Intersectoral collaborations are an integral component of the prevention and control of diseases in a complex health system. On the one hand, One Health (OH) is promoting the establishment of intersectoral collaborations for prevention at the human-animal-environment interface. On the other hand, operationalising OH can only be realized through intersectoral collaborations. This work contributes to broadening the knowledge of the process for operationalising OH by analysing the governance structures behind different initiatives that tackle health problems at the human-animal-environment interface. The cases taken as examples for the analysis are the control and response to rabies and avian influenza under “classical OH”, and the management of floods and droughts for insights into “extended OH”. Data from Ghana and India were collected and compared to identify the key elements that enable ISC for OH. Despite the case studies being heterogeneous in terms of their geographic, economic, social, cultural, and historical contexts, strong similarities were identified on how intersectoral collaborations in OH were initiated, managed, and taken to scale. The actions documented for rabies prevention and control were historically based on one sector being the leader and implementer of activities, while avian influenza management relied more on intersectoral collaborations with clearly defined sectoral responsibilities. The management of the impact of flood and droughts on health provided a good example of intersectoral collaborations achieved by sectoral integration; however, the human health component was only involved in the response stage in the case of Ghana, while for India, there were broader schemes of intersectoral collaborations for prevention, adaptation, and response concerning climate change and disaster.
Weather, climate, and climate change are affecting human health, with scientific evidence increasing substantially over the past two decades, but with very limited research from low- and middle-income countries. The health effects of climate change occur mainly because of the consequences of rising temperatures, rising sea levels, and an increase in extreme weather events. These exposures interact with demographic, socio-economic, and environmental factors, as well as access to and the quality of health care, to affect the magnitude and pattern of risks. Health risks are unevenly distributed around the world, and within countries and across population groups. Existing health challenges and inequalities are likely to be exacerbated by climate change. This narrative review provides an overview of the health impacts of weather, climate, and climate change, particularly on vulnerable regions and populations in sub-Saharan Africa and South Asia, and discusses the importance of protecting human health in a changing climate; such measures are critical to reducing poverty and inequality at all scales. Three case summaries from the INDEPTH Health and Demographic Surveillance Systems highlight examples of research that quantified associations between weather and health outcomes. These and comparable surveillance systems can provide critical knowledge to increase resilience and decrease inequalities in an increasingly warming world.
A study was conducted to understand if the disaster death in Odisha, India across five categories, viz. tropical cyclone, lightning, heat wave, cold wave and extreme precipitation events underwent any significant change during 2001–14. It was based on timeseries data available at the National Data Portal of India. Results of the study suggest that the number of fatalities from sporadic meso-scale meteorological hazards like cyclones and heavy precipitation have drastically reduced due to better forecasting and effective evacuation strategies adopted by the Government. However, fatalities due to more frequent recurring extreme events, such as lightning and heat stress are on the rise. Male adults and middle-aged people (30–44 and 45–59 years respectively) constituted the most vulnerable groups affected by lightning and heat stress which account for maximum number of deaths in the state. Older population (especially older women) were more vulnerable towards cold wave due to reduced thermoregulatory mechanism. The finding is significant, because often deaths due to lightning injury, heat stress and cold wave either go unnoticed or are under-reported. We expect that the present study which focuses on gender and age disaggregated death would help in adopting more targeted mitigation or adaptation strategies in Odisha. The study also points out the need of a single and detailed spatio-temporal data infrastructure for all kinds of disaster deaths for more in-depth and insightful analysis.
The aim of this study was to describe the correlation between the meteorological and air pollution parameters with the temporal pattern of presentation of recent onset allergic eye disease (AED). This cross-sectional hospital-based study included new patients (≤21 years of age) presenting between January 2016 and August 2018 from the district of Hyderabad with a clinical diagnosis of AED and an acute exacerbation of recent onset of symptoms of less than 3 months duration. Correlation analysis was performed with the local environmental rainfall, temperature, humidity, windspeed, and air pollution. Of the 25,354 new patients hailing from the district of Hyderabad, 2494 (9.84%) patients were diagnosed with AED, of which 1062 (4.19%) patients had recent onset of symptoms. The mean monthly prevalence in this cohort was 4.13%, and the month of May (6.09%) showed the highest levels. The environmental parameters of humidity (r(2) = 0.83/p = < 0.0001) and rainfall (r(2) = 0.41/p = 0.0232) showed significant negative correlation, while temperature (r(2) = 0.43/p = 0.0206) and ground-level ozone (r(2) = 0.41/p = 0.0005) showed significant positive correlation with the temporal pattern of AED in the population. An increase in rainfall and humidity was associated with a lower prevalence, and an increase of temperature and ground-level ozone was associated with a higher prevalence of AED cases during the year among children and adolescents.
Gender mediates climate vulnerability and adaptation action. Consequently, climate change adaptation policy has seen a push towards ‘mainstreaming’ gender and prioritizing ‘gender-responsive’ climate action. However, it is unclear to what extent this mainstreaming advances or obscures gender considerations and whether current climate policies reflect developments in the gender and climate change literature. This paper explores how gender is operationalized in adaptation policy in India through a policy review of 28 State Action Plans on Climate Change. We juxtapose normative goals around reducing differential vulnerability with policy approaches to mainstreaming gender and propose entry points that link advances in gender and feminist studies with climate change adaptation policy. Our analysis indicates that most subnational climate policies in India explicitly mention gender as a mediator of vulnerability and adaptive capacity but operationalize it inadequately and unevenly. We also reflect on how the heuristics of mainstreaming get operationalized in policies (gender-blind, gender-sensitive, to gender-transformative approaches) and what that means for addressing gendered vulnerability.
The study of various air pollutants and meteorological parameters are very important for all the researchers. Baleswar was known to be a seaside districts of odisha which is the economic and cultural heart of Northern Odisha.The aim of this study is to measure the air pollutants, meteorological parameters and to enumerate the air pollution index at three specific sites (Sahadevkhunta, Mallikashpur, Rasalpur) according to CPCB procedures. The air pollutants analysed by supplying through specific absorbing reagents and the pollutants were analysed up to 3 year (2017, 2018 and 2019) with a regularity of thrice per week. Analyses of our data sets showing that SO2 and NO2 concentration during summer, rainy and winter season are within the prescribe standard of NAAOS by CPCB but PM10 and PM2.5 are above the prescribed standard except PM2.5 concentration of rainy season in year 2019. Air pollution index is remaining in the condition between clean air (CA) to moderate air pollution (MAP) and it shows that the pollution index in all the sites are reducing from the year 2017 to 2019 may be due to enhancing technologies to reduce the pollutant concentration in air.
OBJECTIVES: Despite periodic outbreaks, the causes and risk factors of acute encephalitis syndrome (AES) in children of Muzaffarpur, Bihar, India, remain unknown. We explored the correlation between AES caseload and the climate parameters. METHODS: Data for 1318 hospitalized children with AES during 2012-20 were used. The correlation between AES cases and daily climate parameters (temperature, sunshine, rainfall, humidity and wind speed) for the previous 24, 48 and 72 h were examined using Pearson’s and Spearman’s rank-order correlation and Poisson regression or negative binomial regression analyses. RESULTS: Most (91.8%) of the AES cases occurred during the summer season (May-July months), especially June month. Pearson’s and Spearman’s rank-order correlation analyses revealed that AES caseload had positive correlations with maximum (r = 0.275, ρ = 0.293) and minimum (r = 0.306, ρ = 0.306) temperatures during past 24 h and heat index (r = 0.325, ρ = 0.325) and negative correlation with humidity (r = -0.222, ρ = -0.222) and rainfall (r = -0.183, ρ = -0.183) (all p < 0.05). The correlation was consistent for the climate parameters for the past 24, 48 and 72 h. Regression analysis also documented a significant association of AES cases with daily maximum (β: 0.32-0.36) and minimum (β: 0.53-0.62) temperatures and heat index (β: 0.92-1.03) over past 24, 48 and 72 h (all p < 0.01). The number of AES cases exponentially increased when the daily maximum and minimum temperatures crossed 40°C and 31°C, respectively. CONCLUSIONS: The climate parameters, especially temperature appears to be a risk factor for AES in children. The definite aetiological role of heat for AES in children needs further exploration.
PURPOSE: Big data is the new gold, especially in health care. Advances in collecting and processing electronic medical records (EMR) coupled with increasing computer capabilities have resulted in an increased interest in the use of big data in health care. Ophthalmology has been an area of focus where results have shown to be promising. The objective of this study was to determine whether the EMR at a multi-tier ophthalmology network in India can contribute to the management of patient care, through studying how climatic and socio-demographic factors relate to eye disorders and visual impairment in the State of Telangana. METHODS: The study was designed by merging a dataset obtained from the Telangana State Development Society to an existing EMR of approximately 1 million patients, who presented themselves with different eye symptoms and diagnosed with several diseases from the years (2011-2019). The dataset obtained included weather and climatic variables to be tested alongside eye disorders. AI creative featuring techniques have been used to narrow down the variables most affected by climatic and demographic factors, with the application of the Cynefin Framework as a guide to simplify and structure the dataset for analysis. RESULTS: Our findings revealed a high presence of cataract in the state of Telangana, mostly in rural areas and throughout the different weather seasons in India. Males tend to be the most affected as per the number of visits to the clinic, while home makers make the most visit to the hospital, in addition to employees, students, and laborers. While cataract is most dominant in the older age population, diseases such as astigmatism, conjunctivitis, and emmetropia, are more present in the younger age population. CONCLUSION: The study appeared useful for taking preventive measures in the future to manage the treatment of patients who present themselves with eye disorders in Telangana. The use of clinical big datasets helps to identify the burden of ocular disorders in the population. The overlaying of meteorological data on the clinical presentation of patients from a geographic region lends insight into the complex interaction of environmental factors on the prevalence of ocular disorders in them.
Globally, billions of people are experiencing food insecurity and malnutrition. The United Nations has set a global target to end hunger by 2030, but we are far from reaching it. Over the decade, climate change, population growth and economic slowdown have impacted food security. Many countries are facing the challenge of both undernutrition and over nutrition. Thus, there is a need to transform the food system to achieve food and nutrition security. One of the ways to reach closer to our goal is to provide an affordable healthy and nutritious diet to all. Millets, the nutri-cereals, have the potential to play a crucial role in the fight against food insecurity and malnutrition. Nutri-cereals are an abundant source of essential macro- and micronutrients, carbohydrates, protein, dietary fiber, lipids, and phytochemicals. The nutrient content and digestibility of millets are significantly influenced by the processing techniques. This review article highlights the nutritional characteristics and processing of Indian millets, viz. foxtail, kodo, proso, little, and pearl millets. It also envisages the effect of traditional and modern processing techniques on millet’s nutritional properties. An extensive literature review was conducted using the research and review articles related to processing techniques of millets such as fermentation, germination, dehulling, extrusion, cooking, puffing, popping, malting, milling, etc. Germination and fermentation showed a positive improvement in the overall nutritional characteristics of millets, whereas excessive dehulling, polishing, and milling resulted in reduction of the dietary fiber and micronutrients. Understanding the changes happening in the nutrient value of millets due to processing can help the food industry, researchers, and consumers select a suitable processing technique to optimize the nutrient value, increase the bioavailability of nutrients, and help combat food and nutrition security.
In low-and-middle-income countries, the provisioning of safe drinking water is a challenge that will likely worsen with climate change. Securing water will require more work and time, burdening women and children the most. Currently, the consequences of this time burden to children’s development remain understudied. To address this gap, we examine the tradeoff between children’s household water collection responsibilities and learning achievement. Using nationally representative data from India, we measure the effect of daily fetching time on primary school children’s learning achievement in a two-stage regression model, with rainfall as the instrument. Our analyses indicate that higher fetching times predict lower mathematics (-1.23 standard deviations, 95CI[-2.32, -0.14]), reading (-1.13 standard deviations, 95CI[-2.07, -0.19]), and writing (-1.21 standard deviations, 95CI[-1.89, -0.51]) test scores. These effects are heterogeneous across sex and infrastructure type. For example, we find girls’ mathematical and reading skills profit more from reductions in fetching time than boys’ (score less affected for boys by β amount: mathematics: β=0.26 points, 95CI[0.095, 0.42]; reading: β=0.27 points, 95CI[0.054, 0.49]). Children using hand pumps, open wells, or tube wells are hurt more academically in mathematics and writing by increases in fetching time than children with mostly off-premises piped access (e.g., writing scores more affected by β amount: hand pump: β=-0.18, 95CI[-0.29, -0.081]; open well: β=-0.18, 95CI[-0.33, -0.040]; tube well: β=-0.14, 95CI[-0.29, -0.00072]). Given these results, we recommend off-premises piped infrastructure in the absence of piped-to-premises water in water-insecure contexts and offer guidance for targeting infrastructure investments in India.
PURPOSE: The aim of this study was to describe the correlation between the temporal pattern of presentation of acute microsporidial keratoconjunctivitis (MKC) with meteorological parameters such as environmental temperature, rainfall, humidity, windspeed, and air pollution. METHODS: This cross-sectional hospital-based study included 182,789 patients presenting between January 2016 and December 2019 hailing from the district of Hyderabad. Patients with a clinical diagnosis of MKC in at least one eye with an acute onset (≤1 week) of presentation were included as cases. Correlation analysis was performed with the local environmental temperature, rainfall, humidity, and windspeed (Telangana State Development and Planning Society) and air pollution (Central Pollution Control Board, Government of India). RESULTS: Overall, 84 (0.05%) patients were diagnosed with acute onset MKC from the district of Hyderabad. The mean monthly prevalence in this cohort was 0.05% with peak prevalence in the months of July (0.08%), August (0.09%), September (0.12%), and October (0.08%). The environmental parameters of rainfall (r(2) = 0.87/P = < 0.0001), humidity (r(2) = 0.78/P = 0.0001), windspeed (r(2) = 0.38/P = 0.0321) were significantly positively correlated and the air pollution parameters such as ground level ozone (r(2) = 0.89/P = < 0.0001), particulate matter PM(10) (r(2) = 0.65/P = 0.0013), PM(2.5) (r(2) = 0.50/P = 0.0095), nitrogen dioxide (r(2) = 0.53/P = 0.0071), and carbon monoxide (r(2) = 0.69/P = 0.0008) were significantly negatively correlated with the temporal pattern of MKC in the population. CONCLUSION: Parasitic infections like MKC show a distinct temporal trend peaking during the monsoon season in the population. An increase in humidity, wind speed, and especially rainfall contributes to a higher prevalence of MKC cases during the year. An increase in ground-level ozone seems to be protective against infection.
Skills are an important predictor of labour, education, and wellbeing outcomes. Understanding the origins of skills formation is important for reducing future inequalities. This paper analyses the effect of shocks in-utero on human capital outcomes in childhood and adolescence in India. Combining historical rainfall data and longitudinal data from Young Lives, we estimate the effect of rainfall shocks in-utero on cognitive and non-cognitive skills development over the first 15 years of life. We find negative effects of rainfall shocks on receptive vocabulary at age 5, and on mathematics and non-cognitive skills at age 15. The negative effects on cognitive skills are driven by boys, while the effect for both cognitive and non-cognitive skills are driven by children of parents with lower education, suggesting that prenatal shocks might exacerbate pre-existing inequalities. Our findings support the implementation of policies aiming at reducing inequalities at very early stages in life.
INTRODUCTION: The impact of climate change on agriculture and food security has been examined quite thoroughly by researchers globally as well as in India. While existing studies provide evidence on how climate variability affects the food security and nutrition, research examining the extent of effect vulnerability of agriculture to climate change can have on nutrition in India are scarce. This study examined a) the association between the degree of vulnerability in agriculture to climate change and child nutrition at the micro-level b) spatial effect of climate vulnerability on child nutrition, and c) the geographical hotspots of both vulnerability in agriculture to climate change and child malnutrition. METHODS: The study used an index on vulnerability of agriculture to climate change and linked it to child malnutrition indicators (stunting, wasting, underweight and anaemia) from the National Family Health Survey 4 (2015-16). Mixed-effect and spatial autoregressive models were fitted to assess the direction and strength of the relationship between vulnerability and child malnutrition at macro and micro level. Spatial analyses examined the within-district and across-district spill-over effects of climate change vulnerability on child malnutrition. RESULTS: Both mixed-effect and spatial autoregressive models found that the degree of vulnerability was positively associated with malnutrition among children. Children residing in districts with a very high degree of vulnerability were more like to have malnutrition than those residing in districts with very low vulnerability. The analyses found that the odds of a child suffering from stunting increased by 32%, wasting by 42%, underweight by 45%, and anaemia by 63% if the child belonged to a district categorised as very highly vulnerable when compared to those categorised as very low. The spatial analysis also suggested a high level of clustering in the spatial distribution of vulnerability and malnutrition. Hotspots of child malnutrition and degree of vulnerability were mostly found to be clustered around western-central part of India. CONCLUSION: Study highlights the consequences that vulnerability of agriculture to climate change can have on child nutrition. Strategies should be developed to mitigate the effect of climate change on areas where there is a clustering of vulnerability and child malnutrition.
