza activities. Our findings shall be useful and important for the development of influenza surveillance and early warning systems.
International reports indicate a rising incidence of nontuberculous mycobacterial (NTM) disease. Many infectious diseases have seasonal variation in incidence, and major weather events and climate change have been implicated. The aim of this study was to explore the relationship between climate variables and NTM incident cases in Queensland, Australia. METHODS: NTM data were obtained from the Queensland notifiable conditions database for the period 2001-2016. Rainfall and temperature data were obtained from the Australian Bureau of Meteorology. Poisson regression models were used to assess notification rates (incidence cases per 100,000 population) over time and to estimate incidence rate ratios (IRR). Cross correlation coefficients were used to examine the relationship between rainfall and temperature data and NTM incidence over time in each Hospital and Health Service (HHS). RESULTS: 12,219 NTM cases were reported. The most common species was M. intracellulare (39.1%), followed by M. avium (9.8%), M abscessus (8.5%), M. fortuitum (8.3%), M. chelonae (3.3%), and M. kansasii (2.4%). The estimated incidence rate increased from 11.10 (95% CI 8.10-15.22) in 2001 to 25.88 (95%CI 21.78-30.73) per 100,000 in 2016. The estimated IRR increased for all common species, except M. kansasii. Although increased IRRs were observed for most NTM species, geospatial heterogeneity was observed. The effect of rainfall and temperature on NTM incidence differed between species and geographic regions. CONCLUSIONS: The incidence of NTM infections increased between 2001 and 2016. Variations in temperature and rainfall may play a role in environmental exposure to some species of NTM. Spatial variation in IRR suggests that there may also be other environmental factors that influence transmission.
Hydroclimatic change may affect the range of some infectious diseases, including tularemia. Previous studies have investigated associations between tularemia incidence and climate variables, with some also establishing quantitative statistical disease models based on historical data, but studies considering future climate projections are scarce. This study has used and combined hydro-climatic projection outputs from multiple global climate models (GCMs) in phase six of the Coupled Model Intercomparison Project (CMIP6), and site-specific, parameterized statistical tularemia models, which all imply some type of power-law scaling with preceding-year tularemia cases, to assess possible future trends in disease outbreaks for six counties across Sweden, known to include tularemia high-risk areas. Three radiative forcing (emissions) scenarios are considered for climate change projection until year 2100, incuding low (2.6 Wm(-2)), medium (4.5 Wm(-2)), and high (8.5 Wm(-2)) forcing. The results show highly divergent changes in future disease outbreaks among Swedish counties, depending primarily on site-specific type of the best-fit disease power-law scaling characteristics of (mostly positive, in one case negative) sub- or super-linearity. Results also show that scenarios of steeper future climate warming do not necessarily lead to steeper increase of future disease outbreaks. Along a latitudinal gradient, the likely most realistic medium climate forcing scenario indicates future disease decreases (intermittent or overall) for the relatively southern Swedish counties Örebro and Gävleborg (Ockelbo), respectively, and disease increases of considerable or high degree for the intermediate (Dalarna, Gävleborg (Ljusdal)) and more northern (Jämtland, Norrbotten; along with the more southern Värmland exception) counties, respectively.
Continental-scale models of malaria climate suitability typically couple well-established temperature-response models with basic estimates of vector habitat availability using rainfall as a proxy. Here we show that across continental Africa, the estimated geographic range of climatic suitability for malaria transmission is more sensitive to the precipitation threshold than the thermal response curve applied. To address this problem we use downscaled daily climate predictions from seven GCMs to run a continental-scale hydrological model for a process-based representation of mosquito breeding habitat availability. A more complex pattern of malaria suitability emerges as water is routed through drainage networks and river corridors serve as year-round transmission foci. The estimated hydro-climatically suitable area for stable malaria transmission is smaller than previous models suggest and shows only a very small increase in state-of-the-art future climate scenarios. However, bigger geographical shifts are observed than with most rainfall threshold models and the pattern of that shift is very different when using a hydrological model to estimate surface water availability for vector breeding.
INTRODUCTION: Snakebites represent a serious global public health problem, especially in tropical countries. In Brazil, the incidence of snakebites ranges from 19 to 22 thousand cases per 100000 persons annually. The state of Rondônia, in particular, has had an increasing incidence of snakebites. METHODS: A retrospective cross-sectional study on snakebites was conducted from January 2007 to December 2018. Brazil’s Information System for Notifiable Diseases was queried for all snakebites reported in Porto Velho, Ariquemes, Cacoal, and Vilhena. Data on land surface temperatures during the day and night, precipitation, and humidity were obtained using the Google Earth Engine. A Bayesian time series model was constructed to describe the pattern of snakebites and their relationship with climate data. RESULTS: In total, 6326 snakebites were reported in Rondônia. Accidents were commonly caused by Bothrops sp. (n=2171, 81.80%). Snakebites most frequently occurred in rural areas (n=2271, 85.5%). Men, with a median age of 34 years (n=2101, 79.1%), were the most frequent bitten. Moderate clinical manifestation was the most common outcome of an accident (n=1101, 41.50%). There were clear seasonal patterns with respect to rainfall, humidity, and temperature. Rainfall and land surface temperature during the day or night did not increase the risk of snakebites in any city; however, changes in humidity increased the risk of snakebites in all cities. CONCLUSION: This study identified the population exposed to snakes and the influence of anthropic and climatic factors on the incidence of snakebites. According to climate data, changes in humidity increased the risk of snakebites.
