Inconsistencies were discovered in the findings regarding the effects of meteorological factors on tuberculosis (TB). This study conducted a systematic review of published studies on the relationship between TB and meteorological factors and used a meta-analysis to investigate the pooled effects in order to provide evidence for future research and policymakers. The literature search was completed by August 3rd, 2021, using three databases: PubMed, Web of Science and Embase. Relative risks (RRs) in included studies were extracted and all effect estimates were combined together using meta-analysis. Subgroup analyses were carried out based on the resolution of exposure time, regional climate, and national income level. A total of eight studies were included after screening for inclusion and exclusion criteria. Our results show that TB risk was positively correlated with precipitation (RR = 1.32, 95% CI: 1.14, 1.51), while temperature (RR = 1.15, 95% CI: 1.00, 1.32), humidity (RR = 1.05, 95% CI: 0.99, 1.10), air pressure (RR = 0.89, 95% CI: 0.69, 1.14) and sunshine duration (RR = 0.95, 95% CI: 0.80, 1.13) all had no statistically significant correlation. Subgroup analysis shows that quarterly measure resolution, low and middle Human Development Index (HDI) level and subtropical climate increase TB risk not only in precipitation, but also in temperature and humidity. Moreover, less heterogeneity was observed in “high and extremely high” HDI areas and subtropical areas than that in other subgroups (I(2) = 0%). Precipitation, a subtropical climate, and a low HDI level are all positive influence factors to tuberculosis. Therefore, residents and public health managers should take precautionary measures ahead of time, especially in extreme weather conditions.
INTRODUCTION: Reunion Island is a French overseas department characterized by a tropical climate with 2 distinct seasons. While the prevalence of asthma among adults in Reunion Island is close to that in mainland France, mortality and hospitalization rates are twice as high. To date, however, no epidemiological studies have evaluated the influence of environmental factors in asthma exacerbations in Reunion Island. METHODS: From January 2010 to June 2013, 1157 residents of Saint-Denis visited the emergency rooms of the Centre hospitalier universitaire site Nord de Saint-Denis for asthma. After exclusion of children under the age of 3, 864 visits were analyzed. These were correlated with the following daily factors: pollens and molds, meteorological parameters (temperature, precipitation levels, humidity and relative humidity levels, wind), pollutants (sulfur dioxide (SO(2)), nitrogen oxide (NO(x)), and the fine particles PM(10) and PM(2.5)), and the influenza virus. The correlation between these factors was evaluated using the DLNM and GO-GARCH models. RESULTS: Of the 864 analyzed visits, 532 were by pediatric patients (aged 3 to 16 years) and 332 by adult patients (aged over 16 years). In adults, pollens positively correlated with asthma exacerbations were Urticaceae, Oleaceae, Moraceae, and Chenopodiaceae. In children, these were Urticaceae, Oleaceae, Poaceae, and Myrtaceae. Molds positively correlated with asthma exacerbations in adults were ascospores and basidiospores. Only basidiospores were positively correlated with exacerbations in children. Temperature was positively correlated with exacerbations in both adults and children. The pollutants PM(10) and NO(x) were positively correlated with exacerbations in children. Influenza epidemics were strongly correlated with exacerbations in both adults and children. CONCLUSION: Our analysis shows that in Reunion Island, asthma is exacerbated by pollens (Urticaceae, Oleaceae, Moraceae, Chenopodiaceae in adults; Urticaceae, Oleaceae, Poaceae, Myrtaceae in children), molds (ascospores and basidiospores in adults; basidiospores in children), temperature, influenza, and the pollutants PM(10) and NO(x) (in children).
The climate is changing, and such changes are projected to cause global increase in the prevalence and geographic ranges of infectious diseases such as anthrax. There is limited knowledge in the tropics with regards to expected impacts of climate change on anthrax outbreaks. We determined the future distribution of anthrax in Kenya with representative concentration pathways (RCP) 4.5 and 8.5 for year 2055. Ecological niche modelling (ENM) of boosted regression trees (BRT) was applied in predicting the potential geographic distribution of anthrax for current and future climatic conditions. The models were fitted with presence-only anthrax occurrences (n = 178) from historical archives (2011-2017), sporadic outbreak surveys (2017-2018), and active surveillance (2019-2020). The selected environmental variables in order of importance included rainfall of wettest month, mean precipitation (February, October, December, July), annual temperature range, temperature seasonality, length of longest dry season, potential evapotranspiration and slope. We found a general anthrax risk areal expansion i.e., current, 36,131 km(2), RCP 4.5, 40,012 km(2), and RCP 8.5, 39,835 km(2). The distribution exhibited a northward shift from current to future. This prediction of the potential anthrax distribution under changing climates can inform anticipatory measures to mitigate future anthrax risk.
Global demand for agricultural products continues to grow. However, efforts to boost productivity exacerbate existing pressures on nature, both on farms and in the wider landscape. There is widespread appreciation of the critical need to achieve balance between biodiversity and human well-being in rural tropical crop production landscapes, that are essential for livelihoods and food security. There is limited empirical evidence of the interrelationships between natural capital, the benefits and costs of nature and its management, and food security in agricultural landscapes. Agroforestry practices are frequently framed as win-win solutions to reconcile the provision of ecosystem services important to farmers (i.e., maintaining soil quality, supporting pollinator, and pest control species) with nature conservation. Yet, underlying trade-offs (including ecosystem disservices linked to pest species or human-wildlife conflicts) and synergies (e.g., impact of ecosystem service provision on human well-being) are seldom analysed together at the landscape scale. Here, we propose a systems model framework to analyse the complex pathways, with which natural capital on and around farms interacts with human well-being, in a spatially explicit manner. To illustrate the potential application of the framework, we apply it to a biodiversity and well-being priority landscape in the Southern Agricultural Growth Corridor of Tanzania, a public-private partnership for increasing production of cash and food crops. Our framework integrates three main dimensions: biodiversity (using tree cover and wildlife as key indicators), food security through crop yield and crop health, and climate change adaptation through microclimate buffering of trees. The system model can be applied to analyse forest-agricultural landscapes as socio-ecological systems that retain the capacity to adapt in the face of change in ways that continue to support human well-being. It is based on metrics and pathways that can be quantified and parameterised, providing a tool for monitoring multiple outcomes from management of forest-agricultural landscapes. This bottom-up approach shifts emphasis from global prioritisation and optimisation modelling frameworks, based on biophysical properties, to local socio-economic contexts relevant in biodiversity-food production interactions across large parts of the rural tropics.
The ability of poor urban populations in developing countries to adapt to rapid increase in surface temperature and likely health effect of a 1.5 °C increase in global temperature is uncertain. Rapid urbanization and poor socio, economic, and technological development may increase heat vulnerabilities of poor urban populations in tropical cities. This study examines the thermal perception of urban populations in Ibadan, south western Nigeria, and sociodemographic characteristics of individuals that influence thermal perception, self-reported health effects, and coping strategies to heat stress using a purposefully designed questionnaire and interviews with aged individuals in the five local government areas of Ibadan metropolis. Differences in sociodemographic characteristics of respondents such as inequalities in monthly income, occupation, ethnicity, housing characteristics, and length of stay in Ibadan significantly influence thermal perception, self-reported health effects of heat exposure, and coping strategies adopted. Perceived thermal conditions reported were warmer temperatures during the day and night (43.75%), warmer day-time temperatures (40.25%), and warmer night-time temperatures (16%). Dehydration and sweating (56%): heat rash, heat exhaustion, headaches, sleep disturbances and dehydration (15.25%), and sleep disturbance and sweating (12.25%) were major combinations of self-reported health effects. Other effects include fainting, diarrhea, raised blood pressure, and restlessness. Temperature variations (minimum and maximum) examined from 1971 to 2018 shows that warmer conditions are being experienced in Ibadan. Increased heat-health awareness and urban designs that respond to people’s thermal perception should be encouraged in developing thermally comfortable environments in Ibadan.
Both climate change and rapid urbanization accelerate exposure to heat in the city of Kampala, Uganda. From a network of low-cost temperature and humidity sensors, operational in 2018-2019, we derive the daily mean, minimum and maximum Humidex in order to quantify and explain intra-urban heat stress variation. This temperature-humidity index is shown to be heterogeneously distributed over the city, with a daily mean intra-urban Humidex Index deviation of 1.2 degrees C on average. The largest difference between the coolest and the warmest station occurs between 16:00 and 17:00 local time. Averaged over the whole observation period, this daily maximum difference is 6.4 degrees C between the warmest and coolest stations, and reaches 14.5 degrees C on the most extreme day. This heat stress heterogeneity also translates to the occurrence of extreme heat, shown in other parts of the world to put local populations at risk of great discomfort or health danger. One station in a dense settlement reports a daily maximum Humidex Index of >40 degrees C in 68% of the observation days, a level which was never reached at the nearby campus of the Makerere University, and only a few times at the city outskirts. Large intra-urban heat stress differences are explained by satellite earth observation products. Normalized Difference Vegetation Index has the highest (75%) power to predict the intra-urban variations in daily mean heat stress, but strong collinearity is found with other variables like impervious surface fraction and population density. Our results have implications for urban planning on the one hand, highlighting the importance of urban greening, and risk management on the other hand, recommending the use of a temperature-humidity index and accounting for large intra-urban heat stress variations and heat-prone districts in urban heat action plans for tropical humid cities.
Malaria is a critical health issue across the world and especially in Africa. Studies based on dynamical models helped to understand inter-linkages between this illness and climate. In this study, we evaluated the ability of the VECTRI community vector malaria model to simulate the spread of malaria in Cameroon using rainfall and temperature data from FEWS-ARC2 and ERA-interim, respectively. In addition, we simulated the model using five results of the dynamical downscaling of the regional climate model RCA4 within two time frames named near future (2035-2065) and far future (2071-2100), aiming to explore the potential effects of global warming on the malaria propagation over Cameroon. The evaluated metrics include the risk maps of the entomological inoculation rate (EIR) and the parasite ratio (PR). During the historical period (1985-2005), the model satisfactorily reproduces the observed PR and EIR. Results of projections reveal that under global warming, heterogeneous changes feature the study area, with localized increases or decreases in PR and EIR. As the level of radiative forcing increases (from 2.6 to 8.5 W.m(-2)), the magnitude of change in PR and EIR also gradually intensifies. The occurrence of transmission peaks is projected in the temperature range of 26-28 °C. Moreover, PR and EIR vary depending on the three agro-climatic regions of the study area. VECTRI still needs to integrate other aspects of disease transmission, such as population mobility and intervention strategies, in order to be more relevant to support actions of decision-makers and policy makers.
Non-typhoidal Salmonella (NTS) ranks first among causes of bloodstream infection in children under five years old in the Democratic Republic of Congo and has a case fatality rate of 15%. Main host-associated risk factors are Plasmodium falciparum malaria, anemia and malnutrition. NTS transmission in sub-Saharan Africa is poorly understood. NTS bloodstream infections mostly occur during the rainy season, which may reflect seasonal variation in either environmental transmission or host susceptibility. We hypothesized that environment- and host-associated factors contribute independently to the seasonal variation in NTS bloodstream infections in children under five years old admitted to Kisantu referral hospital in 2013-2019. We used remotely sensed rainfall and temperature data as proxies for environmental factors and hospital data for host-associated factors. We used principal component analysis to disentangle the interrelated environment- and host-associated factors. With timeseries regression, we demonstrated a direct association between rainfall and NTS variation, independent of host-associated factors. While the latter explained 17.5% of NTS variation, rainfall explained an additional 9%. The direct association with rainfall points to environmental NTS transmission, which should be explored by environmental sampling studies. Environmental and climate change may increase NTS transmission directly or via host susceptibility, which highlights the importance of preventive public health interventions.
The Greater Accra Region is the smallest of the 16 administrative regions in Ghana. It is highly populated and characterized by tropical climatic conditions. Although efforts towards malaria control in Ghana have had positive impacts, malaria remains in the top five diseases reported at healthcare facilities within the Greater Accra Region. To further accelerate progress, analysis of regionally generated data is needed to inform control and management measures at this level. This study aimed to examine the climatic drivers of malaria transmission in the Greater Accra Region and identify inter-district variation in malaria burden. Monthly malaria cases for the Greater Accra Region were obtained from the Ghanaian District Health Information and Management System. Malaria cases were decomposed using seasonal-trend decomposition, based on locally weighted regression to analyze seasonality. A negative binomial regression model with a conditional autoregressive prior structure was used to quantify associations between climatic variables and malaria risk and spatial dependence. Posterior parameters were estimated using Bayesian Markov chain Monte Carlo simulation with Gibbs sampling. A total of 1,105,370 malaria cases were recorded in the region from 2015 to 2019. The overall malaria incidence for the region was approximately 47 per 1000 population. Malaria transmission was highly seasonal with an irregular inter-annual pattern. Monthly malaria case incidence was found to decrease by 2.3% (95% credible interval: 0.7-4.2%) for each 1 °C increase in monthly minimum temperature. Only five districts located in the south-central part of the region had a malaria incidence rate lower than the regional average at >95% probability level. The distribution of malaria cases was heterogeneous, seasonal, and significantly associated with climatic variables. Targeted malaria control and prevention in high-risk districts at the appropriate time points could result in a significant reduction in malaria transmission in the Greater Accra Region.
Malaria remains a serious public health challenge in Ghana including the Greater Accra Region. This study aimed to quantify the spatial, temporal and spatio-temporal patterns of malaria in the Greater Accra Region to inform targeted allocation of health resources. Malaria cases data from 2015 to 2019 were obtained from the Ghanaian District Health Information and Management System and aggregated at a district and monthly level. Spatial analysis was conducted using the Global Moran’s I, Getis-Ord Gi*, and local indicators of spatial autocorrelation. Kulldorff’s space-time scan statistics were used to investigate space-time clustering. A negative binomial regression was used to find correlations between climatic factors and sociodemographic characteristics and the incidence of malaria. A total of 1,105,370 malaria cases were reported between 2015 and 2019. Significant seasonal variation was observed, with June and July being the peak months of reported malaria cases. The hotspots districts were Kpone-Katamanso Municipal District, Ashaiman Municipal Districts, Tema Municipal District, and La-Nkwantanang-Madina Municipal District. While La-Nkwantanang-Madina Municipal District was high-high cluster. The Spatio-temporal clusters occurred between February 2015 and July 2017 in the districts of Ningo-Prampram, Shai-Osudoku, Ashaiman Municipal, and Kpone-Katamanso Municipal with a radius of 26.63 km and an relative risk of 4.66 (p < 0.001). Malaria cases were positively associated with monthly rainfall (adjusted odds ratio [AOR] = 1.01; 95% confidence interval [CI] = 1.005, 1.016) and the previous month's cases (AOR = 1.064; 95% CI 1.062, 1.065) and negatively correlated with minimum temperature (AOR = 0.86, 95% CI = 0.823, 0.899) and population density (AOR = 0.996, 95% CI = 0.994, 0.998). Malaria control and prevention should be strengthened in hotspot districts in the appropriate months to improve program effectiveness.
Malaria is among the greatest public health threats in Mozambique, with over 10 million cases reported annually since 2018. Although the relationship between seasonal trends in environmental parameters and malaria cases is well established, the role of climate in deviations from the annual cycle is less clear. To investigate this and the potential for leveraging inter-annual climate variability to predict malaria outbreaks, weekly district-level malaria incidence spanning 2010-2017 were processed for a cross-analysis with climate data. An empirical orthogonal function analysis of district-level malaria incidence revealed two dominant spatiotemporal modes that collectively account for 81% of the inter-annual variability of malaria: a mode dominated by variance over the southern half of Mozambique (64%), and another dominated by variance in the northern third of the country (17%). These modes of malaria variability are shown to be closely related to precipitation. Linear regression of global sea surface temperatures onto local precipitation indices over these variance maxima links the leading mode of inter-annual malarial variability to the El Nino-Southern Oscillation, such that La Nina leads to wetter conditions over southern Mozambique and, therefore, higher malaria prevalence. Similar analysis of spatiotemporal patterns of precipitation over a longer time period (1979-2019) indicate that the Subtropical Indian Ocean Dipole is both a strong predictor of regional precipitation and the climatic mechanism underlying the second mode of malarial variability. These results suggest that skillful malaria early warning systems may be developed that leverage quasi-predictable modes of inter-annual climate variability in the tropical oceans. Plain Language Summary Malaria is one of the main public health concerns in Mozambique, with millions of reported cases in the country each year. While malaria has been tied to monthly swings in rainfall and temperature, its relationship to year-to-year changes of the climate is less well known. We identified regions where local malaria cases varied together and found two main patterns: a main hotspot over the southern half of Mozambique, and a second hotspot over the northern third of the country. Rainfall drives both of these hotspots. We then tied these patterns to two natural climate phenomena, the El Nino-Southern Oscillation and the Subtropical Indian Ocean Dipole, both of which impact the climate of the region and help drive malaria prevalence. Our results suggest that it may be possible to take advantage of the predictability of these climate phenomena to improve public health planning both in Mozambique and more broadly.
BACKGROUND: This study aimed to assess the seasonality of confirmed malaria cases in Togo and to provide new indicators of malaria seasonality to the National Malaria Control Programme (NMCP). METHODS: Aggregated data of confirmed malaria cases were collected monthly from 2008 to 2017 by the Togo’s NMCP and stratified by health district and according to three target groups: children < 5 years old, children ≥ 5 years old and adults, and pregnant women. Time series analysis was carried out for each target group and health district. Seasonal decomposition was used to assess the seasonality of confirmed malaria cases. Maximum and minimum seasonal indices, their corresponding months, and the ratio of maximum/minimum seasonal indices reflecting the importance of malaria transmission, were provided by health district and target group. RESULTS: From 2008 to 2017, 7,951,757 malaria cases were reported in Togo. Children < 5 years old, children ≥ 5 years old and adults, and pregnant women represented 37.1%, 57.7% and 5.2% of the confirmed malaria cases, respectively. The maximum seasonal indices were observed during or shortly after a rainy season and the minimum seasonal indices during the dry season between January and April in particular. In children < 5 years old, the ratio of maximum/minimum seasonal indices was higher in the north, suggesting a higher seasonal malaria transmission, than in the south of Togo. This is also observed in the other two groups but to a lesser extent. CONCLUSIONS: This study contributes to a better understanding of malaria seasonality in Togo. The indicators of malaria seasonality could allow for more accurate forecasting in malaria interventions and supply planning throughout the year.
Dengue fever is a systemic viral infection of epidemic proportions in tropical countries. The incidence of dengue fever is ever increasing and has doubled over the last few decades. Estimated 50million new cases are detected each year and close to 10000 deaths occur each year. Epidemics are unpredictable and unprecedented. When epidemics occur, health services are over whelmed leading to overcrowding of hospitals. At present there is no evidence that dengue epidemics can be predicted. Since the breeding of the dengue mosquito is directly influenced by environmental factors, it is plausible that epidemics could be predicted using weather data. We hypothesized that there is a mathematical relationship between incidence of dengue fever and environmental factors and if such relationship exists, new cases of dengue fever in the succeeding months can be predicted using weather data of the current month. We developed a mathematical model using machine learning technique. We used Island wide dengue epidemiology data, weather data and population density in developing the model. We used incidence of dengue fever, average rain fall, humidity, wind speed, temperature and population density of each district in the model. We found that the model is able to predict the incidence of dengue fever of a given month in a given district with precision (RMSE between 18- 35.3). Further, using weather data of a given month, the number of cases of dengue in succeeding months too can be predicted with precision (RMSE 10.4-30). Health authorities can use existing weather data in predicting epidemics in the immediate future and therefore measures to prevent new cases can be taken and more importantly the authorities can prepare local authorities for outbreaks.
The effects of climate on infectious diseases could influence the health impacts, particularly in children in countries with the unfair socioeconomic conditions. In a prospective cohort of 461 children under 16-years-of-age in Varanasi city, India, the association of maximum-temperature (Tmax), relative humidity (RH), absolute humidity (AH), rainfall (RF), wind-speed (WS), and solar radiation (SLR) with prevalent infectious diseases (Diarrhea, Common cold and flu, Pneumonia, Skin-disease and Malaria, and Dengue) was examined using binomial-regression, adjusting for confounders and effect modifiers (socioeconomic-status; SES and child anthropometry), from January 2017 to January 2020. Attributable-fraction (AFx) was calculated due to each climate variable for each infectious disease. The result showed that each unit (1 °C) rise in Tmax was associated with an increase in diarrhea and skin-disease cases by 3.97% (95% CI: 2.92, 5.02) and 3.94% (95% CI: 1.67, 6.22), respectively, whereas, a unit decline in Tmax was associated with an increase in cold and flu cases by 3.87% (95% CI: 2.97, 4.76). Rise in humidity (RH) was associated with increase in cases of cold and flu by 0.73% (95% CI: 0.38, 1.08) and malaria (AH) by 7.19% (95% CI: 1.51, 12.87) while each unit (1 g/m(3)) decrease in humidity (AH) observed increase in pneumonia cases by 3.02% (95% CI: 0.75, 5.3). WS was positively associated with diarrhea (14.16%; 95% CI: 6.52, 21.80) and negatively with dengue (17.40%; 12.32, 22.48) cases for each unit change (kmph). RF showed marginal association while SLR showed no association at all. The combined AFx due to climatic factors ranged from 9 to 18%. SES and anthropometric parameters modified the climate-morbidity association in children with a high proportion of children found suffering from stunting, wasting, and underweight conditions. Findings from this study draw the attention of government and policymakers to prioritize effective measures for child health as the present association may increase disease burden in the future under climate-change scenarios in already malnourished paediatric population through multiple pathways.
Background: Climate change is evident around the globe causing heat stress as an emerging public health problem for people working in tropical and subtropical areas. Occupational heat stress can impact the health and productivity of small and mid-sized enterprise workers. Objective: This study aimed to profile the indoor thermal environmental conditions and modify the working practices by recommending the work/rest cycle according to the international organization for standardization 7243. Study Design: This cross-sectional study design included eight industrial (Iron spare parts manufacturing) small and mid-size enterprises in Lahore, Pakistan. The indoor thermal environment, including globe temperature, natural wet bulb temperature, ambient temperature, relative humidity, and air velocity, were recorded during summer to measure the wet bulb globe temperature (WBGT). Quest heat stress meter (model 2500), modified Testo loggers (177-T4), and EL-USB-2-LCD data loggers were placed at different working stations to measure these thermal environmental parameters. A self-administered questionnaire was used to measure the workers’ demographic characteristics and working practices. The International Organization for Standardization 7243 reference was used to estimate and recommend the work/rest cycle. Results: 138 workers aged 28.59 +/- 10.46 years participated in this study. Continuous work of 8.8 +/- 1.5 hours per day with a conventional resting period of 30-60 minutes was recorded on a typical working day. The indoor wet bulb globe temperature ranged from 26.8 degrees C to 36.4 degrees C. The workers were registered for low (72.5%), moderate (18.1%), and high (9.4%) metabolic rates according to the International Organization for Standardization 7243 reference values. Conclusion: A high wet bulb globe temperature was recorded in the selected small and mid-sized enterprises making these workers vulnerable to heat stress and related illnesses. Work/rest cycle evaluation suggested that the workers were required to improve their cool-down time by avoiding continuous exposure to high temperatures and reducing the metabolic rate.
Due to global warming, increase in air temperature is a growing concern at present. This rise in temperature may cause mild to severe thermal discomfort and heat related hazards mostly for the people who are engaged in outside activities throughout the day. The present study shows the inter-spatial monthly distribution of thermal patches over major stations of Madhya Pradesh, viz., Bhopal, Gwalior, Indore, Jabalpur, Hoshangabad, Rewa, Ratlam, Ujjain, Dhar etc. In this study, various Heat Indices applicable for tropical climate including Wet Bulb Globe Temperature (WBGT) are used to estimate the thermal stress by analyzing the meteorological data of Summer-2018 in Madhya Pradesh. Study was carried out for computing indoor, shady and outdoor heat stress separately and heat transfer rates to identify the places vulnerable to severe heat stroke in the month of March, April and May in 2018.It is observed that declaration of heat wave alone at any station is not sufficient for the administration and health organizations to take precautionary actions; also, discomfort indices should be referred for impact based monitoring and making work schedules. It is found that March and April fall in the partial discomfort category for at least half of the districts in Madhya Pradesh. It is interesting to note that several districts fall in discomfort category in outdoor conditions but not in indoor or shady conditions in May month. Severe stresses are observed mainly in the West and Central Madhya Pradesh during April and May months. Comparison of various Heat Indices is too performed along with computing Tropical Summer Index (TSI) and Apparent Temperature (AT) to indicate real feel-like temperatures in Madhya Pradesh during extreme temperature events.
BACKGROUND: Studies on high temperatures and mortality have not focused on underdeveloped tropical regions and have reported the associations of different temperature metrics without conducting model selection. METHODS: We collected daily mortality and meteorological data including ambient temperatures and humidity in Ahmedabad during summer, 1987-2017. We proposed two cross-validation (CV) approaches to compare semiparametric quasi-Poisson models with different temperature metrics and heat wave definitions. Using the fittest model, we estimated heat-mortality associations among general population and subpopulations. We also conducted separate analyses for 1987-2002 and 2003-2017 to evaluate temporal heterogeneity. FINDINGS: The model with maximum and minimum temperatures and without heat wave indicator gave the best performance. With this model, we found a substantial and significant increase in mortality rate starting from maximum temperature at 42 °C and from minimum temperature at 28 °C: 1 °C increase in maximum and minimum temperatures at lag 0 were associated with 9.56% (95% confidence interval [CI]: 6.64%, 12.56%) and 9.82% (95% CI: 6.33%, 13.42%) increase in mortality risk, respectively. People aged ≥65 years and lived in South residential zone where most slums were located, were more vulnerable. We observed flatter increases in mortality risk associated with high temperatures comparing the period of 2003-2017 to 1987-2002. INTERPRETATION: The analyses provided better understanding of the relationship of high temperatures with mortality in underdeveloped tropical regions and important implications in developing heat warning system for local government. The proposed CV approaches will benefit future scientific work.
The elderly are one of the most vulnerable groups to heat-related illnesses and mortality. In tropical countries like India, where heat waves have increased in frequency and severity, few studies have focused on the level of stress experienced by the elderly. The study presented here included 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages about 75 km south of Kolkata. It used miniature monitoring devices to continuously measure temperature, humidity, and heat index experienced during everyday activities over 24-h study periods, during hot summer months. In the Kolkata slum, construction materials and the urban heat island effect combined to create hotter indoor than outdoor conditions throughout the day, and particularly at night. As a result, elderly slum residents were 4.3 times more likely to experience dangerous heat index levels (≥ 45°C) compared to rural village elderly. In both locations, the median 24-h heat indexes of active elderly were up to 2°C higher than inactive/sedentary elderly (F = 25.479, p < 0.001). Among Kolkata slums residents, there were no significant gender differences in heat exposure during the day or night, but in the rural village, elderly women were 4 times more likely to experience dangerous heat index levels during the hottest times of the day compared to elderly men. Given the decline in thermoregulatory capacity associated with aging and the increasing severity of extreme summer heat in India, these results forecast a growing public health challenge that will require both scientific and government attention.
Cholera is a water-borne infectious disease that affects 1.3 to 4 million people, with 21,000 to 143,000 reported fatalities each year worldwide. Outbreaks are devastating to affected communities and their prospects for development. The key to support preparedness and public health response is the ability to forecast cholera outbreaks with sufficient lead time. How Vibrio cholerae survives in the environment outside a human host is an important route of disease transmission. Thus, identifying the environmental and climate drivers of these pathogens is highly desirable. Here, we elucidate for the first time a mechanistic link between climate variability and cholera (Satellite Water Marker; SWM) index in the Bengal Delta, which allows us to predict cholera outbreaks up to two seasons earlier. High values of the SWM index in fall were associated with above-normal summer monsoon rainfalls over northern India. In turn, these correlated with the La Niña climate pattern that was traced back to the summer monsoon and previous spring seasons. We present a new multi-linear regression model that can explain 50% of the SWM variability over the Bengal Delta based on the relationship with climatic indices of the El Niño Southern Oscillation, Indian Ocean Dipole, and summer monsoon rainfall during the decades 1997-2016. Interestingly, we further found that these relationships were non-stationary over the multi-decadal period 1948-2018. These results bear novel implications for developing outbreak-risk forecasts, demonstrating a crucial need to account for multi-decadal variations in climate interactions and underscoring to better understand how the south Asian summer monsoon responds to climate variability.
The aim of this study was to develop a database of historical cold-related mortality in Bangladesh using information obtained from online national newspapers and to analyze such data to understand the spatiotemporal distribution, demographic dynamics, and causes of deaths related to cold temperatures in winter. We prepared a comprehensive database containing information relating to the winter months (December to February) of 2009-2021 for the eight administrative divisions of Bangladesh and systematically removed redundant records. We found that 1249 people died in Bangladesh during this period due to cold and cold-related illnesses, with an average of 104.1 deaths per year. The maximum number of cold-related deaths (36.51%) occurred in the Rangpur Division. The numbers were much higher here than in the other divisions because Rangpur has the lowest average monthly air temperature during the winter months and the poorest socioeconomic conditions. The primary peak of cold-related mortality occurred during 21-31 December, when cold fronts from the Himalayas entered Bangladesh through the Rangpur Division in the north. A secondary peak occurred on 11-20 January each year. Our results also showed that most of the cold-related mortality cases occurred when the daily maximum temperature was lower than 21 °C. Demographically, the highest number of deaths was observed in children aged six years and under (50.68%), followed by senior citizens 65 years and above (20.42%). Fewer females died than males, but campfire burns were the primary cause of female deaths. Most mortality in Bangladesh was due to the cold (75.5%), cold-triggered illness (10.65%), and campfire burns (5.8%). The results of this research will assist policymakers in understanding the importance of taking necessary actions that protect vulnerable public health from cold-related hazards in Bangladesh.
Background The world has been battling several vector-borne diseases since time immemorial. Socio-economic marginality, precipitation variations and human behavioral attributes play a major role in the proliferation of these diseases. Lockdown and social distancing have affected social behavioral aspects of human life and somehow impact on the spread of vector borne diseases. This article sheds light into the relationship between COVID-19 lockdown and global dengue burden with special focus on India. It also focuses on the interconnection of the COVID-19 pandemic (waves 1 and 2) and the alteration of human behavioral patterns in dengue cases. Methods We performed a systematic search using various resources from different platforms and websites, such as Medline; Pubmed; PAHO; WHO; CDC; ECDC; Epidemiology Unit Ministry of Health (Sri Lanka Government); NASA; NVBDCP from 2015 until 2021. We have included many factors, such as different geographical conditions (tropical climate, semitropic and arid conditions); GDP rate (developed nations, developing nations, and underdeveloped nations). We also categorized our data in order to conform to COVID-19 duration from 2019 to 2021. Data was extracted for the complete duration of 10 years (2012 to 2021) from various countries with different geographical region (arid region, semitropic/semiarid region and tropical region). Results There was a noticeable reduction in dengue cases in underdeveloped (70-85%), developing (50-90%), and developed nations (75%) in the years 2019 and 2021. The dengue cases drastically reduced by 55-65% with the advent of COVID-19 s wave in the year 2021 across the globe. Conclusions At present, we can conclude that COVID-19 and dengue show an inverse relationship. These preliminary, data-based observations should guide clinical practice until more data are made public and basis for further medical research.
Climate change is a concerning matter nowadays. It has a long-term effect on human health by spreading vector-borne diseases throughout the world, and West Bengal is not an exception. Vector-borne diseases are life-threatening risk for human; approximately 27,437 people have been infected (2016) every year by this giant killer in West Bengal of India. Temperature and rainfall, two important parameters, have directly influenced the vector-borne diseases. An association between vector-borne diseases and climatic conditions has been established by using geographically weighted regression (GWR) technique. GWR resulted overall r square value more than 0.523 in every case of diseases signifies that the climatic parameters (temperature and rainfall) and vector-borne diseases (Dengue, Malaria, Japanese Encephlities) are strongly correlated. The climatic parameters and positive cases of diseases were mapped out by using inverse distance weight (IDW) interpolation technique in this study. Artificial neural network (ANN) was performed to predict and forecast the climatic condition. The predicted findings have been validated by root mean square error (RMSE) (temperature: 0.301; rainfall: 0.380, i.e., acceptable). This study revealed an insight between climate variables and vector-borne cases in different districts of West Bengal to better understand the effects of climate variability on these diseases. A novel approach of this study is to forecast the spreading of vector-borne diseases for incoming day in West Bengal. After a critical analysis, temperature and rainfall were found to be potent factors for the development of vectors (Aedes Aegypti and Aedes albopictus), and based on this, the risk of vector-borne diseases has been predicted for upcoming years. Forecasted climatic parameters showed that almost all the districts of West Bengal would be reached in a climatic condition where there would be a chance of spreading of vector-borne diseases.