Of the four atoll countries in the world, the Maldives has the lowest average elevation. Therefore, it is likely to be the first country to lose its land when the sea level rises due to climate change. As a countermeasure to sea level rise, the government of the Maldives is constructing an artificial island called Hulhumale by raising an atoll adjacent to the capital city of Male. Other atoll countries may employ the same method to adapt to the anticipated sea level rise. There is a concern that people who are forced to relocate to the artificial island will be affected in various ways. Therefore, the purpose of this study was to identify measures to reduce the potential impacts of migration to artificial islands. This study aimed to identify factors that will work effectively to satisfy migrants from outside the Male region to Hulhumale. At this stage, sea level rise is not a motivating factor for migration to Hulhumale. For the time being, enhancing high-income employment and high-level education in Hulhumale, which are the main motivations for migration, will help sustain voluntary migration. Over the past two decades, rapid economic growth has changed the desire of Maldivians. Hulhumale is attracting people with its new urban environment and employment opportunities. A small-scale questionnaire survey on the satisfaction level of post-migration life was conducted among the residents of Hulhumale and the results showed that those who changed their jobs before and after migration were less satisfied with their migration than those who did not. In Hulhumale, smart cities are being developed and new types of employment are being created. In order to facilitate the smooth migration of residents from remote islands, policies that focus on occupational changes before and after migration are needed, such as public job placement programs that enable migrants to find the same jobs that they had before migration, and job training programs that prepare them for career changes and enable them to adapt smoothly to new jobs. At present, mental health issues among migrants are not a major problem. Strengthening people-to-people networks through the use of information technology (IT) will contribute to smooth migration and resettlement.
BackgroundClimate change in Nepal has posed a considerable challenge to agricultural productivity and has threatened food and nutritional security at multiple levels. This study aims to assess the impacts of climate change on national food production and food and nutritional security as well as document issue-based prioritized adaptation options for a resilient food production system. MethodsThis study considers temperature, precipitation, and their anomalies as the key factors affecting food production in Nepal. Nationwide precipitation trends along with their association with the annual production of major cereal crops in Nepal were assessed using data from the last three decades (1990-2018). The annual productions of the major cereal crops were summed and normalized to calculate the production index scores in the districts. Scores were plotted and visualized into maps using the Geographical Information System. In three ecological regions, the distribution of flood and extreme rainfall events and cases of malnutrition from 2005 to 2018 were plotted. The effects of climate change and highest priority adaptation options at the district level were documented through a review of national policies and literature studies and qualitative research based on Focus Group Discussions (FGDs). ResultsBetween 1990 and 2018, the overall average production of major cereal crops in Nepal was increased by around 2,245 MT annually. In the district level index analysis, the highest production score was found for Jhapa and Morang while the lowest production score was found for Humla. Cases of malnutrition in some districts coincided with flood and heavy rainfall events, indicating that climate change and extreme climatic events have a role to play in food production and security. Growing drought-tolerant crops, changes in crop cycle, riverbed farming practices, developing short-term strategies, such as contingency crop planning, changing planting dates, planting short duration varieties, schemes evacuation, and long-term strategies, such as encouraging out-migration of population to safer locations, resettlement programs with transformative livelihood options, and sustainable agricultural practices were found to be key prioritized adaptation measures for a resilient food production system. ConclusionIn Nepal, climate change and the increasing frequency and magnitude of extreme climatic events adversely affect the food production system, which has become a serious threat to food and nutritional security. The implementation of evidence-based practices to build a resilient food system specific to climate-vulnerable hotspots at the district and local levels is the nation’s current need.
Climate change and water security have become the most challenging global issues of this era, especially for developing countries like Pakistan. Amid many hindrances, poor governance has been identified as one of the most pressing reasons for ineffective action to tackle multifaceted and integrative climate-water issues in Pakistan. This article, therefore, applied a systematic literature review methodology to examine the current climate-water governance archetype, including key areas, major elements, critical gaps, and potential strategy in Pakistan. This study found that key climate-water governance areas in Pakistan are: river basin and watershed management, agriculture and irrigation management, urban and domestic water issues, floods, droughts and disaster management, groundwater management, and transboundary management. Moreover, it is revealed that the major governance elements are political commitment and leadership, policy formulation and regulation, institutional capacity and coordination, stakeholder engagement, and resource management, technology, and infrastructure development. The article also discusses how Pakistan has not effectively employed most of the identified governance elements to tackle its climate-water problems, lacking mostly in political, policy, institutional, coordination, and infrastructure aspects. In conclusion, a four-dimensional governance strategy, encompassing leadership, policy, institutions, and stakeholders is proposed to improve water sector resilience and adaptation to combat climate change in Pakistan.
This study explored food security and climate change issues and assessed how food sovereignty contributes to addressing the climate change impacts on entire food systems. The study aimed to contextualise food security, climate change, and food sovereignty within Sri Lanka’s current development discourse by bringing global learning, experience, and scholarship together. While this paper focused on many of the most pressing issues in this regard, it also highlighted potential paths towards food sovereignty in the context of policy reforms. This study used a narrative review that relied on the extant literature to understand the underlying concepts and issues relating to climate change, food security and food sovereignty. Additionally, eight in-depth interviews were conducted to obtain experts’ views on Sri Lanka’s issues relating to the thematic areas of this study and to find ways forward. The key findings from the literature review suggest that climate change has adverse impacts on global food security, escalating poverty, hunger, and malnutrition, which adversely affect developing nations and the poor and marginalised communities disproportionately. This study argues that promoting food sovereignty could be the key to alleviating such impacts. Food sovereignty has received much attention as an alternative development path in international forums and policy dialogues while it already applies in development practice. Since the island nation has been facing many challenges in food security, poverty, climate change, and persistence of development disparities, scaling up to food sovereignty in Sri Lanka requires significant policy reforms and structural changes in governance, administrative systems, and wider society.
The purpose of this Consensus Statement is to provide a global, collaborative, representative and inclusive vision for educating an interprofessional healthcare workforce that can deliver sustainable healthcare and promote planetary health. It is intended to inform national and global accreditation standards, planning and action at the institutional level as well as highlight the role of individuals in transforming health professions education. Many countries have agreed to ‘rapid, far-reaching and unprecedented changes’ to reduce greenhouse gas emissions by 45% within 10 years and achieve carbon neutrality by 2050, including in healthcare. Currently, however, health professions graduates are not prepared for their roles in achieving these changes. Thus, to reduce emissions and meet the 2030 Sustainable Development Goals (SDGs), health professions education must equip undergraduates, and those already qualified, with the knowledge, skills, values, competence and confidence they need to sustainably promote the health, human rights and well-being of current and future generations, while protecting the health of the planet.The current imperative for action on environmental issues such as climate change requires health professionals to mobilize politically as they have before, becoming strong advocates for major environmental, social and economic change. A truly ethical relationship with people and the planet that we inhabit so precariously, and to guarantee a future for the generations which follow, demands nothing less of all health professionals.This Consensus Statement outlines the changes required in health professions education, approaches to achieve these changes and a timeline for action linked to the internationally agreed SDGs. It represents the collective vision of health professionals, educators and students from various health professions, geographic locations and cultures. ‘Consensus’ implies broad agreement amongst all individuals engaged in discussion on a specific issue, which in this instance, is agreement by all signatories of this Statement developed under the auspices of the Association for Medical Education in Europe (AMEE).To ensure a shared understanding and to accurately convey information, we outline key terms in a glossary which accompanies this Consensus Statement (Supplementary Appendix 1). We acknowledge, however, that terms evolve and that different terms resonate variably depending on factors such as setting and audience. We define education for sustainable healthcare as the process of equipping current and future health professionals with the knowledge, values, confidence and capacity to provide environmentally sustainable services through health professions education. We define a health professional as a person who has gained a professional qualification for work in the health system, whether in healthcare delivery, public health or a management or supporting role and education as ‘the system comprising structures, curricula, faculty and activities contributing to a learning process’. This Statement is relevant to the full continuum of training – from undergraduate to postgraduate and continuing professional development.
Winter Storm Uri, one of the coldest in decades, brought snow and ice to Texas along with record subfreezing temperatures for 5 days February 13-17, 2021, and was followed by Winter Storm Viola, which brought more of the same February 18-19, 2021. Millions of Texans lost electricity and clean, running water for several days, which some suggest was due in part to a state-regulated energy market. Many Texas schools shut down for the entire week, as the death toll rose from these storms due to hypothermia and exposure, carbon monoxide poisoning, fire, drowning, and poor road conditions. Not only were COVID-19 vaccinations halted due to impassable roads but also Texas hospitals struggled to provide electricity and water pressure needed to perform life-saving medical treatments for their patients. The purpose of this article is to provide an overview of the historic winter storm event, identify vulnerable populations and key public health policies, and highlight the potential environmental public health risks associated with the storms.
BACKGROUND: Since climate change, pandemics and population mobility are challenging healthcare systems, an empirical and integrative research to studying and help improving the health systems resilience is needed. We present an interdisciplinary and mixed-methods research protocol, ClimHB, focusing on vulnerable localities in Bangladesh and Haiti, two countries highly sensitive to global changes. We develop a protocol studying the resilience of the healthcare system at multiple levels in the context of climate change and variability, population mobility and the Covid-19 pandemic, both from an institutional and community perspective. METHODS: The conceptual framework designed is based on a combination of Levesque’s Health Access Framework and the Foreign, Commonwealth and Development Office’s Resilience Framework to address both outputs and the processes of resilience of healthcare systems. It uses a mixed-method sequential exploratory research design combining multi-sites and longitudinal approaches. Forty clusters spread over four sites will be studied to understand the importance of context, involving more than 40 healthcare service providers and 2000 households to be surveyed. We will collect primary data through questionnaires, in-depth and semi-structured interviews, focus groups and participatory filming. We will also use secondary data on environmental events sensitive to climate change and potential health risks, healthcare providers’ functioning and organisation. Statistical analyses will include event-history analyses, development of composite indices, multilevel modelling and spatial analyses. DISCUSSION: This research will generate inter-disciplinary evidence and thus, through knowledge transfer activities, contribute to research on low and middle-income countries (LMIC) health systems and global changes and will better inform decision-makers and populations.
Bangladesh, being the world’s most climate-vulnerable country, is affected by plenty of climate-related hazards every year, mostly along its south-western coast. As a consequence, many people relocated from these regions’ worst-affected neighborhoods to Khulna city, and began to live as slum dwellers. They faced a variety of issues in these informal settlements, particularly regarding water, sanitation, and hygiene (WASH) facilities and livelihood options, but no research has been conducted in Bangladesh. With an emphasis on WASH services and livelihood prospects, this study therefore aimed to provide a comprehensive understanding of the challenges/hardships and needs of climate migrants living in urban slums in both general and COVID-19 contexts. Qualitative methods were applied to collect data from the climate migrants of slums in five wards (3, 12, 17, 21, and 30) of the Khulna City Corporation. Nine focus group discussions and four key informant interviews were conducted to collect the data from primary (community people) and secondary (local government and non-government and community-based organizations officials) stakeholders. The thematic analysis was used to analyze the data. The findings revealed that climate migrants experienced significant water scarcity, insufficient drainage systems, a lack of toilets, tube wells, and bathing facilities, inadequate hygiene management, a lack of core skills required for urban jobs, low payment, and an income shortage. Similarly, sustainable drinking water sources, sanitary toilets with WASH blocks, personal hygiene materials and awareness building, skill development for diverse livelihood opportunities, and income-generating capacity development were their top priorities. Overall, the findings of this study provided a holistic overview of the challenges/hardships and needs of climate migrants in urban slums regarding WASH services and livelihood opportunities. The authorities should intervene and develop policy initiatives to alleviate the hardships and meet the needs of climate migrants.
Long-term trends in air quality by studying the criteria pollutants (PM2.5, PM10, CO, O-3, NO2, and SO2) and climate variables (temperature, surface pressure, and relative humidity) were depicted in this study. The 17-year (2003-2019) average values of PM2.5, PM10, CO, O-3, NO2, and SO2 were 88.69 +/- 9.76 mu g/m(3), 124.57 +/- 12.75 mu g/m(3), 0.69 +/- 0.06 ppm, 51.42 +/- 1.82 ppb, 14.87 +/- 2.45 ppb, and 8.76 +/- 2.07 ppb, respectively. The trends among the ambient pollutants were increasingly significant (p < 0.05) except for O-3 with slopes of 1.83 +/- 0.15 mu g/m(3)/year, 2.35 +/- 0.24 mu g/m(3)/year, 0.01 +/- 0.002 ppm/year, 0.47 +/- 0.03 ppb/year, and 0.40 +/- 0.02 ppb/year for PM2.5, PM10, CO, NO2, and SO2, respectively. Pearson correlations revealed a significant association among the pollutants while a noteworthy correlation was observed between ambient pollutants and surface temperature. Principal component analysis (PCA) and positive matrix factorization (PMF) have been employed collectively to examine the main sources of the pollutants. PCA revealed similar trends for PMs and CO, as well as NO2 and SO2 being equally distributed variables. PMF receptor modeling resulted in attributing four sources to the pollutants. The factors inferred from the PMF modeling were signified as vehicular emissions, road/soil dust, biomass burning, and industrial emissions. The hazard quotient (HQ) values were not antagonistic (HQ < 1) in acute exposure levels for the three age groups (infants, children, and adults) while showing significant health risk (HQ < 1) in chronic exposure for infants and children. Children are identified as the worst sufferers among the age groups, which points to low breathing levels and high exposure to traffic pollution in Dhaka, Bangladesh.
In Bangladesh, many people are being displaced in riverine island (char) areas every year due to climate change and its associated natural catastrophes. This study intends to investigate the impact of climate change on internally displaced char people’s lives and livelihoods along with local adaptation strategies and hindrances to the coping mechanism. Data have been collected from 280 internally displaced households in two sub-districts. A mixed-method approach has been considered combined with qualitative and quantitative methods. The results disclose that frequent flooding, riverbank erosion, and crop loss are the leading causes for relocation, and social relations are impeded in the new place of residence. Increasing summer and winter temperatures, recurrent flooding, severity of riverbank erosion, and expanding disease outbreaks are also important indicators of climate change identified by displaced people, which are consistent with observed data. This study also reveals that almost all households come across severe livelihood issues like food shortage, unemployment and income loss, and housing and sanitation problems due to the changing climate associated with disasters in the former and present places. In response to this, the displaced people acclimatize applying numerous adaptation strategies in order to boost the livelihood resilience against climate change. However, fragile housing, financial conditions, and lack of own land are still the highest impediments to the sustainability of adaptation. Therefore, along with the government, several organizations should implement a dynamic resettlement project through appropriate scrutiny to eradicate the livelihood complications of internally displaced people.
Child malnutrition is indisputably a multi-faceted phenomenon. Comprehending the aforesaid crucial issue this paper intended to identify climatic and non-climatic factors for the spatial variation of malnutrition prevalence in Bangladesh. The climatic data on temperature and rainfall are obtained from the WorldClim dataset. We obtained a set of global climate layers that included monthly data on minimum temperature, maximum temperature, mean temperature, and rainfall for the period 1960-1990, at a spatial resolution up to 30 ‘onds (~ 1 × 1 km at the equator). The data are extracted at the district level using the zonal-statistics in QGIS. This study performed a spatial lag regression to evaluate association of malnutrition with climate characteristics and other factors. The prevalence of malnutrition exhibited substantial association with temperature and precipitation. Food production, water access, improved sanitation, literacy, road density, solvency ratio and GDP had a significant association with the spatial variation of malnutrition in Bangladesh.
Introduction: Human exposure is the most visible effect of different pollutants, which come at a hidden cost to society due to their impacts on human health and the environment. Objective: The purpose of this research is to gain a better knowledge of the environmental effects of motorized vehicles’ gas emissions and the resulting economic losses in a developing country. Methods: In this paper, the authors estimated vehicular emissions, emission costs, climate change costs (CCCs), and noise pollution costs (NPCs) for 84 road segments (18 important intersections) in Dhaka City in 2009 and 2017. The top-down method was used to determine the vehicular emissions in each intersection using average daily traffic data and previously defined emission factors. Climatic change costs were evaluated using the damage cost approach, and noise pollution costs were estimated using the bottom-up noise exposure model.Results: Analysis showed that the enormous and uncontrolled surge in personal vehicles resulted in significant spikes in emissions as well as economic losses. Result shows the massive increase of all types of pollutants due to the rise of vehicular populations. From 2009 to 2017, the exhaust emission costs increased by 77.89%, (from 20.71 x 10(6) to 36.84 x 10(6) Tk/day), CCCs by 63.96% (from 18.73 x 10(6) to 30.71 x 10(6) Tk/day), NPCs by 101.61% (from 11.20 x 10(6) to 22.58 x 10(6) Tk/day). The study illustrated the spatial GHG emissions, CCCs, and NPCs statistics of all the traffic nodes and signified the regulation of vehicular activities in a sustainable manner. Conclusion: Proper adaptation of the recommended policies and strategies can improve the scenario and potentially lessen the other negative consequences.