Precipitation extremes are increasing globally due to anthropogenic climate change. However, there remains uncertainty regarding impacts upon flood occurrence and subsequent population exposure. Here, we quantify changes in population exposure to flood hazard across the contiguous United States. We combine simulations from a climate model large ensemble and a high-resolution hydrodynamic flood model-allowing us to directly assess changes across a wide range of extreme precipitation magnitudes and accumulation timescales. We report a mean increase in the 100-year precipitation event of similar to 20% (magnitude) and >200% (frequency) in a high warming scenario, yielding a similar to 30-127% increase in population exposure. We further find a nonlinear increase for the most intense precipitation events-suggesting accelerating societal impacts from historically rare or unprecedented precipitation events in the 21st century. Plain Language Summary Heavy rainfall is increasing globally due to human-caused global warming. However, it is still unclear how these increases in heavy rainfall might affect flood risk. In this paper, we investigate how global warming and population changes together may be affecting the number of people at risk from floods in the United States. We combine simulations from a climate model and flood model-allowing us to consider a wide range of heavy rainfall events. We report a similar to 20% increase in the size and a >200% increase in the frequency of very heavy and rare rainfall events, which leads to a similar to 30-127% increase in the number of people at risk from floods. Finally, we find that the heaviest rainfall events increase by the widest margin-suggesting the possibility of major increases in damage and disruption caused by severe floods in the 21st century.
The impact of climate factors on the epidemiology of diseases in general and leishmaniasis in particular continues to be a subject of research and analysis. Changes in climatic parameters contribute to the creation of ecological conditions favorable to the multiplication of the vectors of certain diseases. With this in mind, this study presents an entomological survey conducted in Meknes prefecture and the study of the link between the abundance of sandflies, an indicator of the risk of leishmaniasis in a given area, and the climatic factors. Monthly trapping of this fauna was carried out during a year from March 2016 until April 2017 using adhesive traps. Climatic data from the region were used to determine the effect of climate on the distribution of sandflies. A total of 941 leishmaniasis vector specimens were captured. The dominant species is Ph. sergenti (73.32), followed by Ph. longicuspis (8.25%), then Ph. perniciosus (7.94%) and Ph. papatasi (6.31%). The sex ratio study showed that males are more abundant than females for all species. The seasonal fluctuation is bimodal with two peaks, the first in July and the second in September. The results show a positive correlation between temperature and abundance of sandflies (r?=?0.99) and a negative correlation with humidity and precipitation with a correlation coefficient of r?=?-0.87 and r?=?-0.72. Indeed, the medium-term climatological forecasts are essential tools to develop a warning system for leishmaniasis.
BACKGROUND: Cutaneous leishmaniasis (CL) is a dermal and parasitic disease.. The aim of this study was to determine the effect of environmental and climate factors on spatial distribution of CL in northeastern Iran by utilizing remote sensing from 20 March 2016 to 19 March 2017. METHODS: In this ecological study, the data were divided into two parts: The descriptive data on human CL cases were gathered from Communicable Diseases center of Iran. The remote sensing techniques and satellite imagery data (TRMM, MODIS-Aqua, MODIS-Terra and AMSR-2 with spatial resolution 0.25°, 0.05°, 5600m and 10km) of environmental and climate factors were used to determine the spatial pattern changes of cutaneous leishmaniasis incidence. RESULTS: The incidence of CL in North Khorasan, Razavi Khorasan, and South Khorasan was 35.80 per 100,000 people (309/863092), 34.14 per 100,000 people (2197/6,434,501) and 7.67 per 100,000 people (59/768,898), respectively. The incidence of CL had the highest correlation with soil moisture and evapotranspiration. Moreover, the incidence of disease was significantly correlated with Normalized Difference Vegetation Index (NDVI) and air humidity while it had the lowest correlation with rainfall. Furthermore, the CL incidence had an indirect correlation relation with the air temperature meaning that with an increase in the temperature, the incidence of disease decreased. CONCLUSION: As such, the incidence of disease was also higher in the northern regions; most areas of North Khorasan and northern regions of Razavi Khorasan; where the rainfall, vegetation, specific humidity, evapotranspiration, and soil moisture was higher than the southern areas.
Infectious diseases are a major health challenge for the worldwide population. Since their rapid spread can cause great distress to the real world, in addition to taking appropriate measures to curb the spread of infectious diseases in the event of an outbreak, proper prediction and early warning before the outbreak of the threat of infectious diseases can provide an important basis for early and reasonable response by the government health sector, reduce morbidity and mortality, and greatly reduce national losses. However, if only traditional medical data is involved, it may be too late or too difficult to implement prediction and early warning of an infectious outbreak. Recently, medical big data has become a research hotspot and has played an increasingly important role in public health, precision medicine, and disease prediction. In this paper, we focus on exploring a prediction and early warning method for influenza with the help of medical big data. It is well known that meteorological conditions have an influence on influenza outbreaks. So, we try to find a way to determine the early warning threshold value of influenza outbreaks through big data analysis concerning meteorological factors. Results show that, based on analysis of meteorological conditions combined with influenza outbreak history data, the early warning threshold of influenza outbreaks could be established with reasonable high accuracy.
INTRODUCTION: Asthma is a disease that has been associated with the presence of different genetic and socio-environmental factors. OBJECTIVE: To identify and evaluate the seasonality of respiratory syncytial virus (RSV) and human rhinovirus (RV) in asthmatic children and adolescents in tropical climate, as well as to assess the socioeconomic and environmental factors involved. METHODS: The study was conducted in a referral hospital, where a total of 151 children were recruited with a respiratory infection. The International Study of Asthma and Allergies in Childhood (ISAAC) protocol and a questionnaire were applied, and a skin prick test was performed. The nasal swab was collected to detect RV and RSV through molecular assay. National Meteorological Institute (INMET) database was the source of climatic information. RESULTS: The socio-environmental characterization of asthmatic children showed the family history of allergy, disturbed sleep at night, dry cough, allergic rhinitis, individuals sensitized to at least one mite. We identified RV in 75% of children with asthma and 66.7% of RSV in children with asthma. There was an association between the presence of RV and the dry season whereas the presence of the RSV was associated with the rainy season. Contributing to these results, a negative correlation was observed between the RSV and the wind speed and the maximum temperature (T. Max) and a positive correlation with precipitation. CONCLUSIONS: The results suggest a high prevalence of RV and RSV in asthmatic children and the seasonality of these viruses were present in different climatic periods. This has significant implications for understanding short- and long-term clinical complications in asthmatic patients.