In recent years, demographic growth has caused cities to expand their urban areas, increasing the risk of overheating, creating insurmountable microclimatic conditions within the urban area, which is why studies have been carried out on the urban heat island effect (UHI) and its mitigation. Therefore, this research aims to evaluate the cooling potential in the application of strategies based on biomimicry for the microclimate in a historical heritage city of Panama. For this, three case studies (base case, case 1, and case 2) of outdoor thermal comfort were evaluated, in which the Envi-met software was used to emulate and evaluate the thermal performance of these strategies during March (highest temperature month) and October (rainier month). The strategies used were extracted from the contrast of zebra skin, human skin, evaporative cooling, and ant skin. The results showed a reduction of 2.8 °C in the air temperature at 11:00, the radiant temperature decreased by 2.2 °C, and the PET index managed to reduce the thermal comfort indicator among its categories. The importance of thinking based on biomimicry in sustainable strategies is concluded; although significant changes were obtained, high risks of discomfort persist due to the layout and proximity of the building.
INTRODUCTION: Cryptococcus gattii (C. gatti) is a rare cause of meningitis in the United States. Outbreaks in new geographic distributions in the past few decades raise concern that climate change may be contributing to a broader distribution of this pathogen. We review a case of C. gattii in a 23-year-old woman in Northern California who was diagnosed via lumbar puncture after six weeks of headache, blurred vision, and tinnitus. CASE REPORT: A 23-year-old previously healthy young woman presented to the emergency department (ED) after multiple visits to primary care, other EDs, and neurologists, for several weeks of headache, nausea, tinnitus, and blurred vision. On examination the patient was found to have a cranial nerve VI palsy (impaired abduction of the left eye) and bilateral papilledema on exam. Lumbar puncture had a significantly elevated opening pressure. Cerebrospinal fluid studies were positive for C. gattii. The patient was treated with serial lumbar punctures, followed by lumbar drain, as well as amphotericin and flucytosine. The patient had improvement in headache and neurologic symptoms and was discharged to another facility that specializes in management of this disease to undergo further treatment with immunomodulators and steroids. CONCLUSION: Fungal meningitis is uncommon in the US, particularly among immunocompetent patients. Due to climate change, C. gattii may be a new pathogen to consider. This finding raises important questions to the medical community about the way global climate change affects day to day medical care now, and how it may change in the future.
Diverse snail species serve as intermediate hosts of the parasitic nematode Angiostrongylus cantonensis, the etiological agent of human neuroangiostrongyliasis. However, levels of A. cantonensis infection prevalence and intensity vary dramatically among these host species. Factors contributing to this variation are largely unknown. Environmental factors, such as precipitation and temperature, have been correlated with overall A. cantonensis infection levels in a locale, but the influence of environment on infection in individual snail species has not been addressed. We identified levels of A. cantonensis prevalence and intensity in 16 species of snails collected from 29 sites along an environmental gradient on the island of Oahu, Hawaii. The relationship between infection levels of individual species and their environment was evaluated using AIC model selection of Generalized Linear Mixed Models incorporating precipitation, temperature, and vegetation cover at each collection site. Our results indicate that different mechanisms drive parasite prevalence and intensity in the intermediate hosts. Overall, snails from rainy, cool, green sites had higher infection levels than snails from dry, hot sites with less green vegetation. Intensity increased at the same rate along the environmental gradient in all species, though at different levels, while the relation between prevalence and environmental variables depended on species. These results have implications for zoonotic transmission, as human infection is a function of infection in the intermediate hosts, ingestion of which is the main pathway of transmission. The probability of human infection is greater in locations with higher rainfall, lower temperature and more vegetation cover because of higher infection prevalence in the gastropod hosts, but this depends on the host species. Moreover, severity of neuroangiostrongyliasis symptoms is likely to be greater in locations with higher rainfall, lower temperature, and more vegetation because of the higher numbers of infectious larvae (infection intensity) in all infected snail species. This study highlights the variation of infection prevalence and intensity in individual gastropod species, the individualistic nature of interactions between host species and their environment, and the implications for human neuroangiostrongyliasis in different environments.
Environmental changes triggered by deforestation, urban expansion and climate change are present-day drivers of the emergence and reemergence of leishmaniasis. This review describes the current epidemiological scenario and the feasible influence of environmental changes on disease occurrence in the state of Yucatan, Mexico. Relevant literature was accessed through different databases, including PubMed, Scopus, Google, and Mexican official morbidity databases. Recent LCL autochthonous cases, potential vector sandflies and mammal hosts/reservoirs also have been reported in several localities of Yucatan without previous historical records of the disease. The impact of deforestation, urban expansion and projections on climate change have been documented. The current evidence of the relationships between the components of the transmission cycle, the disease occurrence, and the environmental changes on the leishmaniasis emergence in the state shows the need for strength and an update to the intervention and control strategies through a One Health perspective.
Though instances of arthropod-borne (arbo)virus co-infection have been documented clinically, the overall incidence of arbovirus co-infection and its drivers are not well understood. Now that dengue, Zika and chikungunya viruses are all in circulation across tropical and subtropical regions of the Americas, it is important to understand the environmental and biological conditions that make co-infections more likely to occur. To understand this, we developed a mathematical model of co-circulation of two arboviruses, with transmission parameters approximating dengue, Zika and/or chikungunya viruses, and co-infection possible in both humans and mosquitoes. We examined the influence of seasonal timing of arbovirus co-circulation on the extent of co-infection. By undertaking a sensitivity analysis of this model, we examined how biological factors interact with seasonality to determine arbovirus co-infection transmission and prevalence. We found that temporal synchrony of the co-infecting viruses and average temperature were the most influential drivers of co-infection incidence. Our model highlights the synergistic effect of co-transmission from mosquitoes, which leads to more than double the number of co-infections than would be expected in a scenario without co-transmission. Our results suggest that appreciable numbers of co-infections are unlikely to occur except in tropical climates when the viruses co-occur in time and space.
BACKGROUND: With the current climate change crisis and its influence on infectious disease transmission there is an increased desire to understand its impact on infectious diseases globally. Hantaviruses are found worldwide, causing infectious diseases such as haemorrhagic fever with renal syndrome (HFRS) and hantavirus cardiopulmonary syndrome (HCPS)/hantavirus pulmonary syndrome (HPS) in tropical regions such as Latin America and the Caribbean (LAC). These regions are inherently vulnerable to climate change impacts, infectious disease outbreaks and natural disasters. Hantaviruses are zoonotic viruses present in multiple rodent hosts resident in Neotropical ecosystems within LAC and are involved in hantavirus transmission. METHODS: We conducted a systematic review to assess the association of climatic factors with human hantavirus infections in the LAC region. Literature searches were conducted on MEDLINE and Web of Science databases for published studies according to Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) criteria. The inclusion criteria included at least eight human hantavirus cases, at least one climatic factor and study from > 1 LAC geographical location. RESULTS: In total, 383 papers were identified within the search criteria, but 13 studies met the inclusion criteria ranging from Brazil, Chile, Argentina, Bolivia and Panama in Latin America and a single study from Barbados in the Caribbean. Multiple mathematical models were utilized in the selected studies with varying power to generate robust risk and case estimates of human hantavirus infections linked to climatic factors. Strong evidence of hantavirus disease association with precipitation and habitat type factors were observed, but mixed evidence was observed for temperature and humidity. CONCLUSIONS: The interaction of climate and hantavirus diseases in LAC is likely complex due to the unknown identity of all vertebrate host reservoirs, circulation of multiple hantavirus strains, agricultural practices, climatic changes and challenged public health systems. There is an increasing need for more detailed systematic research on the influence of climate and other co-related social, abiotic, and biotic factors on infectious diseases in LAC to understand the complexity of vector-borne disease transmission in the Neotropics.
CONTEXT: Tropical areas and small islands are identified as highly vulnerable to climate change, and already experiencing shifts in their temperature distribution. However, the knowledge on the health impacts of temperatures under tropical marine climate is limited. We explored the influence of temperature on mortality in four French overseas regions located in French Guiana, French West Indies, and in the Indian Ocean, between 2000 and 2015. METHOD: Distributed lag non-linear generalized models linking temperature and mortality were developed in each area, and relative risks were combined through a meta-analysis. Models were used to estimate the fraction of mortality attributable to non-optimal temperatures. The role of humidity was also investigated. RESULTS: An increased risk of mortality was observed when the temperature deviated from median. Results were not modified when introducing humidity. Between 2000 and 2015, 979 deaths [confidence interval (CI) 95% 531:1359] were attributable to temperatures higher than the 90th percentile of the temperature distribution, and 442 [CI 95% 178:667] to temperature lower than the 10th percentile. DISCUSSION: Heat already has a large impact on mortality in the French overseas regions. Results suggest that adaptation to heat is relevant under tropical marine climate.
OBJECTIVES: To study the epidemiology of dengue incidence and understand the dynamics of dengue transmission in Makkah, Kingdom of Saudi Arabia (KSA), between 2017-2019. METHODS: This is a cross-sectional study. Health and demographic data was obtained for all confirmed dengue cases in Makkah, KSA, in the years 2017-2019 from the Vector-Borne and Zoonotic Diseases Administration (VBZDA) in Makkah and the Makkah Regional Laboratory, KSA. In addition, entomological data about Aedes density was obtained from the VBZDA. Descriptive epidemiological methods were used to determine the occurrence and distribution of dengue cases. RESULTS: Laboratory-confirmed dengue cases were higher in 2019 as compared to 2017 and 2018, suggesting an outbreak of dengue in Makkah, KSA, in 2019. The incidence of confirmed dengue cases was 204 in 2017, 163 in 2018 and 748 in 2019. Dengue mostly affected people in the 25-44 age group, accounting for approximately half of the annual dengue cases each year. Men were at a higher dengue incidence risk when compared to women, and Saudi women had a higher risk rate for dengue cases when compared to non-Saudi women in all 3 years studied. There was no dengue related death in these 3 years. CONCLUSION: The dengue incidence increased in Makkah, KSA, in 2019 as compared to the previous 2 years, owing to heavy rainfall in 2019. Post-rainfall Vector control efforts may help contain the disease in Makkah, KSA.
Background Over the past ten years Amazon region has experienced multiple environmental changes including high rates of deforestation, and more frequent ‘once in a century’ extreme weather events. Despite this it is still not clear how these events effect food biodiversity, local diets and nutrition of Amazon Indigenous people. Information on food consumption is urgently needed, especially to identify key Amazonian Indigenous foods which may increase nutritional resilience to extreme climate events. Technological tools represent a potential feasible solution to measure diet for population studies. We have partnered with International researchers, local nutritionist, Indigenous leaders and community members to adapt a digital tool to support dietary measurement in Amazonian Indigenous communities. Methods The adaptation had three stages. First working with an international multidisciplinary committee, we identified and compiled existing food composition databases to create a database for the Peruvian myfood24 version to use with communities of Shawi ethnicity. Seven food composition tables were identified, and permission was requested for two cases where information was not public. Six food composition tables, one academic publication and one peruvian report about amazon food species, were used for generating a food composition database. Second, using myfood24 guidelines, we completed a data base using Access software. This process involved cleaning and removing duplicate food items, including conversion values (from raw to cooked foods) and calculations for potential nutrient losses on cooking. We used a series of six online focus groups meetings with three peruvian nutritionists, including one nutritionist expert on the Shawi diet, to identify portions, and combinations. Finally, during a workshop with five local community members, a list of Shawi foods were validated, and food preparation was characterised to develop recipes and to take pictures for use in the online tool. Results The peruvian food composition database to be used with the Shawi communities included a total of 1042 food items, with information for 14 key nutrients. These foods were split into fourteen food categories. Seventy-six possible options on how food is eaten together, and 43 portion measurements were validated in the focus groups. 114 food items were identified in the workshop as commonly consumed by Shawi, with five forest animal foods proving the highest level of iron per 100 g: palm larvae (3.6mg), armadillo (3.5mg), deer (3.5mg), paca (3.4mg) and agouti (3.4mg). Conclusion A comprehensive Peruvian Food Composition Database with a focus on Shawi diet has been created. This data has been incorporated within the online dietary assessment tool, myfood24. A photo Album and recipes will be completed over the next weeks. The new tool with be useful to understand how food and nutrient intakes in this vulnerable population are affected by climate change events.
Environmental factors such as solar ultraviolet radiation (UV), air pollution, and variations in the air temperature (T) and relative humidity (RH) affect skin health. However, it is still unclear what effects on the skin may occur as the result of these combined exposures. This study was designed to quantify environmental exposures during routine daily activities to provide quantitative metrics that inspire future studies on exposome and human health. Two bicyclists were equipped with instruments to collect specific data concerning UV (at different angles), T, RH, ground-level ozone (O-3), and chemical exposures. Measurements were conducted in the summer and winter seasons of 2016-2017 in four touristic and urban Brazilian cities. Erythemal UV doses (EryD) exceeding the minimal erythemal doses (MED) for phototype V (EryD > 600 Jm(-2)) were registered inmost tours, including cloudy weather and during the winter. Significant EryD were also observed in tilted body parts. Humidex Index (HI) higher than 30 degrees C revealed great thermal discomfort in most regions, mainly during the summer. O-3 amounts were generally below the thresholds established by the World Health Organization (WHO), except for two instances in which the peak of O-3 concentrations exceeded the 100 mu gm(-3). More than 10% of chemicals sampled during the tours were identified as Polycyclic Aromatic Hydrocarbons (PAH), including anthracene (peak of 207 ng per gram of air). There was a combination of EryD exceeding the MED, thermal discomfort, and PAH exposure in most studied areas. We concluded that this exposome could accelerate and amplify skin-related damages generally associated with a single environmental factor exposure, such as sunlight exposure at any time of the year, for example. (C) 2021 The Authors. Published by Elsevier B.V.
Biodiversity and ecosystem conservation in the Amazon play a critical role in climate-change mitigation. However, institutional responses have had conflicted and complex relations with Indigenous peoples. There is a growing need for meaningful engagement with-and recognition of-the centrality of Indigenous peoples’ perceptions and understanding of the changes they are experiencing to inform successful and effective place-based adaptation strategies. To fill this gap, this study focuses on the value-based perspectives and pragmatic decision-making of Shawi Indigenous men in the Peruvian Amazon. We are specifically interested in their perceptions of how their food system is changing, why it is changing, its consequences, and how/whether they are coping with and responding to this change. Our results highlight that Shawi men’s agency and conscious envisioning of their future food system intersect with the effects of government policy. Shawi men perceive that the main driver of their food-system changes, i.e., less forest food, is self-driven population growth, leading to emotions of guilt and shame. During our study, they articulated a conscious belief that future generations must transition from forest-based to agricultural foods, emphasising education as central to this transition. Additionally, results suggest that the Peruvian government is indirectly promoting Shawi population growth through policies linking population size to improved service delivery, particularly education. Despite intentional Shawi moves to transition to agriculture, this results in a loss of men’s cultural identity and has mental-health implications, creating new vulnerabilities due to increasing climatic extremes, such as flooding and higher temperatures.
Inequalities in benefits from ecosystem services (ES) challenge the achievement of sustainability goals, because they increase the vulnerability of socio-ecological systems to climate hazards. Yet the unequal effects of changes in ES, and of climate change more generally, on human well-being (HWB) are still poorly accounted for in decision-making around adaptation, particularly in tropical countries. Here, we investigate these dynamics through the lens of local peoples’ perceptions of ES in relation to human well-being (HWB), and how these are affected by climate change in three distinct regional case studies in the Atlantic Forest in Southeast of Brazil. Through structured questionnaires, we found that the local perceptions of important ES are region-dependent, particularly identifying services regulating local climate and air quality, water flow and quality, food provisioning, and cultural services of landscape esthetics related to forest regeneration. HWB was expressed through material (e.g., economic security, environmental conditions) and higher accounts of non-material (e.g., feelings, health and social connections) dimensions. Specific environmental changes were identified by 95% of those responding, 40% of whom included climate change as one of these. When asked about climate directly, 97% of those responding identified relevant changes in regionally relevant ways. Rising temperatures, unbalanced seasons, altered rainfall patterns, drought, increase of extreme events, and sea level rise are negatively affecting both material and non-material dimensions of HWB across regions. These perceived changes aligned with observed and projected climate changes in the regions. Benefits from ES accrue for HWB at different scales depending on the specific ES and region. For example, crop production by small farmers or exported in sugar cane, water captured for agricultural irrigation or used for urban supplies, and fish resources for local consumption and lifestyle or as a recreational attraction for visitors. Policy choices about such balances will affect local vulnerabilities to the expected future climate and other environmental changes in the region. This place fine-scale observations and the empowerment of local knowledge at the core of policy decisions about adaptation to support a climate-resilient future for traditional communities and small farmers.
BACKGROUND: Both cold and hot temperature have been associated with the onset of asthma, but it remains largely unknown about the risk of asthma hospitalisation associated with short-term temperature fluctuation or temperature variability (TV). OBJECTIVE: To explore the association between short-term exposure to TV and asthma hospitalisation in Brazil. METHODS: Data for asthma hospitalisation and weather conditions were collected from 1816 Brazilian cities between 2000 and 2015. TV was calculated as the SD of all daily minimum and maximum temperatures within 0-7 days prior to current day. A time-stratified case-crossover design was performed to quantify the association between TV and hospitalisation for asthma. RESULTS: A total of 2 818 911 hospitalisations for asthma were identified during the study period. Each 1°C increase in 0-7 days’ TV exposure was related to a 1.0% (95% CI 0.7% to 1.4%) increase in asthma hospitalisations. The elderly were more vulnerable to TV than other age groups, while region and season appeared to significantly modify the associations. There were 159 305 (95% CI 55 293 to 2 58 054) hospitalisations, US$48.41 million (95% CI US$16.92 to US$78.30 million) inpatient costs at 2015 price and 450.44 thousand inpatient days (95% CI 156.08 to 729.91 thousand days) associated with TV during the study period. The fraction of asthma hospitalisations attributable to TV increased from 5.32% in 2000 to 5.88% in 2015. CONCLUSION: TV was significantly associated with asthma hospitalisation and the corresponding substantial health costs in Brazil. Our findings suggest that preventive measures of asthma should take TV into account.
Climate change is drastically altering the frequency, duration, and severity of compound drought-heatwave (CDHW) episodes, which present a new challenge in environmental and socioeconomic sectors. These threats are of particular importance in low-income regions with growing populations, fragile infrastructure, and threatened ecosystems. This review synthesizes emerging progress in the understanding of CDHW patterns in Brazil while providing insights about the impacts on fire occurrence and public health. Evidence is mounting that heatwaves are becoming increasingly linked with droughts in northeastern and southeastern Brazil, the Amazonia, and the Pantanal. In those regions, recent studies have begun to build a better understanding of the physical mechanisms behind CDHW events, such as the soil moisture-atmosphere coupling, promoted by exceptional atmospheric blocking conditions. Results hint at a synergy between CDHW events and high fire activity in the country over the last decades, with the most recent example being the catastrophic 2020 fires in the Pantanal. Moreover, we show that HWs were responsible for increasing mortality and preterm births during record-breaking droughts in southeastern Brazil. This work paves the way for a more in-depth understanding on CDHW events and their impacts, which is crucial to enhance the adaptive capacity of different Brazilian sectors.
Changes in climatic patterns are expected to have significant effects on health and wellbeing. However, the literature on the effect of climate on subjective wellbeing remains scant and existing studies focus mostly on developed countries or cross-country analyses. This paper aims to identify the relationship between climate conditions on happiness after controlling for individual and social characteristics. Ecuador, a geographically fragmented country with varying climate conditions across municipalities, constitutes an ideal case study to assess the effect of climate variables on happiness. We employ a cross-section analysis to identify the effect of temperature, precipitation and humidity on happiness. The paper shows that climate conditions constitute an important determinant of people’s subjective wellbeing. The results also suggest that income and education attenuate the effect of temperature on happiness and that substantial differences are observed depending on whether places are hot/humid or cold/dry.
Complete savannization of the Amazon Basin would enhance the effects of climate change on local heat exposure and pose a risk to human health, according to climate model projections. Land use change and deforestation can influence local temperature and climate. Here we use a coupled ocean-atmosphere model to assess the impact of savannization of the Amazon Basin on the wet-bulb globe temperature heat stress index under two climate change scenarios (RCP4.5 and RCP8.5). We find that heat stress exposure due to deforestation was comparable to the effect of climate change under RCP8.5. Our findings suggest that heat stress index could exceed the human adaptation limit by 2100 under the combined effects of Amazon savannization and climate change. Moreover, we find that risk of heat stress exposure was highest in Northern Brazil and among the most socially vulnerable. We suggest that by 2100, savannization of the Amazon will lead to more than 11 million people will be exposed heat stress that poses an extreme risk to human health under a high emission scenario.
Climate change has increased heat exposure in many parts of the tropics, negatively impacting outdoor worker productivity and health. Although it is known that tropical deforestation is associated with local warming, the extent to which this additional heat exposure affects people across the tropics is unknown. In this modeling study, we combine worker health guidelines with satellite, reanalysis, and population data to investigate how warming associated with recent deforestation (2003-2018) affects outdoor working conditions across low-latitude countries, and how future global climate change will magnify heat exposure for people in deforested areas. We find that the local warming from 15 years of deforestation was associated with losses in safe thermal working conditions for 2.8 million outdoor workers. We also show recent large-scale forest loss was associated with particularly large impacts on populations in locations such as the Brazilian states of Mato Grosso and Para ‘. Future global warming and additional forest loss will magnify these impacts.
Climate is considered an important factor in the temporal and spatial distribution of vector-borne diseases. Dengue transmission involves many factors: although it is not yet fully understood, climate is a critical factor as it facilitates risk analysis of epidemics. This study analyzed the effect of seasonal factors and the relationship between climate variables and dengue risk in the municipality of Campo Grande, from 2008 to 2018. Generalized linear models with negative binomial and Poisson distribution were used. The most appropriate model was the one with “minimum temperature” and “precipitation”, both lagged by one month, controlled by “year”. In this model, a 1 degrees C rise in the minimum temperature of one month led to an increase in dengue cases the following month, while a 10 mm increase in precipitation led to an increase in dengue cases the following month.
Dengue fever is a serious and growing public health problem in Latin America and elsewhere, intensified by climate change and human mobility. This paper reviews the approaches to the epidemiological prediction of dengue fever using the One Health perspective, including an analysis of how Machine Learning techniques have been applied to it and focuses on the risk factors for dengue in Latin America to put the broader environmental considerations into a detailed understanding of the small-scale processes as they affect disease incidence. Determining that many factors can act as predictors for dengue outbreaks, a large-scale comparison of different predictors over larger geographic areas than those currently studied is lacking to determine which predictors are the most effective. In addition, it provides insight into techniques of Machine Learning used for future predictive models, as well as general workflow for Machine Learning projects of dengue fever.
The expansion of the invasive mosquito Aedes aegypti L. (Diptera: Culicidae) towards temperate regions in the Americas is causing concern because of its public health implications. As for other insects, the distribution limits of Ae. aegypti have been suggested to be related to minimum temperatures and to be controlled mainly by cold tolerance. The aim of this study was to assess the daily mortality of immature stages of Ae. aegypti under natural winter conditions in Buenos Aires, Argentina, in relation to preceding thermal conditions. The experiment was performed outdoors, and one cohort of larvae was started each week for 16 weeks, and reared up to the emergence of the adults. Three times a week, larvae, pupae and emerged adults were counted, and these data were used to calculate the daily mortality of larvae, pupae and adults and to analyze their relationship with thermal conditions. The results showed that mortality was generally low, with a few peaks of high mortality after cold front events. The mortality of pupae and larvae showed a higher correlation with the cooling degree hours of previous days than with the minimum, maximum or mean temperatures. Pupae and adults showed to be more vulnerable to low temperatures than larvae. A delay in mortality was observed in relation to the low temperature events, with a proportion of individuals dying in a later stage after the end of the cold front. These results suggest that thermal conditions during cold fronts in Buenos Aires are close to the tolerance limit of the local Ae. aegypti population. The wide range of responses of different individuals suggests that low winter temperatures may constitute a selective force, leading the population to a higher tolerance to low temperatures, which might favor the further expansion of this species towards colder regions.
Leishmaniasis is a public health problem worldwide. We aimed to predict ecological niche models (ENMs) for visceral (VL) and cutaneous (CL) leishmaniasis and the sand flies involved in the transmission of leishmaniasis in São Paulo, Brazil. Phlebotomine sand flies were collected between 1985 and 2015. ENMs were created for each sand fly species using Maximum Entropy Species Distribution Modeling software, and 20 climatic variables were determined. Nyssomyia intermedia (Lutz & Neiva, 1912) and Lutzomyia longipalpis (Lutz & Neiva, 1912), the primary vectors involved in CL and VL, displayed the highest suitability across the various regions, climates, and topographies. L. longipalpis was found in the border of Paraná an area currently free of VL. The variables with the greatest impact were temperature seasonality, precipitation, and altitude. Co-presence of multiple sand fly species was observed in the cuestas and coastal areas along the border of Paraná and in the western basalt areas along the border of Mato Grosso do Sul. Human CL and VL were found in 475 of 546 (86.7%) and 106 of 645 (16.4%) of municipalities, respectively. Niche overlap between N. intermedia and L. longipalpis was found with 9208 human cases of CL and 2952 cases of VL. ENMs demonstrated that each phlebotomine sand fly species has a unique geographic distribution pattern, and the occurrence of the primary vectors of CL and VL overlapped. These data can be used by public authorities to monitor the dispersion and expansion of CL and VL vectors in São Paulo state.
INTRODUCTION: Zika virus (ZIKV) is primarily transmitted byAedes aegypti and Aedes albopictus mosquitoes between humans and non-human primates. Climate change may enhance virus reproduction in Aedes spp. mosquito populations, resulting in intensified ZIKV outbreaks. The study objective was to explore how an outbreak similar to the 2016 ZIKV outbreak in Brazil might unfold with projected climate change. METHODS: A compartmental infectious disease model that included compartments for humans and mosquitoes was developed to fit the 2016 ZIKV outbreak data from Brazil using least squares optimization. To explore the impact of climate change, published polynomial relationships between temperature and temperature-sensitive mosquito population and virus transmission parameters (mosquito mortality, development rate, and ZIKV extrinsic incubation period) were used. Projections for future outbreaks were obtained by simulating transmission with effects of projected average monthly temperatures on temperature-sensitive model parameters at each of three future time periods: 2011-2040, 2041-2070, and 2071-2100. The projected future climate was obtained from an ensemble of regional climate models (RCMs) obtained from the Co-Ordinated Regional Downscaling Experiment (CORDEX) that used Representative Concentration Pathways (RCP) with two radiative forcing values, RCP4.5 and RCP8.5. A sensitivity analysis was performed to explore the impact of temperature-dependent parameters on the model outcomes. RESULTS: Climate change scenarios impacted the model outcomes, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the duration of the ZIKV outbreak. Comparing 2070-2100 to 2016, using RCP4.5, the peak incidence was 22,030 compared to 10,473; the time to epidemic peak was 12 compared to 9 weeks, and the outbreak duration was 52 compared to 41 weeks. Comparing 2070-2100 to 2016, using RCP8.5, the peak incidence was 21,786 compared to 10,473; the time to epidemic peak was 11 compared to 9 weeks, and the outbreak duration was 50 compared to 41weeks. The increases are due to optimal climate conditions for mosquitoes, with the mean temperature reaching 28 °C in the warmest months. Under a high emission scenario (RCP8.5), mean temperatures extend above optimal for mosquito survival in the warmest months. CONCLUSION: Outbreaks of ZIKV in locations similar to Brazil are expected to be more intense with a warming climate. As climate change impacts are becoming increasingly apparent on human health, it is important to quantify the effect and use this knowledge to inform decisions on prevention and control strategies.
Amazonia and the Northeast region of Brazil exhibit the highest levels of climate vulnerability in the country. While Amazonia is characterized by an extremely hot and humid climate and hosts the world largest rainforest, the Northeast is home to sharp climatic contrasts, ranging from rainy areas along the coast to semiarid regions that are often affected by droughts. Both regions are subject to extremely high temperatures and are susceptible to many tropical diseases. This study develops a multidimensional Extreme Climate Vulnerability Index (ECVI) for Brazilian Amazonia and the Northeast region based on the Alkire-Foster method. Vulnerability is defined by three components, encompassing exposure (proxied by seven climate extreme indicators), susceptibility (proxied by sociodemographic indicators), and adaptive capacity (proxied by sanitation conditions, urbanization rate, and healthcare provision). In addition to the estimated vulnerability levels and intensity, we break down the ECVI by indicators, dimensions, and regions, in order to explore how the incidence levels of climate-sensitive infectious and parasitic diseases correlate with regional vulnerability. We use the Grade of Membership method to reclassify the mesoregions into homoclimatic zones based on extreme climatic events, so climate and population/health data can be analyzed at comparable resolutions. We find two homoclimatic zones: Extreme Rain (ER) and Extreme Drought and High Temperature (ED-HT). Vulnerability is higher in the ED-HT areas than in the ER. The contribution of each dimension to overall vulnerability levels varies by homoclimatic zone. In the ER zone, adaptive capacity (39%) prevails as the main driver of vulnerability among the three dimensions, in contrast with the approximately even dimensional contribution in the ED-HT. When we compare areas by disease incidence levels, exposure emerges as the most influential dimension. Our results suggest that climate can exacerbate existing infrastructure deficiencies and socioeconomic conditions that are correlated with tropical disease incidence in impoverished areas.
Vector-borne diseases are some of the leading public health problems in the tropics, and their association with climatic anomalies is well known. The current study aimed to evaluate the trend of American cutaneous leishmaniasis cases in the municipality of Manaus, Amazonas-Brazil, and its relationship with climatic extremes (ENSO). The study was carried out using a series of secondary data from notifications on the occurrence of several American cutaneous leishmaniasis cases in the municipality of Manaus between 1990 and 2017 obtained through the Sistema de Informação de Agravos de Notificação. Data regarding temperature, relative humidity, and precipitation for this municipality were derived from the Instituto Nacional de Meteorologia (INMET) and the National Oceanic and Atmospheric Administration (NOAA) websites. Coherence and wavelet phase analysis was conducted to measure the degree of relationship of the occurrence of the cases of cutaneous leishmaniasis and the El Niño-Southern Oscillation (ENSO). The results show that during La Niña events, an increase in American cutaneous leishmaniasis (ACL) cases is anticipated after the increase in rainfall from November, resulting in a more significant number of cases in January, February, and March. It was observed that in the municipality of Manaus, the dynamics of ACL cases are directly influenced by ENSO events that affect environmental variables such as precipitation, temperature, and humidity. Therefore, climatic variations consequently change the ACL incidence dynamics, leading to subsequent increases or decreases in the incidence of ACL cases in the area.
Due to the global increase in mosquito-borne diseases outbreaks it is recommended to increase surveillance and monitoring of vector species to respond swiftly and with early warning indicators. Usually, however, the information about vector presence and activity seems to be insufficient to implement timely and effective control strategies. Here we present an improved mathematical model of Aedes aegypti population dynamics with the aim of making the Dengue surveillance system more proactive. The model considers the four life stages of the mosquito: egg, larva, pupa and adult. As driving factors, it incorporates temperature which affects development and mortality rates at certain stages, and precipitation which is known to affect egg submergence and hatching, as well as larval mortality associated with desiccation. Our mechanistic model is implemented as a free and stand-alone system that automatically retrieves all needed inputs, runs a simulation and shows the results. A major improvement in our implementation is the capacity of the system to predict the population dynamics of Ae. aegypti in the near future, given that it uses gridded weather forecast data. Hence, it is independent by meteorological station proximity. The model predictions are compared with field data from C ‘ ordoba City, Argentina. Although field data have high variability, an overall accordance has been observed. The comparison of results obtained using observed weather data, with the simulations based on forecasts, suggests that the modeled dynamics are accurate up to 15 days in advance. Preliminary results of Ae. aegypti population dynamics for a consecutive three-year period, spanning different eco-regions of Argentina, are presented, and demonstrate the flexibility of the system.
In the last two decades dengue cases increased significantly throughout the world, giving place to more frequent outbreaks in Latin America. In the non-endemic city of San Ramón de la Nueva Orán, located in Northwest Argentina, large dengue outbreaks alternate with several years of smaller ones. This pattern, as well as the understanding of the underlying mechanisms, could be essential to design proper strategies to reduce epidemic size. We develop a stochastic model that includes climate variables, social structure, and mobility between a non-endemic city and an endemic area. Climatic variables were input of a mosquito population ecological model, which in turn was coupled to a meta-population, spatially explicit, epidemiological model. Human mobility was included into the model given the high border crossing to the northern country of Bolivia, where dengue transmission is sustained during the whole year. We tested different hypotheses regarding people mobility as well as climate variability by fitting numerical simulations to weekly clinical data reported from 2009 to 2016. After assessing the number of imported cases that triggered the observed outbreaks, our model allows to explain the observed epidemic pattern. We found that the number of vectors per host and the effective reproductive number are proxies for large epidemics. Both proxies are related with climate variability such as rainfall and temperature, opening the possibility to test these meteorological variables for forecast purposes.