WHAT IS ALREADY KNOWN ON THIS TOPIC? Different socioecological factors were associated with childhood pneumonia in Bangladesh. However, previous studies did not assess spatial patterns, and socioecological factors and spatial variation have the potential to improve the accuracy and predictive ability of existing models. WHAT IS ADDED BY THIS REPORT? The spatial random effects were present at the district level and were heterogeneous. Average temperature, temperature variation, and population density may influence the spatial pattern of childhood pneumonia in Bangladesh. WHAT ARE THE IMPLICATIONS FOR PUBLIC HEALTH PRACTICE? The study results will help policymakers and health managers to identify the vulnerable districts, plan further investigations, help to improve proper resource allocation, and improve health interventions.
Pneumonia is one of the top 10 diseases by morbidity in Bhutan. This study aimed to investigate the spatial and temporal trends and risk factors of childhood pneumonia in Bhutan. A multivariable Zero-inflated Poisson regression model using a Bayesian Markov chain Monte Carlo simulation was undertaken to quantify associations of age, sex, altitude, rainfall, maximum temperature and relative humidity with monthly pneumonia incidence and to identify the underlying spatial structure of the data. Overall childhood pneumonia incidence was 143.57 and 10.01 per 1000 persons over 108 months of observation in children aged < 5 years and 5-14 years, respectively. Children < 5 years or male sex were more likely to develop pneumonia than those 5-14 years and females. Each 1 °C increase in maximum temperature was associated with a 1.3% (95% (credible interval [CrI] 1.27%, 1.4%) increase in pneumonia cases. Each 10% increase in relative humidity was associated with a 1.2% (95% CrI 1.1%, 1.4%) reduction in the incidence of pneumonia. Pneumonia decreased by 0.3% (CrI 0.26%, 0.34%) every month. There was no statistical spatial clustering after accounting for the covariates. Seasonality and spatial heterogeneity can partly be explained by the association of pneumonia risk to climatic factors including maximum temperature and relative humidity.
Mountains are considered as the early indicators of climate change. The study aims to understand how the Himalayan communities perceive climate change, and how this change has impacted the livelihood and sus-tenance of local people particularly in the remote and rural areas of the region. In view of this, 994 house-holds of 25 villages were interviewed from five basins (five villages per basin) of the Indian Himalayan Region. Their perceptions mainly of climate change were validated/compared with the available climatic indices. People perceived rainfall pattern to be less predictable, greater change in land-use pattern, adverse impacts on forests and human health and overall reduction in their harvests. Seasonal increase in temperature was also reported. Capacity-building programmes for the inhabitants, including the most vulnerable communities in the wake of climate change would be significantly fruitful by way of mitigation and adaptation strategies.
Does deprivation of assets imply an increased likelihood of vulnerability to climate change? Our study attempts to answer this question by analyzing the multidimensional poverty in rural Bihar, followed by deciphering the link between the developed poverty index and vulnerability of agriculture to climate change. Vulnerability index used in the present study was developed under the National Initiative on Climate Resilient Agriculture (NICRA) by the Government of India. As most people in rural areas and those dependent on rural based livelihood activities (such as agriculture, forestry and livestock) are more vulnerable to vagaries of weather, related attributes (i.e. land ownership, livestock ownership as well as access to agriculture equipments) are included in our analysis. We found that the extent of multidimensional poverty in rural Bihar was 0.278 indicating that rural poor were deprived in 27.8 percent of the total potential deprivations that they could experience overall. It varied from 0.19 to 0.39 across districts. The findings highlight that a majority of the population were deprived in living standard dimension, followed by health and education dimensions. Further, the districts where the multidimensional poverty was high were also more vulnerable to climate change. The study advocates for formulation of district specific programs that can target major contributing factors resulting in reducing the extent of multidimensional poverty and vulnerability.
Toxic gaseous organic air pollutants such as benzene, toluene, ethylbenzene, and xylene isomers (m, p, and o-x) (BTEX) are considered hazardous due to its adverse impacts on human health and on climate change. This review identifies the major research questions addressed so far and the research gap in research articles, published between 2001 and 2022, focusing on the ambient BTEX concentrations in different locations in India along with its sources, ozone formation potential (OFP), and associated health risks. The ambient levels of BTEX were also compared with those of other Asian countries. A comparison of ambient BTEX levels with different microenvironments in India is also presented. BTEX concentrations were found in the range of 30.95 to 317.18 mu g m(-3) and multi-fold higher in urban environments than those measured in the rural air. In most reported studies, the order of occurrence of BTEX compounds was toluene > benzene > xylene isomers > ethylbenzene and winter had higher concentrations than in other seasons, including summer. As far as BTEX levels in classified areas of urban environments are concerned, traffic locations have shown the highest BTEX concentrations, followed by residential, commercial, and industrial locations. OFP indicated that xylene isomers and toluene contributed to ozone formation. The major gaps in reported studies on BTEX measurement are (1) source apportionment; (2) impact on lower tropospheric chemistry, human health, and climate change; and (3) removal techniques from air.
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.
Climate change and air pollution have been a matter of serious concern all over the world in the last few decades. The present review has been carried out in this concern over the Indian cities with significant impacts of both the climate change and air pollution on human health. The expanding urban areas with extreme climate events (high rainfall, extreme temperature, floods, and droughts) are posing human health risks. The intensified heat waves as a result of climate change have led to the elevation in temperature levels causing thermal discomfort and several health issues to urban residents. The study also covers the increasing air pollution levels above the prescribed standards for most of the Indian megacities. The aerosols and PM concentrations have been explored and hazardous health impacts of particles that are inhaled by humans and enter the respiratory system have also been discussed. The air quality during COVID-2019 lockdown in Indian cities with its health impacts has also been reviewed. Finally, the correlation between climate change, air pollution, and urbanizations has been presented as air pollutants (such as aerosols) affect the climate of Earth both directly (by absorption and scattering) and indirectly (by altering the cloud properties and radiation transfer processes). So, the present review will serve as a baseline data for policy makers in analyzing vulnerable regions and implementing mitigation plans for tackling air pollution. The adaptation and mitigation measures can be taken based on the review in Indian cities to reciprocate human health impacts by regular air pollution monitoring and addressing climate change as well.
Global temperature rises in response to accumulating greenhouse gases is a well-debated issue in the present time. Historical records show that greenhouse gases positively influence temperature. Lockdown incident has brought an opportunity to justify the relation between greenhouse gas centric air pollutants and climatic variables considering a concise period. The present work has intended to explore the trend of air quality parameters, and air quality induced risk state since pre to during the lockdown period in reference to India and justifies the influence of pollutant parameters on climatic variables. Results showed that after implementation of lockdown, about 70% area experienced air quality improvement during the lockdown. The hazardous area was reduced from 7.52% to 5.17%. The spatial association between air quality components and climatic variables were not found very strong in all the cases. Still, statistically, a significant relation was observed in the case of surface pressure and moisture. From this, it can be stated that pollutant components can control the climatic components. This study recommends that pollution source management could be a partially good step for bringing climatic resilience of a region.
This study was carried out to evaluate the heavy metals (Lead (Pb), Nickel (Ni), Chromium (Cr), Copper (Cu), Cadmium (Cd) and Zinc (Zn)) pollution in the Noyyal River of South India by collecting 130 river water samples (65 each in pre- and post-monsoon). The heavy metals were measured using Atomic Absorption Spectrophotometer (AAS). The data were used to calculate the associated health hazards for the inhabitants consume river water. Correlation analyses and average concentration of heavy metals denoted that post-monsoon metal concentrations were lesser compared to the pre-monsoon due to dilution effect. Modified Contamination Degree (MCD) indicated that 45% of pre-monsoon and 25% of post-monsoon samples were classified under extremely polluted category. Heavy metal pollution index (HPI) showed that all the regions fall under highly polluted category except ‘Region I’ where 20% of samples were under safe category during the pre-monsoon, whereas 9%,28%, 17% and 26% of samples in Regions I, II, III and IV were highly polluted during the post-monsoon season, respectively. Ecological Risk Index (ERI) revealed that high risks attained in Regions II (78%) and III (82%) during pre-monsoon, and reduced risks found in Regions II (28%) and III (45%) during post-monsoon season due to dilution by monsoon rainfall. Non-carcinogenic risks as inferred by the Hazard Index (HI) indicated that 78% and 52% of samples for infants, 75% and 49% of samples for teens and 71% and 45% of samples for adults exceeded the threshold limits of USEPA (HI > 1) and possessed risks during pre- and post-monsoon, respectively. The cancer risk assessment based on ingestion of heavy metals indicated that the order of risk is Ni > Cr > Cu. The HI for infants and teens was notably high to that of adults in both the seasons. This study will be useful to develop effective strategies for improving river water quality and to reduce human health hazards.
Rickettsial infections and Q fever are a common cause of acute febrile illness globally. Data on the role of climate and altitude on the prevalence of these infections in lacking from Southern India. In this study, we determined the sero-prevalence of scrub typhus (ST), spotted fever (SF), murine typhus (MT) and Q Fever (QF) in 8 eight geographical regions of North Tamil Nadu by detecting IgG antibodies using ELISA. Totally we tested 2565 people from 86 localities. Among the 27.3% positives, approximately 5% were IgG positive for two or more infections. Sero-prevalence to rickettsioses and Q fever was highest for individuals from rural areas and increased with age (> 30 years). Those in the Nilgiris highlands (wetter and cooler) and Erode, which has the most land under irrigation, demonstrated the least exposure to rickettsioses and Q fever. Lowland plains (AOR: 8.4-22.9; 95% CI 3.1-55.3) and highland areas up to 1000 m (AOR: 6.1-10.3; 95% CI 2.4-23.9) showed the highest risk of exposure to scrub typhus. For spotted fever, the risk of exposure was highest in Jawadhi (AOR:10.8; 95% CI 2.6-44.3) and Kalrayan (AOR:16.6; 95% CI 4.1-66.2). Q fever positivity was most likely to be encountered in Salem (AOR: 5.60; 95% CI 1.01-31.08) and Kalrayan hills (AOR:12.3; 95% CI 2.9-51.6). Murine typhus risk was significant only in Tiruvannamalai (AOR:24.2; 95% CI 3.3-178.6). Our study suggests that prevalence of rickettsial infections and Q fever is low in areas which receive rainfall of ≥ 150 cm/year, with average minimum and maximum temperatures between 15 and 25 °C and elevation in excess of 2000 m. It is also less in well irrigated lowlands with dry climate. These preliminary findings need confirmation by active surveillance in these areas.
OBJECTIVE: To understand how climate change vulnerability is associated with women and children’s health (WCH) at the district level in India. METHODS: The district-specific climate change vulnerability index was mapped to the district level NFHS-5 data (N = 674). Fractional regression and spatial analyses were performed to examine the strength of association and the presence of geographic clustering. RESULTS: Bivariate analysis revealed that the levels of WCH indicators were lower in districts with a high vulnerability index than in those with a low vulnerability index. Multivariable analyses suggested that with a 1% increase in the vulnerability index, the proportion of modern contraceptive use was reduced by 0.22, four or more prenatal care visits by 0.14, postnatal care by 0.11, and full immunization by 0.12; whereas wasting and underweight proportions increased by 0.07 and 0.10, respectively. The spatial analysis found that in about 70-118 districts, mostly in eastern India, where climate vulnerability was high the WCH outcomes were also poor. CONCLUSION: There is a macro-level association between climate change vulnerability and WCH, as districts that had high levels of climate change vulnerability also performed poorly in WCH. There is a need for an integrated approach that considers geography-specific climate change threats to develop health programs.
Indian Himalayan Region (IHR) is prone to climate shock and is highly sensitive to minor climate variance. Yet, there is a dearth of studies evaluating the adaptive capacity and vulnerability of the socio-ecological system. We assessed the household (n = 1346) and village (n = 77) level adaptive capacity and vulnerability to climate stress in Beas, Bhagirathi, and Teesta basins of IHR following a bottom-up approach. The estimation of adaptive capacity scores for surveyed households and villages were done based on preselected indicator scores of the natural, human, financial, and physical capital assets. The exposure to climate shock was obtained from Coupled Model Intercomparison Project (CMIP5) data of different scenarios. The present and future vulnerability scores were assessed based on the adaptive capacity, exposure and sensitivity to climatic shock. The villages and households were grouped in resilient and vulnerable clusters, and major indicators determining the vulnerability were identified. Our result revealed the household and village level adaptive capacity were low in the Bhagirathi and Teesta basin compared to the Beas basin, so as the present and future climate shock. We found that access to different resources as well as natural and financial capital assets were the major governing factor for the adaptive capacity of the villages. We suggest future policy interventions to be on climate sensitive sectors, mostly the natural capital of the region as part of the adaptation and mitigation strategy to climate change.
Climate change induced frequent disasters pose severe threats to agro-based rural livelihoods. Perceptions of risks play a critical role in planning and averting disasters. Lack of analytical documentation concerning how vulnerable communities perceive climate risks is a barrier to addressing and averting disasters and maladaptation. Applying a mixed approach, this study examines the perception of households concerning climate change and analyses the impacts of climate change on livelihood in Arunachal Pradesh, the largest northeastern state of India, with severe climate related challenges. Conceptual livelihood vulnerability index (LVI) framework of Intergovernmental Panel on Climate Change is adopted to analyse the climate change induced vulnerability on livelihood. A total 450 households from 18 villages located in the districts of Arunachal Pradesh were surveyed during October, 2021 for retrieving the ground complexities in the region. Decrease in yields, frequent landslides and floods, livestock losses and unpredictable weather condition were perceived by the sampled households. The LVI analysis indicated that households are vulnerable in Arzoo, Perum, Pekong and Amliang villages requiring priority for lessening livelihood vulnerability and increasing coping capacity of the communities. Correlation analysis indicated that climate variability, natural disaster, health, food and social components attributed to livelihood vulnerability in the study area. Alternate livelihood, enhancing preparedness to disasters, inclusion of women in workforce, sustainable livelihood practices and government assistance are some of the suggestions made to enhance the adaptation of local communities in a sustainable way.
This study attempts to investigate the simulation of heavy precipitation events (HPEs) over the West Coast of India associated with atmospheric rivers (ARs) using the Advanced Research Weather Research and Forecasting (ARW-WRF) model. The study evaluates the sensitivity of five microphysical (Lin, WSM6, Goddard, Thompson, and Morrison) and cumulus (KF, BMJ, Grell3D, Tidtke, and GD) parameterization schemes to explore the capability to reproduce the AR associated HPEs. The model simulations were reasonably successful at reproducing key structural and synoptic characteristics of atmospheric rivers, including well-defined corridors of strong water vapor transport, meteorological variables and circulation features. Deviations in Rainfall and Wind profiles were observed in simulations among the different parameterization schemes. The model better simulated the AR related precipitation using the Lin, Thompson MP and KF, Grell3D CU schemes when compared to observations, and attributed to the moisture laden tendency of the schemes. Nonetheless, differences in precipitation distribution and overestimation of winds among the model runs using different microphysical and cumulus physics schemes were noted. The study highlights that simulation of AR associated HPEs using high-resolution mesoscale mode with suitable representations of physical parameterization schemes are useful for disaster management and to minimize the loss of fatalities and property.
OBJECTIVES: The study aimed to document the association between intussusception in Indian children and meteorological parameters and examine regional variations. DESIGN: A bidirectional (retrospective and prospective) surveillance between July 2010 and September 2017. SETTING: At 20 hospitals in India, retrospective case record review during July 2010 and March 2016 and prospective surveillance during April 2016 and September 2017 were performed. PARTICIPANTS: 2161 children aged 2-24 months with first intussusception episode were included. INTERVENTIONS: The monthly mean meteorological parameters (temperature, sunshine, rainfall, humidity and wind speed) for the study sites were collected. METHODS: The association between monthly intussusception cases and meteorological parameters was examined at pooled, regional and site levels using Pearson (r) and Spearman’s rank-order (ρ) correlation, factorial analysis of variance, and Poisson regression or negative binomial regression analyses. RESULTS: The intussusception cases were highest in summer and lowest in autumn seasons. Pearson correlation analysis showed that temperature (r=0.056; p<0.05), wind speed (r=0.134; p<0.01) and humidity (r=0.075; p<0.01) were associated with monthly intussusception cases. Spearman's rank-order correlation analysis found that temperature (ρ=0.049; p<0.05), wind speed (ρ=0.096; p<0.01) and sunshine (ρ=0.051; p<0.05) were associated with monthly intussusception cases. Poisson regression analysis resulted that monthly intussusception case was associated with rising temperature (North region, p<0.01 and East region, p<0.05), sunshine (North region, p<0.01), humidity (East region, p<0.01) and wind speed (East region, p<0.01). Factorial analysis of variance revealed a significant seasonal difference in intussusception cases for pooled level (p<0.05), 2-6 months age group (p<0.05) and North region (p<0.01). Significant differences in intussusception cases between summer and autumn seasons were observed for pooled (p<0.01), children aged 2-6 months (p<0.05) and 7-12 months (p<0.05). CONCLUSIONS: Significant correlations between intussusception cases and temperature, humidity, and wind speed were observed at pooled and regional level in India. A peak in summer months was noted, which may be used for prediction, early detection and referral for appropriate management of intussusception.