Background: Malaria remains a global challenge with approximately 228 million cases and 405,000 malaria-related deaths reported in 2018 alone; 93% of which were in sub-Saharan Africa. Aware of the critical role than environmental factors play in malaria transmission, this study aimed at assessing the relationship between precipitation, temperature, and clinical malaria cases in East Africa and how the relationship may change under 1.5 C and 2.0 C global warming levels (hereinafter GWL1.5 and GWL2.0, respectively). Methods: A correlation analysis was done to establish the current relationship between annual precipitation, mean temperature, and clinical malaria cases. Differences between annual precipitation and mean temperature value projections for periods 2008-2037 and 2023-2052 (corresponding to GWL1.5 and GWL2.0, respectively), relative to the control period (1977-2005), were computed to determine how malaria transmission may change under the two global warming scenarios. Results: A predominantly positive/negative correlation between clinical malaria cases and temperature/precipitation was observed. Relative to the control period, no major significant changes in precipitation were shown in both warming scenarios. However, an increase in temperature of between 0.5 C and 1.5 C and 1.0 C to 2.0 C under GWL1.5 and GWL2.0, respectively, was recorded. Hence, more areas in East Africa are likely to be exposed to temperature thresholds favourable for increased malaria vector abundance and, hence, potentially intensify malaria transmission in the region. Conclusions: GWL1.5 and GWL2.0 scenarios are likely to intensify malaria transmission in East Africa. Ongoing interventions should, therefore, be intensified to sustain the gains made towards malaria elimination in East Africa in a warming climate.
We examine the impact of extreme heat during pregnancy on infant mortality and check if public interventions can serve as effective adaptation strategies. We show that 2 children die as infants out of 1000 births in India for high temperature during pregnancy, tentatively due to reduced agricultural yields, wages, and greater disease prevalence like diarrhea. The heat-infant mortality relationship holds in rural India only. Using phased introduction of an employment guarantee program and partial introduction of a community health care worker program for identification, we find that only the health program is effective in modifying the temperature-infant mortality relationship in rural India.
Extreme precipitation events may be an important environmental trigger for asthma exacerbations in children. We used a time stratified case-crossover design and data from a large electronic health record database at the Children’s Hospital of Philadelphia (CHOP) to estimate associations of daily heavy precipitation (defined as > 95th percentile of the summertime distribution) with asthma exacerbation among children. We defined control days as those falling on the same day of the week within the same month and year as the case. We restricted our primary analyses to the summer months in years 2011-2016 and used conditional logistic regression models to estimate associations between heavy precipitation and acute asthma exacerbations in both outpatient (primary care, specialty care, and emergency department) and inpatient settings. We investigated numerous individual-level (e.g., age, sex, eczema diagnosis) and environmental measures (e.g., greenspace, particulate matter) as potential effect modifiers. The analysis include 13,483 asthma exacerbations in 10,434 children. Odds of asthma exacerbation were 11% higher on heavy precipitation vs. no precipitation days (95% CI: 1.02-1.21). There was little evidence of effect modification by most measures. These results suggest that heavy summertime precipitation events may contribute to asthma exacerbations. Further research using larger datasets from other health systems is needed to confirm these results, and to explore underlying mechanisms.
Runoff from heavy precipitation events can lead to microbiological contamination of source waters for public drinking water supplies. Philadelphia is a city of interest for a study of waterborne acute gastrointestinal illness (AGI) because of frequent heavy precipitation, extensive impervious landcover, and combined sewer systems that lead to overflows. We conducted a time-series analysis of the association between heavy precipitation and AGI incidence in Philadelphia, served by drinking water from Delaware River and Schuylkill River source waters. AGI cases on each day during the study period (2015-2017) were captured through syndromic surveillance of patients’ chief complaint upon presentation at local emergency departments. Daily precipitation was represented by measurements at the Philadelphia International Airport and by modeled precipitation within the watershed boundaries, and we also evaluated stream flowrate as a proxy of precipitation. We estimated the association using distributed lag nonlinear models, assuming a quasi-Poisson distribution of the outcome variable and with adjustment for potential confounding by seasonal and long-term time trends, ambient temperature, day-of-week, and major holidays. We observed an association between heavy precipitation and AGI incidence in Philadelphia that was primarily limited to the spring season, with significant increases in AGI that peaked from 8 to 16 days following a heavy precipitation event. For example, the increase in AGI incidence related to airport precipitation above the 95th percentile (vs no precipitation) during spring reached statistical significance on lag day 7, peaked on day 16 (102% increase, 95% confidence interval: 16%, 252%), and declined while remaining significantly elevated through day 28. Similar associations were observed in analyses of watershed-specific precipitation in relation to AGI cases within the populations served by drinking water from each river. Our results suggest that heavy precipitation events in Philadelphia result in detectable local increases in waterborne AGI.
Diarrheal diseases remain a significant contributor to the global burden of disease. Climate change may increase their incidence by altering the epidemiology of waterborne pathogens through changes in rainfall patterns. To assess potential impacts of future changes in rainfall patterns, we analyzed 33,927 cases of diarrhea across all Ministry of Health clinical facilities in Esmeraldas Province, Ecuador, for a 24-month period from 2013 to 2014, using mixed-effects Poisson regression. We assessed the association between the incidence of diarrheal diseases and heavy rainfall events (HREs) and antecedent rainfall conditions. In rural areas, we found no significant associations between HREs and incidence. In urban areas, dry antecedent conditions were associated with higher incidence than wet conditions. In addition, HREs with dry antecedent conditions were associated with elevated incidence by up to 1.35 (incidence rate ratio, 95% CI: 1.14-1.60) times compared with similar conditions without HREs. These patterns may be driven by accumulation of fecal contamination during dry periods, followed by a flushing effect during HREs. This phenomenon is more important in dense urban environments with more impervious surfaces. These findings suggest that projected increases in rainfall variability and HREs may increase diarrhea burden in urban regions, which are rapidly expanding globally.