Dengue virus (DENV) is an endemic disease in the hot and humid low-lands of Colombia. We characterize the association of monthly series of dengue cases with indices of El Niño/Southern Oscillation (ENSO) at the tropical Pacific and local climatic variables in Colombia during the period 2007-2017 at different temporal and spatial scales. For estimation purposes, we use lagged cross-correlations (Pearson test), cross-wavelet analysis (wavelet cross spectrum, and wavelet coherence), as well as a novel nonlinear causality method, PCMCI, that allows identifying common causal drivers and links among high dimensional simultaneous and time-lagged variables. Our results evidence the strong association of DENV cases in Colombia with ENSO indices and with local temperature and rainfall. El Niño (La Niña) phenomenon is related to an increase (decrease) of dengue cases nationally and in most regions and departments, with maximum correlations occurring at shorter time lags in the Pacific and Andes regions, closer to the Pacific Ocean. This association is mainly explained by the ENSO-driven increase in temperature and decrease in rainfall, especially in the Andes and Pacific regions. The influence of ENSO is not stationary, given the reduction of DENV cases since 2005, and that local climate variables vary in space and time, which prevents to extrapolate results from one region to another. The association between DENV and ENSO varies at national and regional scales when data are disaggregated by seasons, being stronger in DJF and weaker in SON. Overall, the Pacific and Andes regions control the relationship between dengue dynamics and ENSO at national scale. Cross-wavelet analysis indicates that the ENSO-DENV relation in Colombia exhibits a strong coherence in the 12 to 16-months frequency band, which implies the frequency locking between the annual cycle and the interannual (ENSO) timescales. Results of nonlinear causality metrics reveal the complex concomitant effects of ENSO and local climate variables, while offering new insights to develop early warning systems for DENV in Colombia.
Air pollution from Amazon fires has adverse impacts on human health. The number of fires in the Amazon has increased in recent years, but whether this increase was driven by deforestation or climate has not been assessed. We analyzed relationships between fire, deforestation, and climate for the period 2003 to 2019 among selected states across the Brazilian Legal Amazon (BLA). A statistical model including deforestation, precipitation and temperature explained ∼80% of the variability in dry season fire count across states when totaled across the BLA, with positive relationships between fire count and deforestation. We estimate that the increase in deforestation since 2012 increased the dry season fire count in 2019 by 39%. Using a regional chemistry-climate model combined with exposure-response associations, we estimate this increase in fire resulted in 3,400 (95UI: 3,300-3,550) additional deaths in 2019 due to increased exposure to particulate air pollution. If deforestation in 2019 had increased to the maximum recorded during 2003-2019, the number of active fire counts would have increased by an additional factor of 2 resulting in 7,900 (95UI: 7,600-8,200) additional premature deaths. Our analysis demonstrates the strong benefits of reduced deforestation on air quality and public health across the Amazon.
OBJECTIVE: The frequency and seasonality of viruses in tropical regions are scarcely reported. We estimated the frequency of seven respiratory viruses and assessed seasonality of respiratory syncytial virus (RSV) and influenza viruses in a tropical city. METHODS: Children (age ≤ 18 years) with acute respiratory infection were investigated in Salvador, Brazil, between July 2014 and June 2017. Respiratory viruses were searched by direct immunofluorescence and real-time polymerase chain reaction for detection of RSV, influenza A virus, influenza B virus, adenovirus (ADV) and parainfluenza viruses (PIV) 1, 2 and 3. Seasonal distribution was evaluated by Prais-Winsten regression. Due to similar distribution, influenza A and influenza B viruses were grouped to analyse seasonality. RESULTS: The study group comprised 387 cases whose median (IQR) age was 26.4 (10.5-50.1) months. Respiratory viruses were detected in 106 (27.4%) cases. RSV (n = 76; 19.6%), influenza A virus (n = 11; 2.8%), influenza B virus (n = 7; 1.8%), ADV (n = 5; 1.3%), PIV 1 (n = 5; 1.3%), PIV 3 (n = 3; 0.8%) and PIV 2 (n = 1; 0.3%) were identified. Monthly count of RSV cases demonstrated seasonal distribution (b3 = 0.626; P = 0.003). More than half (42/76 [55.3%]) of all RSV cases were detected from April to June. Monthly count of influenza cases also showed seasonal distribution (b3 = -0.264; P = 0.032). Influenza cases peaked from November to January with 44.4% (8/18) of all influenza cases. CONCLUSIONS: RSV was the most frequently detected virus. RSV and influenza viruses showed seasonal distribution. These data may be useful to plan the best time to carry out prophylaxis and to increase the number of hospital beds.
Fungal infections are still underappreciated and their prevalence is underestimated, which renders them a serious public health problem. Realistic discussions about their distribution, symptoms, and control can improve management and diagnosis and contribute to refinement of preventive actions using currently available tools. This article represents an overview of dermatophytes and endemic fungi that cause infections in humans and animals. In addition, the impact of climate change on the fungal spread is discussed. The endemic fungal infections characterized in this article include coccidioidomycosis, histoplasmosis, blastomycosis, lobomycosis, emergomycosis and sporotrichosis. Moreover the geographic distribution of these fungi, which are known to be climate sensitive and/or limited to endemic tropical and subtropical areas, is highlighted. In turn, dermatophytes cause superficial fungal infections of skin, hairs and nails, which are the most prevalent mycoses worldwide with a high economic burden. Therefore, the possibility of causing zoonoses and reverse zoonoses by dermatophytes is highly important. In conclusion, the article illustrates the current issues of the epidemiology and distribution of fungal diseases, emphasizing the lack of public programmes for prevention and control of these types of infection.
Climate change is with us. As professionals who place value on evidence-based practice, climate change is something we cannot ignore. The current pandemic of the novel coronavirus, SARS-CoV-2, has demonstrated how global crises can arise suddenly and have a significant impact on public health. Global warming, a chronic process punctuated by acute episodes of extreme weather events, is an insidious global health crisis needing at least as much attention. Many neurological diseases are complex chronic conditions influenced at many levels by changes in the environment. This review aimed to collate and evaluate reports from clinical and basic science about the relationship between climate change and epilepsy. The keywords climate change, seasonal variation, temperature, humidity, thermoregulation, biorhythm, gene, circadian rhythm, heat, and weather were used to search the published evidence. A number of climatic variables are associated with increased seizure frequency in people with epilepsy. Climate change-induced increase in seizure precipitants such as fevers, stress, and sleep deprivation (e.g. as a result of more frequent extreme weather events) or vector-borne infections may trigger or exacerbate seizures, lead to deterioration of seizure control, and affect neurological, cerebrovascular, or cardiovascular comorbidities and risk of sudden unexpected death in epilepsy. Risks are likely to be modified by many factors, ranging from individual genetic variation and temperature-dependent channel function, to housing quality and global supply chains. According to the results of the limited number of experimental studies with animal models of seizures or epilepsy, different seizure types appear to have distinct susceptibility to seasonal influences. Increased body temperature, whether in the context of fever or not, has a critical role in seizure threshold and seizure-related brain damage. Links between climate change and epilepsy are likely to be multifactorial, complex, and often indirect, which makes predictions difficult. We need more data on possible climate-driven altered risks for seizures, epilepsy, and epileptogenesis, to identify underlying mechanisms at systems, cellular, and molecular levels for better understanding of the impact of climate change on epilepsy. Further focussed data would help us to develop evidence for mitigation methods to do more to protect people with epilepsy from the effects of climate change.
Snakebite envenoming is a set of intoxication diseases that disproportionately affect people of poor socioeconomic backgrounds in tropical countries. As it is highly dependent on the environment its burden is expected to shift spatially with global anthropogenic environmental (climate, land use) and demographic change. The mechanisms underlying the changes to snakebite epidemiology are related to factors of snakes and humans. The distribution and abundance of snakes are expected to change with global warming via their thermal tolerance, while rainfall may affect the timing of key activities like feeding and reproduction. Human population growth is the primary cause of land-use change, which may impact snakes at smaller spatial scales than climate via habitat and biodiversity loss (e.g. prey availability). Human populations, on the other hand, could experience novel patterns and morbidity of snakebite envenoming, both as a result of snake responses to environmental change and due to the development of agricultural adaptations to climate change, socioeconomic and cultural changes, development and availability of better antivenoms, personal protective equipment, and mechanization of agriculture that mediate risk of encounters with snakes and their outcomes. The likely global effects of environmental and demographic change are thus context-dependent and could encompass both increasing and or snakebite burden (incidence, number of cases or morbidity), exposing new populations to snakes in temperate areas due to “tropicalization”, or by land use change-induced snake biodiversity loss, respectively. Tackling global change requires drastic measures to ensure large-scale ecosystem functionality. However, as ecosystems represent the main source of venomous snakes their conservation should be accompanied by comprehensive public health campaigns. The challenges associated with the joint efforts of biodiversity conservation and public health professionals should be considered in the global sustainability agenda in a wider context that applies to neglected tropical and zoonotic and emerging diseases.
PurposeAs global warming intensifies, climatic conditions are changing dramatically, potentially affecting specific businesses and cities’ livability. The temperature increase in cities significantly affects urban residents whose percentage is to reach about 70% by 2050. This paper aimed at highlighting the climate change risks in cities, particularly focusing on the threats to people’s health due to a continuous temperature increase. Design/methodology/approachThis study was conducted in three main steps. First, the literature review on the effects of climate change, particularly on the continuous temperature rise in cities, was conducted based on the publications retrieved from PubMed, Science Direct, Google Scholar and Research Gate. Second, the survey was conducted for the sample cities for one month. Third, the questionnaire was used to assess possible climate change threats to the livability of cities. FindingsThe findings showed that urban areas are usually warmer than the surrounding rural areas, mainly due to the urban heat island effect, causing more hot days in metropolitan areas compared to rural areas. This paper outlines some mitigation and adaptation measures, which can be implemented to improve the livability in cities, their sustainability and the well-being of their populations. Originality/valueThis study reports on the climate change impacts on the health and livability of 15 cities, in industrialized and developing countries. It examines the average and maximum temperature and relative humidity of each city and its correlation with their livability. It was complemented by a survey focused on 109 cities from Africa, Asia, Europe, Latin America, North America and Oceania.
The objective of this study is to determine the impacts of low-intensity heat on human health in regions with hot, humid summers. Current literature has highlighted an increase in mortality and morbidity rates during significant heat events. While the impacts on high-intensity events are established, the impacts on low-intensity events, particularly in regions with hot, humid summers, are less clear. A scoping review was conducted searching three databases (PubMed, EMBASE, Web of Science) using key terms based on the inclusion criteria. We included papers that investigated the direct human health impacts of low-intensity heat events (single day or heatwaves) in regions with hot, humid summers in middle- and high-income countries. We excluded papers written in languages other than English. Of the 600 publications identified, 33 met the inclusion criteria. Findings suggest that low-intensity heatwaves can increase all-cause non-accidental, cardiovascular-, respiratory- and diabetes-related mortality, in regions experiencing hot, humid summers. Impacts of low-intensity heatwaves on morbidity are less clear, with research predominantly focusing on hospitalisation rates with a range of outcomes. Few studies investigating the impact of low-intensity heat events on emergency department presentations and ambulance dispatches were found. However, the data from a limited number of studies suggest that both of these outcome measures increase during low-intensity heat events. Low-intensity heat events may increase mortality. There is insufficient evidence of a causal effect of low-intensity heat events on increasing morbidity for a firm conclusion. Further research on the impact of low-intensity heat on morbidity and mortality using consistent parameters is warranted.
The Warsaw International Mechanism for Loss and Damage has identified increasing temperatures as a key slow onset event. However, it is the resulting increases in short-term heat events – heatwaves – that have so far been the primary focus of risk assessment and policy, while gradual and sustained increases in temperature have received less attention. This is a global issue but particularly important in tropical and subtropical regions already chronically exposed to extreme heat. This paper reviews recent analyses of intensifying seasonal and year-round extreme heat exposures and how this affects daily life, including worker productivity, health and wellbeing, reduced GDP and economic viability. It frames this as a slow onset event and closes with a brief indication of tools available to assess and address these risks.
The present systematic review was conducted by gathering the impacts of climate change on occupational heat strain, gathering risk factors that may increase susceptibility to climate-related occupational hazards, and gathering measures for controlling the impacts of climate change on occupational heat strain in outdoor workers. Materials and methods: In this study, three main databases PubMed, Scopus, and Web of Science were searched to find relevant literature on climate change and its effects using subject headings, appropriate Mesh terms and experts’ opinion. Results: The evidence suggests an imprecise but positive relationship between climate change and occupational heat strain in outdoor workers, and the most likely mechanism involves dehydration, fatigue, dizziness, confusion, reduced brain function, loss of concentration and discomfort. Conclusion: With predictions of increasing temperatures, the baseline heat strain incidence data from this systematic review study in tropical and subtropical countries with low and middle income may be used to help stakeholders in policy-making, promotion campaigns, occupational health interventions, and choosing appropriate control methods. Strong evidence indicates that, to manage adverse effects of heat stress on outdoor workers, key factors include anticipating, recognizing, evaluating, controlling, researching, risk management, and applying suitable policy development may be useful tools.
PURPOSE OF REVIEW: Melioidosis, caused by the soil-dwelling bacterium Burkholderia pseudomallei, is a tropical infection associated with high morbidity and mortality. This review summarizes current insights into melioidosis’ endemicity, focusing on epidemiological transitions, zoonosis, and climate change. RECENT FINDINGS: Estimates of the global burden of melioidosis affirm the significance of hot-spots in Australia and Thailand. However, it also highlights the paucity of systematic data from South Asia, The Americas, and Africa. Globally, the growing incidence of diabetes, chronic renal and (alcoholic) liver diseases further increase the susceptibility of individuals to B. pseudomallei infection. Recent outbreaks in nonendemic regions have further exposed the hazard from the trade of animals and products as potential reservoirs for B. pseudomallei. Lastly, global warming will increase precipitation, severe weather events, soil salinity and anthrosol, all associated with the occurrence of B. pseudomallei. SUMMARY: Epidemiological transitions, zoonotic hazards, and climate change are all contributing to the emergence of novel melioidosis-endemic areas. The adoption of the One Health approach involving multidisciplinary collaboration is important in unraveling the real incidence of B. pseudomallei, as well as reducing the spread and associated mortality.
This review highlights two intersecting environmental phenomena that have significantly impacted the Tokyo Summer Olympic and Paralympic Games: infectious disease outbreaks and anthropogenic climate change. Following systematic searches of five databases and the gray literature, 15 studies were identified that addressed infectious disease and climate-related health risks associated with the Summer Games and similar sports mega-events. Over two decades, infectious disease surveillance at the Summer Games has identified low-level threats from vaccine-preventable illnesses and respiratory conditions. However, the COVID-19 pandemic and expansion of vector-borne diseases represent emerging and existential challenges for cities that host mass gathering sports competitions due to the absence of effective vaccines. Ongoing threats from heat injury among athletes and spectators have also been identified at international sports events from Asia to North America due to a confluence of rising Summer temperatures, urban heat island effects and venue crowding. Projections for the Tokyo Games and beyond suggest that heat injury risks are reaching a dangerous tipping point, which will necessitate relocation or mitigation with long-format and endurance events. Without systematic change to its format or staging location, the Summer Games have the potential to drive deleterious health outcomes for athletes, spectators and host communities.
BACKGROUND: Mosquito-borne diseases are expanding their range, and re-emerging in areas where they had subsided for decades. The extent to which climate change influences the transmission suitability and population at risk of mosquito-borne diseases across different altitudes and population densities has not been investigated. The aim of this study was to quantify the extent to which climate change will influence the length of the transmission season and estimate the population at risk of mosquito-borne diseases in the future, given different population densities across an altitudinal gradient. METHODS: Using a multi-model multi-scenario framework, we estimated changes in the length of the transmission season and global population at risk of malaria and dengue for different altitudes and population densities for the period 1951-99. We generated projections from six mosquito-borne disease models, driven by four global circulation models, using four representative concentration pathways, and three shared socioeconomic pathways. FINDINGS: We show that malaria suitability will increase by 1·6 additional months (mean 0·5, SE 0·03) in tropical highlands in the African region, the Eastern Mediterranean region, and the region of the Americas. Dengue suitability will increase in lowlands in the Western Pacific region and the Eastern Mediterranean region by 4·0 additional months (mean 1·7, SE 0·2). Increases in the climatic suitability of both diseases will be greater in rural areas than in urban areas. The epidemic belt for both diseases will expand towards temperate areas. The population at risk of both diseases might increase by up to 4·7 additional billion people by 2070 relative to 1970-99, particularly in lowlands and urban areas. INTERPRETATION: Rising global mean temperature will increase the climatic suitability of both diseases particularly in already endemic areas. The predicted expansion towards higher altitudes and temperate regions suggests that outbreaks can occur in areas where people might be immunologically naive and public health systems unprepared. The population at risk of malaria and dengue will be higher in densely populated urban areas in the WHO African region, South-East Asia region, and the region of the Americas, although we did not account for urban-heat island effects, which can further alter the risk of disease transmission. FUNDING: UK Space Agency, Royal Society, UK National Institute for Health Research, and Swedish Research Council.
Gambierdiscus is a dinoflagellate genus widely distributed throughout tropical and subtropical regions. Some members of this genus can produce a group of potent polycyclic polyether neurotoxins responsible for ciguatera fish poisoning (CFP), one of the most significant food-borne illnesses associated with fish consumption. Ciguatoxins and maitotoxins, the two major toxins produced by Gambierdiscus, act on voltage-gated channels and TRPA1 receptors, consequently leading to poisoning and even death in both humans and animals. Over the past few decades, the occurrence and geographic distribution of CFP have undergone a significant expansion due to intensive anthropogenic activities and global climate change, which results in more human illness, a greater public health impact, and larger economic losses. The global spread of CFP has led to Gambierdiscus and its toxins being considered an environmental and human health concern worldwide. In this review, we seek to provide an overview of recent advances in the field of Gambierdiscus and its associated toxins based on the existing literature combined with re-analyses of current data. The taxonomy, phylogenetics, geographic distribution, environmental regulation, toxin detection method, toxin biosynthesis, and pharmacology and toxicology of Gambierdiscus are summarized and discussed. We also highlight future perspectives on Gambierdiscus and its associated toxins.
Tropical diseases (TDs) are among the leading cause of mortality and fatality globally. The emergence and reemergence of TDs continue to challenge healthcare system. Several tropical diseases such as yellow fever, tuberculosis, cholera, Ebola, HIV, rotavirus, dengue, and malaria outbreaks have led to endemics and epidemics around the world, resulting in millions of deaths. The increase in climate change, migration and urbanization, overcrowding, and other factors continue to increase the spread of TDs. More cases of TDs are recorded as a result of substandard health care systems and lack of access to clean water and food. Early diagnosis of these diseases is crucial for treatment and control. Despite the advancement and development of numerous diagnosis assays, the healthcare system is still hindered by many challenges which include low sensitivity, specificity, the need of trained pathologists, the use of chemicals and a lack of point of care (POC) diagnostic. In order to address these issues, scientists have adopted the use of CRISPR/Cas systems which are gene editing technologies that mimic bacterial immune pathways. Recent advances in CRISPR-based biotechnology have significantly expanded the development of biomolecular sensors for diagnosing diseases and understanding cellular signaling pathways. The CRISPR/Cas strategy plays an excellent role in the field of biosensors. The latest developments are evolving with the specific use of CRISPR, which aims for a fast and accurate sensor system. Thus, the aim of this review is to provide concise knowledge on TDs associated with mosquitoes in terms of pathology and epidemiology as well as background knowledge on CRISPR in prokaryotes and eukaryotes. Moreover, the study overviews the application of the CRISPR/Cas system for detection of TDs associated with mosquitoes.
There are more than 3,000 mosquito species. Aedes aegypti, Ae. communis, and C. quinquefasciatus are, among others, three of the most important mosquito allergen sources in the tropics, western, and industrialized countries. Several individuals are sensitized to mosquito allergens, but the epidemiological data indicates that the frequency of sensitization markedly differs depending on the geographical region. Additionally, the geographical localization of mosquito species has been affected by global warming and some mosquito species have invaded areas where they were not previously found, at the same time as other species have been displaced. This phenomenon has repercussions in the pathogenesis and the accuracy of the diagnosis of mosquito allergy. Allergic individuals are sensitized to mosquito allergens from two origins: saliva and body allergens. Exposure to saliva allergens occurs during mosquito bite and induces cutaneous allergic reactions. Experimental and clinical data suggest that body allergens mediate different manifestations of allergic reactions such as asthma and rhinitis. The most studied mosquito species is Ae. aegypti, from which four and five allergens of the saliva and body, respectively, have been reported. Many characterized allergens are homologs to arthropod-derived allergens, which cause strong cross-reactivity at the humoral and cellular level. The generalized use of whole body Ae. communis or C. quinquefasciatus extracts complicates the diagnosis of mosquito allergy because they have low concentration of saliva allergens and may result in poor diagnosis of the affected population when other species are the primary sensitizer. This review article discusses the current knowledge about mosquito allergy, allergens, cross-reactivity, and proposals of component resolved approaches based on mixtures of purified recombinant allergens to replace saliva-based or whole-body extracts, in order to perform an accurate diagnosis of allergy induced by mosquito allergen exposure.
Purpose of Review To asses recent advances in our understanding of the epidemiology, clinical presentation, diagnosis, and treatment of infections caused by free-living amoebas Recent Findings The burden of disease by free-living amoebas is underestimated; global warming could increase incidence in future years. Early recognition of clinical syndromes may allow for prompt initiation of therapy and better disease outcome. Molecular tests allow for rapid identification of the amoeba. Treatment is based on successful clinical outcomes reported using repurposed drugs. The optimal regimen for each of the clinical syndromes is unknown. As global warming increases, clinicians will be challenged to diagnose and treat infections by free-living amoebas. Therefore, awareness of clinical syndromes, diagnostic tools, and therapeutic interventions is crucial.
The acceleration of climate change has been associated with an alarming increase in the prevalence and geographic range of tick-borne diseases (TBD), many of which have severe and long-lasting effects-particularly when treatment is delayed principally due to inadequate diagnostics and lack of physician suspicion. Moreover, there is a paucity of treatment options for many TBDs that are complicated by diagnostic limitations for correctly identifying the offending pathogens. This review will focus on the biology, disease pathology, and detection methodologies used for the Borreliaceae family which includes the Lyme disease agent Borreliella burgdorferi. Previous work revealed that Borreliaceae genomes differ from most bacteria in that they are composed of large numbers of replicons, both linear and circular, with the main chromosome being the linear with telomeric-like termini. While these findings are novel, additional gene-specific analyses of each class of these multiple replicons are needed to better understand their respective roles in metabolism and pathogenesis of these enigmatic spirochetes. Historically, such studies were challenging due to a dearth of both analytic tools and a sufficient number of high-fidelity genomes among the various taxa within this family as a whole to provide for discriminative and functional genomic studies. Recent advances in long-read whole-genome sequencing, comparative genomics, and machine-learning have provided the tools to better understand the fundamental biology and phylogeny of these genomically-complex pathogens while also providing the data for the development of improved diagnostics and therapeutics.
Lungworms in the genus Angiostrongylus cause disease in animals and humans. The spread of Angiostrongylus vasorum within Europe and the recent establishment of Angiostrongylus cantonensis increase the relevance of these species to veterinary and medical practitioners, and to researchers in parasitology, epidemiology, veterinary science and ecology. This review introduces the key members of the genus present in Europe and their impacts on health, and updates the current epidemiological situation. Expansion of A. vasorum from localized pockets to wide distribution across the continent has been confirmed by a rising prevalence in foxes and increasing reports of infection and disease in dogs, while the list of carnivore and mustelid definitive hosts continues to grow. The tropically distributed rat lungworm A. cantonensis, meanwhile, has been recorded on islands south of Europe, previously the Canary Islands, and now also the Balearic Islands, although so far with limited evidence of zoonotic disease. Other members of the genus, namely, A. chabaudi, A. daskalovi and A. dujardini, are native to Europe and mainly infect wildlife, with unknown consequences for populations, although spill-over can occur into domestic animals and those in zoological collections. The epidemiology of angiostrongylosis is complex, and further research is needed on parasite maintenance in sylvatic hosts, and on the roles of ecology, behaviour and genetics in disease emergence. Improved surveillance in animals and humans is also required to support risk assessments and management.
BACKGROUND: Myocardial infarction is an important cause of cardiovascular mortality and can be precipitated by climatic factors. The temperature dependence of myocardial infarction risk has been well examined in temperate settings. Fewer studies have investigated this in the tropics where thermal amplitudes are narrower. This study investigated how ambient temperature influenced the risk of non-ST segment elevation myocardial infarction (NSTEMI), an increasingly common type of myocardial infarction, in the tropical city-state of Singapore. METHODS: All nationally reported NSTEMI cases from 2009 to 2018 were included and assessed for its short-term association with ambient temperature using conditional Poisson regression models that comprised a three-way interaction term with year, month and day of the week and adjusted for relative humidity. The Distributed Lag Non-Linear Modelling (DLNM) was used to account for the immediate and lagged effects of environmental exposures. Stratified analysis by sex and age groups was undertaken to assess potential effect modification. RESULTS: There were 60,643 reports of NSTEMI. Temperature decline (cool effect) was associated with a delayed cumulative, non-linear increase in NSTEMI risk over 10 days post exposure [Relative Risk (RR(lag0)(-)(10, 10th percentile): 1.12, 95%CI: 1.02-1.24)]. Those aged 65 years and above were potentially more susceptible (RR (lag0)(-)(10, 10th percentile): 1.19, 95 % CI: 1.06-1.33) to the cool effect compared to those below that age (RR(lag0)(-)(10, 10th percentile): 1.00, 95 % CI: 0.85-1.18) (p-value for difference = 0.087). CONCLUSION: Short-term temperature fluctuations were independently associated with NSTEMI incidence in the tropics, with age as a potential effect modifier of this association. An increase in the frequency of climate change driven temperature events may trigger more instances of NSTEMI in tropical cosmopolitan cities.
BACKGROUND AND PURPOSE: The correlation between meteorological parameters and intracerebral hemorrhage (ICH) occurrence is controversial. Our research explored the effect of daily meteorological parameters on ICH risk in a subtropical monsoon basin climate. METHODS: We retrospectively analyzed patients with ICH in a teaching hospital. Daily meteorological parameters including temperature (TEM), atmospheric pressure (PRE), relative humidity (RHU), and sunshine duration (SSD) were collected, with the diurnal variation (daily maximum minus minimum) and day-to-day variation (average of the day minus the previous day) calculated to represent their fluctuation. We adopted a time-stratified case-crossover approach and selected conditional logistic regression to explore the effect of meteorological parameters on ICH risk. The influence of monthly mean temperature proceeded via stratified analysis. Air pollutants were gathered as covariates. RESULTS: Our study included 1052 eligible cases with ICH. In a single-factor model, the risk of ICH decreased by 5.9% (P<0.001) for each 1??C higher of the daily mean TEM, and the risk increased by 2.4% (P=0.002) for each 1hPa higher of the daily mean PRE. Prolongation of daily SSD inhibited the risk of ICH, and OR was 0.959 (P=0.007). The risk was raised by 7.5% (P=0.0496) with a 1°C increment of day-to-day variation of TEM. In a two-factor model, the effect of daily mean TEM or daily SSD on ICH risk was still statistically significant after adjusting another factor. The influence of meteorological parameters on ICH risk continued in cold months but disappeared in warm months after stratified analysis. CONCLUSION: This research indicates daily TEM and SSD had an inverse correlation to ICH risk in a subtropical monsoon basin climate. They were independent when adjusted by another factor. Daily PRE and day-to-day TEM variation were positively related to ICH risk. The correlation of daily meteorological factors on ICH risk was affected by the monthly thermal background.
BACKGROUND: Climate change and its subsequent effects on temperature have raised global public health concerns. Although numerous epidemiological studies have shown the adverse health effects of temperature, the association remains unclear for children aged below five years old and those in tropical climate regions. METHODS: We conducted a two-stage time-stratified case-crossover study to examine the association between temperature and under-five mortality, spanning the period from 2014 to 2018 across all six regions in Malaysia. In the first stage, we estimated region-specific temperature-mortality associations using a conditional Poisson regression and distributed lag nonlinear models. We used a multivariate meta-regression model to pool the region-specific estimates and examine the potential role of local characteristics in the association, which includes geographical information, demographics, socioeconomic status, long-term temperature metrics, and Healthcare by region. RESULTS: Temperature in Malaysia ranged from 22 °C to 31 °C, with a mean of 27.6 °C. No clear seasonality was observed in under-five mortality. We found no strong evidence of the association between temperature and under-five mortality, with an “M-” shaped exposure-response curve. The minimum mortality temperature (MMT) was identified at 27.1 °C. Among several local characteristics, only education level and hospital bed rates reduced the residual heterogeneity in the association. However, effect modification by these variables were not significant. CONCLUSION: This study suggests a null association between temperature and under-five mortality in Malaysia, which has a tropical climate. The “M-” shaped pattern suggests that under-fives may be vulnerable to temperature changes, even with a small temperature change in reference to the MMT. However, the weak risks with a large uncertainty at extreme temperatures remained inconclusive. Potential roles of education level and hospital bed rate were statistically inconclusive.
OBJECTIVES: To examine the association among acute bronchiolitis-related hospitalisation in children, meteorological variation and outdoor air pollution. METHODS: We obtained the daily counts of acute bronchiolitis-related admission of children≤2 years old from all public hospitals, meteorological data and outdoor air pollutants’ concentrations between 1 January 2008 and 31 December 2017 in Hong Kong. We used quasi-Poisson generalised additive models together with distributed lag non-linear models to estimate the associations of interest adjusted for confounders. RESULTS: A total of 29 688 admissions were included in the analysis. Increased adjusted relative risk (ARR) of acute bronchiolitis-related hospitalisation was associated with high temperature (ambient temperature and apparent temperature) and was marginally associated with high vapour pressure, a proxy for absolute humidity. High concentration of NO(2) was associated with elevated risk of acute bronchiolitis admission; the risk of bronchiolitis hospitalisation increased statistically significantly with cumulative NO(2) exposure over the range 66.2-119.6 µg/m(3). For PM(10), the significant effect observed at high concentrations appears to be immediate but not long lasting. For SO(2), ARR increased as the concentration approached the 75th percentile and then decreased though the association was insignificant. CONCLUSIONS: Acute bronchiolitis-related hospitalisation among children was associated with temperature and exposure to NO(2) and PM(10) at different lag times, suggesting a need to adopt sustainable clean air policies, especially to target pollutants produced by motor vehicles, to protect young children’s health.
BACKGROUND: The associations between ambient temperatures and stroke are still uncertain, although they have been widely studied. Furthermore, the impact of latitudes or climate zones on these associations is still controversial. The Tropic of Cancer passes through the middle of Taiwan and divides it into subtropical and tropical areas. Therefore, the Taiwan National Health Insurance Database can be used to study the influence of latitudes on the association between ambient temperature and stroke events. METHODS: In this study, we retrieved daily stroke events from 2010 to 2015 in the New Taipei and Taipei Cities (the subtropical areas) and Kaohsiung City (the tropical area) from the National Health Insurance Research Database. Overall, 70,338 and 125,163 stroke events, including ischemic stroke and intracerebral hemorrhage, in Kaohsiung City and the Taipei Area were retrieved from the database, respectively. We also collected daily mean temperatures from the Taipei and Kaohsiung weather stations during the same period. The data were decomposed by ensemble empirical mode decomposition (EEMD) into several intrinsic mode functions (IMFs). There were consistent 6-period IMFs with intervals around 360 days in most decomposed data. Spearman’s rank correlation test showed moderate-to-strong correlations between the relevant IMFs of daily temperatures and events of stroke in both areas, which were higher in the northern area compared with those in the southern area. CONCLUSIONS: EEMD is a useful tool to demonstrate the regularity of stroke events and their associations with dynamic changes of the ambient temperature. Our results clearly demonstrate the temporal association between the ambient temperature and daily events of ischemic stroke and intracranial hemorrhage. It will contribute to planning a healthcare system for stroke seasonally. Further well-designed prospective studies are needed to elucidate the meaning of these associations.