Strategic location of coastal areas across the world causes them to be prone to disaster risks. In the global south, the Indian coast is one of the most susceptible to oceanic extreme events, such as cyclones, storm surge and high tides. This study provides an understanding of the risk experienced (currently as well as back in 2001) by the districts along the Indian coastline by developing a quantitative risk index. In the process, it attempts to make a novel contribution to the risk literature by following the definition of risk as a function of hazard, exposure and vulnerability as stated in the most recent (Fifth) assessment report of the Intergovernmental Panel on Climate Change (IPCC). Indicators of bio-physical hazards (such as cyclones, storm surge, tides and precipitation), and socio-economic contributors of vulnerability (such as infrastructure, technology, finance and social nets) and exposure (space), are combined to develop an overall risk index at a fine administrative scale of district-level over the entire coastline. Further, the study employs a multi-attribute decision-making (MADM) method, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), to combine the contributing indicators and generate indices on hazard, exposure and vulnerability. The product of these three components is thereafter defined as risk. The results suggest that most districts of the eastern coast have higher risk indices compared to those in the west, and the risk has increased since 2001. The higher risk can be attributed to the higher hazard indices in the eastern districts which are aggravated by their higher vulnerability index values. This study is the first effort made to map risk for the entire coastline of India – which in turn has resulted in a new cartographic product at a district-scale. Such assessments and maps have implications for environmental and risk-managers as they can help identify the regions needing adaptive interventions.
OBJECTIVE: In recent times, increased rainfall from tropical cyclones due to climate change affects the agricultural sector, mainly the paddy fields. High windspeed with excessive rain causes lodging of paddy crops, which is difficult to harvest. Mechanized harvesting systems are ineffective in this situation due to waterlogging in the fields. Manual harvesting with a traditional sickle is the only way to harvest lodged crops to save food security crises and economic losses. Collecting the lodged paddy stems lying on the ground for harvesting manually is time-consuming and harvesters need to maintain an awkward posture for a prolonged period compared to harvesting un-lodged crops. METHODS: Seventy-five female harvesters aged 35-75 years were selected for the study from both lodged and un-lodged small-scale farming lands of Kerala, a southwestern coastal state of India. A comparative ergonomic assessment was conducted to measure body pain, perceived exertion, postural risks, and rate of production under both harvesting conditions. RESULTS: The harvesters reported significant higher rates of body pain, perceived exertion, high postural risks, and low productivity in lodged conditions compared to un-lodged condition. CONCLUSION: Harvesting lodged crops involves high risks with low productivity and needs immediate ergonomic design intervention for the well-being of the harvesters.
BACKGROUND: Hurricanes are the immediate ways that people experience climate impacts in the Caribbean. These events affect socio-ecological systems and lead to major disruptions in the healthcare system, having effects on health outcomes. In September 2017, Puerto Rico (PR) and the United States Virgin Islands (USVI) experienced one of the most catastrophic hurricane seasons in recent history (Hurricane Irma was a Category 5 and Hurricane Mar?¡a was a Category 4 when they hit PR). OBJECTIVE: This study examines environmental stressors experienced by women with gynecologic (GYN) cancers from PR and USVI who received oncologic cancer care in PR, in the aftermath of the hurricanes. METHODS: A descriptive qualitative study design was used to obtain rich information for understanding the context, barriers, knowledge, perspectives, risks, vulnerabilities, and attitudes associated to these hurricanes. We performed focus groups among GYN cancer patients (n = 24) and key-informant interviews (n = 21) among health-care providers and administrators. Interviews were conducted from December 2018-April 2019. RESULTS: Environmental health stressors such as lack of water, heat and uncomfortable temperatures, air pollution (air quality), noise pollution, mosquitos, and rats ranked in the top concerns among cancer patients and key-informants. CONCLUSIONS: These findings are relevant to cancer patients, decision-makers, and health providers facing extreme events and disasters in the Caribbean. Identifying environmental secondary stressors and the most relevant cascading effects is useful for decision-makers so that they may address and mitigate the effects of hurricanes on public health and cancer care.
OBJECTIVE: Community characteristics, such as collective efficacy, a measure of community strength, can affect behavioral responses following disasters. We measured collective efficacy 1 month before multiple hurricanes in 2005, and assessed its association to preparedness 9 months following the hurricane season. METHODS: Participants were 631 Florida Department of Health workers who responded to multiple hurricanes in 2004 and 2005. They completed questionnaires that were distributed electronically approximately 1 month before (6.2005-T1) and 9 months after (6.2006-T2) several storms over the 2005 hurricane season. Collective efficacy, preparedness behaviors, and socio-demographics were assessed at T1, and preparedness behaviors and hurricane-related characteristics (injury, community-related damage) were assessed at T2. Participant ages ranged from 21-72 (M(SD) = 48.50 (10.15)), and the majority were female (78%). RESULTS: In linear regression models, univariate analyses indicated that being older (B = 0.01, SE = 0.003, P < 0.001), White (B = 0.22, SE = 0.08, P < 0.01), and married (B = 0.05, SE = 0.02, p < 0.001) was associated with preparedness following the 2005 hurricanes. Multivariate analyses, adjusting for socio-demographics, preparedness (T1), and hurricane-related characteristics (T2), found that higher collective efficacy (T1) was associated with preparedness after the hurricanes (B = 0.10, SE = 0.03, P < 0.01; and B = 0.47, SE = 0.04, P < 0.001 respectively). CONCLUSION: Programs enhancing collective efficacy may be a significant part of prevention practices and promote preparedness efforts before disasters.
National climate change policy and strategies set out a framework for planning and undertaking climate change adaptation as well as mitigation activities at the national and local levels. In this article, we examine the coherence and contradictions between national policies and plans, and its impacts on the implementation of adaptation measures at the local level. We undertook a content review of key climate change policy documents (n = 4) of Nepal. In addition, we conducted a field study in the Rajdevi Community Forest User Group (CFUG) located in the mid-hills of Nepal, which has developed and implemented a community level adaptation plan of action (CAPA). The field study involved household interviews, focus group discussions, and an in-depth analysis of CAPA implementation. The paper found that while policies are coherent for targeting highly affected areas and communities, they deviate from discerning an appropriate planning and implanting unit. The local adaptation plan of action (LAPA) considers the local government as an implementing unit, while the national adaptation program of action (NAPA) puts an emphasis on the local community groups. It suggests that the existing LAPA implementation breaches the provision of community-level institutions for the implementation conceived in the central framework. Despite little attention to promoting food security in climate change policy, through the CAPA, local communities have planned and implemented adaptation measures envisioned in the thematic areas identified in the climate change policy of Nepal: agriculture and food security; forests and biodiversity; water resources and energy; climate-induced disasters; public health; and urban settlements and infrastructure. Nevertheless, the CAPA is not institutionalized under government policies and the institutional framework as a local level implementing unit. So, the consensus for a local implementing unit in the policies has remained a key issue. We suggest identifying a suitable and acceptable unit for implementing climate change adaptation at the community level. Only if an appropriate implementing unit is identified can the policies be successful with a broader acceptance and desirable outcomes enshrined in the climate change policy.
Climate-induced pressures spur on the need for urban green infrastructure (UGI) planning. This approach offers a possible way to improve ecosystem functionality and human well-being in adversely affected urban regions, wherein UGI is perceived as a green and nature-based climate change mitigation/adaptation strategy. In Pakistan, the Khyber Pakhtunkhwa (KP) province lacks such urban landscape and greening policies (ULGP) or legislative frameworks for transitioning to green action plans (GAP), to alleviate the risk of multi-climatic hazards. Thus, this study aims to investigate a sustainable UGI-indicator-based framework model, based on the due inclusion of the concerned stakeholders. The relative importance index (RII) and inter-quartile range (IQR) techniques are employed for field data analysis. The findings proclaim excellent reliability (alpha > 0.7) and internal consistency, wherein sustainable UGI indicators are grouped based on their importance. The results portray the ecological and economic sustainability dimensions as being important (RII = 0.835 and RII = 0.807, respectively), socio-cultural dimensions as being moderately important (RII = 0.795), and a set of UGS elements (RII >= 0.77) as vital for bolstering individual UGI indicators. The main UGS elements emerging in each category can be grouped as follows: ecological category-“reducing rainwater runoff” (RII = 0.94); socio-cultural category-“enhancement of mental and physical health” (RII = 0.90); and eco category-“minimizing the risk of flood disasters” (RII = 0.96). The simulation results demonstrate the need for an inclusive perspective when building the urban green space (UGS) infrastructure (and standards) that will be most suitable for ensuring climate-resilient urban regions. This study contributes to putting the scientific research knowledge of the natural green-landscape-based (NBLB) approach into practice. The study calls for the establishment of an effective, pragmatic relationship between the urban landscape and greening policies, alongside a constructive relationship with the native inhabitants to ensure eco-friendly and resilient settlements.
Pakistan is an agrarian nation that is among the most vulnerable countries to climatic variations. Around 20% of its GDP is produced by agriculture, and livestock-related production contributes more than half of this value. However, few empirical studies have been conducted to determine the vulnerability and knowledge of livestock herders, and particularly the smaller herders. Comprehending individual perceptions of and vulnerabilities to climate change (CC) will enable effective formulation of CC mitigation strategies. This study intended to explore individual perceptions of and vulnerabilities to CC based on a primary dataset of 405 small livestock herders from three agro-ecological zones of Punjab. The results showed that livestock herders’ perceptions about temperature and rainfall variations/patterns coincide with the meteorological information of the study locations. The vulnerability indicators show that Dera Ghazi Khan district is more vulnerable than the other two zones because of high exposure and sensitivity to CC, and lower adaptive capacity. However, all zones experience regular livelihood risks due to livestock diseases and deaths resulting from extreme climatic conditions, lower economic status, and constrained institutional and human resource capabilities, thus leading to increased vulnerability. The results indicate that low-cost local approaches are needed, such as provision of improved veterinary services, increased availability of basic equipment, small-scale infrastructure projects, and reinforcement of informal social safety nets. These measures would support cost-effective and sustainable decisions to enable subsistence livestock herders to adopt climate smart practices.
Natural hazards disrupt the social-ecological system, causing much suffering, death, injury, and devastation of property and the environment. This study explores the factors influencing the disaster psychology and psychological adaptation of people living in disaster-vulnerable areas in Bangladesh. Data have been collected from 100 households in Bangladesh’s riverine island areas (char) of northern Bangladesh. Several criteria have been used to measure char dwellers’ disaster psychology (vulnerability concern, factor, and intensity) and psychological adaptation (weakness concern and emotional response). This study reveals that char dwellers perceived several hazards like floods (100%), riverbank erosion (83%), drought (29%), and earthquakes (14%). It is also found that females (88%) are more concerned about earthquakes than males (12%). The key vulnerability factors in the char areas are geographic position (100%), no access to migration (75%), resources (76%), housing (83%), training (18%), and alternative livelihood (24%). Flood and drought are identified as the most destructive hazards in char areas. Most household heads also felt anxiety (88%). fear (54%), helplessness, sadness, and anger due to natural hazards. The government should implement a context-specific disaster management plan to reduce household vulnerability and create livelihood opportunities in char areas to enhance char dwellers’ psychological resilience against disasters.
Access to quality and affordable mental health care is not always available to disaster-prone countries experiencing climate change, which may result in psychological trauma. Although environmental support has been provided, the consequences of disasters have not been addressed within the mental health realm. Inadequate knowledge and practice about crisis responses for mental health was addressed in Bangladesh with the influx of Rohingya people escaping persecution. To provide mental health support, Crisis Preparedness for Mental Health (CPM-MH) was developed and implemented addressing the psychological consequences of traumatic events. CP M-MH has its foundation in post-trauma stabilization through establishment of psychological equilibrium providing proactive rather than reactive methods linked to positive mental health outcomes. With adoption of CPM-MH in Bangladesh addressing mental health needs after traumatic events, mental health damage experienced by manmade and natural disasters may be considered the best strategy to build coping skills and resiliency for further traumatic event.
The monsoon season in Bangladesh is an example of how climate-related events can have a significant impact on mental wellbeing of affected individuals and communities. In this field report, we reflect on the integration of mental health and psychosocial support (MHPSS) services into emergency preparedness efforts. The report aims to offer an understanding of the risk associated with the monsoon season on both refugees and host communities and how likely this risk could affect mental health and mental health services. The MHPSS working group in Cox’s Bazar identified four major areas resulting from the impact of the monsoon season: increased incidence of mental health and psychosocial problems, relocation of individuals and families from high-risk areas to safer locations, disrupted provision of mental health and psychosocial services, and lack of self-care knowledge and practice for the humanitarian staff. To mitigate these impacts, an emergency preparedness and response plan was developed and included a wide range of activities aiming to better coordinate and scale up mental health services during the monsoon season.
Climate change adversely impacts the health and well-being of billions of people worldwide and will increasingly do so over the next few decades. Although all populations are at risk, some are more vulnerable than others. It is therefore critical to increase resilience to climate-related risks and build the capacity of national health systems by considering climate risks in health policy and decision making, strengthening leadership and governance to address impacts, and implementing strategies to build climate-resilient health care systems.
Bangladesh is a densely populated emerging country in South Asia. Since its harsh independence war, it has suffered from repeated floods and other natural and man-inflicted disasters. Internal migration from rural areas to the urban centres has increased crowdedness, pollution and social conflicts. Furthermore, in recent years, the country has absorbed close to a million refugees from Myanmar. These stressors have been associated with an increase in mental disorders and symptoms with which the country is struggling. Lack of resources and a shortage of human capital have weakened the national capacity to efficiently respond to situational stressors or disasters. For assessment of stress-related mental health issues, information available from the Ministry of Health and the National Institute of Mental Health was collected and supplemented by external reports. It is promising that the government’s approach of responding to mental health needs only after the occurrence of a crisis has recently been replaced by the concept of total management through primary healthcare. There is a need for development of adequate infrastructure, logistics and workforce support, as well as establishment of multidisciplinary teams of management and clinical services. Collaboration of all related sectors of the government and an overall increase in government funding for mental health are essential.
Rural communities are dependent on their native environment for supporting their customs, traditions, and other rural activities. This study attempts to understand the effects of the changing climate on rural individuals by investigating their feelings and experiences of perceived changes in the home environment and village life. Thirty-four in-depth interviews were conducted during the months of May-June 2019 in two districts-Gaya and Jehanabad of South Bihar, India. The findings reveal that the rural population have experienced changes in climate such as a rise in the incidence of heatwaves, erratic rainfall patterns, delay in monsoon onset, early drying of water resources, and loss of particular tree and bird species. Worries and uncertainties of the rural population have emerged from the experiences of involuntary separation from traditional farm activities, forced adaptation strategies, loss of cultural and religious practices, and reduced self-worth in coping with the deteriorating environment. The changing climate instigates feelings of emotional distress, resulting in adverse mental health and psychological well-being outcomes. It is concluded that the changing climate is responsible for the loss of traditional village customs and nature-related cultural practices, subsequently inducing solastalgia among the rural population.
This paper explores physical, psychological, social, and institutional vulnerabilities associated with slow-onset events (SoEs) of climate change. Based on review of interdisciplinary research in the context of Pakistan, this paper reviews the relevance of multi-level vulnerabilities and how they exacerbate impacts of SoEs of climate change. The physical vulnerabilities of climate change have been relatively well researched; however, research on the psychological, social, and institutional vulnerabilities and their intersectional associations with SoEs have been rare. Therefore, this review highlights the need for understanding multi-level vulnerabilities of high-risk groups in Pakistan. This paper emphasizes the need to work with an integrated approach for vulnerabilities of marginalized subgroups such as gender (women’s marginalized status), socio-economic status (lower SES), displacement history, and migration background. Finally, we propose the need for inclusive policy building sensitive to the demands of vulnerable groups in Karachi and elsewhere in Pakistan. We hope that this multilevel and inclusive framework has the potential to guide practitioners, and especially those who are least prepared for the slow-onset events of climate change.
BACKGROUND: It is widely believed that during the Great Depression (1929-1933) there was a rise in suicidal rates which was causally related to the increase in unemployment. There are no studies on the effect the Great Depression had on homicidal rates METHODS: The data concerning suicide, homicide, economic and climatic variables for the years 1900-1940 for the whole of the US were gathered from the US Center for Disease Control, the Maddison Project, the National Bureau of Economic Research and the National Climatic Data Center. Time Series Analysis was performed. RESULTS: The results are inconclusive on the role of economic factors but preclude any role of climate on suicidal rates during the years 1900-1940 in the US. Suicidal rates might have a 24-years periodicity, however much longer time series are needed to confirm this. On the contrary they strongly suggest an effect of higher temperatures on homicidal rates after 1922. CONCLUSIONS: The results of the current study suggest a direct and clear effect of climate (higher temperatures) on the increasing homicidal rates in the US after 1922 but failed to establish a causal relationship between suicide rates and economic or climate variables. These should be considered together with increasing concerns on the possible effect of climate change on mental health.