BACKGROUND: Infection by hepatitis E virus (HEV) can cause a high burden of morbidity and mortality in countries with poor access to clean water and sanitation. Our study aimed to investigate the situation of HEV infections in the Central African Republic (CAR). METHODS: A retrospective analysis of the blood samples and notification forms collected through the national yellow fever (YF) surveillance program, but for which a diagnosis of YF was discarded, was carried out using an anti-HEV IgM ELISA and a HEV-specific RT-PCR. RESULTS: Of 2883 YF-negative samples collected between January 2008 and December 2012, 745 (~?26%) tested positive by at least either of the 2 tests used to confirm HEV cases. The results revealed that the CAR was hit by a large HEV outbreak in 2008 and 2009. The results also showed a clear seasonal pattern with correlation between HEV incidence and rainfall in Bangui. A phylogenetic analysis showed that the circulating strains belonged to genotypes 1e and 2b. CONCLUSIONS: Overall, this study provides further evidences that HEV can be a significant cause of acute febrile jaundice, particularly among adults during rainy season or flood, in a country from Sub-Saharan Africa.
BACKGROUND: Rodent-borne hantaviruses (genus Orthohantavirus) are the etiologic agents causing two human diseases: hemorrhagic fever with renal syndrome (HFRS) in Euroasia; and hantavirus pulmonary syndrome (HPS) in North and South America. In South America fatality rates of HPS can reach up to 35%-50%. The transmission of pathogenic hantaviruses to humans occurs mainly via inhalation of aerosolized excreta from infected rodents. Thus, the epidemiology of HPS is necessarily linked to the ecology of their rodent hosts and the contact with a human, which in turn may be influenced by climatic variability. Here we examined the relationship between climatic variables and hantavirus transmission aim to develop an early warning system of potential hantavirus outbreaks based on ecologically relevant climatic factors. METHODOLOGY AND MAIN FINDINGS: We compiled reported HPS cases in northwestern Argentina during the 1997-2017 period and divided our data into biannual, quarterly, and bimestrial time periods to allow annual and shorter time delays to be observed. To evaluate the relationship of hantavirus transmission with mean temperature and precipitation we used dynamic regression analysis. We found a significant association between HPS incidence and lagged rainfall and temperature with a delay of 2 to 6 months. For the biannual and quarterly models, hantavirus transmission was positively associated with lagged rainfall and temperature; whereas the bimestrial models indicate a direct relationship with the rainfall but inverse for temperature in the second lagged period. CONCLUSIONS/SIGNIFICANCE: This work demonstrates that climate variability plays a significant role in the transmission of hantavirus in northwestern Argentina. The model developed in this study provides a basis for the forecast of potential HPS outbreaks based on climatic parameters. Our findings are valuable for the development of public health policies and prevention strategies to mitigate possible outbreaks. Nonetheless, a surveillance program on rodent population dynamics would lead to a more accurate forecast of HPS outbreaks.
BACKGROUND: As a mosquito-borne infectious disease, dengue fever (DF) has spread through tropical and subtropical regions worldwide in recent decades. Dengue forecasting is essential for enhancing the effectiveness of preventive measures. Current studies have been primarily conducted at national, sub-national, and city levels, while an intra-urban dengue forecasting at a fine spatial resolution still remains a challenging feat. As viruses spread rapidly because of a highly dynamic population flow, integrating spatial interactions of human movements between regions would be potentially beneficial for intra-urban dengue forecasting. METHODOLOGY: In this study, a new framework for enhancing intra-urban dengue forecasting was developed by integrating the spatial interactions between urban regions. First, a graph-embedding technique called Node2Vec was employed to learn the embeddings (in the form of an N-dimensional real-valued vector) of the regions from their population flow network. As strongly interacting regions would have more similar embeddings, the embeddings can serve as “interaction features.” Then, the interaction features were combined with those commonly used features (e.g., temperature, rainfall, and population) to enhance the supervised learning-based dengue forecasting models at a fine-grained intra-urban scale. RESULTS: The performance of forecasting models (i.e., SVM, LASSO, and ANN) integrated with and without interaction features was tested and compared on township-level dengue forecasting in Guangzhou, the most threatened sub-tropical city in China. Results showed that models using both common and interaction features can achieve better performance than that using common features alone. CONCLUSIONS: The proposed approach for incorporating spatial interactions of human movements using graph-embedding technique is effective, which can help enhance fine-grained intra-urban dengue forecasting.
OBJECTIVES: To identify key predictors of general practitioner (GP) consultations for allergic rhinitis (AR) using meteorological and environmental data. DESIGN: A retrospective, time series analysis of GP consultations for AR. SETTING: A large GP surveillance network of GP practices in the London area. PARTICIPANTS: The study population was all persons who presented to general practices in London that report to the Public Health England GP in-hours syndromic surveillance system during the study period (3 April 2012 to 11 August 2014). PRIMARY MEASURE: Consultations for AR (numbers of consultations). RESULTS: During the study period there were 186?401 GP consultations for AR. High grass and nettle pollen counts (combined) were associated with the highest increases in consultations (for the category 216-270 grains/m(3), relative risk (RR) 3.33, 95%?CI 2.69 to 4.12) followed by high tree (oak, birch and plane combined) pollen counts (for the category 260-325 grains/m(3), RR 1.69, 95%?CI 1.32 to 2.15) and average daily temperatures between 15°C and 20°C (RR 1.47, 95%?CI 1.20 to 1.81). Higher levels of nitrogen dioxide (NO(2)) appeared to be associated with increased consultations (for the category 70-85?µg/m(3), RR 1.33, 95%?CI 1.03 to 1.71), but a significant effect was not found with ozone. Higher daily rainfall was associated with fewer consultations (15-20?mm/day; RR 0.812, 95% CI 0.674 to 0.980). CONCLUSIONS: Changes in grass, nettle or tree pollen counts, temperatures between 15°C and 20°C, and (to a lesser extent) NO(2) concentrations were found to be associated with increased consultations for AR. Rainfall has a negative effect. In the context of climate change and continued exposures to environmental air pollution, intelligent use of these data will aid targeting public health messages and plan healthcare demand.