A substantial number of studies have demonstrated the association between air pollution and adverse health effects. However, few studies have explored the potential interactive effects between meteorological factors and air pollution. This study attempted to evaluate the interactive effects between meteorological factors (temperature and relative humidity) and air pollution ([Formula: see text], [Formula: see text], [Formula: see text], and [Formula: see text]) on cardiovascular diseases (CVDs). Next, the high-risk population susceptible to air pollution was identified. We collected daily counts of CVD hospitalizations, air pollution, and weather data in Nanning from January 1, 2014, to December 31, 2015. Generalized additive models (GAMs) with interaction terms were adopted to estimate the interactive effects of air pollution and meteorological factors on CVD after controlling for seasonality, day of the week, and public holidays. On low-temperature days, an increase of [Formula: see text] in [Formula: see text], [Formula: see text], and [Formula: see text] was associated with increases of 4.31% (2.39%, 6.26%) at lag 2; 2.74% (1.65%, 3.84%) at lag 0-2; and 0.13% (0.02%, 0.23%) at lag 0-3 in CVD hospitalizations, respectively. During low relative humidity days, a [Formula: see text] increment of lag 0-3 exposure was associated with increases of 3.43% (4.61%, 2.67%) and 0.10% (0.04%, 0.15%) for [Formula: see text] and [Formula: see text], respectively. On high relative humidity days, an increase of [Formula: see text] in [Formula: see text] was associated with an increase of 5.86% (1.82%, 10.07%) at lag 0-2 in CVD hospitalizations. Moreover, elderly (≥ 65 years) and female patients were vulnerable to the effects of air pollution. There were interactive effects between air pollutants and meteorological factors on CVD hospitalizations. The risk that [Formula: see text], [Formula: see text], and [Formula: see text] posed to CVD hospitalizations could be significantly enhanced by low temperatures. For [Formula: see text] and [Formula: see text], CVD hospitalization risk increased in low relative humidity. The effects of [Formula: see text] were enhanced at high relative humidity.
OBJECTIVE: Gout is a chronic disease caused by the deposition of sodium urate (MSU) crystals. Available data on the association between environmental hazards and gout are scarce. The present study was present to investigate the relationship between short-term exposure to air pollution and hospitalizations for acute gout from 2016 to 2020 in Anqing City, China. METHODS: Daily records of hospital admissions for acute gout in Anqing from 1 January 2016 to 31 December 2020 were retrieved from the tertiary first-class hospitals in Anqing. Air pollutants and meteorological data were obtained from the China Environmental Monitoring Station and China Meteorological Data Service Center respectively. We used a time-series analysis to explore the association between air pollution (NO(2), O(3), and CO) and hospitalizations for acute gout, and conducted stratified analyses by gender, age and season. RESULTS: We observed an association between NO(2) and hospitalizations for gout (lag 0, relative risk (RR):1.022, 95% confidence interval (CI):1.004-1.041). For every 1 mg/m(3) increase in CO concentration, hospitalizations for gout increased by 3.9% (lag 11 days, RR=1.039, 95% CI: 1.004-1.076). Intriguingly, there was a negative association between O(3) and hospitalizations for gout (lag0, RR=0.986, 95% CI: 0.976-0.996). Stratified analyses showed that exposure to high levels of NO(2) was considered to be more vulnerable to gout in cold season. CONCLUSION: Our study showed that short-term exposure to NO(2) and CO has a significant effect on hospitalizations for acute gout.
Australia has experienced an astonishing increase in liver cancer over the past few decades and the epidemiological reasons behind this are puzzling. The existing recognized risk factors for liver cancer, viral hepatitis, and alcohol consumption, are inconsistent with the trend in liver cancer. Behind the effects of migration and metabolic disease lies a potential contribution of climate change to an increase in liver cancer. This study explored the climate-associated distribution of high-risk areas for liver cancer by comparing liver cancer to lung cancer and finds that the incidence of liver cancer is more pronounced in hot and humid areas. This study showed the risk of liver cancer was higher in the equatorial region and tropical regions. These results will extend the study on the health consequences of climate change and provide more ideas and directions for future researchers.
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.
BACKGROUND: Although low temperature and air pollution exposures have been associated with the risk of anxiety, their combined effects remain unclear. OBJECTIVE: To investigate the independent and interactive effects of low temperature and air pollution exposures on anxiety. METHOD: Using a case-crossover study design, the authors collected data from 101,636 outpatient visits due to anxiety in three subtropical Chinese cities during the cold season (November to April in 2013 through 2018), and then built conditional logistic regression models based on individual exposure assessments [temperature, relative humidity, particulate matter (PM(2.5), PM(10)), sulfur dioxide (SO(2)), and nitrogen dioxide (NO(2))] and twelve cold spell definitions. Additive-scale interactions were assessed using the relative excess risk due to interaction (RERI). RESULTS: Both cold spell and air pollution were significantly associated with outpatients for anxiety. The effects of cold spell increased with its intensity, ranging from 8.98% (95% CI: 2.02%, 16.41%) to 15.24% (95% CI: 6.75%, 24.39%) in Huizhou. Additionally, each 10 μg/m(3) increase of PM(2.5), PM(10), NO(2) and SO(2) was associated with a 1.51% (95% CI: 0.61%, 2.43%), 1.58% (95% CI: 0.89%, 2.28%), 13.95% (9.98%, 18.05%) and 11.84% (95% CI: 8.25%, 15.55%) increase in outpatient visits for anxiety. Synergistic interactions (RERI >0) of cold spell with all four air pollutants on anxiety were observed, especially for more intense cold spells. For particulate matters, these interactions were found even under mild cold spell definitions [RERI: 0.11 (95% CI: 0.02, 0.21) for PM(2.5), and 0.24 (95% CI: 0.14, 0.33) for PM(10)]. Stratified analyses yielded a pronounced results in people aged 18-65 years. CONCLUSIONS: These findings indicate that both cold spell and air pollution are important drivers of the occurrence of anxiety, and simultaneous exposure to these two factors might have synergistic effects on anxiety. These findings highlight the importance of controlling air pollution and improving cold-warning systems.
Previous studies have suggested an association between air pollution and lung disease. However, few studies have explored the relationship between chronic lung diseases classified by lung function and environmental parameters. This study aimed to comprehensively investigate the relationship between chronic lung diseases, air pollution, meteorological factors, and anthropometric indices. We conducted a cross-sectional study using the Taiwan Biobank and the Taiwan Air Quality Monitoring Database. A total of 2889 participants were included. We found a V/U-shaped relationship between temperature and air pollutants, with significant effects at both high and low temperatures. In addition, at lower temperatures (<24.6 °C), air pollutants including carbon monoxide (CO) (adjusted OR (aOR):1.78/Log 1 ppb, 95% CI 0.98-3.25; aOR:5.35/Log 1 ppb, 95% CI 2.88-9.94), nitrogen monoxide (NO) (aOR:1.05/ppm, 95% CI 1.01-1.09; aOR:1.11/ppm, 95% CI 1.07-1.15), nitrogen oxides (NO(x)) (aOR:1.02/ppm, 95% CI 1.00-1.05; aOR:1.06/ppm, 95% CI 1.04-1.08), and sulfur dioxide (SO(2)) (aOR:1.29/ppm, 95% CI 1.01-1.65; aOR:1.77/ppm, 95% CI 1.36-2.30) were associated with restrictive and mixed lung diseases, respectively. Exposure to CO, NO, NO(2), NO(x) and SO(2) significantly affected obstructive and mixed lung disease in southern Taiwan. In conclusion, temperature and air pollution should be considered together when evaluating the impact on chronic lung diseases.
Air temperature and humidity have a great impact on public health, leads to heat stress. The US National Weather Service uses temperature and relative humidity to build a heat index (HI) as a metric to identify the thresholds for heat stress as felt by the public. Under climate change conditions and especially in hot humid weather during summer, the number of hot days in Hanoi has increased in recent times. Subsequently, the heat index is rising in both number of occurrences and level of intensity leading to increasing temperature stress on people’s health. The daily heat index for the future was simulated using maximum daily temperature and minimum daily relative humidity based on climate change scenarios. Maximum daily temperature was provided by the climate change model, while minimum daily relative humidity was estimated from the following: maximum daily temperature, mean daily temperature and daily rainfall. Results show that in the future, the heat index will increase by 0.0777 degrees C/year in the RCP 4.5 scenario and 0.08 degrees C/year in the RCP 8.5 scenario. Number of weeks with heat at danger tends to increase to 5.5 weeks/5 year for scenario RCP 4.5, and it is 6 weeks/5 years under RCP 8.5 scenario. In particular, the number of days of heatstroke over a 30-year period (from 1991 to 2020) amounted to only 4, that is an average of 0.13 days of the year, which represents a very rare weather phenomenon in the past. In contrast, under an RCP 4.5 scenario in the future over a 30-year period, the average number of days per year will be 2, 57 days; while the average number of days per year under an RCP 8.5 scenario would be 3, 87 days. This phenomenon will be mainly concentrated in the months of June, July, and August. Projections of this type are a key tool for communities working out how they will adapt to heat stress in the context of climate change.
Public health is threatened by climate change and extreme temperature events worldwide. Differences in health predispositions, access to cooling infrastructure and occupation raises an issue of heat-related health inequality in those vulnerable and disadvantaged demographic groups. To address these issues, a comprehensive understanding of the effect of elevated body temperatures on human biological systems and overall health is urgently needed. In this paper we look at the inner workings of the human innate immunity under exposure to heat stress induced through exposure to environment and physical exertion. We couple two experimentally validated computational models: the innate immune system and thermal regulation of the human body. We first study the dynamics of critical indicators of innate immunity as a function of human core temperature. Next, we identify environmental and physical activity regimes that lead to core temperature levels that can potentially compromise the performance of the human innate immunity. Finally, to take into account the response of innate immunity to various intensities of physical activities, we utilise the dynamic core temperatures generated by a thermal regulation model. We compare the dynamics of all key players of the innate immunity for a variety of stresses like running a marathon, doing construction work, and leisure walking at speed of 4 km/h, all in the setting of a hot and humid tropical climate such as present in Singapore. We find that exposure to moderate heat stress leading to core temperatures within the mild febrile range (37, 38][Formula: see text], nudges the innate immune system into activation and improves the efficiency of its response. Overheating corresponding to core temperatures beyond 38[Formula: see text], however, has detrimental effects on the performance of the innate immune system, as it further induces inflammation, which causes a series of reactions that may lead to the non-resolution of the ongoing inflammation. Among the three physical activities considered in our simulated scenarios (marathon, construction work, and walking), marathon induces the highest level of inflammation that challenges the innate immune response with its resolution. Our study advances the current state of research towards understanding the implications of heat exposure for such an essential physiological system as the innate immunity. Although we find that among considered physical activities, a marathon of 2 h and 46 min induces the highest level of inflammation, it must be noted that construction work done on a daily basis under the hot and humid tropical climate, can produce a continuous level of inflammation triggering moieties stretched at a longer timeline beating the negative effects of running a marathon. Our study demonstrates that the performance of the innate immune system can be severely compromised by the exposure to heat stress and physical exertion. This poses significant risks to health especially to those with limited access to cooling infrastructures. This is due in part to having low income, or having to work on outdoor settings, which is the case for construction workers. These risks to public health should be addressed through individual and population-level measures via behavioural adaptation and provision of the cooling infrastructure in outdoor environments.
This study investigates the varies in human physiological response, subjective sensation and acute subclinical health symptoms with increasing activity levels at different high temperatures. Thirty-two healthy subjects were recruited to walk on a treadmill in a climate chamber at a speed of 4 km/h. They experienced four temperature conditions (26 degrees C, 30 degrees C, 33 degrees C and 37 degrees C), each exposure lasting 85 min. Eardrum temperature, heart rate, skin temperature, systolic blood pressure, respiratory flow, and respiration rate changed significantly with increasing temperatures. At temperature of 37 degrees C, the SpO2 decreased significantly compared with at 33 degrees C. Subjects perceived the environment unacceptable at 37 degrees C. The perceived air quality and air freshness correlated linearly with the enthalpy of air. The intensity of headache, dizziness, fatigue and sleepiness increased with increasing temperatures, while only aggravated significantly at 37 degrees C. Additionally, compared with the results at light activity level, heart rate and other key physiological parameters increased significantly with increasing activity levels. The subjects felt “very hot” at 37 degrees C, and the change trend in symptoms reported by subjects increased significantly at 37 degrees C with the increased exposure time, while no significant change was observed in 26-33 degrees C. It indicates that exposure to 37 degrees C impairs the health and safety of heat acclimatized subjects. Using linear fitting curve to predict human physiological tolerance time suggested by ISO 9986. The result shows that eardrum temperature exceeded 38.5 degrees C for 97min continuously walk at 37 degrees C. This provides valuable information involved physiological and psychological responses when human exposed to high temperatures in daily life or industrial production.
Purpose Weather is one of the main factors affecting labour productivity. Existing weather-productivity models focussed on hot and cold climates paying less attention to the tropics. Many tropical countries are expected to be the most areas affected by accelerated climate change and global warming, which may have a severe impact on labour health and productivity. The purpose of this paper is to assess whether the existing models can be used to predict labour productivity based on weather conditions in the tropics. Design/methodology/approach Five models are identified from the literature for evaluation. Using real labour productivity data of a high-rise building project in Malaysia, the actual productivity rate was compared with predicted productivity rates generated using the five models. The predicted productivity rates were generated using weather variables collected from an adjusting weather station to the project. Findings Compared with other models evaluated in this paper, the United States Army Corps of Engineers (USACE) was found to be the best model to predict productivity based on the case study data. However, the result shows only a 57% accuracy level of the USACE model indicating the need to develop a new model for the tropics for more accurate prediction. Originality/value The result of this study is perhaps the first to apply meteorological variables to predict productivity rates and validate them using actual productivity data in the tropics. This study is the first step to developing a more accurate productivity model, which will be useful for project planning and more accurate productivity rate estimation.
Introduction: In a tropical country like India, heat-related illnesses are a common occurrence in the unforgiving summer months. Our study aimed to study the profile and outcome of patients with heat-related illnesses presenting to the emergency department (ED).Materials and Methods: This retrospective, cross-sectional study included all patients with heat-related illnesses to the ED during the months of April, May, and June of 2016. Baseline demographic characteristics, computed tomography (CT) brain findings, and hospital outcome were noted.Results: During the 3-month study period, 72 patients presented with heat-related illnesses. Two-thirds (46/72: 63.8%) suffered from heat stroke, whereas one-third (26/72: 36.2%) had heat exhaustion. Classical and exertional types were seen in 46% and 54% of heat strokes, respectively. The mean age (standard deviation) of the patients was 59.7 (13.3) years with a male preponderance (56.9%). Homemakers (37.5%) and manual laborers (20.8%) were most commonly affected. Hypotension at ED arrival was noticed in 20.8% (15/72), whereas tachycardia and tachypnea were noted in 80.5% (58/72) each. The findings on CT of the brain included acute infarcts (5/26: 19.6%) and an intra-cranial bleed (1/26: 3.8%). The mortality rate was 19.5% (14/72).Conclusion: Heat-related illnesses cause significant mortality during the relentless hot summers of a tropical country like India. Homemakers and manual labors were the most affected group. Acute changes were seen in CT brain of a quarter of patients with heat stroke.The following core competencies are addressed in this article: Patient care, Systems-based practice, Medical knowledge, Practice-based learning and improvement.
The health and economic impacts of extreme heat on humans are especially pronounced in populations without the means to adapt. We deployed a sensor network across 12 informal settlements in Makassar, Indonesia to measure the thermal environment that people experience inside and outside their homes. We calculated two metrics to assess the magnitude and frequency of heat stress conditions, wet bulb temperature and wet bulb globe temperature, and compared our in situ data to that collected by weather stations. We found that informal settlement residents experience chronic heat stress conditions, which are underestimated by weather stations. Wet bulb temperatures approached the uppermost limits of human survivability, and wet bulb globe temperatures regularly exceeded recommended physical activity thresholds, both in houses and outdoors. Under a warming climate, a growing number of people living informally will face potentially severe impacts from heat stress that have likely been previously overlooked or underestimated.
Heat waves are unusually high temperature events over consecutive days and may cause adverse impacts such as morbidity and mortality. The interaction between heat waves and urban heat island (UHI) effects has remained a subject of debate, as some studies prove heat wave-UHI synergy while others do not. Furthermore, heat waves affect tropical cities more severely than mid-latitude cities, but there is a disproportionate lack of heat wave studies focusing on tropical cities. We attempt to narrow this gap by studying the heat wave in Singapore in April 2016 using ground observations and the Weather Research and Forecasting (WRF) model. Compared to non-heat wave days, the ground observations show that daytime temperatures can be 3 degrees C higher during the heat wave. Despite the temperature spike, the UHI intensity is not amplified during the heat wave, maintaining its peak near 2.5 degrees C during both heat wave and non-heat wave periods. WRF simulation results also agree well with measurements and predict UHI peaks near 2.5 degrees C during both periods, showing no heat wave-UHI synergy. The spatially averaged UHI intensity also shows no such synergy. There is no significant change of wind speed, soil moisture availability or heat storage flux during the heat wave. Therefore, the lack of heat wave-UHI synergy in our study is consistent with current understanding of factors contributing to UHI. This study shows that the heat wave-UHI interaction in a tropical city can be different from that in cities in the temperate climate zone and more studies should be conducted in tropical cities, which are projected to suffer larger impacts of increasing heat stress.
BACKGROUND: Excessive heat exposure and dehydration among agricultural workers have been reported to reduce kidney function and lead to chronic kidney disease of unknown etiology (CKDu). OBJECTIVE: This cross-sectional study aimed to assess heat exposure, factors related to dehydration and the relationship between dehydration and biomarkers of kidney function among sea salt workers in Thailand. MATERIAL AND METHODS: Wet bulb globe temperature (WBGT) was used at the time workers started work outdoors on salt farms. Urine-specific gravity, urine osmolarity, and serum creatinine were collected from 50 workers after work. RESULTS: The results showed that more than 50% of the participants were dehydrated after work. The maximum hours spent working per day was 10. The average water intake was 1.51 L. Urine specific gravity was highly significant correlated with urine osmolality (rs = 0.400, p<0.01), and urine osmolality was significantly correlated with the estimated glomerular filtration rate (eGFR) (rs = 0.349, p<0.05). In bivariate analysis adjusted for age, sex, and current alcohol consumption, we found that a WBGTTWA ≥ 30°C (OR = 0.08, 95% CI = 0.01-0.44, p = 0.003) and hours spent working (OR=2.22, 95% CI = 1.42-3.47, p <0.001) were independently associated with dehydration. This suggests that workers should increase their time spent on breaks and increase water consumption. CONCLUSIONS: Educational program on heat exposure and heat-related illness prevention strategies should be provided.
Extreme thermal environment harms the health of outdoor workers and poses a potential threat to workplace safety. A field survey, including thermal parameter measurements, was conducted at construction sites in South China during the summer of 2019. The relationship between health risk and thermal parameters was obtained. The thermal sensation and satisfaction rate of the workers at different outdoor environmental conditions were analyzed, and recommendations were made based on the comparison of thermal indices. The thermal stress categories of the thermal indices were also investigated. The results suggest that the intensity of working conditions should be reduced when the air temperature is higher than 34 degrees C; the satisfaction rate of workers was found to be relatively high when the outdoor temperature is lower than 34 degrees C and the wind speed is greater than 1.3 m/s. Thermal indicators used to evaluate the comfort level of outdoor workers need to be modified according to the local climate and working environment to avoid excessive exposure to high-temperature work environments.
BACKGROUND: Heat exposure is a risk factor for urologic diseases. However, there are limited existing studies that have examined the relationship between high temperatures and urologic disease. The aim of this study was to examine the associations between heat exposure and hospitalizations for urologic diseases in Queensland, Australia, during the hot seasons of 1995-2016 and to quantify the attributable risks. METHODS: We obtained 238 427 hospitalized cases with urologic diseases from Queensland Health between 1 December 1995 and 31 December 2016. Meteorological data were collected from the Scientific Information for Land Owners-a publicly accessible database of Australian climate data that provides daily data sets for a range of climate variables. A time-stratified, case-crossover design fitted with the conditional quasi-Poisson regression model was used to estimate the associations between temperature and hospitalizations for urologic diseases at the postcode level during each hot season (December-March). Attributable rates of hospitalizations for urologic disease due to heat exposure were calculated. Stratified analyses were performed by age, sex, climate zone, socio-economic factors and cause-specific urologic diseases. RESULTS: We found that a 1°C increase in temperature was associated with a 3.3% [95% confidence interval (CI): 2.9%, 3.7%] increase in hospitalization for the selected urologic diseases during the hot season. Hospitalizations for renal failure showed the strongest increase 5.88% (95% CI: 5.25%, 6.51%) among the specific causes of hospital admissions considered. Males and the elderly (≥60 years old) showed stronger associations with heat exposure than females and younger groups. The sex- and age-specific associations with heat exposure were similar across specific causes of urologic diseases. Overall, nearly one-fifth of hospitalizations for urologic diseases were attributable to heat exposure in Queensland. CONCLUSIONS: Heat exposure is associated with increased hospitalizations for urologic disease in Queensland during the hot season. This finding reinforces the pressing need for dedicated public health-promotion campaigns that target susceptible populations, especially for those more predisposed to renal failure. Given that short-term climate projections identify an increase in the frequency, duration and intensity of heatwaves, this public health advisory will be of increasing urgency in coming years.
Extreme urban heat alongside higher ambient temperatures in urban areas causes serious energy, comfort, health and environmental problems. The implementation of urban heat mitigation techniques can significantly reduce urban temperatures and counterbalance the impact of extreme urban heat. This study assesses the potential cooling ability of modified urban albedo strategies through the implementation of reflective and super reflective materials, as well as the global climatic impacts on a subtropical desert urban environment in Dubai, UAE. Three scenarios using low, average and high albedo modifications are designed and evaluated in parallel to a reference scenario. A physically-based mesoscale urban modeling system is used to assess the thermal and meteorological impacts of the albedo modifications during both the summer and winter seasons at a city scale. The reduction of ambient temperature during the peak of a summer day (14:00 LT) is shown to be 0.6 degrees C, 1.4 degrees C and 2.6 degrees C when urban albedo is increased by 0.20, 0.45 and 0.60 respectively. The winter cooling penalty ranges between 0.6 degrees C and 1.1 degrees C for the different albedo scenarios. The increase of the urban albedo also significantly reduces the planetary boundary layer (PBL) depth due to the loss of sensible heat and decreases the intensity of the convective mixing and advection flows from the desert to the city, improving the mitigation potential of the reflective materials; however this increases the risk of a higher pollutants concentration. A much higher mitigation potential is observed for the high-density parts of the city when compared to that of the low-density parts of the city. Irrespective of linear function in the drop of ambient temperature and changing fraction of global albedo, our results reported that the cooling potential of reflective materials is highly influenced by the climate, landscape, and urban characteristics of the cities.
Average global temperatures and frequencies of heat waves are increasing with detrimental effects on health and wellbeing. This study presents a case study from two cities in the Northern Territory with the aim of exploring if and how people make deliberate adaptations to cope with increasing heat. Results show that 37% of all respondents made adjustments, with the most common being increased use of air-conditioning (65% of those responding to heat), followed by staying inside more often (22%) and passive cooling through modifications of house and garden (17%). Young people increasingly refrain from outside activities as temperatures increase. We also found that adaptive capacity was a function of education, long-term residency, home ownership and people’s self-rated wellbeing. Homeowners were more likely to adjust their living environment to the heat and renters less so. Being a property owner was commonly associated with the installation of solar panels to pay for high energy bills needed to run air-conditioning. Those who had solar panels at home were about ten times more likely to use air-conditioning more frequently in response to increasing heat. Our results confirm a growing dependence on artificially controlled environments to cope with heat in cities.
Vietnam is highly vulnerable to climate change-related extreme weather events such as heatwaves. This study assesses the association between heatwaves and hospitalizations due to mental and behavioral disorders (MBDs) in Ho Chi Minh City (HCMC). We collected daily MBD hospital admissions data at the HCMC Mental Health Hospital from 2017 to 2019. Heatwaves effects were characterized into the main effect (i.e., the intensity of temperature during heatwaves) and the added effect (i.e., the duration of heatwaves). Time series Poisson regression coupled with a distributed lag linear model (DLM) was used to quantify the 14-day lags effect of heatwaves. Confounders including long-term trend, seasonality, days of the week, holidays, and relative humidity were included in the model. Heatwaves increased all-cause MBD hospitalization by 62% (95%Cl, 36-93%) for the main effect and by 8% (95% Cl, - 3% to 19%) for the added effect. Noticeably, the group aged 18-60 years old was affected by the main effect of the heatwave, while the group aged 61 years and older was affected by the added effect of the heatwave. The effects of heatwaves differed among groups of MBD hospitalizations. The mental and behavioral disorder group due to psychoactive substance use was significantly affected by the main effect of heatwaves (RR:2.21; 95%Cl:1.55-3.15). The group of schizophrenia, schizotypal and delusional disorders were highly vulnerable towards both the main and the added effect of heatwaves with RR = 1.50 (95%CI, 1.20-1.86) and RR = 1.14 (95%CI, 1.01-1.30), respectively.
BACKGROUND: Few multicity studies have evaluated the association between cold spells and mortality risk and burden. OBJECTIVES: We aimed to estimate the association between cold spells and cause-specific mortality and to evaluate the mortality burden in China. METHODS: We conducted a time-series analysis with a nationally representative Disease Surveillance Points System database during the cool seasons spanning from 2013 to 2015 in 272 Chinese cities. We used 12 cold-spell definitions and overdispersed generalized additive models with distributed lag models to estimate the city-specific cumulative association of cold spells over lags of 0-28 d. We controlled for the nonlinear and lagged effects of cold temperature over 0-28 d to evaluate the added effect estimates of cold spell. We also quantified the nationwide mortality burden and pooled the estimated association at national and different climatic levels with meta-regression models. RESULTS: For the cold-spell definition of daily mean temperatures of ≤ 5th percentile of city-specific daily mean temperature and duration of ≥ 4 consecutive d, the relative risks (i.e., risk ratios) associated with cold spells were 1.39 [95% confidence interval (CI): 1.15, 1.69] for non-accidental mortality, 1.66 (95% CI: 1.20, 2.31) for coronary heart disease mortality, 1.49 (95% CI: 1.12, 1.97) for stroke mortality, and 1.26 (95% CI: 0.85, 1.87) for chronic obstructive pulmonary disease mortality. Cold spells showed a maximal lagged association of 28 d with the risks peaked at 10-15 d. A statistically significant attributable fraction (AF) of non-accidental mortality [2.10% (95% CI: 0.94%, 3.04%)] was estimated. The risks were higher in the temperate continental and the temperate monsoon zones than in the subtropical monsoon zone. The elderly population was especially vulnerable to cold spells. DISCUSSION: Our study provides evidence for the significant relative risks of non-accidental, cardiovascular, and respiratory mortality associated with cold spells. The findings on vulnerable populations and differential risks in different climatic zones may help establish region-specific forecasting systems against the hazardous impact of cold spells. https://doi.org/10.1289/EHP9284.
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.
Leptospirosis has been recognized as a major public health concern in Thailand following dramatic outbreaks. We analyzed human leptospirosis incidence between 2004 and 2014 in Mahasarakham province, Northeastern Thailand, in order to identify the agronomical and environmental factors likely to explain incidence at the level of 133 sub-districts and 1982 villages of the province. We performed general additive modeling (GAM) in order to take the spatial-temporal epidemiological dynamics into account. The results of GAM analyses showed that the average slope, population size, pig density, cow density and flood cover were significantly associated with leptospirosis occurrence in a district. Our results stress the importance of livestock favoring leptospirosis transmission to humans and suggest that prevention and control of leptospirosis need strong intersectoral collaboration between the public health, the livestock department and local communities. More specifically, such collaboration should integrate leptospirosis surveillance in both public and animal health for a better control of diseases in livestock while promoting public health prevention as encouraged by the One Health approach.
The tropical climate of Thailand encourages very high mosquito densities in certain areas and is ideal for dengue transmission, especially in the southern region where the province Nakhon Si Thammarat is located. It has the longest dengue fever transmission duration that is affected by some important climate predictors, such as rainfall, number of rainy days, temperature and humidity. We aimed to explore the relationship between weather variables and dengue and to analyse transmission hotspots and coldspots at the district-level. Poisson probability distribution of the generalized linear model (GLM) was used to examine the association between the monthly weather variable data and the reported number of dengue cases from January 2002 to December 2018 and geographic information system (GIS) for dengue hotspot analysis. Results showed a significant association between the environmental variables and dengue incidence when comparing the seasons. Temperature, sea-level pressure and wind speed had the highest coefficients, i.e. β=0.17, β= -0.12 and β= -0.11 (P<0.001), respectively. The risk of dengue incidence occurring during the rainy season was almost twice as high as that during monsoon. Statistically significant spatial clusters of dengue cases were observed all through the province in different years. Nabon was identified as a hotspot, while Pak Phanang was a coldspot for dengue fever incidence, explained by the fact that the former is a rubber-plantation hub, while the agricultural plains of the latter lend themselves to the practice of pisciculture combined with rice farming. This information is imminently important for planning apt sustainable control measures for dengue epidemics.
OBJECTIVE: The aim research was to analyze the association between temperature and humidity and the incidence of dengue fever in Manado Municipality. METHODS: The research design used analytical descriptive with a cross-sectional survey approach. Data were analyzed using the Spearman rank test. RESULT: The highest temperature was in August (28.7 °C), the highest humidity was January (88%), and the most DHF incidence was in January (409 cases). There is a significant association between temperature and the prevalence of DHF (p=0.000, r=-0.845). Humidity with the prevalence of DHF (p=0.000, r=0.873). CONCLUSION: It was found that two variables had a significant association between temperature and humidity on the prevalence of DHF in Manado Municipality based on observations of patterns of temperature and humidity characteristics every month during 2019.
BACKGROUND: Dengue fever (DF) is a mosquito-borne infectious disease that has threatened tropical and subtropical regions in recent decades. An early and targeted warning of a dengue epidemic is important for vector control. Current studies have primarily determined weather conditions to be the main factor for dengue forecasting, thereby neglecting that environmental suitability for mosquito breeding is also an important factor, especially in fine-grained intra-urban settings. Considering that street-view images are promising for depicting physical environments, this study proposes a framework for facilitating fine-grained intra-urban dengue forecasting by integrating the urban environments measured from street-view images. METHODS: The dengue epidemic that occurred in 167 townships of Guangzhou City, China, between 2015 and 2019 was taken as a study case. First, feature vectors of street-view images acquired inside each township were extracted by a pre-trained convolutional neural network, and then aggregated as an environmental feature vector of the township. Thus, townships with similar physical settings would exhibit similar environmental features. Second, the environmental feature vector is combined with commonly used features (e.g., temperature, rainfall, and past case count) as inputs to machine-learning models for weekly dengue forecasting. RESULTS: The performance of machine-learning forecasting models (i.e., MLP and SVM) integrated with and without environmental features were compared. This indicates that models integrating environmental features can identify high-risk urban units across the city more precisely than those using common features alone. In addition, the top 30% of high-risk townships predicted by our proposed methods can capture approximately 50-60% of dengue cases across the city. CONCLUSIONS: Incorporating local environments measured from street view images is effective in facilitating fine-grained intra-urban dengue forecasting, which is beneficial for conducting spatially precise dengue prevention and control.
In 2014 and 2015, Southern Taiwan experienced two unprecedented outbreaks, with more than 10,000 laboratory-confirmed dengue cases in each outbreak. The present study was aimed to investigate the influence of meteorological and spatial factors on dengue outbreaks in Southern Taiwan and was conducted in Kaohsiung City, which is the most affected area in Taiwan. The distributed lag nonlinear model was used to investigate the role of climatic factors in the 2014 and 2015 dengue outbreaks. Spatial statistics in the Geographic Information System was applied to study the relationship between the dengue spreading pattern and locations of traditional markets (human motility) in the 2015 dengue outbreak. Meteorological analysis results suggested that the relative risk of dengue fever increased when the weekly average temperature was more than 15°C at lagged weeks 5 to 18. Elevated relative risk of dengue was observed when the weekly average rainfall was more than 150 mm at lagged weeks 12 to 20. The spatial analysis revealed that approximately 83% of dengue cases were located in the 1000 m buffer zone of traditional market, with statistical significance. These findings support the influence of climatic factors and human motility on dengue outbreaks. Furthermore, the study analysis may help authorities to identify hotspots and decide the timing for implementation of dengue control programs.
BACKGROUND: The mosquitoes Aedes aegypti and Ae. albopictus are the primary vectors of dengue virus, and their geographic distributions are predicted to expand further with economic development, and in response to climate change. We aimed to estimate the impact of future climate change on dengue transmission through the development of a Suitable Conditions Index (SCI), based on climatic variables known to support vectorial capacity. We calculated the SCI based on various climate change scenarios for six countries in the Asia-Pacific region (Australia, China, Indonesia, The Philippines, Thailand and Vietnam). METHODS: Monthly raster climate data (temperature and precipitation) were collected for the period January 2005 to December 2018 along with projected climate estimates for the years 2030, 2050 and 2070 using Representative Concentration Pathway (RCP) 4·5, 6·0 and 8·5 emissions scenarios. We defined suitable temperature ranges for dengue transmission of between 17·05-34·61 °C for Ae. aegypti and 15·84-31·51 °C for Ae. albopictus and then developed a historical and predicted SCI based on weather variability to measure the expected geographic limits of dengue vectorial capacity. Historical and projected SCI values were compared through difference maps for the six countries. FINDINGS: Comparing different emission scenarios across all countries, we found that most South East Asian countries showed either a stable pattern of high suitability, or a potential decline in suitability for both vectors from 2030 to 2070, with a declining pattern particularly evident for Ae. albopictus. Temperate areas of both China and Australia showed a less stable pattern, with both moderate increases and decreases in suitability for each vector in different regions between 2030 and 2070. INTERPRETATION: The SCI will be a useful index for forecasting potential dengue risk distributions in response to climate change, and independently of the effects of human activity. When considered alongside additional correlates of infection such as human population density and socioeconomic development indicators, the SCI could be used to develop an early warning system for dengue transmission.