BACKGROUND & OBJECTIVES: Issues such as emerging and re-emerging infectious diseases, antimicrobial resistance, food security, biosafety and biosecurity are associated with changes in land use, population growth, urbanization, global travel and trade and climate change. As a result, a trans-disciplinary approach among human, animal and environmental health disciplines gained support. The Indian Council of Medical Research (ICMR) and Indian Council of Agricultural Research (ICAR) decided to establish a National Institute of One Health at Nagpur, Maharashtra, India. In this context, two collaborative research projects, funded by the ICAR and ICMR were initiated to conduct the epidemiological surveillance of selected zoonotic diseases in Central India. METHODS: Disease surveillance and molecular detection employing standard techniques like enzyme linked immunosorbent assay (ELISA), immuno-fluroscent assay (IFA), standard tube agglutination test (STAT) , Rose Bengal plate test (RBPT) and polymerase chain reaction (PCR) were undertaken based on the disease to be screened. RESULTS: In animals, the seropositivities for listeriosis (7.66%) and brucellosis (11.69%) were recorded. The occurrence of tuberculosis (3.8%) and leptospirosis (6.33%) was detected by PCR. Through cross-sectional studies from suspected human population with associated risk factors for zoonotic diseases, the seropositivity of brucellosis (1.83-11%), listeriosis (1.01-10.18 %), leptospirosis (8.14-12.67%) and scrub typhus (1.78-20.34%) was recorded. The investigations on scrub typhus indicated bimodal pattern during the months of pre-monsoon and post-monsoon season with a peak in post-monsoon in human cases. Ornithonyssus bacoti mites were identified from the rodents as a vector harbouring Orientia tsutsugamushi. The bovine tuberculosis was detected in 1.43 per cent human cases employing molecular assay. INTERPRETATION & CONCLUSIONS: The data indicated the occurrence of important zoonotic diseases adversely affecting the livestock health and human wellbeing. The scientific collaboration between veterinary and medical faculties has set an example for effective implementation of One Health (OH) programme for the establishment of National Institute of OH.
This study aimed at assessing the Livelihood Vulnerability Index (LVI) using the IPCC framework approach and a modified approach to estimate climate change vulnerability in south-west coastal area of Bangladesh. Nine Upazillas (sub-districts) in the south west coastal community were considered for this study. The major component indices of LVI such as socio-demographic profile, livelihood strategies, social network, health, food, water, natural disaster and climate variability were calculated based on the household survey data. The LVI based on the IPCC approach (LVI-IPCC) in nine upazillas in southwest coastal region of Bangladesh were found within a range of -0.02 to + 0.04 (on the scale of -1 to +1). In the modified approach. the LVI for the nine study areas was found within a wide range from 0.253 to 0.544 (on a scale of 0 to 1). For the LVI-IPCC approach, although the contributing factors (exposure, sensitivity and adaptive capacity) individually show variations in their indices from one to another, no significant variation is observed for the total livelihood index. However, the modified approach shows significant variation in LVI among the studied nine areas. It is concluded that the modified approach is suitable for community or district level assessment, whereas the LVI-IPCC may be suitable for regional level evaluation.
Bangladesh is one of the countries that is most likely to be affected by natural disasters and climate change. However, much less is known about the integrated livelihood and climate vulnerabilities of coastal communities to natural disasters in southwestern Bangladesh. Therefore, this paper proposes a holistic approach to measuring livelihood vulnerability in the southwestern coast of Bangladesh based on primary data from 300 respondents through face-to-face interviews, focus group discussion (FGD), and key informant interviews (KII), and secondary data on rainfall and temperature for the years 2010-2017. This study developed the livelihood vulnerability index (LVI), the climate vulnerability index (CVI), and the LVI-IPCC to estimate climate vulnerability by incorporating 36 indicators of 9 major components under three dimensions. The pragmatic results show that the three coastal unions have different LVI, CVI, and LVI-IPCC values. Still, the households of the Gabura union showed more vulnerability than the rest of the two, with the highest LVI, CVI, and LVI-IPCC values due to their inadequate access to fresh water, limited physical resources, fewest livelihood strategies, the least variety of crops, and worst health conditions. This logical approach may be applied in data-scarce regions to assess vulnerability and evaluate potential policy efficiency for baseline comparison. The study demonstrates that the requirement for focused interventions and context-specific sustainable policies and development approaches should be implemented to lessen the vulnerability of coastal dwellers. These findings have implications for developing and implementing household resilience and climate change adaptation projects by the government, donor organizations, and other pertinent groups in three susceptible unions.
This study has been conducted to identify vulnerabilities and effects of climate change on women in 12 unions in Shyamnagar upazila in the Satkhira district in the Southwestern Coastal Region of Bangladesh (SWCRB). Climate vulnerability and gender inequality may increase due to climate change. Women may, thus, face specific conditions of vulnerability in society and daily livelihood. This paper focuses on investigating factors that influence women’s vulnerability from climate change, their adaptations, and the importance of women empowerment to reduce their inequality in SWCRB. This study also emphasizes gender inequality caused by climate change, and looks at accommodations for women to reduce hostile influences of climate change. From the 9 unions in SWCRB, a total of 320 household respondents were randomly selected to complete a questionnaire. The results of the statistical analysis showed that most of the survey’s perimeter has significant. Interviews, case studies, focus group discussions, workshops, and key informant interviews were also conducted from 12 unions, and it was found that climate change impacts men and women differently, with women being more vulnerable than men. Through case study this paper investigated the main factors influencing the vulnerability of women. In terms of empowerment women may also be well positioned to lead adaptation efforts alongside men, as this analysis represent that gender inequalities are leading by social norms. Women being more vulnerable both in short-term i.e., major natural disasters, cyclones, flood, and long-term i.e., sea level rise, salinity intrusion in water and soil, land erosion, droughts, climatic events, as they enhance gender inequalities. Further, gender inequality is seen in illiteracy, food shortages and poor health conditions, traditional norms, religious taboos, and patriarchy. Moreover, gender-based economic opportunities, women’s mobility, and income are changing, while household authority relations and gender-based socio-economic, cultural, and institutional constraints remain. This study examines the increased vulnerability of women in SWCRB to climate change, which can be mitigated through women empowerment; female involvement with environmentally friendly stoves, rural electrification and renewable energy development, microfinancing, and nakshikantha. (Nakshikantha is a special type of sewing art that is made by creating designs with different types of colored threads on plain stitches). Lastly, women may also lead adaptation efforts alongside men, make decisions, and promote their participation.
Severe pneumonia is one of the leading contributors to morbidity and deaths among hospitalized under-five children. We aimed to assess the association of the socio-demographic characteristics of the patients and the climatic factors with the length of hospital stay (LoS) of under-five children with severe pneumonia managed at urban hospitals in Bangladesh. We extracted relevant data from a clinical trial, as well as collecting data on daily temperature, humidity, and rainfall from the Meteorological Department of Bangladesh for the entire study period (February 2016 to February 2019). We analyzed the data of 944 children with a generalized linear model using gamma distribution. The average duration of the hospitalization of the children was 5.4 ± 2.4 days. In the multivariate analysis using adjusted estimation of duration (beta; β), extended LoS showed remarkably positive associations regarding three variables: the number of household family members (β: 1.020, 95% confidence intervals (CI): 1.005-1.036, p = 0.010), humidity variation (β: 1.040, 95% Cl: 1.029-1.052, p < 0.001), and rainfall variation (β: 1.014, 95% Cl: 1.008-1.019), p < 0.001). There was also a significant negative association with LoS for children's age (β: 0.996, 95% Cl: 0.994-0.999, p = 0.006), well-nourishment (β: 0.936, 95% Cl: 0.881-0.994, p = 0.031), and average rainfall (β: 0.980, 95% Cl: 0.973-0.987, p < 0.001). The results suggest that the LoS of children admitted to the urban hospitals of Bangladesh with severe pneumonia is associated with certain socio-demographic characteristics of patients, and the average rainfall with variation in humidity and rainfall.
Integrating noncommunicable disease (NCD) in health care delivery during emergency response posed a major challenge post-floods in Kerala. Kerala experienced an abnormally high rainfall during mid-2018 where more than 400 people lost their lives. State health officials and the Disaster Response Team were sensitized about the importance of including NCDs in the response action. More than 80% of patients with hypertension and diabetes were not under control in Kerala. Under the state NCD cell, an NCD expert group was consulted for drafting the treatment and referral strategies. Steps to tackle NCDs during the disaster response were formulated. The state NCD cell decided to integrate NCDs in the response measures. The technical guidance document by the World Health Organization South-East Asia Region was consulted to formulate actions. The activities were implemented in 6 steps: prioritizing of major NCDS, patient estimation and drug stock preparation, standard treatment protocol, mapping of referral facilities, public engagement, and daily reporting of NCD consultations. Prioritizing the continuum of care of NCDs during floods among the program managers and care providers was crucial. The health education and communication campaign was done to sensitize the known NCD patients to seek early care. Daily reporting of consultations was established.
Communities are ever-evolving, cities are constantly expanding, and the threat of natural hazards has escalated like never before. Cities can develop and prosper only if their society is resilient to external shocks. Measuring community resilience over time is crucial with the influence of technology and change in community lifestyles. With the frequent onset of floods in Kerala in recent years, the community must be well-prepared for future calamities. Thus, this paper develops a community resilience index for Kerala’s urban flood-prone areas (CRIF) through a rigorous bottom-up approach. The criteria for the index were developed using multi-criteria decision analysis that covered a fuzzy Delphi study, an empirical study using multi-variate probit regression, and an AHP analysis. The fuzzy Delphi study selected seven criteria: ‘social’, ‘economical’, ‘governance/political’, ‘health’, ‘communication/coordination, ‘education’, and ‘infrastructure’ from 65 experts. The empirical study helped apprehend the public’s viewpoints under each criterion. Finally, the AHP analysis helped assign appropriate weights to the criteria which 28 experts designated. The index is also designed according to the Sendai Framework for Disaster Risk Reduction (2015-2030). Further, the CRIF Index is put into action through a case study of the Kochi Municipal Corporation area, and the results are also validated using the Spearman’s rank correlation coefficient method. Results from validation returned a value of 0.7209 for the perceived CRIF method and 0.5798 for the external validation method, which corresponds to a ‘high’ and ‘moderate’ correlation, respectively. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11069-022-05299-7.
Recurring floods and erosion result in displacement, which adversely impacts women who are ‘left behind’ when men migrate. Policy and programme measures for disaster response and climate adaptation often perceive women as homogenous, vulnerable groups, instead of addressing underlying structural and conceptual barriers and strengthening their adaptive capacities to disasters and displacement. This article draws upon a political ecology lens to understand gendered recovery processes following disasters across four districts in Assam, northeastern India using empirical research from 2012 to 2018. The findings add nuances to the displacements of women in Assam as being ‘climate-induced’ by showing the different mechanisms of displacement and how it impacts particular groups of women, as well as their differential ways of coping with these changes. This article draws on sustained long-term qualitative research among rural villagers, particularly women, in Assam where migration is connected to riverbank erosion, exacerbated by the construction of a new embankment, and disrupted due to waterlogging caused by embankments and government relocation schemes in order to construct further dams/embankments.
Objective Flood is an annual phenomenon in Assam. This study aims to understand the after flood effects on children in the worst flood-hit districts of Assam during the last decades most devastating flood where more than 1,00,000 people were affected. Study design A cross sectional population-based study was done covering 7512 children of 0-12 years of age in 35 worse flood-affected villages in three districts of lower Assam for nutritional risk profiling, low birth weight and morbidity pattern. Method Anthropometric measurements of the children were compared with standard WHO definitions for nutritional risk profiling. ANOVA was conducted to see any relationship of nutritional status between the age groups and BMI for the districts. Two-factor ANOVA to analyse the effect of ARI on the morbidity status of different districts was done. District-wise and village-wise heat maps were generated to understand different nutritional parameters for analysing which areas within each district are more affected and why. Results The moderate (< 2SD) and severely underweight (< 3SD) children under 5 years of age were highest in the Barpeta district (45.5% and 24.2% respectively). The moderate and severe stunting was highest in Morigaon (47.6%) and Barpeta (24.3%) respectively. The moderate and severe wasting was highest in the Morigaon district (46.1% and 20.6% respectively). All the nutritional indicators were less than the WHO standard. The age-wise and district-wise distribution of nutritional status shows variations in all three districts. Severe underweight was observed highest among 24-35 months' children (50.9%) in Barpeta. The moderate and severe undernutrition status was found to be higher among the age group of 10-12 years of age compared to 5 to 10 years. Conclusion This survey has provided a comprehensive picture of the nutritional status of the targeted children in the worst flood-affected areas. However, attention to its impact on health particularly among those exposed at very early stages in life is still lacking. This kind of rapid assessment helps to understand the health and nutritional status of the vulnerable groups in a deeper way and to plan robust region-specific interventions.
India witness floods during the summer monsoon (June-September) that disproportionately affect the socioeconomic well-being of millions of people. Nonstructural measures such as flood early warning systems play a crucial role in mitigating the impacts; however, these require a proper understanding of flood drivers. The drivers of floods in the Indian river basins have not been examined for the observed and projected future climate. Here using a novel framework, we examine antecedent moisture conditions and precipitation characteristics before high flow events. We estimate the probability of occurrence of flood drivers and their association with peak flood magnitude under the observed and projected future climate in Indian river basins. Multiday precipitation, a proxy to heavy precipitation on wet soil conditions, was found as the predominant flood driver in the observed and projected future climate. We show that multiday precipitation is more prominent driver than extreme soil moisture conditions in larger rivers basins while extreme precipitation drives floods in smaller river basins. The frequency of major drivers of floods is projected to rise in the future, which may pose a greater risk to agriculture and infrastructure under the warming climate.
Natural disasters inflict severe damage on almost the entire spectrum of social and natural habitats. This ranges from housing and shelter, water, food, health, sanitation to information and communication networks, supply of power and energy, transportation infrastructure, and others. Nepal is a risk prone country for Glacial Lake Outburst Flood (GLOF). GLOFs exist as major challenges as they repeatedly cause a heavy toll of life and property. During such a disaster, major challenges are indeed the protection of life, property and vital life-supporting infrastructure. Any delay or laxity in disaster relief can escalate the magnitude of distress for the victims. Thus, rather than trying to take curative measures, it is better to minimize the impacts of GLOF. These measures subsequently help in reducing the magnitude of death and casualties due to a GLOF event. This reduction of impact is often achieved by optimizing preventive measures. For applying necessary deterrent measures, it is essential to disseminate information about the danger beforehand. Early Warning System (EWS) is an important step for such information dissemination for GLOF disaster management and helps to anticipate the risk of disaster and disseminate information to lives at risk. It is impossible and impractical to reduce all GLOF risks, but it is possible to reduce several impacts of a GLOF through the implementation of the EWS. This paper presents the design and implementation of an EWS for monitoring potential outbursts of a glacier lake in the Dudh-Koshi Basin, Nepal.
Torrential rainfall following the monsoon season occurs annually in Pakistan and adversely affects health service delivery and population health. This qualitative study was undertaken in five flood-prone districts to examine district health systems’ performance during floods in Pakistan. The first of its kind study to gather an in-depth assessment of the capacity of district health systems in maintaining healthcare services during floods. Key informant interviews were conducted with 37 district stakeholders and 42 frontline healthcare providers. Nine focus group discussions were also conducted with 56 lady health workers. World Health Organization health systems’ six building blocks framework was utilized to assess the performance of district health systems. The findings illustrated increased reporting of diseases, and domestic and sexual violence against females. The damaged roads and unavailability of transportation during floods affected outreach services in the communities. The inadequate availability of funds resulted in critical gaps in the supply chain for essential medicines and supplies, impeding outreach services. Shortage of female medical staff was reported in addition to poor attention to the training of staff for disaster response. Furthermore, reporting mechansim varied across provinces with daily reporting system of acute illnesses instituted. Moreover, district health systems lacked gender-sensitive responses in responding to flood emergencies. This study identified multiple health system constraints that resulted in poor district health systems’ capacity in delivering essential healthcare services during floods. This study, therefore, highlighted a need to improve district health systems’ capacity in effectively responding to healthcare service needs during floods.
Using household surveys for 2008 and 2011, a multidimensional destitution measure is constructed for Pakistan’s most populated province – Punjab. Using a non-monetary framework for dimensions of health, education and standard of living, the study paints a temporal picture of the extremely impoverished households in districts and towns, while highlighting the impact of the destructive 2010 floods. Results reveal the existence of pervasive destitution, with half of the multidimensionally poor households also identified as destitute. Destitution is higher for rural as compared to urban households, while the geography of destitution highlights its concentration in south-west Punjab, providing insights for targeted interventions.
Pakistan is vulnerable and most affected by adverse impacts of climate change. The study examines the impact of climate change on Pakistan during the year 2022, resulting into unprecedented heatwave and drought in summers followed by the abnormal rains and floods during monsoon season. Agriculture is the backbone of Pakistan’s economy, which has been devastated by both drought and floods. While the flood water is gradually receding, the stagnant contaminated water is causing several health risks for the inhabitants. This research argues that water security is the emerging national security challenge for Pakistan. The article investigates the status of water availability vis-a-vis the burgeoning population, agriculture, and other uses of water. Impact of abnormal melting of glaciers, nonavailability of dams for storage of rainwater, and lack of smart means for agriculture water have been examined to empirically validate the arguments.