Climate change affects the dynamics of vector-borne diseases. Culex pipiens Linnaeus is the main vector of West Nile fever, a widely distributed arbovirus, it is continuously increasing its distribution. Using a species distribution model, maps of suitable habitats of Cx. pipiens were generated for Chile in the current climate and three climate change scenarios, using global and regional georeferenced vector presence records as input, plus bioclimatic variables. Since this virus has not yet arrived in Chile, the purpose of this study is to anticipate potential risk areas and to prevent the establishment and spread of the virus. Cx. pipiens is widely distributed in Chile. The suitable habitats in Chile were concentrated mostly from 32 degrees to 35 degrees S, increasing in future scenarios up to 113 % in the northern zone and moving towards the mountains. This species conserves around 90 % of its niche in the future, and shows a reduction of 11.4 % in the severe climate change scenario. It is anticipated that Chile will experience an increase in the environmental suitability for Cx. pipiens moving from the Andes to the coastal zone throughout the country, mainly in the center-south. This will raise the risk of local virus transmission if the virus is introduced to the country via diverse routes.
Leptospirosis outbreaks in various parts of the world have been linked to changes in the weather. Furthermore, the effects have been shown to occur at different lags of up to 10 months, affecting the performance of simulation models that predict leptospirosis occurrence. In Malaysia, the link between different weather parameters, at different time lags, has yet to be established despite an increasing number of cases in recent years. In this study, a combination of data mining and machine learning is used to analyze, capture, and predict the relation between leptospirosis occurrence and temperature, rainfall, and relative humidity using the Seremban district in Malaysia as a case study. First, the optimal time lags for rainfall were determined using graphical exploratory data analysis (EDA) while non-graphical EDA was used for temperature. Then, an artificial neural network (ANN) model is developed to classify the combination of selected features into disease occurrence and non-occurrence using back-propagation training, optimizing the number of hidden layers and hidden nodes. The success is measured using accuracy, sensitivity, and specificity of each model. EDA has shown that leptospirosis occurrence in Seremban is highly correlated with weekly average temperature at lag 16 weeks and weekly rainfall amount at lag 12-20 weeks. Using these selected features, the ANN model achieved the highest accuracy, sensitivity, and specificity at 84.00, 86.44, and 79.33%, respectively. Overall, the EDA approach has increased the accuracy of the predictive model by 13.30-31.26% from the baseline models.
Although only a small proportion of the landmass of South Africa is classified as high risk for malaria, the country experiences on-going challenges relating to malaria outbreaks. Climate change poses a growing threat to this already dire situation. While considerable effort has been placed in public health campaigns in the highest-risk regions, and national malaria maps are updated to account for changing climate, malaria cases have increased. This pilot study considers the sub-population of South Africans who reside outside of the malaria area, yet have the means to travel into this high-risk region for vacation. Through the lens of the governmental “ABC of malaria prevention”, we explore this sub-population’s awareness of the current boundaries to the malaria area, perceptions of the future boundary under climate change, and their risk-taking behaviours relating to malaria transmission. Findings reveal that although respondents self-report a high level of awareness regarding malaria, and their boundary maps reveal the broad pattern of risk distribution, their specifics on details are lacking. This includes over-estimating both the current and future boundaries, beyond the realms of climate-topographic possibility. Despite over-estimating the region of malaria risk, the respondents reveal an alarming lack of caution when travelling to malaria areas. Despite being indicated for high-risk malaria areas, the majority of respondents did not use chemoprophylaxis, and many relied on far less-effective measures. This may in part be due to respondents relying on information from friends and family, rather than medical or governmental advice.
Malaria occurrence in the Chittagong Hill Tracts in Bangladesh varies by season and year, but this pattern is not well characterized. The role of environmental conditions on the occurrence of this vector-borne parasitic disease in the region is not fully understood. We extracted information on malaria patients recorded in the Upazila (sub-district) Health Complex patient registers of Rajasthali in Rangamati district of Bangladesh from February 2000 to November 2009. Weather data for the study area and period were obtained from the Bangladesh Meteorological Department. Non-linear and delayed effects of meteorological drivers, including temperature, relative humidity, and rainfall on the incidence of malaria, were investigated. We observed significant positive association between temperature and rainfall and malaria occurrence, revealing two peaks at 19 °C (logarithms of relative risks (logRR) = 4.3, 95% CI: 1.1-7.5) and 24.5 °C (logRR = 4.7, 95% CI: 1.8-7.6) for temperature and at 86 mm (logRR = 19.5, 95% CI: 11.7-27.3) and 284 mm (logRR = 17.6, 95% CI: 9.9-25.2) for rainfall. In sub-group analysis, women were at a much higher risk of developing malaria at increased temperatures. People over 50 years and children under 15 years were more susceptible to malaria at increased rainfall. The observed associations have policy implications. Further research is needed to expand these findings and direct resources to the vulnerable populations for malaria prevention and control in the Chittagong Hill Tracts of Bangladesh and the region with similar settings.