BACKGROUND: Global incidence of dengue has surged rapidly over the past decade. Each year, an estimated 390 million infections occur worldwide, with Asia-Pacific countries bearing about three-quarters of the global dengue disease burden. Global warming may influence the pattern of dengue transmission. While previous studies have shown that extremely high temperatures can impede the development of the Aedes mosquito, the effect of such extreme heat over a sustained period, also known as heatwaves, has not been investigated in a tropical climate setting. AIM: We examined the short-term relationships between maximum ambient temperature and heatwaves and reported dengue infections in Singapore, via ecological time series analysis, using data from 2009 to 2018. METHODS: We studied the effect of two measures of extreme heat – (i) heatwaves and (ii) maximum ambient temperature. We used a negative binomial regression, coupled with a distributed lag nonlinear model, to examine the immediate and lagged associations of extreme temperature on dengue infections, on a weekly timescale. We adjusted for long-term trend, seasonality, rainfall and absolute humidity, public holidays and autocorrelation. RESULTS: We observed an overall inhibitive effect of heatwaves on the risk of dengue infections, and a parabolic relationship between maximum temperature and dengue infections. A 1 °C increase in maximum temperature from 31 °C was associated with a 13.1% (Relative Risk (RR): 0.868, 95% CI: 0.798, 0.946) reduction in the cumulative risk of dengue infections over six weeks. Weeks with 3 heatwave days were associated with a 28.3% (RR: 0.717, 95% CI: 0.608, 0.845) overall reduction compared to weeks with no heatwave days. Adopting different heatwaves specifications did not substantially alter our estimates. CONCLUSION: Extreme heat was associated with decreased dengue incidence. Findings from this study highlight the importance of understanding the temperature dependency of vector-borne diseases in resource planning for an anticipated climate change scenario.
BACKGROUND: Studies have shown that tropical cyclones are associated with several infectious diseases, while very few evidence has demonstrated the relationship between tropical cyclones and dengue fever. This study aimed to examine the potential impact of tropical cyclones on dengue fever incidence in the Pearl River Delta, China. METHODS: Data on daily dengue fever incidence, occurrence of tropical cyclones and meteorological factors were collected between June and October, 2013-2018 from nine cities in the Pearl River Delta. Multicollinearity of meteorological variables was examined via Spearman correlation, variables with strong correlation (r>0.7) were not included in the model simultaneously. A time-stratified case-crossover design combined with conditional Poisson regression model was performed to evaluate the association between tropical cyclones and dengue fever incidence. Stratified analyses were performed by intensity grades of tropical cyclones (tropical storm and typhoon), sex (male and female) and age-groups (<18, 18-59, ≥60 years). RESULTS: During the study period, 20 tropical cyclones occurred and 47,784 dengue fever cases were reported. Tropical cyclones were associated with an increased risk of dengue fever in the Pearl River Delta region, with the largest relative risk of 1.62 with the 95% confidence interval (1.45-1.80) occurring on the lag 5 day. The strength of association was greater and lasted longer for typhoon than for tropical storm. There was no difference in effect estimates between males and females. However, individuals aged over 60 years were more vulnerable than others. CONCLUSIONS: Tropical cyclones are associated with increased risk of local dengue fever incidence in south China, with the elderly more vulnerable than other population subgroups. Health protective strategies should be developed to reduce the potential risk of dengue epidemic after tropical cyclones.
The identification of the key factors influencing dengue occurrence is critical for a successful response to the outbreak. It was interesting to consider possible differences in meteorological factors affecting dengue incidence during epidemic and non-epidemic periods. In this study, the overall correlation between weekly dengue incidence rates and meteorological variables were conducted in southern Taiwan (Tainan and Kaohsiung cities) from 2007 to 2017. The lagged-time Poisson regression analysis based on generalized estimating equation (GEE) was also performed. This study found that the best-fitting Poisson models with the smallest QICu values to characterize the relationships between dengue fever cases and meteorological factors in Tainan (QICu = −8.49 × 10−3) and Kaohsiung (−3116.30) for epidemic periods, respectively. During dengue epidemics, the maximum temperature with 2-month lag (β = 0.8400, p < 0.001) and minimum temperature with 5-month lag (0.3832, p < 0.001). During non-epidemic periods, the minimum temperature with 3-month lag (0.1737, p < 0.001) and mean temperature with 2-month lag (2.6743, p < 0.001) had a positive effect on dengue incidence in Tainan and Kaohsiung, respectively.
BACKGROUND: Previous studies have shown associations between local weather factors and dengue incidence in tropical and subtropical regions. However, spatial variability in those associations remains unclear and evidence is scarce regarding the effects of weather extremes. OBJECTIVES: We examined spatial variability in the effects of various weather conditions on the unprecedented dengue outbreak in Guangdong province of China in 2014 and explored how city characteristics modify weather-related risk. METHODS: A Bayesian spatial conditional autoregressive model was used to examine the overall and city-specific associations of dengue incidence with weather conditions including (1) average temperature, temperature variation, and average rainfall; and (2) weather extremes including numbers of days of extremely high temperature and high rainfall (both used 95th percentile as the cut-off). This model was run for cumulative dengue cases during five months from July to November (accounting for 99.8% of all dengue cases). A further analysis based on spatial variability was used to validate the modification effects by economic, demographic and environmental factors. RESULTS: We found a positive association of dengue incidence with average temperature in seven cities (relative risk (RR) range: 1.032 to 1.153), a positive association with average rainfall in seven cities (RR range: 1.237 to 1.974), and a negative association with temperature variation in four cities (RR range: 0.315 to 0.593). There was an overall positive association of dengue incidence with extremely high temperature (RR:1.054, 95% credible interval (CI): 1.016 to 1.094), without evidence of variation across cities, and an overall positive association of dengue with extremely high rainfall (RR:1.505, 95% CI: 1.096 to 2.080), with seven regions having stronger associations (RR range: 1.237 to 1.418). Greater effects of weather conditions appeared to occur in cities with higher economic level, lower green space coverage and lower elevation. CONCLUSIONS: Spatially varied effects of weather conditions on dengue outbreaks necessitate area-specific dengue prevention and control measures. Extremes of temperature and rainfall have strong and positive associations with dengue outbreaks.
OBJECTIVES: Evidence of the relationship between climate variability, air pollution and human parainfluenza virus (HPIV) infections has been inconsistent. We assessed this in a paediatric population from a highly urbanized tropical city-state. METHODS: We analysed all reports of HPIV infections in children <5 years old obtained from a major specialist women and children's hospital in Singapore. Assuming a negative binomial distribution and using multivariable fractional polynomial modelling, we examined the relations between climate variability, air quality and the risk of HPIV infections, adjusting for time-varying confounders. RESULTS: We identified 6393 laboratory-confirmed HPIV infections from 2009 to 2019. Every 1 °C decline in temperature was associated with a 5.8% increase (RR: 0.943, 95% Confidence Interval [95% CI]: 0.903-0.984) in HPIV infection risk 6 days later. Every 10% decrease in relative humidity was associated with a 15.8% cumulative increase in HPIV risk over the next 6 days (cumulative RR: 0.842, 95% CI: 0.771-0.919). Rainfall was positively associated with HPIV risk 2 days later (RR: 1.021, 95% CI: 1.000-1.043). A within-year seasonal rise of HPIV was driven by HPIV-3 and HPIV-1 and preceded by a seasonal decline in temperature. Gender was an effect modifier of the climate-HPIV relationship. Air quality was not associated with HPIV risk. CONCLUSIONS: This study demonstrates a close association between HPIV infection risk and tropical climate variability. The climate dependence and seasonal predictability of HPIV can inform the timing of community campaigns aimed at reducing infection risk and the development of hospital resources and climate adaption plans.
Extreme heat and poor air quality arising from landscape fires are an increasing global concern driven by anthropogenic climate change. Previous studies have shown these environmental conditions are associated with negative health outcomes for vulnerable people. Managing and adapting to these conditions in a warming climate can present substantial difficulties, especially in climates already challenging for human habitation. This study was set in the tropical city of Darwin, Australia. We recruited individuals from population groups vulnerable to outdoor hazards: outdoor workers, teachers and carers, and sportspeople, to participate in focus group discussions. We aimed to gain an understanding of the impacts of extreme heat and poor air quality and how individuals perceived and managed these environmental conditions. We identified a number of key themes relating to impacts on health, work and activity, and adaptive behaviors, while identifying gaps in policy and infrastructure that could improve the lives and protect the health of vulnerable people living, working, and playing in this region. In addition, these outcomes potentially provide direction for other regions with similar environmental challenges. Extreme heat and poor air quality place an additional burden on the lives of people in high-risk settings, such as outdoor workers, teachers and carers, and sportspeople.
We investigated the association between climate variables and pulmonary tuberculosis (PTB) incidence in Brunei-Muara district, Brunei Darussalam. Weekly PTB case counts and climate variables from January 2001 to December 2018 were analysed using distributed lag non-linear model framework. After adjusting for long-term trend and seasonality, we observed positive but delayed relationship between PTB incidence and minimum temperature, with significant adjusted relative risk (adj.RR) at 25.1 °C (95th percentile) when compared to the median, from lag 30 onwards (adj.RR = 1.17 [95% Confidence Interval (95% CI): 1.01, 1.36]), suggesting effect of minimum temperature on PTB incidence after 30 weeks. Similar results were observed from a sub-analysis on smear-positive PTB case counts from lag 29 onwards (adj.RR = 1.21 [95% CI: 1.01, 1.45]), along with positive and delayed association with total rainfall at 160.7 mm (95th percentile) when compared to the median, from lag 42 onwards (adj.RR = 1.23 [95% CI: 1.01, 1.49]). Our findings reveal evidence of delayed effects of climate on PTB incidence in Brunei, but with varying degrees of magnitude, direction and timing. Though explainable by environmental and social factors, further studies on the relative contribution of recent (through primary human-to-human transmission) and remote (through reactivation of latent TB) TB infection in equatorial settings is warranted.
OBJECTIVES: The aim of this study was to explore whether indoor or outdoor relative humidity (RH) modulates the influenza epidemic transmission in temperate and subtropical climates. METHODS: In this study, the daily temperature and RH in 1558 households from March 2017 to January 2019 in five cities across both temperate and subtropical regions in China were collected. City-level outdoor temperature and RH from 2013 to 2019 were collected from the weather stations. We first estimated the effective reproduction number (R(t)) of influenza and then used time-series analyses to explore the relationship between indoor/outdoor RH/absolute humidity and the R(t) of influenza. Furthermore, we expanded the measured 1-year indoor temperature and the RH data into 5 years and used the same method to examine the relationship between indoor/outdoor RH and the R(t) of influenza. RESULTS: Indoor RH displayed a seasonal pattern, with highs during the summer months and lows during the winter months, whereas outdoor RH fluctuated with no consistent pattern in subtropical regions. The R(t) of influenza followed a U-shaped relationship with indoor RH in both temperate and subtropical regions, whereas a U-shaped relationship was not observed between outdoor RH and R(t). In addition, indoor RH may be a better indicator for R(t) of influenza than indoor absolute humidity. CONCLUSION: The findings indicated that indoor RH may be the driver of influenza seasonality in both temperate and subtropical locations in China.
Neglected tropical diseases (NTDs) are a diverse group of diseases that continue to affect >1 billion people, with these diseases disproportionately impacting vulnerable populations and territories. Climate change is having an increasing impact on public health in tropical and subtropical areas and across the world and can affect disease distribution and transmission in potentially diverse ways. Improving our understanding of how climate change influences NTDs can help identify populations at risk to include in future public health interventions. Articles were identified by searching electronic databases for reports of climate change and NTDs between 1 January 2010 and 1 March 2020. Climate change may influence the emergence and re-emergence of multiple NTDs, particularly those that involve a vector or intermediate host for transmission. Although specific predictions are conflicting depending on the geographic area, the type of NTD and associated vectors and hosts, it is anticipated that multiple NTDs will have changes in their transmission period and geographic range and will likely encroach on regions and populations that have been previously unaffected. There is a need for improved surveillance and monitoring to identify areas of NTD incursion and emergence and include these in future public health interventions.
The increasing distribution and prevalence of fasciolosis in both human and livestock are concerning. Here, we examine the various types of factors influencing fasciolosis transmission and burden and the interrelations that may exist between them. We present the arsenal of molecules, ‘adjusting’ capabilities and parasitic strategies of Fasciola to infect. Such features define the high adaptability of Fasciola species for parasitism that facilitate their transmission. We discuss current environmental perturbations (increase of livestock and land use, climate change, introduction of alien species and biodiversity loss) in relation to fasciolosis dynamics. As Fasciola infection is directly and ultimately linked to livestock management, living conditions and cultural habits, which are also changing under the pressure of globalization and climate change, the social component of transmission is also discussed. Lastly, we examine the implication of increasing scientific and political awareness in highlighting the current circulation of fasciolosis and boosting epidemiological surveys and novel diagnostic techniques. From a joint perspective, it becomes clear that factors weight differently at each place and moment, depending on the biological, environmental, social and political interrelating contexts. Therefore, the analyses of a disease as complex as fasciolosis should be as integrative as possible to dissect the realities featuring each epidemiological scenario. Such a comprehensive appraisal is presented in this review and constitutes its main asset to serve as a fresh integrative understanding of fasciolosis.
This review seeks to explain three features of viral respiratory illnesses that have perplexed generations of virologists: (1) the seasonal timing of respiratory illness and the rapid response of outbreaks to weather, specifically temperature; (2) the common viruses causing respiratory illness worldwide, including year-round disease in the Tropics; (3) the rapid arrival and termination of epidemics caused by influenza and other viruses. The inadequacy of the popular explanations of seasonality is discussed, and a simple hypothesis is proposed, called temperature dependent viral tropism (TDVT), that is compatible with the above features of respiratory illness. TDVT notes that viruses can spread more effectively if they moderate their pathogenicity (thereby maintaining host mobility) and suggests that endemic respiratory viruses accomplish this by developing thermal sensitivity within a range that supports organ-specific viral tropism within the human body, whereby they replicate most rapidly at temperatures below body temperature. This can confine them to the upper respiratory tract and allow them to avoid infecting the lungs, heart, gut etc. Biochemical and tissue-culture studies show that ‘wild’ respiratory viruses show such natural thermal sensitivity. The typical early autumn surge of colds and the occurrence of respiratory illness in the Tropics year-round at intermediate levels are explained by the tendency for strains to adapt their thermal sensitivity to their local climate and season. TDVT has important practical implications for preventing and treating respiratory illness including Covid-19. It is testable with many options for experiments to increase our understanding of viral seasonality and pathogenicity.
Lymphatic filariasis (LF) is an important neglected parasitic disease according to the World Health Organization. In this study, we aimed to determine the prevalence of human LF in Asia using a systematic review and meta-analysis approach. Records from 1990 to 2018 in reputable databases including PubMed, Science Direct, Embase, and Cochrane Library were searched using a panel of related keywords. All 48 countries of Asia were searched one by one in combination with the keywords. In all, 41,742 cases identified in this study were included in the analysis. According to our findings, the pooled prevalence of LF in Asia was estimated at 3% (95% CI: [1.7, 5.2]). There was no major trend in the cumulative prevalence of LF over time. Some countries in Asia including China, Japan, Vietnam, and South Korea succeeded in eliminating LF as a public health problem, but others still need to monitor the disease. Based on the initiative of the WHO starting in 2000, some countries in Asia succeeded in eliminating LF as a public health problem. Other countries have taken steps to eliminate the disease with variable degrees of success. These efforts might be affected by issues such as climate change.
Mosquitoes are the most crucial insects in public health due to their vector capacity and competence to transmit pathogens, including arboviruses, bacterias and parasites. Re-emerging and emerging arboviral diseases, such as yellow fever virus (YFV), dengue virus (DENV), zika virus (ZIKV), and chikungunya virus (CHIKV), constitute one of the most critical health public concerns in Latin America. These diseases present a significant incidence within the human settlements increasing morbidity and mortality events. Likewise, among the different genus of mosquito vectors of arboviruses, those of the most significant medical importance corresponds to Aedes and Culex. In Latin America, the mosquito vector species of YFV, DENV, ZIKV, and CHIKV are mainly Aedes aegypti and Ae. Albopictus. Ae. aegypti is recognized as the primary vector in urban environments, whereas Ae. albopictus, recently introduced in the Americas, is more prone to rural settings. This minireview focuses on what is known about the epidemiological impact of mosquito-borne diseases in Latin American countries, with particular emphasis on YFV, DENV, ZIKV and CHIKV, vector mosquitoes, geographic distribution, and vector-arbovirus interactions. Besides, it was analyzed how climate change and social factors have influenced the spread of arboviruses and the control strategies developed against mosquitoes in this continent.
Pakistan is amongst the developing countries, which have been strongly affected by several emerging and re-emerging disease outbreaks as a consequence of climate change. Various studies have clearly demonstrated the impact of climate change on human health in Pakistan. This has increased the rate of morbidity and mortality, related not only to vector-borne, water-borne and food-borne diseases but has also contributed to the prevalence of neurological, cardiovascular and respiratory disorders. It is therefore important to take adequate measurements for water management and improve sanitary conditions especially in case of natural disasters. In order to effectively control the emerging and re-emerging infections in the country, an early, more Rigorous response is required, by the national health department, to monitor and evaluate the spread of infections in future. Therefore, precise planning and management strategies should be defined in order to circumvent the damage caused by the natural disasters associated with climate changes. This mini-review gives an overview about the public health issues associated with environmental change with special reference to Pakistan. This will provide a baseline for policymakers to develop public health surveillance programs in Pakistan.
PURPOSE OF REVIEW: This review aims to describe briefly the general information of arboviruses dengue, Zika, and chikungunya infections and emphasize the clinical manifestations of each, to help identify and make a quick diagnosis of each. RECENT FINDINGS: The most relevant advances in the study of these arboviruses’ infections have been in the epidemiological distribution, mainly due to international travel, migration, and climate change; in the clinical manifestations of these diseases, the development of clinical decision-making software, which can help improve the management and outcomes of these patients; and in the prevention of this disease. SUMMARY: Although arboviruses infections constitute a clinical challenge for the attending physician in the scope of a febrile returning traveler, a thorough clinical history and exam can help to aid diagnostic reasoning. The characteristics of the rash are a very helpful clue in the evaluation of these patients. Currently, there are clinical decision aid tools that help to get the diagnosis more quickly.
The association between floods and the risk of dysentery remain controversial. Therefore, we performed a meta-analysis to clarify this relationship. A literature search was performed in PubMed, Web of science, and Embase for relevant articles published up to November 2019. Random-effects model was used to pool relative risks with 95% confidence intervals. The sensitivity analysis was carried out to evaluate the stability of the results. Publication bias was estimated using Egger’s test. Eleven studies from 10 articles evaluated the association between floods and the risk of dysentery in China. The pooled RR (95% CI) of dysentery for the flooded time versus non-flooded period was 1.48 (95% CI: 1.14-1.91). Significant association was found in subgroup analysis stratified by dysentery styles [dysentery: 1.61 (95% CI: 1.34-1.93) and bacillary dysentery: 1.46 (95% CI: 1.06-2.01)]. The pooled RR (95%CI) of sensitivity analysis for dysentery was 1.26 (95% CI: 1.05-1.52). No significant publication bias was found in our meta-analysis. This meta-analysis confirms that floods have significantly increased the risk of dysentery in China. Our findings will provide more evidence to reduce negative health outcomes of floods in China.
Purpose of Review The impacts of climate change on biodiversity in the last three decades have increasingly assumed from significant to threatening proportions and this causes major global concerns. This study aims at examining the recent and future impacts of global climate change on both ecological resources and human well-being. This review study is based on the general concept of ecological resilience: that coping with climate change stresses and disturbances depends on social resilience, political and environmental strategies accessible in a community. The study assessed over 300 peer-reviewed publications, both articles and books, which linked climate change impacts on ecosystems to social/health resilience of people in the specific regions. Publications on that were focused on general impacts of climate change on global ecology, ecosystem distribution shifts and phenology change; the ecological and social/health resilience, in the tropic and polar regions, were reviewed. Recent Findings The major finding of this study is that there is considerable variation in magnitudes and patterns of responses to climate change in different regions, even with an overall review of scientific studies on the global ecosystem and human health. Despite this, what is obvious is that change in the ecosystem in Polar Regions will continue to have significant impacts on the global environment, flora, fauna and ultimately human well-being. There are many uncertainties, though, on the possible effects of climate change ecosystem and soils and their severe biological, social, cultural and economic consequences. Notwithstanding these uncertainties, the impacts of climate change on both ecosystem and human socio-cultural activities are very likely to become even more widespread in the near future.
While the East Asia Pacific (EAP) region has experienced tremendous economic growth and development, the resulting public health gains from reductions in its neglected tropical diseases (NTDs) have been less than expected due to opposing forces of urbanization, political instability, food insecurity, and climate change, together with co-morbidities with non-communicable diseases, including diabetes and hypertension. To be sure there’s been progress towards the elimination of lymphatic filariasis and trachoma through mass drug administration, and there are opportunities to extend MDA to yaws and scabies, but for most of the other NTDs we’ll require new biotechnologies. So far, EAP’s major technology hubs in China, Japan, Malaysia, Singapore, South Korea, and Taiwan have mostly failed to shift their attention towards new innovations for the NTDs, including new drugs, diagnostics, and vaccines, and vector control. Unless this situation changes the EAP could be facing a new grim reality of unhealthy megacities beset by emerging arbovirus infections, widespread antimicrobial resistance, and urban helminth infections.
INTRODUCTION: We are witnessing an alarming increase in the burden and range of mosquito-borne arboviral diseases. The transmission dynamics of arboviral diseases is highly sensitive to climate and weather and is further affected by non-climatic factors such as human mobility, urbanization, and disease control. As evidence also suggests, climate-driven changes in species interactions may trigger evolutionary responses in both vectors and pathogens with important consequences for disease transmission patterns. AREAS COVERED: Focusing on dengue and chikungunya, we review the current knowledge and challenges in our understanding of disease risk in a rapidly changing climate. We identify the most critical research gaps that limit the predictive skill of arbovirus risk models and the development of early warning systems, and conclude by highlighting the potentially important research directions to stimulate progress in this field. EXPERT OPINION: Future studies that aim to predict the risk of arboviral diseases need to consider the interactions between climate modes at different timescales, the effects of the many non-climatic drivers, as well as the potential for climate-driven adaptation and evolution in vectors and pathogens. An important outcome of such studies would be an enhanced ability to promulgate early warning information, initiate adequate response, and enhance preparedness capacity.
According to United Nations, cities situated in the tropical belt occupy only 36% of the Earth’s surface yet account for 1/3 of the entire global population. The increasing number of compact dense cities and the rapid population growth in the tropics have also been accompanied by increased urban air temperature. Increased air temperature is often associated with heat waves, and increased energy consumption. Therefore, the urban heat island (UHI) phenomenon and thermal stress have received much research attention and, as a result, the establishment of heat mitigation technologies has become critical. Although studies on urban climate in the tropics have shown progress, the situation in these areas remains complex and warrants further investigation. Accordingly, this paper examines the available heat mitigation techniques and their effectiveness in tropical areas from five perspectives, namely, shading (modifications in urban geometry), urban ventilation (street orientation, sun, and wind), urban greening (green roofs, trees, parks, and walls), albedo, and water bodies. This review paper showed that adopting a combination of mitigation approaches is the most effective method in reducing temperature in tropical cities. The use of shading and/or urban ventilation has also been proven to be more promising than the extensive use of vegetation, water bodies, or albedo modifications in reducing air temperature in tropical cities, where there is already a high level of humidity exists. Some key planning actions to combat UHI and thermal discomfort in tropical areas are eventually provided that can help urban planners integrate urban climatic knowledge into their practices.
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.
BACKGROUND: Globally, dengue, Zika virus, and chikungunya are important viral mosquito-borne diseases that infect millions of people annually. Their geographic range includes not only tropical areas but also sub-tropical and temperate zones such as Japan and Italy. The relative severity of these arboviral disease outbreaks can vary depending on the setting. In this study we explore variation in the epidemiologic potential of outbreaks amongst these climatic zones and arboviruses in order to elucidate potential reasons behind such differences. METHODOLOGY: We reviewed the peer-reviewed literature (PubMed) to obtain basic reproduction number (R(0)) estimates for dengue, Zika virus, and chikungunya from tropical, sub-tropical and temperate regions. We also computed R(0) estimates for temperate and sub-tropical climate zones, based on the outbreak curves in the initial outbreak phase. Lastly we compared these estimates across climate zones, defined by latitude. RESULTS: Of 2115 studies, we reviewed the full text of 128 studies and included 65 studies in our analysis. Our results suggest that the R(0) of an arboviral outbreak depends on climate zone, with lower R(0) estimates, on average, in temperate zones (R(0) = 2.03) compared to tropical (R(0) = 3.44) and sub-tropical zones (R(0) = 10.29). The variation in R(0) was considerable, ranging from 0.16 to 65. The largest R(0) was for dengue (65) and was estimated by the Ross-Macdonald model in the tropical zone, whereas the smallest R(0) (0.16) was for Zika virus and was estimated statistically from an outbreak curve in the sub-tropical zone. CONCLUSIONS: The results indicate climate zone to be an important determinant of the basic reproduction number, R(0), for dengue, Zika virus, and chikungunya. The role of other factors as determinants of R(0), such as methods, environmental and social conditions, and disease control, should be further investigated. The results suggest that R(0) may increase in temperate regions in response to global warming, and highlight the increasing need for strengthening preparedness and control activities.
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.
Leptospirosis is a zoonotic and waterborne disease worldwide. It is a neglected, reemerging disease of global public health importance with respect to morbidity and mortality both in humans and animals. Due to negligence, rapid, unplanned urbanization, and poor sanitation, leptospirosis emerges as a leading cause of acute febrile illness in many of the developing countries. Every individual has a risk of getting infected as domestic and wild animals carry leptospires; the at-risk population varies from the healthcare professionals, animal caretakers, farmers and agricultural workers, fishermen, rodent catchers, water sports people, National Disaster Response Force (NDRF) personnel, people who volunteer rescue operations in flood-affected areas, sanitary workers, sewage workers, etc. The clinical manifestations of leptospirosis range from flu-like illness to acute kidney failure (AKF), pneumonia, jaundice, pulmonary hemorrhages, etc. But many rare and uncommon clinical manifestations are being reported worldwide. This review will cover all possible updates in leptospirosis from occurrence, transmission, rare clinical manifestations, diagnosis, treatment, and prophylactic measures that are currently available, their advantages and the future perspectives, elaborately. There are less or very few reviews on leptospirosis in recent years. Thus, this work will serve as background knowledge for the current understanding of leptospirosis for researchers. This will provide a detailed analysis of leptospirosis and also help in finding research gaps and areas to focus on regarding future research perspectives.
This article explores the development of public health infrastructure in George Town, Penang, before the 1930s. It argues that the extreme weather of the tropical climate led to a unique set of health challenges for George Town’s administrators, as the town grew from a small British base to a multi-cultural and thriving port. Weather and public health were (and still are) integrally connected, although the framing of this relationship has undergone significant shifts in thinking and appearance over time. One lens into this association is the situation and expression of these elements within municipal structures. During the nineteenth century, government departments were fewer and shared roles and responsibilities. The Medical Department, for example, observed the weather. making connections between rain. drought and the incidence of disease. Engineers asked critical questions about mortality rates from disease after floods. As ideas about climate and health developed and changed, the shift became evident in the style, concerns and proliferation of governmental departments. This article thus considers the different ways in which weather, public health, and town planning were understood, managed and enacted by the Straits Settlements’ administration until the 1930s. It will start by exploring the situation facing the settlement’s inhabitants, in terms of specific climate and health challenges. It will then consider how these challenges were understood and addressed, why and by whom, and how these elements were repositioned over the period in question.
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.
The Mediterranean Basin is undergoing a warming trend with longer and warmer summers, an increase in the frequency and the severity of heat waves, changes in precipitation patterns and a reduction in rainfall amounts. In this unique populated region, which is characterized by significant gaps in the socio-economic levels particularly between the North (Europe) and South (Africa), parallel with population growth and migration, increased water demand and forest fires risk – the vulnerability of the Mediterranean population to human health risks increases significantly. Indeed, climatic changes impact the health of the Mediterranean population directly through extreme heat, drought or storms, or indirectly by changes in water availability, food provision and quality, air pollution and other stressors. The main health effects are related to extreme weather events (including extreme temperatures and floods), changes in the distribution of climate-sensitive diseases and changes in environmental and social conditions. The poorer countries, particularly in North Africa and the Levant, are at highest risk. Climate change affects the vulnerable sectors of the region, including an increasingly older population, with a larger percentage of those with chronic diseases, as well as poor people, which are therefore more susceptible to the effects of extreme temperatures. For those populations, a better surveillance and control systems are especially needed. In view of the climatic projections and the vulnerability of Mediterranean countries, climate change mitigation and adaptation become ever more imperative. It is important that prevention Health Action Plans will be implemented, particularly in those countries that currently have no prevention plans. Most adaptation measures are “win-win situation” from a health perspective, including reducing air pollution or providing shading solutions. Additionally, Mediterranean countries need to enhance cross-border collaboration, as adaptation to many of the health risks requires collaboration across borders and also across the different parts of the basin.
INTRODUCTION: Yellow fever (YF) is primarily transmitted by Haemagogus species of mosquitoes. Under climate change, mosquitoes and the pathogens that they carry are expected to develop faster, potentially impacting the case count and duration of YF outbreaks. The aim of this study was to determine how YF virus outbreaks in Brazil may change under future climate, using ensemble simulations from regional climate models under RCP4.5 and RCP8.5 scenarios for three time periods: 2011-2040 (short-term), 2041-2070 (mid-term), and 2071-2100 (long-term). METHODS: A compartmental model was developed to fit the 2017/18 YF outbreak data in Brazil using least squares optimization. To explore the impact of climate change, temperature-sensitive mosquito parameters were set to change over projected time periods using polynomial equations fitted to their relationship with temperature according to the average temperature for years 2011-2040, 2041-2070, and 2071-2100 for climate change scenarios using RCP4.5 and RCP8.5, where RCP4.5/RCP8.5 corresponds to intermediate/high radiative forcing values and to moderate/higher warming trends. A sensitivity analysis was conducted to determine how the temperature-sensitive parameters impacted model results, and to determine how vaccination could play a role in reducing YF in Brazil. RESULTS: Yellow fever case projections for Brazil from the models varied when climate change scenarios were applied, including the peak clinical case incidence, cumulative clinical case incidence, time to peak incidence, and the outbreak duration. Overall, a decrease in YF cases and outbreak duration was observed. Comparing the observed incidence in 2017/18 to the projected incidence in 2070-2100, for RCP4.5, the cumulative case incidence decreased from 184 to 161, and the outbreak duration decreased from 21 to 20 weeks. For RCP8.5, the peak case incidence decreased from 184 to 147, and the outbreak duration decreased from 21 to 17 weeks. The observed decrease was primarily due to temperature increasing beyond that suitable for Haemagogus mosquito survival. CONCLUSIONS: Climate change is anticipated to have an impact on mosquito-borne diseases. We found outbreaks of YF may reduce in intensity as temperatures increase in Brazil; however, temperature is not the only factor involved with disease transmission. Other factors must be explored to determine the attributable impact of climate change on mosquito-borne diseases.
Small island developing states in the Caribbean are among the most vulnerable countries on the planet to climate variability and climate change. In the last 3 decades, the Caribbean region has undergone frequent and intense heat waves, storms, floods, and droughts. This has had a detrimental impact on population health and well-being, including an increase in infectious disease outbreaks. Recent advances in climate science have enhanced our ability to anticipate hydrometeorological hazards and associated public health challenges. Here, we discuss progress towards bridging the gap between climate science and public health decision-making in the Caribbean to build health system resilience to extreme climatic events. We focus on the development of climate services to help manage mosquito-transmitted disease epidemics. There are numerous areas of ongoing biological research aimed at better understanding the direct and indirect impacts of climate change on the transmission of mosquito-borne diseases. Here, we emphasise additional factors that affect our ability to operationalise this biological understanding. We highlight a lack of financial resources, technical expertise, data sharing, and formalised partnerships between climate and health communities as major limiting factors to developing sustainable climate services for health. Recommendations include investing in integrated climate, health and mosquito surveillance systems, building regional and local human resource capacities, and designing national and regional cross-sectoral policies and national action plans. This will contribute towards achieving the Sustainable Development Goals (SDGs) and maximising regional development partnerships and co-benefits for improved health and well-being in the Caribbean.