Stunting is a significant public health problem in low- and middle-income countries. This study assessed the prevalence of stunting and associated risk factors of stunting among preschool and school-going children in flood-affected areas of Pakistan. A cross-sectional study was conducted by visiting 656 households through multi-stage sampling. Respondent’s anthropometric measurements, socio-demographic information and sanitation facilities were explored. A logistic regression model was used to determine determinants of stunting, controlling for all possible confounders. The overall prevalence of stunting in children was 40.5%, among children 36.1% boys and 46.3% of girls were stunted. The prevalence of stunting in under-five children was 50.7%. Female children (OR=1.35, 95% CI:0.94-2.0), children aged 13-24 months (OR=6.5, 95% CI: 3.0-13.9), mothers aged 15-24 years (OR=4.4, 95% CI: 2.6-7.2), joint family (OR=2.1, 95% CI: 1.4-3.0) did not have access to improved drinking water (OR=3.3, 95% CI: 1.9-5.9), and the toilet facility (OR=2.8, 95% CI, 1.9-4.3), while the children from district Nowshera (OR=1.7, 95% CI: 0.9-3.2) were significantly (P<0.05) associated in univariate analysis. The regression model revealed that child age, maternal age, family type, quality of water, and toilet facility, were the significant (P<0.05) factors contributing to child stunting in the flood-hit areas. Identification of key factors might be helpful for policymakers in designing comprehensive community-based programs for the reduction of stunting in flood-affected areas. In disasters such as flood, the detrimental consequences of the stunting problem could be even more on children. Evidence-based education and care must be provided to the families in the flood-affected regions to reduce the stunting problem. The determinants of stunting should be targeted by making comprehensive policies regarding proper nutrition, livelihood, clean water, and sanitation facilities in flood-hit regions.
There is minimal literature regarding micronutrient deficiencies in flood-affected regions. In our study, we aimed to find the prevalence of micronutrient deficiencies (vitamin A, calcium, zinc, iron, and iodine) among preschool and school-age children in flood-hit areas of Khyber Pakhtunkhwa, Pakistan. In this cross-sectional study, a multi-stage sampling technique was used for the selection of 656 households. Serum micronutrient status was detected in the targeted population in the affected districts. The least significant difference test was used with analysis of variance to determine significant differences in nutrient contents in different areas. Of the total respondents, 90.8% of the children were calcium deficient, 88.3% were zinc deficient, 26.7% were iron deficient, 53.5% were vitamin A deficient, and 39.5% were had an iodine deficiency in flood-affected areas. A significant difference (P < 0.05) was found in different age groups of children for zinc (5.7-42.63 μg/dL) and urinary iodine (69.6-85.4 μg/L). The 10- to 12-year-old age group had a lower serum zinc concentration (5.7 μg/dL), whereas the 1- to 3-year-old age group had a lower urinary iodine concentration (69.6 μg/L) than other groups. There was no significant difference (P > 0.05) between male and female children and various age groups for calcium and iron status. Vitamin A levels were significantly (P < 0.05) different among different age groups (high in age group 4-6 years) and districts. Vitamin A concentration was lower in the Nowshera District, whereas serum iron and zinc were lower in the Dera Ismail Khan District. All the important micronutrients in the population of children were deficient in the flood-affected areas of Pakistan. Therefore, policymakers should implement potential prevention strategies, such as food security, school health nutrition, food fortification, nutrition in the first 1,000 golden days, nutrition knowledge, and awareness of the local population, to reduce the burden of micronutrients deficiencies in flood-affected areas.
Low- and middle-income countries are usually at high risk of malnutrition. Not only that but the prevalence of malnutrition is much higher. It is important to evaluate the determinants of malnutrition in flood-affected areas of Pakistan. The present study examined the prevalence and risk factors of MUAC-based child malnutrition in flood-hit regions of Khyber Pakhtunkhwa, Pakistan. Multi-stage sampling was employed to select 656 households. Finally, 298 children of 6-59 months were selected. MUAC, an independent anthropometric parameter, was used to investigate the nutritional status of children. An automated logistic regression model was used to identify the risk factors of MUAC-based malnutrition. The prevalence of MUAC-based malnutrition was found 46%, including 40.5% females and 52.1% males. More than 90% of people had improved water quality and soap hand washing facility. Almost 17% of respondents had no toilet facility. Through automated logistic model, child age, maternal age, family size, income level, mother education, water quality, toilet facility were the significant determinants (P < .05) of MUAC-based undernutrition in flood affecting the area. The findings suggest that MUAC-based malnutrition can be minimized in flood-hit areas by targeting the listed risk factors. Community-based awareness programs regarding guidance on nutrition might be a key to reducing malnutrition in the target areas.
With accelerating climate change, US coastal communities are experiencing increased flood risk intensity, resulting from accelerated sea level rise and stronger storms. These conditions place pressure on municipalities and local residents to consider a range of new disaster risk reduction programs, climate resilience initiatives, and in some cases transformative adaptation strategies (e.g., managed retreat and relocation from highly vulnerable, low-elevation locations). Researchers have increasingly understood that these climate risks and adaptation actions have significant impacts on the quality of life, well-being, and mental health of urban coastal residents. We explore these relationships and define conditions under which adaptation practices will affect communities and residents. Specifically, we assess climate and environmental stressors, community change, and well-being by utilizing the growing climate change literature and the parallel social science literature on risk and hazards, environmental psychology, and urban geography work, heretofore not widely integrated into work on climate adaptation.
Food insecurity is a key global health challenge that is likely to be exacerbated by climate change. Though climate change is associated with an increased frequency of extreme weather events, little is known about how multiple environmental shocks in close succession interact to impact household health and well-being. In this paper, we assess how earthquake exposure followed by monsoon rainfall anomalies affect food insecurity in Nepal. We link food security data from the 2016 Nepal Demographic and Health Survey to data on shaking intensity during the 2015 Gorkha earthquake and rainfall anomalies during the 2015 monsoon season. We then exploit spatial variation in exposure to the earthquake and monsoon rainfall anomalies to isolate their independent and compound effects. We find that earthquake exposure alone was not associated with an increased likelihood of food insecurity, likely due in part to effective food aid distribution. However, the effects of rainfall anomalies differed by severity of earthquake exposure. Among households minimally impacted by the earthquake, low rainfall was associated with increased food insecurity, likely due to lower agricultural productivity in drought conditions. Among households that experienced at least moderate shaking, greater rainfall was positively associated with food insecurity, particularly in steep, mountainous areas. In these locations, rainfall events disproportionately increased landslides, which damaged roads, disrupted distribution of food aid, and destroyed agricultural land and assets. Additional research on the social impacts of compound environmental shocks is needed to inform adaptation strategies that work to improve well-being in the face of climate change.
PURPOSE: This report describes the general impact and direct health effects including death and traumatic injuries on populations impacted by the 2017 landslides in the affected hilly and coastal districts in southeastern Bangladesh. The medical response including emergency treatment and rehabilitation provided at pre-hospital and hospital care sites is also described. MATERIALS AND METHODS: An electronic literature search of appropriate databases was performed to identify relevant articles on landslides in Bangladesh, Southeast Asia, and other developing countries from 1990-2017. Summary landslide impact data was extracted from official government and non-government reports and injury data from selected district and tertiary level hospitals was reviewed. RESULTS AND CONCLUSIONS: Most fatalities in the 2017 Bangladesh landslides were due to suffocation and asphyxiation from burial. In Rangamati District, 6343 persons with minor injuries were treated in 22 emergency shelters. One hundred fifty-four injuries were treated at Rangamati General Hospital and 12 of the most severely injured persons were referred to regional tertiary Chittagong Medical College Hospital for specialized injury and rehabilitation management. Physical rehabilitation capacity and services in future landslides may be increased by providing rehabilitation technical skills training to responders and augmenting the emergency response with individual rehabilitation specialists and/or teams of rehabilitation professionals.Implications for rehabilitationLandslides may result in significant direct health effects including death and rehabilitation conditions such as severe traumatic physical injuries and less severe musculoskeletal conditions.Pre-hospital and hospital emergency medical response systems may lack capacity to adequately manage the surge of rehabilitation conditions in landslides.Physical rehabilitation treatment capacity in future landslides may be increased by providing rehabilitation technical skills training to responders and augmenting the emergency response structure with individual rehabilitation specialists and/or teams of rehabilitation professionals.Rehabilitation, disability, emergency management, and other stakeholders are advised to employ such training and workforce strategies to reduce rehabilitation-related health effects in Bangladesh and other South-East Asian countries which are heavily impacted by landslides due to seasonal monsoons.
Landslides being a widespread disaster are associated with susceptibility, vulnerability and risk. The physical factors inducing landslides are relatively well-known. However, how landslide susceptibility will be exacerbated by climate change, impede the attainment of the sustainable development goals and increase health vulnerability is relatively less explored. We present an integrated assessment of landslide susceptibility, health vulnerability and overall risk to understand these interconnected dimensions using Arunachal Pradesh, India, as a case study, which is susceptible to landslides due to its topography and climate conditions. Landslide susceptibility was examined using twenty landslide conditioning parameters through the fuzzy analytical hierarchy process (FAHP). The susceptibility map was validated using the area under the ROC curve (AUC). National Family Health Survey (NFHS 4) data were used to analyze the health vulnerability, while the overall risk was computed through the integration of susceptibility and vulnerability. Landslide susceptibility analysis indicated that nearly 22% area of the state is characterized by moderate susceptibility followed by high (17%) and very high susceptibility (13%). High elevation, slope, rainfall, SPI, drainage density and complex geology were identified as the causative factors of landslides. In the case of health vulnerability, East Kameng and Lohit districts were found to be very highly vulnerable, while Papum Pare, Changlang and Tirap districts experience high health vulnerability due to high degree of exposure and sensitivity. Overall risk analysis revealed over 16.8% area of the state is under moderate risk followed by high (9.8%) and very high (4.2%) risk. Linking this analysis with the climate change projections and SDG goals attainment revealed that Papum Pare, Upper Subansiri, Tirap and West Kameng require priority for lessening susceptibility, vulnerability and risk for achieving sustainable development. A strong correlation (99%) between HVI and risk further demonstrates the need for lessening health vulnerability and risk in the study area. Furthermore, our study contributes additional insights into landslide susceptibility by considering heal vulnerability and risk which may help in planning sustainable development strategies in a changing climate.
Bangladesh is repeatedly threatened by tropical storms and cyclones, exposing one-third of the total population of the country. As a preparedness measure, several cyclone shelters have been constructed, yet a large proportion of the coastal population, especially women, are unwilling to use them. Existing studies have demonstrated a range of concerns that discourage women from evacuating and have explored the limitations of the shelters, but the experiences of female evacuees have not been apparent in these stories. This study explores the lived-experiences of women in the cyclone shelters of Bangladesh and discusses their health and well-being as evacuees in the shelters. Nineteen women from three extremely vulnerable districts of coastal Bangladesh were interviewed. Seven research themes were identified from the participants’ narratives using van Manen’s thematic analysis process. The most salient theme, being understood (as a woman), portrayed the quintessential image of these women, which subsequently influenced their vulnerability as evacuees. The next themes-being a woman during crisis, being in a hostile situation, being fearful, being uncertain, being faithful, and being against the odds-focused on the incidents they lived through which affected their physical and mental health and the emotions they felt as evacuees. The paper offers a deep inquiry into women’s experiences of well-being in the shelters and recognizes the significance of women’s voices to improve their experiences as evacuees.
BACKGROUND: Early Identification of disaster victims with mental health problems may be useful, but information within a short period after a disaster is scarce in developing countries. This study examined anxiety, depression, and post-traumatic stress symptoms at 1 month following 2019 Cyclone Fani in Odisha, India. METHOD: Post-traumatic stress symptoms (PTSS) were assessed by the Primary care PTSD screen for DSM 5 (PC-PTSD-5), anxiety symptoms by the Generalised Anxiety Disorder (GAD-7), and depression by the Patient Health Questionnaire (PHQ-9). The survey included participants’ disaster experience e.g., evacuation, fear of death, injury, death in family, damage to house, difficulty for food, displacement, and effect on livelihood. RESULTS: Proportion of sample (n = 80) with probable PTSD was 42.9%, with severe anxiety was 36.7%, moderately severe depression was 16.5%, and severe depression was 3.8%. Suicidal cognitions were reported to increase by 14%. Comorbidity was common; with significant (P < 0.01) correlation between PTSS and anxiety (r = 0.69), depression (r = 0.596), and between anxiety and depression (r = 0.63). Damage of house and displacement were associated significantly with PTSD; evacuation and displacement with moderate and severe depression; and displacement with severe anxiety. No specific demographic factors were significantly linked to the psychiatric morbidities. CONCLUSION: A considerable proportion of victims had psychiatric morbidities at 1 month. Associated risk factors included housing damages, evacuation, and displacement, suggesting the need to improve the disaster-management process.
Age differences in posttraumatic stress disorder (PTSD) are widely researched, but findings remain inconclusive. The mixed findings may in part result from sampling participants exposed to different trauma types at different times. Here, we controlled for this issue by sampling participants exposed to the same devastating hurricane. A total of 1.5 months after Hurricane Florence (T1), we asked 174 adults living in two severely affected states to describe their hurricane experience and fill in measures of PTSD and event centrality. Then, 7 months after the hurricane (T2), participants were reinvited to the survey, and 98 filled in the same questionnaire. The hurricane descriptions were coded for level of exposure severity. When controlling for trauma characteristics, including level of severity, younger age significantly predicted PTSD at T1 but not T2. When also controlling for event centrality, younger age predicted PTSD at both measurement times. Moreover, from T1 to T2, young adults significantly increased how severely they described their hurricane experience to be, whereas such amplification was absent in the older age groups. Overall, the findings provide some evidence that younger age increase vulnerability for PTSD and increase the perception of trauma severity over time.
OBJECTIVE: This study was undertaken to assess the health status of newborns discharged from Sick Newborn Care Units (SNCU) of the Cyclone Fani affected districts of Odisha, which is amongst the highest neonatal mortality rate states in the country. METHODS: Cyclone Fani hit the coast of Odisha on May 3, 2019. This cross-sectional study was conducted in 5 districts and targeted the babies discharged from SNCU’s from January to May 2019. A telephonic interview of the caregivers was conducted to assess the health status of the newborns. Data was collected in a web-based portal and analyzed by statistical package for social sciences SPSS (IBM Corp., Armonk, New York, USA). RESULTS: We inquired about 1840 babies during the study period but only 875 babies could be followed up, with the highest proportion of the babies from the most affected district. Out of 875 babies, 111 (12.7%) had 1 or more illnesses during follow up. Distance from the health facility and time constraints were the major reasons for not seeking health care. Of the babies, 35.7% were reported as being underweight. Poor breastfeeding (14.1%) and kangaroo mother care (31.7%) practices were reported. Only 32% of the babies were completely immunized. CONCLUSION: The health status of the babies discharged from the SNCUs was found to be poor. Newborn care can be strengthened by improving home-based and facility-based newborn care.
Construction workers are at a high risk of exposure to excessive heat generated by several factors such as intensive physical activities, personal protective clothing, and frequent heat events at construction sites. Previous studies attempted to evaluate the occupational risk of heat stress by concentrating on environmental variables or the self-assessment measures of perceived heat. Despite their potentials, most of these approaches were intrusive, inaccurate, and intermittent. More importantly, they mainly overlooked the disparities in workers’ physical and physiological characteristics. To address these limitations, this study proposes a heat-stress risk-assessment process to evaluate workers’ bodily responses to heat – heat strain – based on the continuous measurement of their physiological signals. To this end, workers’ physiological signals were captured using a wristband-type biosensor. Subsequently, their physiological signals were decontaminated from noises, resampled into an array of informative features, and finally interpreted into distinct states of individuals’ heat strain by employing several supervised learning algorithms. To examine the performance of the proposed process, physiological signals were collected from 18 subjects while performing specific construction tasks under three predetermined environmental conditions with a different probability of exposure to heat stress. The analysis results revealed the proposed process could predict the risk of heat strain with more than 92% accuracy, illuminating the potentials of wearable biosensors to continuously assess workers’ heat strain. The long-term implications of this study can be capitalized as guidelines to improve systematic evaluation of heat strain and promote workers’ occupational safety and well-being through early detection of heat strain at construction sites.