Floods are acknowledged as one of the most serious threats to people’s lives and properties worldwide. To mitigate the flood risk, it is possible to act separately on its components: hazard, vulnerability, exposure. Emergency management plans can actually provide effective nonstructural practices to decrease both human exposure and vulnerability. Crowding maps depending on characteristic time patterns, herein referred to as dynamic exposure maps, represent a valuable tool to enhance the flood risk management plans. In this paper, the suitability of mobile phone data to derive crowding maps is discussed. A test case is provided by a strongly urbanized area subject to frequent flooding located on the western outskirts of Brescia (northern Italy). Characteristic exposure spatiotemporal patterns and their uncertainties were detected with regard to land cover and calendar period. This novel methodology still deserves verification during real-world flood episodes, even though it appears to be more reliable than crowdsourcing strategies, and seems to have potential to better address real-time rescues and relief supplies.
INTRODUCTION: Haemagogus are mosquitoes with diurnal habits that live preferentially in forest areas. In Brazil, they are considered the primary vectors of wild yellow fever. METHODS: The ecological relationships between Haemagogus spegazzinii, the environment, and some of its activities in the semiarid region of Rio Grande do Norte were analyzed by collecting eggs with ovitraps, actively searching in tree holes, capturing adults in Shannon traps, and conducting an investigation for viral infections. RESULTS: A total of 2420 eggs, 271 immature specimens (larvae and pupae), and 206 adults were collected. Egg collection depended on rainfall and relative humidity, with oviposition occurring between January and May. Larvae were found in five plant species, including Tabebuia aurea (craibeira), with 160 larvae collected. We observed shared breeding sites between Hg. spegazzinii and the following species: Aedes albopictus, Aedes terrens, Culex spp., and Toxorhynchites theobaldi. Adults exhibited greater activity between 5 pm and 6 pm, when 191 (92.7%) specimens were captured, while only 1 (0.5%) was collected between 7 pm and 8 pm. The relationship between Hg. spegazzinii and rainfall was significant, with positive correlations with accumulated rainfall 5, 10, 15, 20, and 30 days before mosquito collection. We found that the species was infected with the DENV-2 virus. CONCLUSIONS: This work contributes new information on the bioecology of Hg. spegazzinii, with data on the main reproduction periods, oviposition, breeding sites, activity times, and the relationship between the species and meteorological variables in the Caatinga of northeastern Brazil.
Objective: To establish a spatial geo-database for scorpions in Iran, and to identify the suitable ecological niches for the most dangerous scorpion species under different climate change scenarios. Methods: The spatial distribution of six poisonous scorpion species of Iran were modeled: Hemiscorpius lepturus, Androctonus crassicauda, Mesobuthus eupeus, Hottentotta saulcyi, Hottentotta zagrosensis, and Odontobuthus (O.) doriae, under RCP2.6 and RCP8.5 climate change scenarios. The MaxEnt ecological niche model was used to predict climate suitability for these scorpion species in the 2030s and 2050s, and the data were compared with environmental suitability under the current bioclimatic data. Results: A total of 73 species and subspecies of scorpions belonging to 19 genera in Iran were recorded. Khuzestan Province has the highest species diversity with 34 species and subspecies. The most poisonous scorpion species of Iran are scattered in the semi-arid climates, at an altitudinal range between 11 m and 2 954 m above sea level. It is projected that O. doriae, Androctonus crassicauda and Mesobuthus eupeus species would be widely distributed in most parts of the country, whereas the most suitable ecological niches for the other species would be limited to the west and/or southwestern part of Iran. Conclusions: Although the environmental suitability for all the species would change under the two climate change scenarios, the change would be more significant for O. doriae under RCP8.5 in the 2050s. These findings can be used as basis for future studies in the areas with the highest environmental suitability for the most dangerous scorpion species to fill the gaps in the ecology of scorpion species in these areas.
Increasing population and economic growth has intensified water supply pressure on the Olifants River Basin causing it to become water-stressed. Climate change is expected to aggravate existing water supply challenges in the basin if urgent interventions are not implemented. This study evaluates the impacts of climate change on water availability and demand in the Olifants River Basin of South Africa, and assesses to what extent a combination of management strategies can mitigate current and longer term impacts using the Water Evaluation and Planning (WEAP) model. The results demonstrated by the two projected climate change scenarios (RCP4.5 and RCP8.5) showed a rise in temperature of approximately 1 degrees C-4 degrees C, and a decrease in precipitation of 5%-30%, as compared to the baseline climate of 1976-2005. Results also showed that pressure on water supply due to increased economic activities and a decline in streamflow will increase unmet water demand by 58% and 80% for the mid and end century periods respectively. Results further revealed that the combination of management measures proposed by decision makers is expected to decrease future unmet water demand from 1006MCM to 398MCM, 1205MCM to 872MCM and 1251MCM to 940MCM for reference, RCP4.5 and RCP 8.5 scenario respectively. The study therefore concludes that the combination of management strategies provides a much better and more efficient solution to water scarcity issues in the basin, compared to a reliance on a single strategy.
Climatic variability affects many underlying determinants of child malnutrition, including food availability, access, and utilization. Evidence of the effects of changing temperatures and precipitation on children’s nutritional status nonetheless remains limited. Research addressing this knowledge gap is merited given the shortand long-run consequences of malnutrition. We address this issue by estimating the effects of temperature and precipitation anomalies on the weight and wasting status of children ages 0-59 months across 18 countries in sub-Saharan Africa. Linear regression models show that high temperatures and low precipitation are associated with reductions in child weight, and that high temperatures also lead to increased risk of wasting. We find little evidence of substantively meaningful differences in these effects across sub-populations of interest. Our results underscore the vulnerability of young children to climatic variability and its second-order economic and epidemiological effects. The study also highlights the corresponding need to design and assess interventions to effectively mitigate these impacts.