Risk to health from extreme heat is gaining attention in scholarship and policy. Demographic and socio-economic factors affect the extent to which a person is at risk from extreme heat, whilst empirical research of social vulnerability to heat outside a ‘Western’ context is relatively limited. Many countries still rely on expert judgements to draw locally specific context for heat vulnerability assessment. Yet, their view might not be evidence-informed and the result is influenced by who are involved. This paper reflects this point by eliciting expert views of social heat vulnerability in Taiwan through an expert questionnaire survey using the Analytic Hierarchy Process method, and the result was compared to existing empirical research. Our study finds that experts consider factors related to adaptive capacity, especially societal support, as the most important; but rate gender and ethnicity as the least important. Although experts point to the importance of adaptive capacity, there are relatively few empirical studies to date in societal support, and the low priority given to gender and ethnicity also contradicts prior empirical research. For heat risk assessment, our findings show that whilst systematic elicitation of expert judgement may help to fill gaps in empirical evidence specific to the local context, caution should be paid to the significant divergence with existing empirical data and expert opinions depending on who are selected to involve.
This study evaluated the effect of extreme temperatures on events requiring emergency room visits (ERVs) for hypertensive disease, ischemic heart disease (IHD), cerebrovascular disease, and chronic kidney disease (CKD) for population stratified by sex and age living in Taiwan’s metropolitan city from 2000 to 2014. The distributed lag non-linear model was adopted to examine the association between ambient temperature and area-age-sex-disease-specific ERVs for a population aged 40 years and above. The reference temperature was defined by a percentile value to describe the temperature in each city. Area-age-sex-disease-specific relative risk (RR) and 95% confidence intervals (CI) were estimated in association with extreme high (99th percentile) and low (5th percentile) temperatures. Temperature-related ERV risks varied by area, age, sex, and disease. Patients with CKD tend to have comorbidities with hypertensive disease. All study populations with hypertensive disease have significant risk associations with extreme low temperatures with the highest RR of 2.64 (95% CI: 2.08, 3.36) appearing in New Taipei City. The risk of IHD was significantly associated with extreme high temperature for male subpopulation aged 40-64 years. A less significant association was observed between the risks of cerebrovascular disease with extreme temperature. The risk of CKD was most significantly associated with extreme high temperature especially for a subpopulation aged 40-64 years. All study subpopulations with hypertensive disease have significant risk associations with extreme low temperature. Male subpopulations were more vulnerable to extreme temperatures, especially for those aged 40-64 years.
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.
Influenza is an acute respiratory disease that seriously threatens public health. The occurrence of influenza has been proved to be related to a variety of meteorological factors. However, less attention has been paid to the effect of relative humidity (RH) on different types of influenza, especially in subtropical regions. Daily data on laboratory-confirmed influenza cases, weather variables, and air pollutants in Hefei covering the 2014-2019 period were collected. The seasonality and trend of daily influenza cases were explored by the time series seasonal decomposition method. Generalized linear model was fitted in conjunction with distributed lag nonlinear model to quantify the associations of RH with influenza A and influenza B. Subgroup analyses were conducted by sex, age (0-4, 5-17, and ?18 years), and season (cold and warm seasons). A total of 5238 influenza cases including 2847 influenza A cases and 2391 influenza B cases were recorded. The epidemic of influenza presented a distinct seasonal pattern, and the number of daily influenza cases increased steadily since 2016. High RH was related to an increased risk of influenza A (maximum RR = 1.683, 95%CI: 1.365-2.076), especially among males, females, and school-age children. Low RH was associated with an increased risk of influenza B (maximum RR = 1.252, 95%CI: 1.169-1.340). The contrasting relationships of RH with influenza A and B remained significant in cold seasons. High RH and low RH were significantly associated with the increased risk of influenza A and B, respectively. The findings of our study may provide clues for proposing new effective interventions.
Aedes albopictus (Diptera: Culicidae) distribution is bounded to a subtropical area in Argentina, while Aedes aegypti (Diptera: Culicidae) covers both temperate and subtropical regions. We assessed thermal and photoperiod conditions on dormancy status, development time and mortality for these species from subtropical Argentina. Short days (8 light : 16 dark) significantly increased larval development time for both species, an effect previously linked to diapause incidence. Aedes albopictus showed higher mortality than Ae. aegypti at 16?°C under long day treatments (16 light : 8 dark), which could indicate a lower tolerance to a sudden temperature decrease during the summer season. Aedes albopictus showed a slightly higher percentage of dormant eggs from females exposed to a short day, relative to previous research in Brazilian populations. Since we employed more hours of darkness, this could suggest a relationship between day-length and dormancy intensity. Interestingly, local Ae. aegypti presented dormancy similar to Ae. albopictus, in accordance with temperate populations. The minimum dormancy in Ae. albopictus would not be sufficient to extend its bounded distribution. We believe that these findings represent a novel contribution to current knowledge about the ecophysiology of Ae. albopictus and Ae. aegypti, two species with great epidemiological relevance in this subtropical region.
To date, research evidence suggests that extreme ambient temperatures may lead to preterm birth. Since the results of studies in subtropical humid monsoon climate are inconclusive, we investigated the association between extreme ambient temperatures and the risk of preterm birth in Xuzhou, China. We analyzed the association between the birth data of 103,876 singleton deliveries (from July 1, 2016 to June 30, 2019) and ambient temperature. We used a quasi-Poisson model with distributed lag nonlinear models (DLNM) to investigate the delay and nonlinear effects of temperature, taking into account the effects of air pollutants and relative humidity. During the study period, the number of hospitalizations for preterm birth was 4623. Taking the median temperature (16.8 °C) as a reference, the highest risk estimate at extreme cold temperature (- 2.8 °C, 1st percentile) was found at lag 0-1 days. Exposure to extreme cold (- 2.8 °C, 1st percentile), or moderate cold (6.8 °C, 25th percentile) were associated with 1.659 (95% confidence interval [CI] 1.177-2.338) and 1.456 (95% CI 1.183-1.790) increased risks of preterm birth, respectively. In the further stratified analysis of the age of pregnant women, we found that there were significant associations between cold temperatures and preterm birth in both groups (older group ? 35; younger group < 35). In a subtropical humid monsoon climate, low ambient temperatures may lead to preterm birth, suggesting that women should stay away from low temperatures during pregnancy.
The Urban Heat Island effect has been the focus of several studies concerned with the effects of urbanisation on human and ecosystem health. Humidity, however, remains much less studied, although it is useful for characterising human thermal comfort, the Urban Dryness Island effect and vegetation development. Furthermore, variability in microscale climate due to differences in land cover is increasingly crucial for understanding urbanisation effects on the health and wellbeing of living organisms. We used regression analysis to investigate the spatial and temporal dynamics of temperature, humidity and heat index in the tropical African city of Kampala, Uganda. We gathered data during the wet to dry season transition from 22 locations that represent the wide range of urban morphological differences in Kampala. Our analysis showed that the advancement of the dry season increased variability of climate in Kampala and that the most built-up locations experienced the most profound seasonal changes in climate. This work stresses the need to account for water availability and humidity to improve our understanding of human and ecosystem health in cities.
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.
In Colombia, little is known on the distribution of the Asian mosquito Aedes albopictus, main vector of dengue, chikungunya, and Zika in Asia and Oceania. Therefore, this work sought to estimate its current and future potential geographic distribution under the Representative Concentration Paths (RCP) 2.6 and 8.5 emission scenarios by 2050 and 2070, using ecological niche models. For this, predictions were made in MaxEnt, employing occurrences of A. albopictus from their native area and South America and bioclimatic variables of these places. We found that, from their invasion of Colombia to the most recent years, A. albopictus is present in 47% of the country, in peri-urban (20%), rural (23%), and urban (57%) areas between 0 and 1800 m, with Antioquia and Valle del Cauca being the departments with most of the records. Our ecological niche modelling for the currently suggests that A. albopictus is distributed in 96% of the Colombian continental surface up to 3000 m (p < 0.001) putting at risk at least 48 million of people that could be infected by the arboviruses that this species transmits. Additionally, by 2050 and 2070, under RCP 2.6 scenario, its distribution could cover to nearly 90% of continental extension up to 3100 m (?55 million of people at risk), while under RCP 8.5 scenario, it could decrease below 60% of continental extension, but expand upward to 3200 m (< 38 million of people at risk). These results suggest that, currently in Colombia, A. albopictus is found throughout the country and climate change could diminish eventually its area of distribution, but increase its altitudinal range. In Colombia, surveillance and vector control programs must focus their attention on this vector to avoid complications in the national public health setting.
Newly emerging or re-emerging infections are posing continuous threat to both public health system and clinical care globally. The emergence of infections especially caused by arboviruses can be linked to several mechanisms which include geographical expansion linked to human development and transportation, global warming, enhanced transmission in peridomestic area and close proximity of human habitations to domestic as well as wild animals. The co-circulation of Dengue, Chikungunya and Zika is a matter of public health priority due to the fact that they are transmitted by the same vector as well as increase in the number of reported cases of severe dengue, post-chikungunya chronic joint disease and microcephaly related to Zika virus disease. The study was designed to estimate the prevalence of these arboviral infections in Odisha. About 5198 cases presenting with common clinical symptoms of fever, arthralgia, headache, myalgia and malaise were screened during 2016-2019. A total of 42.2% patients tested positive for dengue NS1 antigen (n?=?4154), 30.2% for dengue IgM (n?=?2161) and 14.3% for chikungunya IgM (n?=?1816). A total of 1684 samples were subjected to Zika RT-PCR and none was tested positive. Peak in the numbers of dengue/ chikungunya cases was evident in the post-monsoon months of July – October. Circulation of all four serotypes of dengue i.e. DEN 1, 2, 3, and 4 was noticed in the state. Molecular investigation of suspected Chik cases in early phases showed circulation of Eastern Central Southern African genotype (E1:226A). There is dearth of knowledge about disease severity during arbovirus co-infections and importance of adequate management of patients at an early stage residing in risk areas. It is the first study in Odisha to study the pattern and status of these three arboviral diseases Dengue, Chikungunya and Zika. The outcome of this study will help in focusing and improvement of existing surveillance systems and vector control tools, as well as on the development of suitable antiviral agents and formulating candidate vaccine.
BACKGROUND: Understanding and describing the regional and climatic patterns associated with increasing dengue epidemics in Nepal is critical to improving vector and disease surveillance and targeting control efforts. METHODS: We investigated the spatial and temporal patterns of annual dengue incidence in Nepal from 2010 to 2019, and the impacts of seasonal meteorological conditions (mean maximum, minimum temperature and precipitation) and elevation on those patterns. RESULTS: More than 25 000 laboratory-confirmed dengue cases were reported from 2010 to 2019. Epidemiological trends suggest that dengue epidemics are cyclical with major outbreaks occurring at 2- to 3-y intervals. A significant negative relationship between dengue incidence and increasing elevation (metres above sea level) driven by temperature was observed (p<0.05) with dengue risk being greatest below 500 m. Risk was moderate between 500 and 1500 m and decreased substantially above 1500 m. Over the last decade, increased nightly temperatures during the monsoon months correlated with increased transmission (p<0.05). No other significant relationship was observed between annual dengue cases or incidence and climatological factors. CONCLUSIONS: The spatial analysis and interpretation of dengue incidence over the last decade in Nepal confirms that dengue is now a well-established public health threat of increasing importance, particularly in low elevation zones and urbanised areas with a tropical or subtropical climate. Seasonal variations in temperature during the monsoon months are associated with increased transmission.
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.
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.
Particulate matter (PM) has been occurring regularly during the dry season in the upper north of Thailand including Lamphun Province that might be influenced by various factors including climatologic and other pollutants. This paper aims to investigate the climatologic and gaseous factors influencing the occurrence of PM(10) concentration using Pollution Control Department (PCD) data. The secondary data of 2009 to 2017 obtained from the PCD was used for analysis. We used descriptive statistics, Pearson’s correlation coefficient, multiple regression and graphic presentation using R program (R packages of ‘open air’ and ‘ncdf4’) and Microsoft Excel Spreadsheet®. In addition, the periodic measurement of PM(2.5) and PM(10) were investigated to determine the ratio of PM(2.5)/PM(10). The results indicated that haze episodes (daily PM(10) concentration always over the PCD standard) normally occur during the dry season from February to April. The maximum concentration was always found in March. The PM(10) concentration was negatively associated with relative humidity and temperature while the PM(10) concentration showed a strongly positive association with CO and NO(2) concentration with correlation values of 0.70 and 0.57, respectively. Furthermore, we found CO and PM(10) concentration was associated with ozone concentration. This finding will benefit local communities and the public health sector to provide a warning system for preparation and response plans to react to PM(10) episodes in their responsible areas.
The International Agency for Research on Cancer (IARC) classifies benzene in group 1 (carcinogenic to humans). Particulate matter (PM) has recently also been classified in this category. This was an advance toward prioritizing the monitoring of particles in urban areas. The aim of the present study was to assess levels of PM(2.5) and BTEX (benzene, toluene, ethylbenzene, and xylene), the influence of meteorological variables, the planetary boundary layer (PBL), and urban variables as well as risks to human health in the city of Fortaleza, Brazil, in the wet and dry periods. BTEX compounds were sampled using the 1501 method of NIOSH and determined by GC-HS-PID/FID. PM(2.5) was monitored using an air sampling pump with a filter holder and determined by the gravimetric method. Average concentrations of BTEX ranged from 1.6 to 45.5 ?g m(-3), with higher values in the wet period, which may be explained by the fact that annual distribution is influenced by meteorological variables and the PBL. PM(2.5) levels ranged from 4.12 to 33.0 ?g m(-3) and 4.18 to 86.58 ?g m(-3) in the dry and wet periods, respectively. No seasonal pattern was found for PM(2.5), probably due to the influence of meteorological variables, the PBL, and urban variables. Cancer risk ranged from 2.46E(-04) to 4.71E(-03) and 1.72E(-04) to 2.01E(-03) for benzene and from 3.07E(-06) to 7.04E(-05) and 3.08E(-06) to 2.85E(-05) for PM(2.5) in the wet and dry periods, respectively. Cancer risk values for benzene were above the acceptable limit established by the international regulatory agency in both the dry and wet periods. The results obtained of the noncarcinogenic risks for the compounds toluene, ethylbenzene, and xylene were within the limits of acceptability. The findings also showed that the risk related to PM is always greater among smokers than nonsmokers.
Achieving environmental sustainability by improving the urban microclimate is a key principle in mitigating the urban heat island (UHI) effect. This study aimed to (a) investigate the outdoor thermal comfort by establishing Heat Index (HI) values to identify thermal hot spots and (b) model green infrastructure possibilities to alleviate UHI in Colombo urban metropolitan in Sri Lanka using ENVImet climate model. Daytime temperature and humidity values of 14 urban locations were collected to determine HI to recognize thermal urban hotspots in Colombo area. A pretested comprehensive random-stratified questionnaire survey has been conducted to appraise the thermal discernment of the general public. ENVImet microclimate model was accompanied to test the temperature reduction levels in different bioclimatic green infrastructure scenarios [Two belts (R-1), three belts (R-2), four belts (R-3), five belts (R-4)] in the selected study site. Five sites (Borella, Colombo Fort, Maradana, Wellawaththa, Liberty junction) were identified as thermal hotspots in Colombo metropolitan. HI values were fluctuated within 33.82-40.35 degrees C range and the highest average day time HI value was observed at Maradana (40.35 degrees C) and the lowest HI was observed at Thummulla (33.82 degrees C). Survey results revealed that 89.3% people are affected with thermal uncomfortability and 5% were affected with heat-related skin diseases. Inserting trees into curbsides (R-4) reduced temperature remarkably by 2.07 degrees C in the urban metropolitan. Therefore, the proposed green infrastructure scenario has proved to be the most suitable way to improve the thermal comfort conditions of urban environment, as it can reduce the UHI effects.
Tropospheric ozone is known to have adverse effects on human health. Ozone pollution events are often associated with specific atmospheric circulation conditions. Therefore, studying the relationship between atmospheric circulation and ozone is particularly important for early warning and forecasting of ozone pollution events. Focusing on the Yangtze River Delta region, particularly in four important large industrial cities (Xuzhou, Nanjing, Shanghai, and Hangzhou) in the Yangtze River Delta, the T-mode objective classification method was applied to classify the weather circulation that mainly affects the Yangtze River Delta region into nine types. Local wind fields for the four industrial cities were classified according to their propensity for ventilation, stagnation, and recirculation based on the Allwine and Whiteman method. Based on the analysis of large-scale atmospheric circulation, we concluded that certain circulation patterns correspond to excessive ozone concentrations, while other circulation patterns correspond to good air quality. Moreover, ozone pollution was not closely related to local regional transmission. The importance of high temperatures in potentiating ozone pollution was also identified in the study area, whereas the effect of relative humidity was negligible. Finally, the importance of the different scale atmospheric motions was analyzed by studying two specific ozone pollution events in Xuzhou area (March, 2019) and Nanjing area (July-August, 2017). This analysis was complemented by HYSPLIT model’s outputs to simulate the pollutant diffusion path. Regarding the first episode, ozone concentration is often closely related to the slowly approaching thermal high-pressure system. In the second episode, local transmission had little effect on the generation and spread of ozone pollution. Furthermore, and comparing the circulation conditions with local meteorological factors, it was found that the increase in ozone concentration was often accompanied by higher temperature, and the response to humidity was not clear.
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.
The health of smallholder farmers is crucial for ensuring food and nutritional security for two billion people. However, their health is in jeopardy for several reasons including challenges from climate change impacts. Using a narrative literature review supported by field observations and informal interviews with key informants in India, Bangladesh and Malawi, this paper identifies and discusses the health impacts of climate change under four categories: (i) communicable diseases, (ii) non-communicable diseases, (iii) mental health, and (iv) occupational health, safety and other health issues. The health impacts of climate change on smallholder farmers will hamper the realization of many of the United Nations’ Sustainable Development Goals, and a series of recommendations are made to regional and country governments to address the increasing health impacts of accelerating climate change among smallholder farmers.
Difficulties in controlling the effects of outdoor thermal environment on the human body are attracting considerable research attention. This study investigated the outdoor thermal comfort of urban pedestrians by assessing their perceptions of the tropical, micrometeorological, and physical conditions via a questionnaire survey. Evaluation of the outdoor thermal comfort involved pedestrians performing various physical activities (sitting, walking, and standing) in outdoor and semi-outdoor spaces where the data collection of air temperature, globe temperature, relative humidity, wind speed, solar radiation, metabolic activity, and clothing insulation data was done simultaneously. A total of 1011 participants were interviewed, and the micrometeorological data were recorded under outdoor and semi-outdoor conditions at two Malaysian university campuses. The neutral temperatures obtained which were 28.1 °C and 30.8 °C were within the biothermal acceptable ranges of 24-34 °C and 26-33 °C of the PET thermal sensation ranges for the outdoor and semi-outdoor conditions, respectively. Additionally, the participants’ thermal sensation and preference votes were highly correlated with the PET and strongly related to air and mean radiant temperatures. The findings demonstrated the influence of individuals’ thermal adaptation on the outdoor thermal comfort levels. This knowledge could be useful in the planning and designing of outdoor environments in hot and humid regions to create better thermal environments.
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.
Many occupational settings located outdoors in direct sun, such as open cut mining, pose a health, safety, and productivity risk to workers because of their increased exposure to heat. This issue is exacerbated by climate change effects, the physical nature of the work, the requirement to work extended shifts and the need to wear protective clothing which restricts evaporative cooling. Though Ghana has a rapidly expanding mining sector with a large workforce, there appears to be no study that has assessed the magnitude and risk of heat exposure on mining workers and its potential impact on this workforce. Questionnaires and temperature data loggers were used to assess the risk and extent of heat exposure in the working and living environments of Ghanaian miners. The variation in heat exposure risk factors across workers’ gender, education level, workload, work hours, physical work exertion and proximity to heat sources is significant (p<0.05). Mining workers are vulnerable to the hazards of heat exposure which can endanger their health and safety, productive capacity, social well-being, adaptive capacity and resilience. An evaluation of indoor and outdoor Wet Bulb Globe Temperature (WBGT) in the working and living environment showed that mining workers can be exposed to relatively high thermal load, thus raising their heat stress risk. Adequate adaptation policies and heat exposure management for workers are imperative to reduce heat stress risk, and improve productive capacity and the social health of mining workers.
Climate extreme events have significant impacts on the livelihoods of smallholder women farmers. The aim of the present study is to investigate the coping and adaptation measures that women farmers use to respond to specific climate extreme events. The data for the study comes from 187 smallholder women farmers from Upper West region of Ghana. The study employed the Bivariate Probit model in the empirical analysis. The results revealed that membership of farmer-based organizations and the use of climate information were the key factors which influenced women farmers’ coping strategies against climate extreme events. Women farmers’ adaptation measures were mainly influenced by access to credit. The key policy variable that influenced both coping and adaptation measures of women farmers was access to agricultural extension services. The study recommends that policy should focus on the promotion of specific coping and adaptation interventions against climate extreme events among women farmers. Policy should create enabling environment for the establishments of farmer-based organizations, increase women farmers’ contact with women agricultural extension officers and remove institutional barriers that impede access to credit and the use of climate information.Climate extreme events have significant impacts on the livelihoods of smallholder women farmers. The aim of the present study is to investigate the coping and adaptation measures that women farmers use to respond to specific climate extreme events. The data for the study comes from 187 smallholder women farmers from Upper West region of Ghana. The study employed the Bivariate Probit model in the empirical analysis. The results revealed that membership of farmer-based organizations and the use of climate information were the key factors which influenced women farmers’ coping strategies against climate extreme events. Women farmers’ adaptation measures were mainly influenced by access to credit. The key policy variable that influenced both coping and adaptation measures of women farmers was access to agricultural extension services. The study recommends that policy should focus on the promotion of specific coping and adaptation interventions against climate extreme events among women farmers. Policy should create enabling environment for the establishments of farmer-based organizations, increase women farmers’ contact with women agricultural extension officers and remove institutional barriers that impede access to credit and the use of climate information.
BACKGROUND: Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions. METHODS: Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature. RESULTS: A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier. CONCLUSIONS: The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.
Cumulative and synergistic impacts from environmental pressures, particularly in low-lying tropical coastal regions, present challenges for the governance of ecosystems, which provide natural resource-based livelihoods for communities. Here, we seek to understand the relationship between responses to the impacts of El Niño and La Niña events and the vulnerability of mangrove-dependent communities in the Caribbean region of Colombia. Using two case study sites, we show how communities are impacted by, and undertake reactive short-term responses to, El Niño and La Niña events, and how such responses can affect their adaptive capacity to progressive environmental deterioration. We show that certain coping measures to climate variability currently deliver maladaptive outcomes, resulting in circumstances that could contribute to system ‘lock-in’ and engender undesirable ecological states, exacerbating future livelihood vulnerabilities. We highlight the significant role of social barriers on vulnerabilities within the region, including perceptions of state abandonment, mistrust and conflicts with authorities. Opportunities to reduce vulnerability include enhancing the communities’ capacity to adopt more positive and preventative responses based on demonstrable experiential learning capacity. However, these will require close cooperation between formal and informal organisations at different levels, and the development of shared coherent adaptation strategies to manage the complexity of multiple interacting environmental and climatic pressures.
BACKGROUND: During the period 2001 to 2016, the maximum temperatures in Thailand rose from 38-41(o)C to 42-44(o)C. The current occupational heat exposure standard of Thailand issued in 2006 is based on wet bulb globe temperature (WBGT) defined for three workload levels without a work-rest regimen. This study examined whether the present standard still protects most workers. METHODS: The sample comprised 168 heat acclimatized workers (90 in construction sites, 78 in foundries). Heart rate and auditory canal temperature were recorded continuously for 2 hours. Workplace WBGT, relative humidity, and wind velocity were monitored, and the participants’ workloads were estimated. Heat-related symptoms and signs were collected by a questionnaire. RESULTS: Only 55% of the participants worked in workplaces complying with the heat standard. Of them, 79% had auditory canal temperature ? 38.5(o)C, compared with only 58% in noncompliant workplaces. 18% and 43% of the workers in compliant and noncompliant workplaces, respectively, had symptoms from heat stress, the trend being similar across all workload levels. An increase of one degree (C) in WBGT was associated with a 1.85-fold increase (95% confidence interval: 1.44-2.48) in odds for having symptoms. CONCLUSION: Compliance with the current occupational heat standard protects 4/5 of the workers, whereas noncompliance reduces this proportion to one half. The reasons for noncompliance include the gaps and ambiguities in the law. The law should specify work/rest schedules; outdoor work should be identified as an occupational heat hazard; and the staff should include occupational personnel to manage heat stress in establishments involving heat exposure.
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.
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.
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.
Around 27% of South Americans live in central and southern Brazil. Of 19,400 human malaria cases in Brazil in 2018, some were from the southern and southeastern states. High abundance of malaria vectors is generally positively associated with malaria incidence. Expanding geographic distributions of Anopheles vector mosquito species (e.g. A. cruzii) in the face of climate change processes would increase risk of such malaria transmission; such risk is of particular concern in regions that hold human population concentrations near present limits of vector species’ geographic distributions. We modeled effects of likely climate changes on the distribution of A. cruzii, evaluating two scenarios of future greenhouse gas emissions for 2050, as simulated in 21 general circulation models and two greenhouse gas scenarios (RCP 4.5 and RCP 8.5) for 2050. We tested 1305 candidate models, and chose among them based on statistical significance, predictive performance, and complexity. The models closely approximated the known geographic distribution of the species under current conditions. Under scenarios of future climate change, we noted increases in suitable area for the mosquito vector species in São Paulo and Rio de Janeiro states, including areas close to 30 densely populated cities. Under RCP 8.5, our models anticipate areal increases of >75% for this important malaria vector in the vicinity of 20 large Brazilian cities. We developed models that anticipate increased suitability for the mosquito species; around 50% of Brazilians reside in these areas, and ?89% of foreign tourists visit coastal areas in this region. Under climate change thereefore, the risk and vulnerability of human populations to malaria transmission appears bound to increase.
BACKGROUND: Understanding the association between floods and bacillary dysentery (BD) incidence is necessary for us to assess the health risk of extreme weather events. This study aims at exploring the association between floods and daily bacillary dysentery cases in main urban areas of Chongqing between 2005 and 2016 as well as evaluating the attributable risk from floods. METHODS: The association between floods and daily bacillary dysentery cases was evaluated by using distributed lag non-linear model, controlling for meteorological factors, long-term trend, seasonality, and day of week. The fraction and number of bacillary dysentery cases attributable to floods was calculated. Subgroup analyses were conducted to explore the association across age, gender, and occupation. RESULTS: After controlling the impact of temperature, precipitation, relative humidity, long-term trend, and seasonality, a significant lag effect of floods on bacillary dysentery cases was found at 0-day, 3-day, and 4-day lag, and the cumulative relative risk (CRR) over a 7-lag day period was 1.393 (95%CI 1.216-1.596). Male had higher risk than female. People under 5?years old and people aged 15-64?years old had significantly higher risk. Students, workers, and children had significantly higher risk. During the study period, based on 7-lag days, the attributable fraction of bacillary dysentery cases due to floods was 1.10% and the attributable number was 497 persons. CONCLUSIONS: This study confirms that floods can increase the risk of bacillary dysentery incidence in main urban areas of Chongqing within an accurate time scale, the risk of bacillary dysentery caused by floods is still serious. The key population includes male, people under 5?years old, students, workers, and children. Considering the lag effect of floods on bacillary dysentery, the government and public health emergency departments should advance to the emergency health response in order to minimize the potential risk of floods on public.
Heatwaves pose a serious threat to human health worldwide but remain poorly documented over Africa. This study uses mainly the ERA5 dataset to investigate their large-scale drivers over the Sahel region during boreal spring, with a focus on the role of tropical modes of variability including the Madden-Julian Oscillation (MJO) and the equatorial Rossby and Kelvin waves. Heatwaves were defined from daily minimum and maximum temperatures using a methodology that retains only intraseasonal scale events of large spatial extent. The results show that tropical modes have a large influence on the occurrence of Sahelian heatwaves, and, to a lesser extent, on their intensity. Depending on their convective phase, they can either increase or inhibit heatwave occurrence, with the MJO being the most important of the investigated drivers. A certain sensitivity to the geographic location and the diurnal cycle is observed, with nighttime heatwaves more impacted by the modes over the eastern Sahel and daytime heatwaves more affected over the western Sahel. The examination of the physical mechanisms shows that the modulation is made possible through the perturbation of regional circulation. Tropical modes thus exert a control on moisture and the subsequent longwave radiation, as well as on the advection of hot air. A detailed case study of a major event, which took place in April 2003, further supports these findings. Given the potential predictability offered by tropical modes at the intraseasonal scale, this study has key implications for heatwave risk management in the Sahel.
Both global climate change and urbanization trends will demand adaptation measures in cities. Large agglomerations and impacts on landscape and natural environments due to city growth will require guided densification schemes in urban areas, particularly in developing countries. Human biometeorological indices such as the Universal Thermal Climate Index (UTCI) could guide this process, as they provide a clear account of expected effects on thermal sensation from a given change in outdoor settings. However, an earlier step should optimally include an adequacy test of suggested comfort and thermal stress ranges with calibration procedures based on surveys with the target population. This paper compares obtained thermal comfort ranges for three different locations in Brazil: Belo Horizonte, 20° S, Aw climate type; Curitiba, 25.5° S, Cfb subtropical climate, both locations in elevation (above 900 m a.s.l.); and Pelotas, at sea level, latitude 32° S, with a Cfa climate type. In each city, a set of outdoor comfort field campaigns has been carried out according to similar procedures, covering a wide range of climatic conditions over different seasons of the year. Obtained results indicate a variation of neutral temperatures up to 3 °C (UTCI units) as a possible latitude and local climate effect between the southern locations relative to the northernmost location. Low UTCI values were found in the two subtropical locations for the lower threshold of the thermal comfort band as compared with the original threshold. A possible explanation for that is a longer exposure to cold conditions as buildings are seldom provided with heating systems.
Evidence of the impact of ambient temperatures on emergency ambulance calls (EACs) in developing countries contributes to the improvement and complete understanding of the acute health effects of temperatures. This study aimed to examine the impacts and burden of heat on EACs in China, quantify the contributions of regional modifiers, and identify the vulnerable populations. A semi-parametric generalized additive model with a Poisson distribution was used to analyze the city-specific impacts of the daily maximum temperature (T-ma(x)) on EACs in June-August in 2014-2017. Stratified analyses by sex and age were performed to identify the vulnerable sub-populations. Meta-analysis was undertaken to illustrate the pooled associations. Further subgroup analysis, stratified by climate, latitude, and per capita disposable income (PCDI), and meta-regression analysis were conducted to explore the regional heterogeneity and quantify the contributions of possible modifiers. The city- and region-specific attributable fractions of EACs attributable to heat were calculated. Strong associations were observed between the daily T-max and total EACs in all cities. A total of 11.7% (95% confidence interval (CI): 11.2%-12.3%) of EACs were attributed to high temperatures in ten Chinese cities, and the central region with a low level of PCDI had the highest attributable fraction of 17.8% (95% CI: 17.2%-18.4%). People living in the central region with lower PCDI, and those aged 18-44 and 0-6 years were more vulnerable to heat than the others. The combined effects of PCDI, temperature, and latitude contributed 88.6% of the regional heterogeneity. The results complemented the understanding of the burden of EACs attributable to heat in developing countries and the quantitative contribution of regional modifiers.
In the Northeast Brazil (NEB), the impacts of climate extreme events such as severe droughts are aggravated by poverty and poor socioeconomic conditions. In this region, such events usually result in the spread of endemic diseases, problems in water distribution, and agricultural losses, often leading to an increase in the population’s vulnerability. Thus, this study aims to evaluate the microregions of the Rio Grande do Norte (RN) state, in the NEB, according to the Epidemiological Index for Drought Vulnerability (EIDV). We mapped and classified the microregions according to three dimensions of vulnerability: risk, susceptibility, and adaptive capacity. We also verified potential associations between drought risk and epidemiological vulnerability. The EIDV was calculated by considering the three dimensions of vulnerability as mutually exclusive events and applying the third axiom of probability. Then we carried out a cluster analysis in order to classify the microregions according to similarities in the EIDV. Odds ratio were also calculated in order to evaluate the odds of microregions having a high susceptibility to diseases and high vulnerability given the drought risk. Results showed that the Pau dos Ferros, Seridó Ocidental, Seridó Oriental, and Umarizal microregions were the most vulnerable, while Natal and Litoral Sul were the least vulnerable. Regarding the dimensions of vulnerability, we observed that almost the entire RN state exhibited high drought risk. Pau dos Ferros and Umarizal had the highest susceptibility and Litoral Nordeste presented the worst adaptive capacity to the effects of drought on health. The EIDV revealed that the population of the RN state needs improvements in living conditions and health, since socioeconomic status is one of the factors that most influence the vulnerability of microregions, which in turn is aggravated by drought risk.