Heat stress illnesses represent a rising public health threat; however, associations between environmental heat and observed adverse health outcomes across populations and geographies remain insufficiently elucidated to evaluate risk and develop prevention strategies. In particular, military-relevant large-scale studies of daily heat stress morbidity responses among physically active, working-age adults to various indices of heat have been limited. We evaluated daily means, maximums, minimums, and early morning measures of temperature, heat index, and wet bulb globe temperature (WBGT) indices, assessing their association with 31,642 case-definition heat stroke and heat exhaustion encounters among active duty servicemembers diagnosed at 24 continental US installations from 1998 to 2019. We utilized anonymized encounter data consisting of hospitalizations, ambulatory (out-patient) visits, and reportable events to define heat stress illness cases and select the 24 installations with the highest case counts. We derived daily indices of heat from hourly-scale gridded climate data and applied a case-crossover study design incorporating distributed-lag, nonlinear models with 5 days of lag to estimate odds ratios at one-degree increments for each index of heat. All indices exhibited nonlinear odds ratios with short-term lag effects throughout observed temperature ranges. Responses were positive, monotonic, and exponential in nature, except for maximum daily WBGT, minimum daily temperature, temperature at 0600 h (local), and WBGT at 0600 h (local), which, while generally increasing, showed decreasing risk for the highest heat category days. The risk for a heat stress illness on a day with a maximum WBGT of 32.2 °C (90.0 °F) was 1.93 (95% CI, 1.82 – 2.05) times greater than on a day with a maximum WBGT of 28.6 °C (83.4 °F). The risk was 2.53 (2.36-2.71) times greater on days with a maximum heat index of 40.6 °C (105 °F) compared to 32.8 °C (91.0 °F). Our findings suggest that prevention efforts may benefit from including prior-day heat levels in risk assessments, from monitoring temperature and heat index in addition to WBGT, and by promoting control measures and awareness across all heat categories.
BACKGROUND: Maternal exposure to weather-related extreme heat events (EHEs) has been associated with congenital heart defects (CHDs) in offspring. Certain medications may affect an individual’s physiologic responses to EHEs. We evaluated whether thermoregulation-related medications modified associations between maternal EHE exposure and CHDs. METHODS: We linked geocoded residence data from the U.S. National Birth Defects Prevention Study, a population-based case-control study, to summertime EHE exposures. An EHE was defined using the 90(th) percentile of daily maximum temperature (EHE90) for each of six climate regions during postconceptional weeks 3-8. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for associations between EHE90 and the risk of CHDs were estimated by strata of maternal thermoregulation-related medication use and climate region. Interaction effects were evaluated on multiplicative and additive scales. RESULTS: Over 45% of participants reported thermoregulation-related medication use during the critical period of cardiogenesis. Overall, these medications did not significantly modify the association between EHEs and CHDs. Still, medications that alter central thermoregulation increased aORs (95% CI) of EHE90 from 0.73 (0.41, 1.30) among non-users to 5.09 (1.20, 21.67) among users in the Southwest region, U.S. This effect modification was statistically significant on the multiplicative (P = 0.03) and additive scales, with an interaction contrast ratio (95% CI) of 1.64 (0.26, 3.02). CONCLUSION: No significant interaction was found for the maternal use of thermoregulation-related medications with EHEs on CHDs in general, while medications altering central thermoregulation significantly modified the association between EHEs and CHDs in Southwest U.S. This finding deserves further research.
BACKGROUND: Elevated temperature is well-recognized as a health hazard, and may be particularly harmful to pregnant women, including increasing risk of stillbirth. We conducted a study in Northern and Central Florida, an area prone to periodic extreme heat but with significant seasonal variation, focusing on the most socioeconomically vulnerable populations least able to mitigate the impact of heat. METHODS: We obtained electronic health records data from the OneFlorida Data Trust for the period 2012-2017, with 1876 stillbirths included in the analysis. We used a case-crossover design to examine the risk of stillbirth associated with acute exposures to elevated heat prior to the outcome, contrasting the case period (the week preceding the stillbirth) with a control period (the week prior to the case period and the week after the stillbirth). Average heat index and maximum warning level during the case and control periods of each woman were assigned by ZIP code. Conditional logistic regression models were used to assess the association between stillbirth and heat exposure, controlling for PM(2.5) and O(3). RESULTS: The adjusted odds ratio showed no overall association with stillbirth except for a weak association for exposure above the 90th percentile which was larger among the most socioeconomically deprived and non-Hispanic Black women. In the hot months, there was a clear association for all indices of heat exposure, but largest again for the most socioeconomically deprived population (aOR = 2.4, 95% CI: 1.2-5.2 in the 4th vs. 1st quartile) and among non-Hispanic Black women (aOR = 1.8, 95% CI: 1.0-3.2 in the 4th vs. 1st quartile). CONCLUSIONS: Our results provide further evidence that elevated ambient heat is related to stillbirth and encourage a focus on the most susceptible individuals and possible clinical pathways.
South Asia, with more than one-fifth of the world’s population, is highly vulnerable to heatwaves and associated health consequences. The population experiences considerably higher residential vulnerability due to limited infrastructural capacities, economic resources, and health and environmental quality deficiencies. However, a limited number of studies are available from the region to account for the health effects of heatwaves. Therefore, this study has conducted a comprehensive review to characterize heatwaves across South Asian countries. The review explicitly identifies the population’s vulnerability to heatwaves during recent years and heatwave management policies in the region. The literature review suggests increased heat-related deaths in most South Asian countries, with few exceptions. In addition, the analysis of historical temperature records identified an upward trend in annual average temperature across the South Asian countries. The study highlights various heatwave definitions that have been used in the region to facilitate comparative evidence. The review of policies identified that only a few South Asian countries have functional heatwave management plans and majorly lack community and residential preparedness for heatwaves. Therefore, this study identifies potential community- and residential-based adaptation strategies to mitigate heat discomfort. As prospective solutions, the study recommends adaptation strategies such as blue-green spaces, indoor passive cooling, infrastructural adjustments, heat action plans, etc. However, such adaptation measures require a holistic amalgamation of different stakeholders to fabricate heatwave-resilient cities.
Despite recent advancements in global population well-being and food security, climate change threatens to undermine child nutritional health, particularly for marginalized populations in tropical low- and middle-income countries. South Asia is at particular risk for climate-driven undernutrition due to a combination of historical weather exposures, existing nutritional deficits, and a lack of sanitation access. Previous studies have established that precipitation extremes increase rates of undernutrition in this region, but the existing literature lacks adequate consideration of temperature anomalies, mediating social factors, and the developmentally-relevant timing of exposure. We combine high-resolution temperature and precipitation data with large-sample survey data on household demographics and child anthropometry, using an approach that incorporates three key developmental periods and a rigorous fixed effects design. We find that precipitation extremes in the first year of life significantly decrease children’s height-for-age (HAZ) in South Asia. The detrimental effects of extreme precipitation are especially concentrated in under-resourced households, such as those lacking access to proper sanitation and education for women, while anomalous heat is particularly harmful for children in Pakistan, though it tends to benefit children in some demographic groups. These results indicate that nutritional status in South Asia is highly responsive to climate exposures, and that addressing sanitation infrastructure and other development priorities is a pathway towards reducing this vulnerability.
Urban parks play an essential role in urban settings; significantly contribute to the health of every age group person. Parks provide opportunities for families to connect with nature and breathe in the fresh air. Due to global climate change and increased urbanisation in the past few decades, extreme heat can be experienced in urban areas. Mental and physical health issues arise primarily due to a sedentary lifestyle in cities. Staying at parks for a longer duration could promote stress reduction and perceived physical health. The present study aims to assess the thermal comfort conditions at an urban park in the hot semi-arid climate(BSh) of Haryana, India. The present study investigated the outdoor thermal comfort range and thermal sensations of visitors at a park during the summer season using the onsite monitoring of the microclimate parameters and questionnaire survey in the hot-semi arid region of India. Thermal comfort indices, Physiological equivalent temperature (PET) and Universal Thermal Climate Index (UTCI) and Wet bulb globe temperature(WBGT) have been applied to investigate the outdoor thermal comfort conditions. The seven-point sensation scale has been used to record the visitors’ thermal sensations. The results indicated that:1) WBGT was found to be the most suitable index to investigate the OTC conditions. The neutral UTCI, PET, and WBGT ranged within 28.03 degrees C to 35.6 degrees C, 24.04 degrees C to 37.5 degrees C, and 23.5 degrees C to 26.1 degrees C, respectively. 2) The neutral PET ,UTCI, and WBGT were found to be 30.8 degrees C, 31.8 degrees C, and 24.8 degrees C, respectively.3) Dry bulb temperature is the most significant thermal comfort parameter affecting visitors’ thermal sensations, followed by mean radiant temperature.4) Thermal comfort indices were found to be most significantly affected by globe temperature. The study’s outcome could provide theoretical design reference to urban designers to develop new parks and existing parks, ultimately promoting public health. Copyright (c) 2022 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the F-EIR Conference 2021 on Environment Concerns and its Remediation: Materials Science
Climate change has significantly increased the frequency and intensity of human thermal stress, with relatively more severe impacts than those of pure temperature extremes. Despite its major threats to public health, limited studies have assessed spatiotemporal changes in human thermal stress in densely populated regions, like South Asia (SAS). The present study assessed spatiotemporal changes in human thermal stress characteristics in SAS, based on daily minimum, maximum, and mean Universal Thermal Climate Indices (i.e. UTCImin, UTCImax, and UTCImean) using the newly developed high-spatial-resolution database of the thermal-stress Indices over South and East Asia for the period 1981-2019. This study is the first of its kind to assess spatiotemporal changes in UTCI indices over the whole of SAS. The study also carried out extreme events analysis of the UTCI indices and explored their nexus with El Nino-Southern Oscillation (ENSO) index. Results revealed a significant increase in heat stress in SAS, with the highest human thermal stress in western Afghanistan, the Indo-Gangetic Plain, and southeastern, and central parts. The extreme event analysis showed that the study region is likely to observe more frequent and intense heat extremes in the coming decades. The correlation of UTCI indices with ENSO exhibited a robust positive coherence in southeastern and central India, southern Pakistan, and northwestern Afghanistan. The findings of the study are critical in understanding human thermal stress and adopting effective risk reduction strategies against heat extremes in SAS. To better understand the dynamic mechanism of thermal extremes, the study recommends a detailed investigation of the underlying drivers of UTCI variability in SAS.
Safety zones (SZs) are critical tools that can be used by wildland firefighters to avoid injury or fatality when engaging a fire. Effective SZs provide safe separation distance (SSD) from surrounding flames, ensuring that a fire’s heat cannot cause burn injury to firefighters within the SZ. Evaluating SSD on the ground can be challenging, and underestimating SSD can be fatal. We introduce a new online tool for mapping SSD based on vegetation height, terrain slope, wind speed, and burning condition: the Safe Separation Distance Evaluator (SSDE). It allows users to draw a potential SZ polygon and estimate SSD and the extent to which that SZ polygon may be suitable, given the local landscape, weather, and fire conditions. We begin by describing the algorithm that underlies SSDE. Given the importance of vegetation height for assessing SSD, we then describe an analysis that compares LANDFIRE Existing Vegetation Height and a recent Global Ecosystem Dynamics Investigation (GEDI) and Landsat 8 Operational Land Imager (OLI) satellite image-driven forest height dataset to vegetation heights derived from airborne lidar data in three areas of the Western US. This analysis revealed that both LANDFIRE and GEDI/Landsat tended to underestimate vegetation heights, which translates into an underestimation of SSD. To rectify this underestimation, we performed a bias-correction procedure that adjusted vegetation heights to more closely resemble those of the lidar data. SSDE is a tool that can provide valuable safety information to wildland fire personnel who are charged with the critical responsibility of protecting the public and landscapes from increasingly intense and frequent fires in a changing climate. However, as it is based on data that possess inherent uncertainty, it is essential that all SZ polygons evaluated using SSDE are validated on the ground prior to use.
Every year Bangladesh faces enormous damages due to flooding. Facing these damages the Government adopts various recovery approaches. However, the psychological dimension of any disaster is generally overlooked in disaster management. Researchers have found that the spatial distribution of post-disaster mental health can help the authorities to apply recovery procedures where they are most needed. For this research, Posttraumatic Stress Checklist (PCL-5), Patient Health Questionnaire (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to estimate posttraumatic stress, major depressive disorder and anxiety following three episodes of severe floods in 2017 that affected at least 8 million people. To better understand the spatial pattern of psychological vulnerability and reach a comprehensive scenario of post-disaster mental health, Moran’s I was applied for spatial autocorrelation and Pearson’s correlation and regression analysis for a study of the relationship between the psychological aspects. It was found that psychological vulnerability showed a spatial clustering pattern and that there was a strong positive linear relationship among psychological aspects in the study area. This research might help to adopt disaster management policies that consider the psychological dimension and spatial distribution of various psychological aspects to identify areas characterized by high vulnerability and risk so that they can be reached without delay.
BACKGROUND: Bangladeshi flood survivors are reported with such higher mental disorders that are not ever observed in any other cohorts. Although there are a few studies that assessed mental disorders, suicide or suicidal behaviors are not investigated yet. Hence, the present study for the first time investigated suicidal behaviors and its relationship with socio-demographics, flood effects and psychopathology. METHODS: A cross-sectional interview study was carried out between November and December 2019, after 4/5 months of the flood occurrence. Two completely affected villages from two districts residing in two parts of the country were randomly selected (whereas Manikganj district was less affected by the recent flood compared to Kurigram), and a total of 348 flood survivors were interviewed (45.53 ± 14.85 years). Questions related to basic socio-demographics, flood effects, psychological impacts, and suicidal behaviors were asked in the interviews. RESULTS: In the total sample, 57.5% of flood survivors reported having suicidal ideation, whereas 5.7% and 2.0% madea suicide plan and suicide attempt, respectively. Within two study sites, participants belonging to Kurigram reported significantly higher suicidal ideation compared to Manikganj (84.8% vs 33.2%, χ (2) = 94.475, p<0.001). Belonging to a lower-class family, having less education, and less earning members in the family, being affected severely by the flood, suffering from depression, anxiety, and PTSD, and experiencing financial threat, and economic hardship were suicidal behavior risk factors in the total sample. CONCLUSION: Considering the present findings (ie, suicidality commensurately increases with flood effects), a multi-sectoral policy and its effective implementation should be adopted for alleviating the flood-related psychological burdens.
BACKGROUND: Globally, post traumatic stress disorder (PTSD) is one of the most common psychiatric illnesses following a disaster. We aimed to evaluate the relationship between the socio-economic and flood exposure factors with PTSD, depression and anxiety among the flood-affected populations in Kerala, India. METHODS: A cross-sectional household survey was conducted from November 2019 to January 2020 in Kozhikode district of Kerala, India. Adults (≥ 18 years), who were permanent residents and had been directly exposed to the flood, were invited to take part in the study. Individuals with a history of mental health issues and those who had other stressful situations in the past were excluded. The survey questionnaire was based on three screening tools: (1) PTSD Checklist for DSM-5 (PCL-5); (2) patient health questionnaire (PHQ-9); and (3) generalized anxiety disorder (GAD-7). Data included sociodemographic factors and flood exposure variables. The primary outcome variable was psychiatric morbidity (PTSD, anxiety and depression). RESULTS: A total of 276 respondents (150 males/126 females) participated in the study. A significant correlation was observed between total score on PCL-5 and GAD-7 (r=0.339, p=0.001) and PHQ-9 (r=0.262, p=0.001). Females had significantly higher total PTSD symptom severity scores (8.24±5.88 vs. 6.07±5.22; p=0.001), severity of symptoms of intrusion (4.66±3.60 vs. 3.69±3.20; p=0.04), increased level of anxiety (2.54±1.94 vs. 1.79±1.53; p=0.001) and depression (3.02±2.26 vs. 2.04±1.67; p=0.001) compared to males. However, the gender difference for PTSD symptoms disappeared when controlling for age. CONCLUSION: The findings of this survey revealed that the vast majority of respondents (92 percent females and 87 percent males) still had subclinical psychiatric symptoms one year after the flood. Therefore, tailored psychological interventions are warranted to counter the long-lasting impact of flooding on the mental health of individuals.
INTRODUCTION: Disasters can have deep physical and psychological impact among survivors. An extraordinary southwest monsoon has unleashed floods and landslides in Kerala state in 2018. Adolescents are more vulnerable to psychological impairment after a disaster and trauma during initial stages of life can etch an indelible signature in the individual’s development and may lead to future disorders. OBJECTIVES: 1. To screen for PTSD and associated factors among adolescents 8 months post floods in selected schools in flood-affected areas of Alleppey district of Kerala 2. To compare the proportion of adolescents screened positive for PTSD in public and private schools. METHODOLOGY: A 3-month, Cross-sectional study was done among 670 adolescents in private and public schools using stratified sampling in Alleppey district. The study tool included a structured questionnaire that collected information on sociodemographics, flood-related variables, Trauma screening questionnaire and academic performance. RESULTS: The mean age of the participants was 16.03 ± 0.73 years with almost equal gender distribution. One-third of students reported flood-related damage to house/property, and a few lost their pets. Nearly 50% of the students reported that they still re-experience and get upsetting memories about flood events. The prevalence of probable PTSD noted to be 34.9%. We observed that 31% of students in public school screened positive for PTSD compared to 38.8% of private school students. (odds ratio = 1.409, CI 1.024-1.938). Male gender (Odds ratio = 1.503, CI 1.093-2.069), higher age (Odds ratio = 1.701, CI 1.120-2.585), damage during floods (Odds ratio = 2.566, CI 1.814-3.630), presence of morbidity (Odds ratio = 3.568, CI 1.888-6.743), camp stay (Odds ratio = 3.788, CI 2.364-6.067) and loss of pets (Odds ratio = 3.932, CI 2.019-7.657) were the factors significantly associated with PTSD. We noted a deterioration in academic performance in 45.9% of students who screened positive for PTSD. CONCLUSION AND RECOMMENDATIONS: High prevalence of stress disorder highlights the need for early identification and intervention for PTSD and including trained counsellors as a part of the disaster management team in future.