Background: Rotavirus diarrhea is often referred as “winter diarrheal disease” as it causes nearly 50% of the pediatric hospitalizations during winter season. This study was done with the objective of bringing out the epidemiological nexus of rotavirus cases with different seasonal parameters like maximum, minimum temperature, humidity, and average rainfall. Methods: This prospective observational study was conducted in a tertiary care teaching hospital of Eastern India from February 2016 to December 2018. Data on daily maximum and minimum temperature, relative humidity, and rainfall were collected. Result: Of 964 children admitted, 768 stool samples were collected for rotavirus assay. A total of 222 children (29%) were positive. The maximum, minimum temperature, average rainfall, and average humidity of 83.4 mm, 79.2%, 28.1, and 21.9, respectively, were significantly associated with positive rotaviral cases. Conclusions: The incidence of rotavirus positivity cases was found to be inversely associated with average temperature, humidity, and rainfall. The knowledge about the seasonal pattern in a particular geographical area would help in the reallocation of hospital services (staff and bed) to tackle the epidemic or emergency situations resulting from clustering of cases.
While the associations of heat with health outcomes is well researched, there is less consensus on the measures used to define heat exposure and the short-term and delayed impacts of different temperature metrics on health outcomes. We investigate the nonlinear and short-term relationship of three temperature metrics and reported incidence of three gastrointestinal illnesses: salmonellosis, campylobacteriosis and cryptosporidiosis in the Australian Capital Territory (ACT). We also examine the nonlinear association of these illnesses with extreme heat (5th, 75th, 90th percentile of all heat measures). Generalized linear models with Poisson regression accounting for overdispersion, seasonal and long-term trend, weekly number of outbreaks and rainfall were developed for mean and maximum weekly temperature and the heat stress index (EHI(accl)). Bacterial illnesses (salmonellosis and campylobacteriosis) showed an overall positive association with extreme heat (75th and 90th percentile of all three heat measures) and an inverse association with low temperature (5th percentile). The shape of the exposure-response curve across a range of temperatures and the lagged effects varied for each disease. Modelling the short-term and delayed effects of heat using different metrics across a range of illnesses can help identify the most appropriate measure to inform local public health intervention planning for heat-related emergencies.
Aims: Leptospirosis is an infectious disease that is endemic to many tropical regions. Large epidemics usually happen after heavy rainfall and flooding. This potentially fatal zoonosis is caused by pathogenic bacteria belonging to the genus Leptospira. Leptospirosis can be diagnosed using specific biomarkers such as target genes and virulence indicators that are well preserved across various Leptospira spp., including those that are prevalent in clinical samples and in the environment. To date, several pathogenicity-determinant genes, including lipL32 and lipL41, have been described and used for diagnosing leptospirosis. However, prevalence of these genes in leptospiral strains is unclear. Methodology and results: In the present study, we assessed the distribution of eight pathogenicity-determinant genes in reference Leptospira strains and environmental isolates in Malaysia, by polymerase chain reaction (PCR). We found that only lipL32 and ligB were consistently expressed in all pathogenic Leptospira strains compared with the other tested genes. Moreover, our results suggested that the use of lipL41, lipL21, ompL1, lfb1, ligA, and ligC as biomarkers could incorrectly misdetect pathogenic Leptospira strains present in the environment. Conclusion: Thus, our results suggest that the pathogenicity-determinant genes lipL32 and ligB can be used as biomarkers for detection pathogenic Leptospira.
The history of the Eastern Mediterranean is punctuated by major crises that have influenced many of the region’s established socioeconomic models. Recent studies have underscored the role of drought and temperature oscillations in driving changes but attempts to quantify their magnitude remain equivocal, hindering long-term assessments of the potential interplay between climate and society. Here, we fill this knowledge gap using a 6,000-year pollen-based reconstruction of temperature and precipitation from Hala Sultan Tekke, Cyprus. We find that major social changes and plague outbreaks often occurred in tandem with cooler climate conditions, with anomalies ranging from -3 +/- 0.4 degrees C to -1 +/- 0.5 degrees C, coupled with changing precipitation patterns. We suggest that major climate changes may weaken societies by affecting primary livelihood systems. This long-term view highlights recurrent cold periods in the Eastern Mediterranean’s climate history and advocates that, despite frequent adversity and pandemics, Near Eastern populations adapted and were ultimately resilient to major climate changes.
BACKGROUND: Dengue, a febrile illness, is caused by a Flavivirus transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Climate influences the ecology of the vectors. We aimed to identify the influence of climatic variability on the occurrence of clinical dengue requiring hospitalization in Zone-5, a high incidence area of Dhaka City Corporation (DCC), Bangladesh. METHODS AND FINDINGS: We retrospectively identified clinical dengue cases hospitalized from Zone-5 of DCC between 2005 and 2009. We extracted records of the four major catchment hospitals of the study area. The Bangladesh Meteorological Department (BMD) provided data on temperature, rainfall, and humidity of DCC for the study period. We used autoregressive integrated moving average (ARIMA) models for the number of monthly dengue hospitalizations. We also modeled all the climatic variables using Poisson regression. During our study period, dengue occurred throughout the year in Zone-5 of DCC. The median number of hospitalized dengue cases was 9 per month. Dengue incidence increased sharply from June, and reached its peak in August. One additional rainy day per month increased dengue cases in the succeeding month by 6% (RR = 1.06, 95% CI: 1.04-1.09). CONCLUSIONS: Dengue is transmitted throughout the year in Zone-5 of DCC, with seasonal variation in incidence. The number of rainy days per month is significantly associated with dengue incidence in the subsequent month. Our study suggests the initiation of campaigns in DCC for controlling dengue and other Aedes mosquito borne diseases, including Chikunguniya from the month of May each year. BMD rainfall data may be used to determine campaign timing.