The indoor human thermal comfort (HTC) was investigated in residences located in the Pelotas City, southern Brazil, by the effective temperature index (ETI). In this study, temperature and relative humidity were measured inside 429 houses, located in different regions of Pelotas city, from January 11 to August 27, 2019. Samples were obtained using HOBO data loggers, indoor sensors, installed in different regions of the municipality, in the context of a cohort study of children between 2 and 4 years old and their respective mothers, led by Epidemiological Research Center of the Federal University of Pelotas (UFPEL). In general, all regions had average hourly values of effective temperature index above the comfort zone in summer and below the comfort zone in the winter. In terms of spatial variability, the indoor HTC was dependent on environmental factors such as lake breeze and indoor behavior factors, such as the use of air conditioning system in the downtown buildings.
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.
A comprehensive risk assessment of different types of natural disasters at the county level can promote quantitative disaster risk assessment and can provide a scientific basis for the formulation of disaster prevention measures. Focusing on climate-related hazards and based on natural disaster risk assessment theories and methods, this study integrates disaster statistics, meteorological data, geographic information, and other multivariate data to quantify the hazards of various disasters and the vulnerability and exposure of hazard-bearing bodies and conducts an integrated assessment of comprehensive risks of multiple climate-related hazards in Cangnan County, Zhejiang Province. Typhoon disaster risk is high in the central and northern parts of this county and low in its surroundings, with high-risk areas mainly distributed in Lingxi Town to the north. The comprehensive risk distribution patterns of drought and flood disasters in Cangnan County are similar: low in the south and high in the north. With the method of standard deviation, the comprehensive risk of multiple climate-related hazards in Cangnan County shows a distribution pattern of being low in the south and high in the north, with high risk in the northeast and low risk in the northwest and south.
Ambient air pollutants have been linked to adverse health outcomes, but evidence is still relatively rare in college students. Upper respiratory tract infection (URTI) is a common disease of respiratory system among college students. In this study, we assess the acute effect of air pollution on clinic visits of college students for URTI in Wuhan, China. Data on clinic visits due to URTI were collected from Wuhan University Hospital, meteorological factors (including daily temperature and relative humidity) provided by Wuhan Meteorological Bureau, and air pollutants by Wuhan Environmental Protection Bureau. In the present study, generalized additive model with a quasi-Poisson distribution link function was used to examine the association between ambient air pollutants (fine particulate matter (PM(2.5)), particulate matter (PM(10)), sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and ozone (O(3))) and the daily number of clinic visits of college students for URTI at Wuhan University Hospital in Wuhan, China. In the meantime, the model was adjusted for the confounding effects of long-term trends, seasonality, day of the week, public holidays, vacation, and meteorological factors. The best degrees of free in model were selected based on AIC (Akaike Information Criteria). The effect modification by gender was also examined. A total of 44,499 cases with principal diagnosis of URTI were included from January 1, 2016, to December 31, 2018. In single-pollutant models, the largest increment of URTI visits were found at lag 0 day in single-day lags, and the effect values in cumulative lags were greater than those in single-day lags. PM(2.5) (0.74% (95%CI: 0.05, 1.44)) at lag 0 day, PM(10) (0.61% (95%CI: 0.12, 1.11)) and O(3) (1.01% (95%CI: 0.24, 1.79)) at lag 0-1 days, and SO(2) (9.18% (95%CI: 3.27, 15.42)) and NO(2) (3.40% (95% CI:1.64, 5.19)) at lag 0-3 days were observed to be strongly and significantly associated with clinic visits for URTI. PM(10) and NO(2) were almost still significantly associated with URTI after controlling for the other pollutants in our two-pollutant models, where the effect value of SO(2) after inclusion of O(3) appeared to be the largest and the effects of NO(2) were also obvious compared with the other pollutants. Subgroups analysis demonstrated that males were more vulnerable to PM(10) and O(3), while females seemed more vulnerable to exposure to SO(2) and NO(2). This study implied that short-term exposure to ambient air pollution was associated with increased risk of URTI among college students at Wuhan University Hospital in Wuhan, China. And gaseous pollutants had more negative health impact than solid pollutants. SO(2) and NO(2) were the major air pollutants affecting the daily number of clinic visits on URTI, to which females seemed more vulnerable than males.
BACKGROUND: Zika virus (ZIKV) emerged in the Pacific Ocean and subsequently caused a dramatic Pan-American epidemic after its first appearance in the Northeast region of Brazil in 2015. The virus is transmitted by Aedes mosquitoes. We evaluated the role of temperature and infectious doses of ZIKV in vector competence of Brazilian populations of Ae. aegypti and Ae. albopictus. METHODOLOGY/PRINCIPAL FINDINGS: Two Ae. aegypti (Rio de Janeiro and Natal) and two Ae. albopictus (Rio de Janeiro and Manaus) populations were orally challenged with five viral doses (102 to 106 PFU / ml) of a ZIKV strain (Asian genotype) isolated in Northeastern Brazil, and incubated for 14 and 21 days in temperatures mimicking the spring-summer (28°C) and winter-autumn (22°C) mean values in Brazil. Detection of viral particles in the body, head and saliva samples was done by plaque assays in cell culture for determining the infection, dissemination and transmission rates, respectively. Compared with 28°C, at 22°C, transmission rates were significantly lower for both Ae. aegypti populations, and Ae. albopictus were not able to transmit the virus. Ae. albopictus showed low transmission rates even when challenged with the highest viral dose, while both Ae. aegypti populations presented higher of infection, dissemination and transmission rates than Ae. albopictus. Ae. aegypti showed higher transmission efficiency when taking virus doses of 105 and 106 PFU/mL following incubation at 28°C; both Ae. aegypti and Ae. albopictus were unable to transmit ZIKV with virus doses of 102 and 103 PFU/mL, regardless the incubation temperature. CONCLUSIONS/SIGNIFICANCE: The ingested viral dose and incubation temperature were significant predictors of the proportion of mosquito’s biting becoming infectious. Ae. aegypti and Ae. albopictus have the ability to transmit ZIKV when incubated at 28°C. However Brazilian populations of Ae. aegypti exhibit a much higher transmission potential for ZIKV than Ae. albopictus regardless the combination of infection dose and incubation temperature.
As global temperatures continue to rise it is imperative to understand the adverse effects this will pose to workers laboring outdoors. The purpose of this study was to investigate the relationship between increases in wet bulb globe temperature (WBGT) and risk of occupational injury or dehydration among agricultural workers. We used data collected by an agribusiness in Southwest Guatemala over the course of four harvest seasons and Poisson generalized linear modelling for this analysis. Our analyses suggest a 3% increase in recorded injury risk with each degree increase in daily average WBGT above 30 °C (95% CI: -6%, 14%). Additionally, these data suggest that the relationship between WBGT and injury risk is non-linear with an additional 4% acceleration in risk for every degree increase in WBGT above 30 °C (95% CI: 0%, 8%). No relationship was found between daily average WBGT and risk of dehydration. Our results indicate that agricultural workers are at an increased risk of occupational injury in humid and hot environments and that businesses need to plan and adapt to increasing global temperatures by implementing and evaluating effective occupational safety and health programs to protect the health, safety, and well-being of their workers.
Mitigation and adaption measures must be designed strategically by urban planners, designers, and decision-makers to reduce urban heat island (UHI) related risks. We employed the Weather Research and Forecasting (WRF) model to assess UHI mitigation scenarios for the tropical city of Singapore during April 2016, including two heat wave periods. The local climate zones for Singapore were used as the land use/land cover data to account for the intra-urban variability. The simulations show that the canopy layer UHI intensity in Singapore can reach up to 5 degrees C in compact areas during nighttime. The results reveal that city-scale deployment of cool roofs can provide an overall reduction of 1.3 degrees C in the near-surface daytime air temperature in large lowrise areas. Increasing the thermostat set temperature to 25 degrees C from 21 degrees C in city-wide buildings can potentially reduce the air temperature due to less (similar to 20%) waste heat discharge from airconditioning units. A densification scenario considering an increase from approximately 7 841 people/km(2) (2016) to 9040-9,600 people/km(2) (2030) under the current climate leads to air temperature increase of 1.4 degrees C, which demonstrates the importance of limiting the densification of less compact areas in maintaining thermal comfort in the future.
In the aftermath of the 2015 pandemic of Zika virus, concerns over links between climate change and emerging arboviruses have become more pressing. Given the potential that much of the world might remain at risk from the virus, we used a previously established temperature-dependent transmission model for Zika virus (ZIKV) to project climate change impacts on transmission suitability risk by mid-century (a generation into the future). Based on these model predictions, in the worst-case scenario, over 1.3 billion new people could face suitable transmission temperatures for ZIKV by 2050. The next generation will face substantially increased ZIKV transmission temperature suitability in North America and Europe, where naïve populations might be particularly vulnerable. Mitigating climate change even to moderate emissions scenarios could significantly reduce global expansion of climates suitable for ZIKV transmission, potentially protecting around 200 million people. Given these suitability risk projections, we suggest an increased priority on research establishing the immune history of vulnerable populations, modeling when and where the next ZIKV outbreak might occur, evaluating the efficacy of conventional and novel intervention measures, and increasing surveillance efforts to prevent further expansion of ZIKV.
It is well known that sudden variations of air temperature have the potential to cause severe impacts on human health. Therefore, it becomes necessary to provide information capable of quantifying the severity of the problem, considering that the continuous increase of temperature due to global warming and urban development will cause more intense effects in heavily populated areas. Due to its geographical location and local characteristics, Ecuador, a country located on the western coast of South America, is characterized by a high vulnerability to climatic extremes. The present research develops an evaluation of urban climate change effects through the analysis of extreme temperature indices using four meteorological stations situated in the city of Guayaquil (southwest Ecuador). Since the available data are not adequate for extreme temperature indices criteria, it was necessary to employ an infilling method for times series in an innovative way that can be applicable at the small scale. Thus, a cross-correlation-enhanced inverse distance weighting (CC-IDW) method was proposed. The method entails a spatial interpolation based on data of urban stations situated outside of Guayaquil by taking into account cross-correlation among times series at precise lags that leads to an improvement in the way of estimating the missing values. Subsequently, a homogeneity test, data quality control and the calculation of extreme temperature indices chosen from those proposed by the World Meteorological Organization (WMO) were implemented. The results show that there is a general tendency of warming with quite homogenous temperatures for all considered stations. However, it should be recognized that the climate pattern of this region is strongly modulated by the El Nino Southern Oscillation (ENSO) cycle. Only for two extreme indices: the highest maximum temperature (TXx) and the warm days (TX90p), are the resulting trend co-efficients statistically significant. The study suggests a deteriorated climatic condition due to heat stress that warrants further study using the available database for the city of Guayaquil.
This paper explores the perceived adaptation preference of rural island communities in addressing future climate change risks, particularly those concerning sea-level rise. The research explores the role of culture and local politics, and differences among various age and gender groups within the community regarding preferred adaptation pathways for coping with the impacts of future sea-level rise. A participatory action approach, in the form of a community workshop, was employed, which separated participants into community identified groupings. Differences in community groups’ adaptation preferences emerged, though the range of adaptation measures considered were limited, probably due to the participants’ limited exposure to adaptation mechanisms in their immediate surroundings. Overall, the communities surveyed tended to be conservative, especially in their attitudes towards western adaptation solutions developed in non-island contexts.
Fuel poverty has increasingly been associated with thermal discomfort, health related issues and winter deaths in the Global North because it can force families to choose between food and a warmer environment. Juxtaposing the concept of fuel poverty in rural tropical areas of the Global South, it is likely that a similar pattern between fuel poverty and heat related illnesses can be found. A recent study shows that between 1.8 and 4.1 billion people, especially in India, Southeast Asia and Sub-Saharan Africa will need indoor cooling to avoid heat related health issues. This paper aims to address a blind spot in the literature on the links between fuel poverty, thermal comfort and cooling strategies in the Brazilian Amazon. This study draws from current definitions and indicators of fuel poverty in the Global North and juxtaposes it in the context of tropical areas to understand how fuel poverty affects human health, livelihood strategies and social justice in rural communities that live in hot climates. To do so, this paper uses qualitative methods and a conceptual framework to guide the analysis. I call the intersection between vernacular architecture and sustainable cooling practices ‘energy relief.
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.
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.
BACKGROUND: Compared to hospital admissions (HAs), emergency ambulance dispatches (EADs) can be considered a real-time outcome for evaluating the public health impacts of ambient temperature. OBJECTIVES: This study aimed to assess if temperature has a causal effect on cause-specific EADs and its potential main and added effect in Shenzhen from 2013 to 2017. METHODS: A distributed lag nonlinear model (DLNM) with quasi-Poisson distribution was applied to quantify the association between temperature and EADs. Likewise, the fraction of EADs attributable to different temperature ranges was calculated to identify extreme temperature ranges affecting population health. We then explored the main and added wave effects of heatwaves. RESULTS: Ambient temperature showed a U-shaped association with EADs. The minimum risk temperature was 17 °C (16th percentile of the daily mean temperature). Compared with the cold, the relative risk (RR) of heat on EADs presented smaller but the attributable risk larger. The main effects of heatwaves on EADs varied with external causes; and the peak RR of heat on EADs was observed in suicidal behaviors with heatwaves defined as 3 or more days with temperatures above the 75th percentile (RR = 4.53, 95% CI: 1.23-16.68), followed by assault (RR = 2.36, 95% CI: 1.25-4.48) and accidents (RR = 1.72, 95% CI: 1.30-2.28), while the added wave effect was negligible. CONCLUSIONS: Heat was responsible for a higher proportion of EADs than cold. Most of the increase in health risk during warm season can be simply ascribed to the independent effects of daily temperature occurrences whether it is or not on the heat-wave day. And the main effects of heatwaves on cause-specific EADs showed varied change trends, of which the incidence of suicides seems more susceptible, followed by assault and accidents.
BACKGROUND: For pediatric pneumonia, the meteorological and air pollution indicators had been frequently investigated for their association with viral circulation, however, not for their impact on disease severity. METHODS: We performed a 10-year prospective observational study in one hospital in Chongqing, China to recruit children with pneumonia. Eight commonly seen respiratory viruses were tested. Autoregressive distributed lag (ADL) and Random forest (RF) models were performed to fit monthly detection rates of each virus at population level and predict the possibility of severe pneumonia at individual level, respectively. RESULTS: Between 2009?2018, 6 611 pediatric pneumonia patients were included, and 4 846 (73.3%) tested positive for at least one respiratory virus. The median age of the patients was 9 (IQR: 4?20) months. ADL models demonstrated a decent fitting of detection rates of four viruses (R2 >0.7 for RSV, HRV, PIV, and HMPV). Based on the RF models, the AUC for host-related factors alone is 0.88 (95% CI: 0.87?0.89), 0.86 (95% CI: 0.85?0.88) for meteorological and air pollution indicators alone, and 0.62 (95% CI: 0.60?0.63) for viral infections alone. The final model indicated that nine weather and air pollution indicators were important determinants of severe pneumonia, with relative contribution of 62.53%, significantly higher than respiratory viral infections (7.36%). CONCLUSIONS: Meteorological and air pollution predictors contributed more to severe pneumonia in children than respiratory viruses. These meteorological data could help predict times when children would be at increased risk for severe pneumonia, and interventions such as reducing outdoor activities, may be warranted.
Introduction: Altered weather patterns and changes in precipitation, temperature and humidity resulting from climate change could affect the distribution and incidence of cholera. This study is to quantify climate-induced increase in morbidity rates of cholera. Material and Methods: Monthly cholera cases and monthly temperature, precipitation, and relative humidity data from 2004 to 2014 were obtained from the Malaysian Ministry of Health and Malaysian Meteorological Department, respectively. Poisson generalized linear models were developed to quantify the relationship between meteorological parameters and the number of reported cholera cases. Results: The findings revealed that the total number of cholera cases in Malaysia during the 11 year study period was 3841 cases with 32 deaths. Out of these, 45.1% of the cases were among children below 12 years old and 75% of the cases were from Sabah. Temperature and precipitation gave significant impact on the cholera cases in Sabah, (p<0.001) while precipitation were significant in Terengganu (p<0.001), and Sarawak (p=0.013). Monthly lag temperature data at Lag 0, 1, and 2 months were associated with the cholera cases in Sabah (p<0.001). The change in odds of having cholera cases were by the factor of 3.5 for every 1 degrees C increase in temperature. However, the contribution of rainfall was very mild, whereby an increase of 1 mm in precipitation will increase the excess risk of cholera by up to 0.8%. Conclusion: This study concludes that climate does influence the number of cholera cases in Malaysia.
BACKGROUND: Little is known about the association between ambient temperature and cause-specific mental disorders, especially in subtropical areas. OBJECTIVE: To investigate the effect of ambient temperature on mental disorders in subtropical cities. METHOD: Daily morbidity data for mental disorders in three Chinese cities (Shenzhen, Zhaoqing, and Huizhou) were collected from medical record systems of local psychiatric specialist hospitals, covering patients of all ages. Case-crossover design combined with a distributed lag nonlinear model (DLNM) was used to assess the nonlinear and delayed effects of temperatures on five specific mental disorders (affective disorders, anxiety, depressive disorders, schizophrenia, and organic mental disorders), with analyses stratified by gender and age. The temperature of minimum effect was used as the reference value to calculate estimates. RESULTS: We observed inversed J-shaped exposure-response curves between temperature and mental morbidity and observed that low temperatures had a significant and prolonged effect on most types of mental disorders in the three cities. For example, the effect of the cold (2.5th percentile) on anxiety was consistently observed in the three cities with an odds ratio (OR) of 1.29 (95% CI: 1.06-1.57) in Zhaoqing, 1.26 (95% CI: 1.18-1.34) in Shenzhen, and 1.45 (95% CI: 1.17-1.81) in Huizhou. Low temperature was also associated with an increased risk of depressive disorders and schizophrenia. For the high temperature exposure (97.5th percentile), we only observed a significant, harmful effect on anxiety [OR = 1.30 (95% CI: 1.08, 1.58) in Shenzhen, OR = 1.16 (95% CI: 1.00, 1.34) in Zhaoqing], affective disorders [OR = 1.32 (95% CI: 1.08, 1.62) in Shenzhen], and schizophrenia [OR = 1.24 (95% CI: 1.03, 1.48) in Zhaoqing, OR = 1.03 (95% CI: 1.00, 1.06) in Huizhou]. CONCLUSIONS: Our study suggests that both low and high temperatures might be important drivers of morbidity from mental disorders, and low temperature may have a more general and wide-spread effect on this cause-specific morbidity than high temperature.
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.
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.
Previous studies have revealed associations of meteorological factors with tuberculosis (TB) cases. However, few studies have examined their lag effects on TB cases. This study was aimed to analyse nonlinear lag effects of meteorological factors on the number of TB notifications in Hong Kong. Using a 22-year consecutive surveillance data in Hong Kong, we examined the association of monthly average temperature and relative humidity with temporal dynamics of the monthly number of TB notifications using a distributed lag nonlinear models combined with a Poisson regression. The relative risks (RRs) of TB notifications were >1.15 as monthly average temperatures were between 16.3 and 17.3 °C at lagged 13-15 months, reaching the peak risk of 1.18 (95% confidence interval (CI) 1.02-1.35) when it was 16.8 °C at lagged 14 months. The RRs of TB notifications were >1.05 as relative humidities of 60.0-63.6% at lagged 9-11 months expanded to 68.0-71.0% at lagged 12-17 months, reaching the highest risk of 1.06 (95% CI 1.01-1.11) when it was 69.0% at lagged 13 months. The nonlinear and delayed effects of average temperature and relative humidity on TB epidemic were identified, which may provide a practical reference for improving the TB warning system.
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: 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.
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 increasing frequency and intensity of heat events have weighty impacts on public health in Vietnam, but their effects vary across regions. In this study, we have applied a vulnerability assessment framework (VAF) to systematically assess the spatial pattern of health vulnerability to heatwaves in Vietnam. The VAF was computed as the function of three dimensions: exposure, sensitivity, and adaptive capacity, with the indicators for each dimension derived from the relevant literature, consultation with experts, and available data. An analytic hierarchy process (AHP) was used to determine the weight of indicators. Each province in Vietnam’s vulnerability to the health impacts of heatwaves was evaluated by applying the vulnerability index, computed using 13 indicators (sensitivity index, 9; adaptive capacity index, 3; and exposure index, 1). As a result of this analysis, this study has identified heatwave vulnerability ‘hotspots’, primarily in the Southeast, Central Highlands, and South Central Coast of Vietnam. However, these hotspots are not necessarily the same as the area most vulnerable to climate change, because some areas that are more sensitive to heatwaves may have a higher capacity to adapt to them due to a host of factors including their population characteristics (e.g. rates of the elderly or children), socio-economic and geographical conditions, and the availability of air-conditioners. This kind of information, provided by the vulnerability index framework, allows policymakers to determine how to more efficiently allocate resources and devise appropriate interventions to minimise the impact of heatwaves with strategies tailored to each region of Vietnam.
BACKGROUND: Malaria continues to be a disease of massive burden in Africa, and the public health resources targeted at surveillance, prevention, control, and intervention comprise large outlays of expense. Malaria transmission is largely constrained by the suitability of the climate for Anopheles mosquitoes and Plasmodium parasite development. Thus, as climate changes, shifts in geographic locations suitable for transmission, and differing lengths of seasons of suitability will occur, which will require changes in the types and amounts of resources. METHODS: The shifting geographic risk of malaria transmission was mapped, in context of changing seasonality (i.e. endemic to epidemic, and vice versa), and the number of people affected. A published temperature-dependent model of malaria transmission suitability was applied to continental gridded climate data for multiple future AR5 climate model projections. The resulting outcomes were aligned with programmatic needs to provide summaries at national and regional scales for the African continent. Model outcomes were combined with population projections to estimate the population at risk at three points in the future, 2030, 2050, and 2080, under two scenarios of greenhouse gas emissions (RCP4.5 and RCP8.5). RESULTS: Estimated geographic shifts in endemic and seasonal suitability for malaria transmission were observed across all future scenarios of climate change. The worst-case regional scenario (RCP8.5) of climate change predicted an additional 75.9 million people at risk from endemic (10-12 months) exposure to malaria transmission in Eastern and Southern Africa by the year 2080, with the greatest population at risk in Eastern Africa. Despite a predominance of reduction in season length, a net gain of 51.3 million additional people is predicted be put at some level of risk in Western Africa by midcentury. CONCLUSIONS: This study provides an updated view of potential malaria geographic shifts in Africa under climate change for the more recent climate model projections (AR5), and a tool for aligning findings with programmatic needs at key scales for decision-makers. In describing shifting seasonality, it was possible to capture transitions between endemic and epidemic risk areas, to facilitate the planning for interventions aimed at year-round risk versus anticipatory surveillance and rapid response to potential outbreak locations.
Diurnal temperature range (DTR) is a key indicator reflecting climate stability. Many previous studies have examined the effects of ambient temperature, both hot and cold, on human morbidity and mortality, but few studies have evaluated health effects of DTR, especially those in developing countries. This study aimed to investigate the association between short-term exposure to DTR and hospital admissions for cardiovascular and respiratory diseases in Bangkok, Thailand. We obtained daily meteorological variables from the Thai Meteorological Department from January 2006 through December 2014 and daily hospital admissions from the National Health Security Office during the same period. Quasi-Poisson generalized linear regression model combined with distributed lag non-linear model was used to examine the association between DTR and cardiovascular and respiratory hospital admissions controlling for daily average temperature, relative humidity, day of the week, public holiday, and seasonal and long-term trend. A J-shape relationship between DTR and hospital admissions was observed. With 7.8 °C DTR as a reference value, the relative risks for cardiovascular and respiratory hospital admission associated with extremely high DTR (11.6 °C) at cumulative lag 0-21 (21-day cumulative effects) were 1.206 (95% CI: 1.002-1.452) and 1.021 (95% CI: 0.856-1.218), respectively. The effects of extremely high DTR relative to a reference value did not significantly differ between males and females, as well as between young people (<65 years) and the elderly (?65 years) for both cardiovascular and respiratory admission. When stratifying the effects by season, the effect of extremely high DTR in winter was greater than that in summer and rainy season. This study showed that short-term exposure to extremely high DTR was significantly associated with increased risk of hospital admissions for cardiovascular disease in Bangkok, especially during winter. Results from this study could provide important scientific evidence for policy decision making to protect populations from adverse health effects of DTR.
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.
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: Extreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil. METHODS: A time series study was carried out to explore the associations between daily air pollutants (SO(2), NO(2), O(3), and PM(10)) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM). RESULTS: Significant associations between environmental conditions (10??g/m(3) increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009-1.0357) for men, and 1.0407 (95% CI: 1.0230-1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165-1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213-1.1117) for women, and 1.0215 (95% CI: 1.0195-1.0716) for men. CONCLUSIONS: This study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.
OBJECTIVES: There has been increasing interest in identifying the adverse effects of ambient environmental factors on asthma exacerbations (AE), but season-stratified effects of meteorological factors on childhood asthma remain unclear. We explored the season-stratified effects of meteorological factors on childhood AE in Shanghai, China. METHODS: Poisson generalized linear regression model combined with a distributed lag nonlinear model was used to examine the lagged and nonlinear effects of meteorological factors on childhood AE after adjustment for putative confounders. We also performed a season-stratified analysis to determine whether the season modified the relationship between meteorological factors and childhood AE. RESULTS: There were 23,103 emergency department visits (EDVs) for childhood AE, including 15,466 boys and 7637 girls during 2008-2017. Most meteorological factors (e.g., temperature, diurnal temperature range (DTR), relative humidity (RH) and wind speed (WS)) were significantly associated with EDVs for childhood AE, even after adjustment for the confounding effects of air pollutants. In the whole year, extreme cold, moderate heat, higher DTR, lower RH and WS increased the relative risk (RR) for childhood AE. In the cold season, lower RH and wind speed increased the risks of childhood AE (RR(lag0-28) for the 5th percentile (p5) of RH: 9.744, 95% CI: 3.567, 26.616; RR(lag0-28) for the p5 of wind speed: 10.671, 95% CI: 1.096, 103.879). In the warm season, higher temperature and DTR, lower RH and WS increased the RR for childhood AE (RR(lag0-5) for the p95 of temperature: 1.871, 95% CI: 1.246, 2.810; RR(lag0-2) for the p95 of DTR: 1.146, 95% CI: 1.010, 1.300; RR(lag0-5) for the p5 of RH: 1.931, 95% CI: 1.191, 3.128; RR(lag0-2) for the p5 of WS: 1.311, 95% CI: 1.005, 1.709). CONCLUSIONS: Extreme meteorological factors appeared to be triggers of EDVs for childhood AE in Shanghai and the effects modified by season. These findings provide evidence for developing season-specific and tailored strategies to prevent and control childhood AE.
This study aimed to evaluate the relationship between weather factors (temperature, humidity, solar radiation, wind speed, and rainfall) and COVID-19 infection in the State of Rio de Janeiro, Brazil. Solar radiation showed a strong (-0.609, p < 0.01) negative correlation with the incidence of novel coronavirus (SARS-CoV-2). Temperature (maximum and average) and wind speed showed negative correlation (p < 0.01). Therefore, in this studied tropical state, high solar radiation can be indicated as the main climatic factor that suppress the spread of COVID-19. High temperatures, and wind speed also are potential factors. Therefore, the findings of this study show the ability to improve the organizational system of strategies to combat the pandemic in the State of Rio de Janeiro, Brazil, and other tropical countries around the word.
The coronavirus disease 2019 (COVID-19) pandemic is the most severe global health and socioeconomic crisis of our time, and represents the greatest challenge faced by the world since the end of the Second World War. The academic literature indicates that climatic features, specifically temperature and absolute humidity, are very important factors affecting infectious pulmonary disease epidemics – such as severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS); however, the influence of climatic parameters on COVID-19 remains extremely controversial. The goal of this study is to individuate relationships between several climate parameters (temperature, relative humidity, accumulated precipitation, solar radiation, evaporation, and wind direction and intensity), local morphological parameters, and new daily positive swabs for COVID-19, which represents the only parameter that can be statistically used to quantify the pandemic. The daily deaths parameter was not considered, because it is not reliable, due to frequent administrative errors. Daily data on meteorological conditions and new cases of COVID-19 were collected for the Lombardy Region (Northern Italy) from 1 March, 2020 to 20 April, 2020. This region exhibited the largest rate of official deaths in the world, with a value of approximately 1700 per million on 30 June 2020. Moreover, the apparent lethality was approximately 17% in this area, mainly due to the considerable housing density and the extensive presence of industrial and craft areas. Both the Mann-Kendall test and multivariate statistical analysis showed that none of the considered climatic variables exhibited statistically significant relationships with the epidemiological evolution of COVID-19, at least during spring months in temperate subcontinental climate areas, with the exception of solar radiation, which was directly related and showed an otherwise low explained variability of approximately 20%. Furthermore, the average temperatures of two highly representative meteorological stations of Molise and Lucania (Southern Italy), the most weakly affected by the pandemic, were approximately 1.5 °C lower than those in Bergamo and Brescia (Lombardy), again confirming that a significant relationship between the increase in temperature and decrease in virulence from COVID-19 is not evident, at least in Italy.
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.
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.
Outdoor Thermal Comfort (OTC) is largely influenced by urban morphology and geometry of the urban landscape. In this study, the Local Climatic Zones (LCZs) approach was adopted to assess the OTC in different settings of Sriniketan-Santiniketan Planning Area (SSPA) during the summer season. The basic objective of this study is to assess OTC from both subjective and objective perspectives over eight LCZs. This study assessed OTC over LCZs using both field measurements and questionnaire survey. Non-parametric tests such as ANOVA and Kruskal-Wallis tests were also performed to find out the significant difference of perception across LCZs. The result of ANOVA and Krushkal-Walls test showed that subjective perception of OTC across LCZs varied due to diversified physical landscape settings. The result also showed that the maximum (above 40 degrees C) and minimum (28 degrees C) temperature was recorded in built types (particularly compact low rise) and natural land cover types (dense forest and water) respectively. Highest PET was also recorded over the built-up LCZs (about 50 degrees C) that led to this planning region thermally very hot or extreme heat stress. The respondents living in LCZ3 and LCZ6 were more sensitive to the thermal sensation as compared to those living in other LCZs.This study was probably the first attempt dealing with the assessment of OTC over the tropical planning region using LCZ approach from subjective and objective perspectives. Therefore, this research study has an immense potentiality to formulate strategies to deal with the outdoor thermal conditions as well to implement climate sensitive planning for urban sustainability in tropical cities.
Extreme heat and associated health risks increasingly become threats to urban populations, especially in developing countries of the tropics. Although human thermal exposure in cities has been studied across the globe, current narratives insufficiently discuss mixed-used spaces, informal economic activity settings, and informal settlements. This study assessed outdoor human thermal comfort in the tropical city of Kolkata, India where uncomfortable hot and humid climatic conditions prevail year-round. Thermal Comfort Perception Surveys (TCPS) and biometeorological observations were conducted during summer and winter in three microentrepreneurial neighborhoods (Kumartuli, Boipara, and Mallickghat). A one-way ANOVA was performed to investigate the variance in Physiologically Equivalent Temperature (PET) values of 318 survey samples across neighborhoods. Through multiple linear regression and ANCOVA, significant relationships were established between various climatic and non-climatic parameters. No respondent reported a neutral thermal sensation during the summer. Annual neutral PET across neighborhoods was 23.6 °C with a neutral PET range of 19.5 °C to 27.6 °C. Annual neutral PET was 22.7 °C and 26.5 °C in Mallickghat and Boipara, respectively. Respondents in Boipara were more sensitive towards warmer sensation than in Mallickghat. Even in the winter, people reported warmer sensation votes. PET was a better predictor of the mean Thermal Sensation Vote (mTSV) compared to air temperature. In a few cases, acclimatization and expectations improved thermal comfort. Results can be useful in formulating strategies towards improving outdoor microclimate and heat health in tropical cities.
In this study, we applied the Weather Research and Forecasting model to project 2050 urban and rural temperature. We applied a time-stratified analysis to compare it with mortality between 2001 and 2014 and between 2011 and 2014, to estimate the elevated risk of a 2050 heat event. We included change in daytime versus nighttime and urban versus rural temperatures as factors to project mortality, to evaluate the potential influence of climate change on mortality risk. Increases of 2.9 degrees C and 2.6 degrees C in maximum and minimum air temperature are projected in a 2050 heat event, with a day and a night that will have respective temperatures 9.8 degrees C and 4.9 degrees C higher than 2001-2014. Significantly higher mortality risk is forecasted in 2050 compared to 2001-2014 (IRR 1.721 [1.650, 1.796]) and 2011-2014 (IRR 1.622 [1.547, 1.701]) without consideration of temperature change. After consideration of changing temperature, change in maximum temperature in rural areas will induce the highest mortality risk during 2050, possibly due to rapid urbanization across the city, and with the second highest mortality risk induced by the change in minimum temperature in urbanized areas, possibly because local people in the city have been adapted to the maximum level of urban thermal stress during a summer day. Improvements to heat warning systems and sustainable planning protocols are urgently needed for climate change mitigation.
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.
Rising temperature and heat stress risks in the changing climate scenario might potentially affect workers globally, especially the ones with strenuous workload in tropical settings. We used a cross-sectional study design to profile the heat exposures of similar to 1900 workers from eight industrial sectors using a QuesTemp Wet Bulb Globe Temperature (WBGT) monitor, quantified select heat-strain indicators viz., rise in Core Body Temperature, Sweat Rate, and Urine Specific Gravity and evaluated the perceived health impacts of heat stress using a structured questionnaire. Heat exposures (average WBGT: 30.1 +/- 2.6 degrees C) exceeded the Threshold Limit Value for 67% workers and was positively associated with the rise in Core Body Temperature >1 degrees C in 13% and elevated Urine Specific Gravity >1.020 in 9% workers. Heat-related health concerns were reported by 86% workers, and the heat-exposed workers had 2.3 times higher odds of adverse health outcomes compared to unexposed workers (p < 0.0001). Exposure to higher WBGT and adverse renal health among salt-pan workers were significantly associated (p = 0.004), and steel workers had 9% prevalence of kidney stones. Evidence presented clearly points to heat stress as a health and productivity risk factor that could have long-term and irreversible health impacts. In-depth assessments are urgently needed to develop scientifically sound preventative interventions and protective labor policies to avert the adverse occupational health and productivity consequences for millions of workers globally, thereby aiding poverty reduction.
Ciguatera poisoning (CP), arising from ciguatoxins produced by toxic dinoflagellate Gambierdiscus, is one of the most common food-borne diseases in the South Pacific. Climate change as well as its related events have been hypothesized to a higher abundance and wider presence of toxic dinoflagellates, hence a higher risk of the disease. Yet existing studies assessing the relationship between climate factors and CP are limited or based on old data. In this study, we used prewhitened cross-correlation analysis and auto-regressive integrated moving-average (ARIMA) modeling to develop predictive models of monthly CP incidence in Cook Islands and French Polynesia, two ciguatera-endemic regions in the South Pacific, utilizing the latest epidemiological data. Results reveal the significant time-lagged associations between the monthly CP incidence rate and several indicators relating to sea surface temperature (SST). In particular, SST anomaly is proven to be a strong positive predictor of an increased ciguatera incidence for both countries. If these time-lags can be supported by more investigations, it will allow health authorities to take appropriate actions, to limit or avoid an epidemic risk, especially on high-risk climate scenarios.
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.
Global warming is projected to intensify during the twenty-first century. Yet, only few studies investigate how global warming could be perceived by future populations. Here, we propose an assessment of how climate change could be perceived by combining climatological indicators. We analyse extremes of temperature (T-99) and simplified Wet-Bulb Globe Temperature (WBGT(99)), a heat stress index assessing the combined effect of elevated temperature and humidity on the human body. The speed of change is defined for each year as the difference between the previous 20 years and the twenty upcoming years (i.e. with a moving baseline), and we assess how these speeds emerge from each last 20-year interannual variability. Using a set of 12 CMIP5 models, speeds of change ofT(99)and WBGT(99)in 2080 are both twice as fast compared with current speeds in mid-latitudes, and by up to four times faster in the tropics under the RCP8.5 scenario. Warming accelerations are thus similar forT(99)and WBGT(99). However, these speeds in tropical regions in 2080 are projected to be 2.3 times larger than the last 20-year interannual variability for WBGT(99), and only 1.5 to 1.8 times larger forT(99). According to the models, the WBGT(99)intensification will be more emergent from the recent year-to-year variability than theT(99)warming. This analysis suggests that the accelerated warming of heat extremes will be felt more strongly by populations than current changes for RCP8.5, and that this evolution will be more perceived in heat stress than in temperature, particularly within the tropics.
The tropical fire ant (TFA, Solenopsis geminata) is an aggressive fire ant species that can cause health problems in humans and damages ecosystems. The TFA can be found across the world, from North and South America to Africa, Asia, and Oceania; furthermore, it has been introduced into new areas by human transport or natural flights. In this study, species distribution modeling was applied to the TFA for the first time, and its potential distribution as a response to climate change was evaluated. This study used CLIMEX as the climate-specific species distribution modeling tool with the distribution data for TFA, current global meteorological data, and two types of climate change scenarios. Thus, although the climatic suitability of the TFA was assumed to decrease with climate change, its distribution limit was expected to increase. In addition, the difference between potential distributions predicted using Special Report on Emissions Scenarios A1 B and Special Report on Emissions Scenarios A2 increased over time. In conclusion, even with an overall decrease in climatic suitability, in the future, the TFA will still be able to invade a new area that it cannot inhabit under the current climatic scenario. As the first study that predicts TFA distribution using a species distribution model, we expect that this study will provide the basic information for further TFA modeling and for setting up quarantine and control measures. (C) 2020 National Science Museum of Korea (NSMK) and Korea National Arboretum (KNA), Publishing Services by Elsevier.
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.
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.
Heat-health risk is a growing concern in many regions of China due to the more frequent occurrence of extremely hot weather. Spatial indexes based on various heat assessment frameworks can be used for the assessment of heat risks. In this study, we adopted two approaches-Crichton’s risk triangle and heat vulnerability index (HVI) to identify heat-health risks in the Northern Jiangxi Province of China, by using remote sensing and socio-economic data. The Geographical Information System (GIS) overlay and principal component analysis (PCA) were separately used in two frameworks to integrate parameters. The results show that the most densely populated community in the suburbs, instead of city centers, are exposed to the highest heat risk. A comparison of two heat assessment mapping indicates that the distribution of HVI highlights the vulnerability differences between census tracts. In contrast, the heat risk index of Crichton’s risk triangle has a prominent representation for regions with high risks. The stepwise multiple linear regression zero-order correlation coefficient between HVI and outdoor workers is 0.715, highlighting the vulnerability of this particular group. Spearman’s rho nonparametric correlation and the mean test reveals that heat risk index is strongly correlated with HVI in most of the main urban regions in the study area, with a significantly lower value than the latter. The analysis of variance shows that the distribution of HVI exhibits greater variety across urban regions than that of heat risk index. Our research provides new insight into heat risk assessment for further study of heat health risk in developing countries.
OBJECTIVE: In 2011-2012, severe El Niño Southern Oscillation (ENSO) conditions (La Niña) led to massive flooding and temporarily displacement in the Peruvian Amazon. Our aims were to examine the impact of this ENSO exposure on child diets, in particular: (1) frequency of food consumption patterns, (2) the amount of food consumed (g/d), (3) dietary diversity (DD), (4) consumption of donated foods, among children aged 9-36 months living in the outskirts of City of Iquitos in the Amazonian Peru. DESIGN: This was a longitudinal study that used quantitative 24-h recall dietary data collection from children aged 9-36 months from 2010 to 2014 as part of the MAL-ED birth cohort study. SETTING: Iquitos, Loreto, Peru. PARTICIPANTS: Two hundred and fifty-two mother-child dyads. RESULTS: The frequency of grains, rice, dairy and sugar in meals reduced by 5-7 %, while the frequency of plantain in meals increased by 24 % after adjusting for covariates. ENSO exposure reduced girl’s intake of plantains and sugar. Despite seasonal fluctuations in the availability of fruits, vegetables and fish, DD remained constant across seasons and as children aged. However, DD was significantly reduced under moderate La Niña conditions by 0·32 (P < 0·05) food groups. Adaptive social strategies such as consumption of donated foods were significantly higher among households with girls. CONCLUSIONS: This is the first empirical study to show differential effect of the ENSO on the dietary patterns of children, highlighting differences by gender. Public health nutrition programmes should be climate- and gender-sensitive in their efforts to safeguard the diets of vulnerable populations.
Leptospirosis is a serious bacterial infection that occurs worldwide, with fatality rate of up to 40% in the most severe cases. The number of cases peaks during the rainy season and may reach epidemic proportions in the event of flooding. It is possible that people living in areas affected by natural disasters are at greater risk of contracting the disease. The aim of this study was to identify clusters of relatively higher risk for leptospirosis occurrence, both in space and time, in six municipalities of Santa Catarina, Brazil, which had the highest incidence of the disease between 2000 and 2016, and to evaluate if these clusters coincide with the occurrence of natural disasters. The cases were geocoded with the geographic coordinates of patients’ home addresses, and the analysis was performed using SaTScan software. The areas mapped as being at risk for hydrological and mass movements were compared with the locations of detected leptospirosis clusters. The disease was more common in men and in the age group from 15 to 69 years. In the scan statistics performed, only space-time showed significant results. Clusters were detected in all municipalities in 2008, when natural disasters preceded by heavy rainfall occurred. One of the municipalities also had clusters in 2011. In these clusters, most of the cases lived in urban areas and areas at risk for experiencing natural disasters. The interaction between time (time of disaster occurrence) and space (areas at risk of experiencing natural disasters) were the determining factors affecting cluster formation.
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.
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.
Rapid and significant range expansion of both Zika virus (ZIKV) and its Aedes vector species has resulted in ZIKV being declared a global health threat. Mean temperatures are projected to increase globally, likely resulting in alterations of the transmission potential of mosquito-borne pathogens. To understand the effect of diurnal temperature range on the vectorial capacity of Ae. aegypti and Ae. albopictus for ZIKV, longevity, blood-feeding and vector competence were assessed at two temperature regimes following feeding on infectious blood meals. Higher temperatures resulted in decreased longevity of Ae. aegypti [Log-rank test, ?2, df 35.66, 5, P < 0.001] and a decrease in blood-feeding rates of Ae. albopictus [Fisher's exact test, P < 0.001]. Temperature had a population and species-specific impact on ZIKV infection rates. Overall, Ae. albopictus reared at the lowest temperature regime demonstrated the highest vectorial capacity (0.53) and the highest transmission efficiency (57%). Increased temperature decreased vectorial capacity across groups yet more significant effects were measured with Ae. aegypti relative to Ae. albopictus. The results of this study suggest that future increases in temperature in the Americas could significantly impact vector competence, blood-feeding and longevity, and potentially decrease the overall vectorial capacity of Aedes mosquitoes in the Americas.
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.
Dengue, a mosquito-borne infectious disease caused by the dengue viruses, is present in many parts of the tropical and subtropical regions of the world. All four serotypes of dengue viruses are endemic in Singapore, an equatorial city-state. Frequent outbreaks occur, sometimes leading to national epidemics. However, few studies have attempted to characterize breakpoints which precede large rises in dengue case counts. In this paper, Bayesian regime switching (BRS) models were employed to infer epidemic and endemic regimes of dengue transmissions, each containing regime specific autoregressive processes which drive the growth and decline of dengue cases, estimated using a custom built multi-move Gibbs sampling algorithm. Posterior predictive checks indicate that BRS replicates temporal trends in Dengue transmissions well and nowcast accuracy assessed using a post-hoc classification scheme showed that BRS classification accuracy is robust even under limited data with the AUC-ROC at 0.935. LASSO-based regression and bootstrapping was used to account for plausibly high dimensions of climatic factors affecting Dengue transmissions, which was then estimated using cross-validation to conduct statistical inference on long-run climatic effects on the estimated regimes. BRS estimates epidemic and endemic regimes of dengue in Singapore which are characterized by persistence across time, lasting an average of 20 weeks and 66 weeks respectively, with a low probability of transitioning away from their regimes. Climate analysis with LASSO indicates that long-run climatic effects up to 20 weeks ago do not differentiate epidemic and endemic regimes. Lastly, by fitting BRS to simulated disease data generated from a stochastic Susceptible-Infected-Recovered model, mechanistic links between infectivity and regimes classified using BRS were provided. The model proposed could be applied to other localities and diseases under minimal data requirements where transmission counts over time are collected.
BACKGROUND: The aim of this study was to investigate the correlation between meteorological factors and the occurrence of acute aortic dissection (AAD) in Fujian Province, China. METHODS: The clinical data of 2004 patients diagnosed with AAD in our hospital and the relevant local meteorological data from January 2013 to November 2019 were retrospectively analyzed. RESULTS: The incidence of AAD had a clear tendency toward concentration, and the corresponding peak in terms of the occurrence date was from January 13 to 14. The average minimum temperature, the average maximum temperature, and the average daily temperature differences on the “day with AAD” were significantly lower than those on the “day without AAD”. From 5?days to 3?days before AAD onset, the average daily temperature difference showed a downward trend, but statistical analysis showed that the average minimum, average maximum and average daily temperature differences were not significantly different from the values 5?days to 0?days before AAD onset. CONCLUSIONS: The incidence of AAD is related to the season and month. The lowest average temperature may increase the incidence of AAD in patients with complicated cardiovascular diseases.
BACKGROUND: Many studies have shown an association of childhood respiratory diseases with short-term temperature variability such as diurnal temperature range (DTR) and temperature change between two neighboring days (TCN). However, the impact of temperature variability on allergic rhinitis (AR) has not been investigated so far. This study sought to evaluate the short-term effect of temperature variability (i.e., TCN and DTR) on AR, as well as to identify vulnerable subpopulations. METHOD: We collected daily data on emergency room visits and outpatients for AR and weather variables in Hefei, China during 2014-2016. A distributed lag non-linear model that controlled for long-term trend and seasonality, mean temperature, relative humidity, day of week was used to fit the associations of AR with DTR and TCN. Stratified analyses by age, sex and occupation were also performed. RESULTS: During the study period, there were a total of 53,538 cases and the average values of DTR and TCN were 8.4?°C (range: 1.0?°C to 21.2?°C) and 0?°C (range: -?12.2?°C to 5.9?°C), respectively. While we did not observe an adverse effect of DTR on AR, TCN was significantly associated with increased risk of AR. Specifically, a large temperature drop between two adjacent days (3.8?°C, 5th percentile of TCN) has a delayed and short-lasting effect on AR, with the estimated relative risk of 1.02 (95% confidence interval: 1.01 to 1.04) at lag 12. Moreover, boys and children older than 15?years seemed to be more vulnerable to the effect of TCN. CONCLUSIONS: This study provided evidence of an adverse effect of large temperature drops between two adjacent days on childhood AR. Attention paid to boys and older children may help prevent AR attacks.
In recent decades, the occurrence and distribution of arboviral diseases transmitted by Aedes aegypti mosquitoes has increased. In a new control strategy, populations of mosquitoes infected with Wolbachia are being released to replace existing populations and suppress arboviral disease transmission. The success of this strategy can be affected by high temperature exposure, but the impact of low temperatures on Wolbachia-infected Ae. aegypti is unclear, even though low temperatures restrict the abundance and distribution of this species. In this study, we considered low temperature cycles relevant to the spring season that are close to the distribution limits of Ae. aegypti, and tested the effects of these temperature cycles on Ae. aegypti, Wolbachia strains wMel and wAlbB, and Wolbachia phage WO. Low temperatures influenced Ae. aegypti life-history traits, including pupation, adult eclosion, and fertility. The Wolbachia-infected mosquitoes, especially wAlbB, performed better than uninfected mosquitoes. Temperature shift experiments revealed that low temperature effects on life history and Wolbachia density depended on the life stage of exposure. Wolbachia density was suppressed at low temperatures but densities recovered with adult age. In wMel Wolbachia there were no low temperature effects specific to Wolbachia phage WO. The findings suggest that Wolbachia-infected Ae. aegypti are not adversely affected by low temperatures, indicating that the Wolbachia replacement strategy is suitable for areas experiencing cool temperatures seasonally.
BACKGROUND: Dengue is an arbovirus that has caused serious problem in Brazil, putting the public health system under severe stress. Understanding its incidence and spatial distribution is essential for disease control and prevention. OBJECTIVE: To perform an analysis on dengue incidence and spatial distribution in a medium-sized, cool-climate and high-altitude city. DESIGN AND SETTING: Ecological study carried out in a public institution in the city of Garanhuns, Pernambuco, Brazil. METHODS: Secondary data provided by specific agencies in each area were used for spatial analysis and elaboration of kernel maps, incidence calculations, correlations and percentages of dengue occurrence. The Geocentric Reference System for the Americas (Sistema de Referência Geocêntrico para as Américas, SIRGAS), 2000, was the software of choice. RESULTS: The incidence rates were calculated per 100,000 inhabitants. Between 2010 and 2019, there were 6,504 cases and the incidence was 474.92. From 2010 to 2014, the incidence was 161.46 for a total of 1,069 cases. The highest incidence occurred in the period from 2015 to 2019: out of a total of 5,435 cases, the incidence was 748.65, representing an increase of 485.97%. Population density and the interaction between two climatic factors, i.e. atypical temperature above 31 °C and relative humidity above 31.4%, contributed to the peak incidence of dengue, although these variables were not statistically significant (P > 0.05). CONCLUSION: The dengue incidence levels and spatial distribution reflected virus and vector adjustment to the local climate. However, there was no correlation between climatic factors and occurrences of dengue in this city.
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.
Dengue fever is an important arboviral disease in many countries. Its incidence has increased during the last decade in central Vietnam. Most dengue studies in Vietnam focused on the northern area (Hanoi) and southern regions but not on central Vietnam. Dengue transmission dynamics and relevant environmental risk factors in central Vietnam are not understood. This study aimed to evaluate spatiotemporal patterns of dengue fever in central Vietnam and effects of climatic factors and abundance of mosquitoes on its transmission. Dengue and mosquito surveillance data were obtained from the Department of Vector Control and Border Quarantine at Nha Trang Pasteur Institute. Geographic Information System and satellite remote sensing techniques were used to perform spatiotemporal analyses and to develop climate models using generalized additive models. During 2005-2018, 230,458 dengue cases were reported in central Vietnam. Da Nang and Khanh Hoa were two major hotspots in the study area. The final models indicated the important role of Indian Ocean Dipole, multivariate El Niño-Southern Oscillation index, and vector index in dengue transmission in both regions. Regional climatic variables and mosquito population may drive dengue transmission in central Vietnam. These findings provide important information for developing an early dengue warning system in central Vietnam.
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.
Background: Air pollution is a global problem and also linked to respiratory diseases. Wildfire smog is a major cause of air pollution in the upper northern area of Thailand. Thus, in the current study, we examined whether long-term exposure to wildfire smog induces lung function changes in a population from the upper northern area of Thailand. Methods: The lung function of 115 participants with long-term exposure smog was determined using peak flow meter. Results: Long-term smoke exposure participants decreased FEV1 (forced expiratory volume in 1 second)/FVC (forced vital capacity) ratio (56.49 +/- 23.88 in males and 56.29 +/- 28.23 in females) compared with general Thai population. Moreover, the reduction of FVC, FEV1, and peak expiratory flow rate (PEFR) values also showed in both male and female subjects. These results suggest that long-term smoke exposure induces obstructive lung abnormality. Moreover, itchy/watery nose, cough, phlegm, and chest pain also reported in these subjects. Conclusion: Wildfire smog could be induced respiratory pathway inflammation and easily collapsible respiratory airways.
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.
Temperature record-breaking events, such as the observed more intense, longer-lasting, and more frequent heat waves, pose a new global challenge to health sectors worldwide. These threats are of particular interest in low-income regions with limited investments in public health and a growing urban population, such as Brazil. Here, we apply a comprehensive interdisciplinary climate-health approach, including meteorological data and a daily mortality record from the Brazilian Health System from 2000 to 2015, covering 21 cities over the Metropolitan Region of Rio de Janeiro. The percentage of absolute mortality increase due to summer extreme temperatures is estimated using a negative binomial regression modeling approach and maximum/minimum temperature-derived indexes as covariates. Moreover, this study assesses the vulnerability to thermal stress for different age groups and both genders and thoroughly analyzes four extremely intense heat waves during 2010 and 2012 regarding their impacts on the population. Results showed that the highest absolute mortality values during heat-related events were linked to circulatory illnesses. However, the highest excess of mortality was related to diabetes, particularly for women within the elderly age groups. Moreover, results indicate that accumulated heat stress conditions during consecutive days preferentially preceded by persistent periods of moderate-temperature, lead to higher excess mortality rather than sporadic single hot days. This work may provide directions in human health policies related to extreme climate events in large tropical metropolitan areas from developing countries, contributing to altering the historically based purely reactive response.
Assessing heatwave-induced human health risk is of critical importance in order to mitigate hazards caused by extreme environmental events. Air temperature or land surface temperature in previous studies was often used to characterize the severity of heatwaves, and human perception of the thermal environment was neglected as a key component in the heatwave-induced risk assessment. In order to redress this issue, in this study we applied the Universal Thermal Climate Index (UTCI) to represent human thermal comfort perception and embedded the measure within an assessment framework of heat stress-social vulnerability-human exposure. The heatwave-induced human health risk was then evaluated in Wuhan City, China across 177 blocks covering the entire city area and local risk governance measures were also explored based on risk zoning. The results showed that spatial patterns of heatwave-induced human health risk followed a decreasing trend from the city center towards the surrounding areas, with the average risk of the main urban area being 1.6 times that beyond the metropolitan development area. Through the heatwave-induced human health risk zoning, about 73.45% of the 177 blocks in Wuhan City demonstrated a positive relationship between heat stress and human exposure, and both were opposite with social vulnerability. Multiple linear regression between UTCI and the proportion of greenspace, water body and construction land indicated that, more blue or green infrastructure should be integrated within the urban fabric to help mitigate heat stress particularly in the main urban area, while in the metropolitan development area construction land dominating heat stress should be strictly regulated. Furthermore, protecting vulnerable groups such as left-behind children and elderly people should be a priority in rural areas that were generally associated with higher levels of social vulnerability. This study proposed a new heatwave-induced human health risk framework with a local evidence in Wuhan City, and further emphasized that risk zoning could be used as a basic yet important approach to facilitating more effective urban planning guidelines for risk governance.
BACKGROUND: Many studies have shown associations between rising temperatures, El Niño events and dengue incidence, but the effect of sustained periods of extreme high temperatures (i.e., heatwaves) on dengue outbreaks has not yet been investigated. This study aimed to compare the short-term temperature-dengue associations during different dengue outbreak periods, estimate the dengue cases attributable to temperature, and ascertain if there was an association between heatwaves and dengue outbreaks in Hanoi, Vietnam. METHODOLOGY/PRINCIPAL FINDINGS: Dengue outbreaks were assigned to one of three categories (small, medium and large) based on the 50th, 75th, and 90th percentiles of distribution of weekly dengue cases during 2008-2016. Using a generalised linear regression model with a negative binomial link that controlled for temporal trends, temperature variation, rainfall and population size over time, we examined and compared associations between weekly average temperature and weekly dengue incidence for different outbreak categories. The same model using weeks with or without heatwaves as binary variables was applied to examine the potential effects of extreme heatwaves, defined as seven or more days with temperatures above the 95th percentile of daily temperature distribution during the study period. This study included 55,801 dengue cases, with an average of 119 (range: 0 to 1454) cases per week. The exposure-response relationship between temperature and dengue risk was non-linear and differed with dengue category. After considering the delayed effects of temperature (one week lag), we estimated that 4.6%, 11.6%, and 21.9% of incident cases during small, medium, and large outbreaks were attributable to temperature. We found evidence of an association between heatwaves and dengue outbreaks, with longer delayed effects on large outbreaks (around 14 weeks later) than small and medium outbreaks (4 to 9 weeks later). Compared with non-heatwave years, dengue outbreaks (i.e., small, moderate and large outbreaks combined) in heatwave years had higher weekly number of dengue cases (p<0.05). Findings were robust under different sensitivity analyses. CONCLUSIONS: The short-term association between temperature and dengue risk varied by the level of outbreaks and temperature seems more likely affect large outbreaks. Moreover, heatwaves may delay the timing and increase the magnitude of dengue outbreaks.
Heatwaves are defined as unusually high temperature events that occur for at least three consecutive days with major impacts to human health, economy, agriculture and ecosystems. This paper investigates: 1) changes in heatwave characteristics such as peak temperature, number of events, frequency and duration over a past 67-year period in Australia; 2) projected changes in heatwave characteristics for this century in Queensland, northeast Australia; and 3) the avoided heatwave impacts of limiting global warming by 1.5 °C, 2.0 °C and 3.0 °C. The results reveal that heatwaves have increased in intensity, frequency and duration across Australia over the past 67 years, such intensification was particularly higher on recent decades. Downscaled future climate projections for Queensland suggest that heatwaves will further intensify over the current century. The projections also highlight that distinct climatic regions within Queensland may have different heatwave responses under global warming, where tropical and equatorial heatwaves appear to be more sensitive to elevated atmospheric CO(2) concentrations than temperate and arid regions. The results offer new insights to support climate adaptation and mitigation at regional scales. These findings are already being used by health and emergency services to inform the development of statewide policies to mitigate heatwave impacts.
The effect of tropical deforestation on heat exposure and subsequent human health outcomes remains understudied, especially among an increasingly vulnerable population-healthy, adult subsistence workers in rural industrializing tropical countries. We report on a field experiment that estimated the short-term effects of heat exposure from deforestation on cognitive performance. We randomly assigned rural, adult subsistence workers in East Kalimantan, Indonesia to deforested or forested settings, and standard or high incentive piece rate payments. Participants worked in forested or deforested settings for up to 90 min, where ambient and black globe temperatures in deforested areas were, on average, 2.1 degrees C and 10 degrees C higher. After completing the experimental task, participants were asked to take a validated general cognitive assessment test (CAT) and episodic memory test (EMT). We found participants in deforested settings had statistically significant lower scores on both CAT and EMT. Effects were largely driven by heat effects on male participants and those working after noon. Our results highlight how heat exposure from tropical deforestation may lead to declines in cognitive performance even in favorable work settings. Policymakers should consider how land use planning that takes into account the cooling services of trees can play a significant role in increasing resilience to heat from climate and land use change in the tropics.
There is an urgent need to map the geographic location of climate change risks and vulnerability, especially for cities in sub-Saharan Africa, which are experiencing the greatest urban development challenges and vulnerability to climate change impacts. The aim of this study is to investigate current and projected future heat risk, expressed as a heat stress exposure index using high-resolution climate change projections, and a social vulnerability index, to identify areas of potential future heat stress risk in the Durban (eThekwini) metropolitan area, South Africa. Additionally, this is the first study to use high-resolution downscaled climate change projections under Representative Concentration (RCP) 8.5, to construct the heat exposure index using apparent temperature and increases in minimum temperature and a social vulnerability index, using demographic and socio-economic census and land use data to, derived from principal component analysis (PCA) to spatially characterize heat stress within a South African city. Results show that while heat stress is not a current concern, it is projected to increase and become a future concern, mainly as a function of social vulnerability due to household demographic and infrastructural characteristics, and will be experienced in both the rural and inner-city areas of the metro. This study contributes a heat risk framework to identify locations for specific research and adaptation activities on heat stress risk and for urban planning in sub-Saharan African cities, which are characterized by both rural and urban contexts, to address climate change adaptation targeting and priority setting.
Prolonged or intense exposure to heat can lead to a range of health effects. This study investigated heat exposure and heat-related symptoms which sugarcane workers (90 sugarcane cutters and 93 factory workers) experienced during a harvesting season in Thailand. During the hottest month of harvesting season, wet bulb globe temperature was collected in the work environment, and workloads observed, to assess heat stress. Urine samples for dehydration test, blood pressure, heart rate, and body temperature were measured pre- and post-shift to measure heat strain. Fluid intake and heat-related symptoms which subjects had experienced during the harvesting season were gathered via interviews at the end of the season. From the results, sugarcane cutters showed high risk for heat stress and strain, unlike factory workers who had low risk based on the American Conference of Governmental Industrial Hygiene (ACGIH) threshold limit values (TLVs) for heat stress. Dehydration was observed among sugarcane cutters and significant physiological changes including heart rate, body temperature, and systolic blood pressure occurred across the work shift. Significantly more sugarcane cutters reported experiencing heat-related symptoms including weakness/fatigue, heavy sweating, headache, rash, muscle cramp, dry mouth, dizziness, fever, dry/cracking skin, and swelling, compared to sugarcane factory workers. We conclude that the heat stress experienced by sugarcane cutters working in extremely hot environments, with high workloads, is associated with acute health effects. Preventive and control measures for heat stress are needed to reduce the risk of heat strain.
Available guidance to mitigate health risks from exposure to freshwater harmful algal blooms (HABs) is largely derived from temperate ecosystems. Yet in tropical ecosystems, HABs can occur year-round, and resource-dependent populations face multiple routes of exposure to toxic components. Along Winam Gulf, Lake Victoria, Kenya, fisher communities rely on lake water contaminated with microcystins (MCs) from HABs. In these peri-urban communities near Kisumu, we tested hypotheses that MCs exceed exposure guidelines across seasons, and persistent HABs present a chronic risk to fisher communities through ingestion with minimal water treatment and frequent, direct contact. We tested source waters at eleven communities across dry and rainy seasons from September 2015 through May 2016. We measured MCs, other metabolites, physicochemical parameters, chlorophyll a, phytoplankton abundance and diversity, and fecal indicators. We then selected four communities for interviews about water sources, usage, and treatment. Greater than 30% of source water samples exceeded WHO drinking water guidelines for MCs (1?g/L), and over 60% of source water samples exceeded USEPA guidelines for children and immunocompromised individuals. 50% of households reported sole use of raw lake water for drinking and household use, with alternate sources including rain and boreholes. Household chlorination was the most widespread treatment utilized. At this tropical, eutrophic lake, HABs pose a year-round health risk for fisher communities in resource -limited settings. Community-based solutions and site-specific guidance for Kisumu Bay and similarly impacted regions is needed to address a chronic health exposure likely to increase in severity and duration with global climate change.
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.
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.
Arboviruses transmitted by Aedes aegypti and Aedes albopictus have been introduced to Florida on many occasions. Infrequently, these introductions lead to sporadic local transmission and, more rarely, sustained local transmission. Both mosquito species are present in Florida, with spatio-temporal variation in population composition. We developed a two-vector compartmental, deterministic model to investigate factors influencing Chikungunya virus (CHIKV) establishment. The model includes a nonlinear, temperature-dependent mosquito mortality function based on minimum mortality in a central temperature region. Latin Hypercube sampling was used to generate parameter sets used to simulate transmission dynamics, following the introduction of one infected human. The analysis was repeated for three values of the mortality function central temperature. Mean annual temperature was consistently important in the likelihood of epidemics, and epidemics increased as the central temperature increased. Ae. albopictus recruitment was influential at the lowest central temperature while Ae. aegypti recruitment was influential at higher central temperatures. Our results indicate that the likelihood of CHIKV establishment may vary, but overall Florida is permissive for introductions. Model outcomes were sensitive to the specifics of mosquito mortality. Mosquito biology parameters are variable, and improved understanding of this variation will improve our ability to predict the outcome of introductions.
Wet bulb globe temperature (WBGT), a combined measure of temperature and humidity effects on thermal comfort, is used to define heat stress waves (HSWs). While emerging research has raised concerns on future changes in heat stress, for the first time, this study examines spatiotemporal changes in multiple HSW characteristics (intensity, duration, frequency, and cumulative mean intensity) in the 21st century under three emissions scenarios. It is the sustained nature of HSWs that impose more adverse impacts than extreme heat on a single day. HSWs are expected to be more intense, persistent, frequent, and influential due to anthropogenic influence. Models project the largest increases in multiple HSW characteristics will occur over the tropics and subtropics. The exception is maximum intensity, which displays a relative uniform increase over most global land areas. Analysis of regional population exposure to HSWs under different climate and socioeconomic scenarios emphasizes the importance of aggressive mitigation to minimize the potential impacts of HSWs. We further investigate how different regional HSW characteristics are projected to change relative to increasing global mean surface temperature (GMST). Our results confirm the varying rates and different trajectories at which regional HSWs change, independent of forcing pathway, strongly related to GMST. On both globally aggregated and regional scales, the maximum intensity and GMST are highly linearly associated, with an approximately 1:1 increase. However, the other three HSW characteristics are projected to change at a nonlinear rate per degree of GMST increase in general and display large regional variation in the rates of their changes. Plain Language Summary Besides air temperature, air humidity is another important factor in determining the impact of heat waves on humans. High humidity will reduce the efficiency of evaporative cooling and, when combined with high temperature, could pose a serious threat to human health or even life safety. Heat stress indices, taking into account both temperature and humidity effects, are considered to be better indicators of environmental conditions conducive to heat stress on human health. We here employ a widely used heat stress index, wet bulb globe temperature, to define heat waves, namely, heat stress waves (HSWs). Heat waves can be considered through a number of characteristics, and it is their distinctive characteristics that result in the vast array of adverse impacts. This also applies to HSWs. Our results show that more intense, longer-lasting, frequent, and influential HSWs are anticipated during the 21st century, and anthropogenic warming substantially increases the occurrence of HSWs. Except intensity, tropical regions will generally witness the largest increases in multiple HSW characteristics and the number of people that may be exposed to HSWs. Changes in HSW characteristics are confirmed not to depend on whether a particular warming is reached sooner or later; they are strongly related to global mean surface temperature.