Snakebite envenoming is an important public health problem in Iran, despite its risk not being quantified. This study aims to use venomous snakes’ habitat suitability as an indicator of snakebite risk, to identify high-priority areas for snakebite management across the country. Thus, an ensemble approach using five distribution modelling methods: Generalized Boosted Models, Generalized Additive Models, Maximum Entropy Modelling, Generalized Linear Models, and Random Forest was applied to produce a spatial snakebite risk model for Iran. To achieve this, four venomous snakes’ habitat suitability (Macrovipera lebetinus, Echis carinatus, Pseudocerastes persicus and Naja oxiana) were modelled and then multiplied. These medically important snakes are responsible for the most snakebite incidents in Iran. Multiplying habitat suitability models of the four snakes showed that the northeast of Iran (west of Khorasan-e-Razavi province) has the highest snakebite risk in the country. In addition, villages that were at risk of envenoming from the four snakes were identified. Results revealed that 51,112 villages are at risk of envenoming from M. lebetinus, 30,339 from E. carinatus, 51,657 from P. persicus and 12,124 from N. oxiana. Precipitation seasonality was identified as the most important variable influencing distribution of the P. persicus, E. carinatus and M. lebetinus in Iran. Precipitation of the driest quarter was the most important predictor of suitable habitats of the N. oxiana. Since climatic variables play an important role in shaping the distribution of the four venomous snakes in Iran, thus their distribution may alter with changing climate. This paper demonstrates application of species distribution modelling in public health research and identified potential snakebite risk areas in Iran by using venomous snakes’ habitat suitability models as an indicating factor. Results of this study can be used in snakebite and human-snake conflict management in Iran. We recommend increasing public awareness of snakebite envenoming and education of local people in areas which identified with the highest snakebite risk.
BACKGROUND: Sedentary behavior is a worldwide public health concern. There is consistent and growing evidence linking sedentary behavior to mortality and morbidity. Early monitoring and assessment of environmental factors associated with sedentary behaviors at a young age are important initial steps for understanding children’s sedentary time and identifying pertinent interventions. OBJECTIVE: This study examines the association between daily temperature (maximum, mean, minimum, and diurnal variation) and all-day sedentary time among 4-6 year old children in Mexico City (n = 559) from the year 2013 to 2015. METHODS: We developed a spatiotemporally resolved hybrid satellite-based land use regression temperature model and calculated percent daily sedentary time from aggregating 10-second epoch vertical counts captured by accelerometers that participants wore for one week. We modeled generalized additive models (GAMs), one for each temperature type as a covariate (maximum, mean, minimum, and diurnal variation). All GAMs included percent all-day sedentary time as the outcome and participant-level random intercepts to account for repeated measures of sedentary time. Our models were adjusted for demographic factors and environmental exposures. RESULTS: Daily maximum temperature, mean temperature, and diurnal variation have significant negative linear relationships with all-day sedentary time (p<0.01). There is no significant association between daily minimum temperature and all-day sedentary time. Children have on average 0.26% less daily sedentary time (approximately 2.2 minutes) for each 1°C increase in ambient maximum temperature (range 7.1-30.2°C), 0.27% less daily sedentary time (approximately 2.3 minutes) for each 1°C increase in ambient mean temperature (range 4.3-22.2°C), and 0.23% less daily sedentary time (approximately 2.0 minutes) for each 1°C increase in diurnal variation (range 3.0-21.6°C). CONCLUSIONS: These results are contrary to our hypothesis in which we expected a curvilinear relationship between temperature (maximum, mean, minimum, and diurnal variation) and sedentary time. Our findings suggest that temperature is an important environmental factor that influences children’s sedentary behavior.
Following a distinct summer heat wave, nine autochthonous cases of West Nile fever and West Nile neuroinvasive disease, including one fatality, were observed in Leipzig, Germany, in August and September 2020. Phylogenetic analysis demonstrated close relationships in viruses from humans, animals and mosquitos in eastern Germany, obtained during the preceding 2 years. The described large cluster of autochthonous West Nile virus infections in Germany indicates endemic seasonal circulation of lineage 2 viruses in the area.
This paper describes the development of a scenario-based approach that couples 2D hydrodynamic modeling with Geographic Information System (GIS) network analysis to assess the vulnerability of emergency services to surface water flooding at a large city scale. The method is demonstrated for Emergency Medical Service and Fire & Rescue Service in the city of Shanghai, China. Considering four representative traffic conditions, accessibility in terms of service area, response time, and population coverage within specified timeframes (8-, 12-, and 15-minute for Emergency Medical Service and 5-, 10-, and 15-minute for Fire & Rescue Service) is quantified and mapped under normal as well as pluvial flood scenarios of various magnitudes (5-, 20-, and 100-year return periods). Results show that the performance of operational responses largely depends on the functioning of transportation system, dramatically decreasing from unobstructed to congested traffic. Surface water flooding is found to result in limited (i.e. site-specific) but nonlinear impacts on the city-wide emergency service provisions. The results provide detailed information for optimizing the distribution of emergency stations and developing strategic contingency planning for vulnerable populations and facilities.
Compound dry and hot events (CDHEs) are commonly defined as occurrences of dry and hot events at the same time or in close succession. These events have occurred frequently in past decades and caused great losses to multiple sectors including water security, food security, and human health. This calls for an improved understanding of their characteristics and variations. This study provides a database for different characteristics, including frequency, severity, duration, and magnitude, and their variations of CDHEs for the period 1951-2012 over global land areas. We first demonstrate different characteristics of CDHEs during the summers of 2003 and 2010 in Europe to compare these two events from different perspectives. We then evaluate changes in different characteristics of CDHEs over global land areas for the past 62 years. The frequency, severity, duration, and magnitude of CDHEs during 1951-2012 show temporal increases over global land areas with the slope of 0.15 days/decade, 0.25%/decade, 0.06 days/decade, and 0.52%/decade, respectively. Besides, remarkable increases in these characteristics are observed in regions such as central Africa, Europe, Mediterranean regions, and northern parts of East Asia. The results of this study could shed light on ways to improve the documentation and understanding of CDHEs to mitigate their negative impacts.