Rapid and unplanned urbanization has resulted in the settlement and expansion of marginalized communities in flood-prone areas. Consequently, the devastating impacts of urban flooding have increased recently, further augmented by the changing climatic patterns resulting in more frequent flooding. However, to effectively enhance resilience at the community level, it is essential first to understand its components and indicators. This study proposed and tested a methodology to assess community resilience against urban flooding – 57 indicators of resilience were identified, which were classified into six domains, namely social, economic, infrastructural, institutional, natural, and psychological. The data was collected through a questionnaire survey in three com-munities of Rawalpindi, Sialkot, and Muzaffargarh cities in the province of Punjab, Pakistan. The data of resilience indicators were standardized, and an index-based approach was used to assess the community resil-ience in the six domains. The relative importance of each domain was evaluated through input from field experts translated into weights through the analytic hierarchy process method. Thereafter, overall community resilience was constructed, and statistical methods were employed to compare resilience and its domains. A significant difference in resilience was observed among the selected communities. Recommendations based on relative urgency, complexity, and impact were devised to help institutions make informed decisions to improve com-munity resilience against floods.
In the Ganges-Brahmaputra-Meghna delta, covering most of Bangladesh, more than 165 million people live in low-lying coasts facing major extreme climatic events, such as cyclones. This article reviews the current scientific literature publications (2007-2020) in order to define vulnerability in the context of coastal Bangladesh facing cyclonic flooding. Based on this review, a new metric, called the socio-spatial vulnerability index (SSVI), is defined as function of both the probability of the cyclonic flood hazard and the sensitivity of delta inhabitants. The main result shows that the districts of Shariatpur, Chandpur and Barisal situated in the tidal floodplain of the Ganges-Brahmaputra-Meghna delta are in the fourth quartile, i.e., highest category, the most vulnerable areas. These districts are very densely populated (from 870 up to 1400 inhabitants per square kilometer) and exposed to inundation hazards with a large number of vulnerability factors. Finally, the delta’s mouth was identified as a very vulnerable area to cyclonic flooding as well.
Floods are a common natural hazard in Bangladesh, and climate change is expected to further increase flooding frequency, magnitude and extent. Pregnant women in flood contexts could face challenges in utilisation of maternal healthcare. The aim of this paper is to analyse associations between flood exposure and the use of maternal healthcare (antenatal care visits, birth assisted by skilled birth attendants, and giving birth in a health facility) in Bangladesh for pregnancies/births between 2004 and 2018. Bangladesh Demographic and Health Survey data from four surveys in the time period 2007-2018 and data on floods from the Emergency Events Database and the Geocoded Disasters Dataset are analysed using multilevel linear probability models. In line with previous results, we find clear bivariate associations between exposure to flooding and maternal healthcare use. These associations are largely confounded by socioeconomic and demographic variables. In general, exposure to flooding – whether measured as exposure to any floods or severe floods – does not affect maternal healthcare use, and we suggest that the lower usage of maternal healthcare in areas exposed to flooding rather relates to the characteristics of the flood-prone areas and their populations, which also relate to lower maternal healthcare use. However, we find negative associations in some supplementary analyses, which suggest that even if there is no effect of floods on average, specific floods may have negative effects on maternal healthcare use.
Purpose The quality and availability of sexual and reproductive health care are key determinants to reducing maternal mortalities and morbidities in disaster settings; yet, these services are often lacking in developing countries. Reducing maternal mortality and morbidity is currently the main targets of the UN’s Sustainable Development Goal (SDG) 3. The purpose of this study was to develop an intervention package called RHCC (Reproductive Health Kit 8; Capacity building; Community awareness), and to implement and evaluate it in three primary health-care (PHC) facilities in Belkuchi, Bangladesh, in order to improve the quality and availability of post-abortion care (PAC) during the 2017 floods. Design/methodology/approach This research used both quantitative and qualitative methods to develop, implement and assess the RHCC in three flood-prone PHC facilities in Belkuchi. Findings The RHCC was implemented during the floods of 2017. The findings pre- and post-intervention suggest it led to an increase in skilled management among health workers, an increase in the quality of care for clients and the availability of PAC at three PHC facilities during floods. Originality/value Due to its geographic location, Bangladesh is exposed to recurrent floods and cyclones. Evidence-based integrated intervention packages, such as the RHCC, can improve the quality and availability of reproductive health care during disasters at PHC level and, in doing so, can promote the UN’s agenda on “disaster resilient health system” to achieve the SDG 3, and the WHO’s campaign on universal health coverage.
OBJECTIVES: As climate change continues to increase the frequency and severity of flooding in Bangladesh and globally, it becomes increasingly critical to understand the pathways through which flooding influences health outcomes, particularly in lower-income and subsistence-based communities. We aim to assess economic pathways that link flooding to nutritional outcomes among Shodagor fishing families in Bangladesh. METHODS: We examine longitudinal economic data on kilograms of fish caught, the income earned from those fish, and household food expenditures (as a proxy for dietary intake) from before, during, and after severe flooding in August-September of 2017 to enumerate the impacts of flooding on Shodagor economics and nutrition. We also analyze seasonally collected anthropometric data to model the effects of flooding and household food expenditures on child growth rates and changes to adult body size. RESULTS: While Shodagor fishing income declined during the 2017 flooding, food expenditures simultaneously spiked with market inflation, and rice became the predominant expenditure only during and immediately following the flood. Our nutritional models show that children and adults lost more body mass in households that spent more money on rice during the flood. Shodagor children lost an average of 0.36 BMI-for-age z-scores and adults lost an average of 0.32 BMI units during the flooded 2017 rainy season, and these metrics continued to decline across subsequent seasons and did not recover by the end of the study period in 2019. CONCLUSIONS: These results show major flood-induced economic impacts that contributed to loss of child and adult body mass among Shodagor fishing families in Bangladesh. More frequent and severe flooding will exacerbate these nutritional insults, and more work is needed to effectively stabilize household nutrition throughout natural disasters and economic hardship.
We study the educational outcomes of the 1974-75 Bangladesh famine among early life survivors using the 1991 Bangladesh micro-census data. We find that famine adversely affected survivor children in areas that experienced higher rice prices relative to labour wages. However, children living in wealthy households in famine-stricken areas escaped the adverse effects and had similar educational outcomes as those with no famine exposure. We also find that, surprisingly, exposure to a double catastrophe (i.e., concurrent famine and flood) in early life had weaker effects on survivor children’s education than exposure to a single catastrophe. We show that disaster-alleviation mechanisms were more effective in districts affected by double disasters.
The Tista floodplain is one of the major food baskets of North Bengal and is sensitive to a multitude of issues regarding vulnerability. The riparian areas and the river island or charland of the lower Tista River basin in India, specifically from Sevoke to the Indo-Bangladesh border, generally suffer due to flood-prone, river course shifting, limited livelihood activities, low adaptive capacity, and poor accessibility. The present work is conducted to assess the livelihood vulnerability based on the livelihood vulnerability index (LVI) framework of the agriculture-dependent riparian villages and the charlands of the River Tista in the Jalpaiguri district. Total 337 households of five villages from the Mal and Maynaguri block at the left bank of the Tista River were selected to conduct the field survey. The livelihood vulnerability was assessed based on eight major components (viz., socio-demographic profile, health condition, livelihood strategies, food support, water support, climatic variability, flood hazards, and social safety) and 42 sub-components. The three contributing factors, i.e., adaptive capacity, sensitivity, and exposure, have been combined to calculate the livelihood vulnerability employing the LVI and LVI-IPCC methodologies. The outcome of the study exhibit that LVI scored highest in Premganj Majhiali (0.436), followed by Basusuba (0.403), Uttar Marichbari (0.349), Domohani (0.335), and Chat Rarpur village (0.328). According to the LVI-IPCC results, Basusuba has the most vulnerability (0.015), whereas Domohani has the least (0.007). In terms of flood hazard, variations were noticed based on increasing distance from the river. Lack of adaptive capacity prevailed in the villages with significant flooding events. Building awareness of the inhabitants will be an effective way to improve the adaptive capacity of the rural villagers. Therefore, giving priority to the policies depending on the natural environment of the active flood-prone region would make long-term sustainability.
INTRODUCTION: Extreme heat is a significant cause of morbidity and mortality, and the incidence of acute heat illness (AHI) will likely increase secondary to anthropogenic climate change. Prompt diagnosis and treatment of AHI are critical; however, relevant diagnostic and surveillance tools have received little attention. In this exploratory cross-sectional and diagnostic accuracy study, we evaluated three tools for use in the prehospital setting: 1) case definitions; 2) portable loggers to measure on-scene heat exposure; and 3) prevalence data for potential AHI risk factors. METHODS: We enrolled 480 patients who presented to emergency medical services with chief complaints consistent with AHI in Ahmedabad, India, from April-June 2016 in a cross-sectional study. We evaluated AHI case definition test characteristics in reference to trained prehospital provider impressions, compared on-scene heat index measured by portable loggers to weather station measurements, and identified AHI behavioral and environmental risk factors using logistic regression. RESULTS: The case definition for heat exhaustion was 23.8% (12.1-39.5%) sensitive and 93.6% (90.9-95.7%) specific. The positive and negative predictive values were 33.5% (20.8-49.0%) and 90.1% (88.5-91.5%), respectively. Mean scene heat index was 6.7°C higher than the mean station heat index (P < 0.001), and station data systematically underestimated heat exposure, particularly for AHI cases. Heat exhaustion cases were associated with on-scene heat index ≥ 49°C (odds ratio [OR] 2.66 [1.13-6.25], P = 0.025) and a history of recent exertion (OR 3.66 [1.30-10.29], P = 0.014), while on-scene air conditioning was protective (OR 0.29 [0.10-0.85], P = 0.024). CONCLUSION: Systematic collection of prehospital data including recent activity history and presence of air conditioning can facilitate early AHI detection, timely intervention, and surveillance. Scene temperature data can be reliably collected and improve heat exposure and AHI risk assessment. Such data may be important elements of surveillance, clinical practice, and climate change adaptation.
Extreme weather conditions, especially heatwave, are a threat to society, affecting livability, wellbeing, and social interactions. The present study aims to assess the monthly heat stress in the outdoor environment from 2010 to 2019 in Sonepat’s municipality, representing a hot semi-arid climate. The authors applied three heat stress indices, namely, Wet bulb globe temperature (WBGT), Physiological equivalent temperature (PET), and Universal thermal climate index (UTCI), to estimate the grade of heat stress. While calculations, the highest average WBGT was found in July (33.4 +/- 0.77 degrees C), demonstrating July in the “Extreme heat stress” category. The highest mean PET was found in June (42.47 +/- 2.34 degrees C), indicating June in the “Extreme heat stress” category. The highest mean UTCI was found in June (38.58 +/- 1.82 degrees C), demonstrating “Very strong heat stress.” The dry bulb temperature was found to be the most dominant parameter among meteorological parameters promoting extreme heat stress. It was concluded that extreme heat stress was observed in the Pre-monsoon hot weather season and summer monsoon season (especially in June), making the population vulnerable to mortality and morbidity. The findings could provide valuable information to people from various disciplines like Climate scientists, landscape designers, architects, and all relevant stakeholders to develop a heatwave action plan against adverse heat stress.(c) 2021 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of the scientific committee of the F-EIR Conference 2021 on Environment Concerns and its Remediation: Materials Science.
OBJECTIVES: Global warming and more intense heat wave periods impact health. Heat illness during heat waves has not been studied in the prehospital setting of a low- and middle-income country (LMIC). Early intervention in the community and in the prehospital setting can improve outcomes. Hence, this paper aims to describe the characteristics of heat illness patients utilizing the ambulance service in Telangana state, India with the aim of optimizing public prevention and first aid strategies and prehospital response to this growing problem. METHODS: This retrospective observational study reviewed patients presenting to Telangana’s prehospital emergency care system with heat illness symptoms during the heat wave period from March through June in 2018 and 2019. Descriptive analysis was done on the prehospital, dispatch, and environmental data looking at the patients’ characteristics and prehospital intervention. RESULTS: There were 295 cases in 2018 and 230 cases in 2019 from March-June. The overall incidence of calls with heat illness symptoms was 1.5 cases per 100,000 people. The Scheduled Tribes (ST) had the highest incidence of 4.5 per 100,000 people. Over 96% were from the white income group (below poverty line) while two percent were from the pink income group (above poverty line). From geospatial mapping of the cases, the highest incidence of calls came from the rural, tribal areas. However, the time to response in rural areas was longer than that in an urban area. Males with an average age of 47 were more likely to be affected. The three most common symptoms recorded by the first responders were vomiting (44.4%), general weakness (28.7%), and diarrhea (15.9%). The three most common medical interventions on scene were oxygen therapy (35.1%), oral rehydration salt (ORS) solution administration (26.9%), and intravenous fluid administration (27.0%), with cold sponging infrequently mentioned. CONCLUSION: This descriptive study provides a snapshot of the regions and groups of people most affected by heat illness during heat waves and the heterogeneous symptom presentation and challenges with management in the prehospital setting. These data may aid planning of prehospital resources and preparation of community first responders during heat wave periods.
This study investigated children’s perceptions and adaptive behaviors related to indoor thermal conditions of classrooms in primary schools with no air-conditioning systems during both summer and winter in Dehradun City, Uttarakhand, India. Responses were collected from 5297 school children aged 6-13 years. During the measurement periods, 100% and 94% of the samples were obtained under conditions outside an 80% thermally acceptable comfort range in winter and summer, respectively. The analysis using receiver operating characteristics suggested that the students had the least sensitivity to the temperature variation for all scales of the thermal sensation vote (TSV). Approximately 95.1% of students were “very satisfied”, “satisfied”, or “slightly satisfied” with the thermal conditions under the condition of “extreme caution” or “danger” of heat risk. In contrast, adaptive thermal behaviors, such as adjusting clothing insulation ensembles, opening or closing classroom windows and doors, and utilizing ceiling fans, were found to be the most affordable options for optimizing indoor thermal comfort. Children’s reports of thermal sensations and thermal satisfaction did not correspond to the actual physical environment. This draws attention to the adequacy of applying widely used methods of TSV-based identification of the thermal comfort range in classrooms for children, especially in hot environments. The findings of this study are expected to serve as an evidence-based reference for local governments and authorities to take appropriate measures to mitigate heat risks for schoolchildren in the future.
The climate of a place has a decisive role in human adaptations. Man’s health, adaptability, behavioural patterns, food, shelter, and clothing are mainly influenced by the temperatures of the area. Hence, a study is undertaken to analyse the spatial distribution, frequency, and trend in the heat waves over the country. The statistical characteristics of heat waves over India are addressed in this study. Gridded daily temperature data sets for the period 1951-2019 were used to compute the arithmetic mean (AM), standard deviation (SD), coefficient of variation (CV), and trends of monthly maximum temperature. The number of heat wave days were identified using the criteria given by India Meteorological Department (IMD) i.e., a heat wave is recognized when the daily normal maximum temperature of a station is less than or equal to (greater than) 40 degrees C than it will be considered as a heat wave if the daily maximum temperature exceeds the daily normal maximum temperature by 5 degrees C (4 degrees C). The analysis was confined to the two summer months of April and May only. The spatial distribution of the AM shows higher values during May, and the core hot region with temperatures exceeding 40 degrees C lies over central India extending towards the northwest. The SD distribution shows higher values over the northeast of central India decreasing towards the southwest. The CV distribution shows higher values over the north decreasing toward the south. Higher numbers of heat waves are observed during May and the number is higher over Andhra Pradesh and south Telangana regions of southeast India. This study concludes that a moderate hot region experiences a higher number of heat wave days over India.
In the present research work, the authors investigated the seasonal thermal environment and thermal perception of university subjects in a naturally ventilated workshop building under the composite climate of India. Total 1460 subjective responses were collected during the field study in the year, 2019. Standard Effective Temperature (SET*) has been used as a rationally derived thermal comfort index to study the combined effects of air temperature, relative humidity and airspeed on perceived thermal sensation and occupant’s preference under high metabolic rates. Probit analysis showed more than 80% of subjects were voting comfortable (+/- 1 Thermal sensation votes) when SET* ranged between 25 degrees C-33 degrees C. Seasonal mean comfort temperature varied more than 4.8 degrees C, while, preferred temperature was noted about 3 degrees C lower than their mean Griffiths comfort temperature. The adaptive relation developed from the collected database under high metabolic activities was compared with existing national and international comfort standards. The slope coefficient for adaptive relation was observed close to the adaptive model of ASHRAE Standard 55-2017 but lower than the National Building Code of India, 2016. Further, adaptive use of fans and windows were analyzed using logistic regression models and predicted about 80% of fans and windows were in operation at 30 degrees C. To confirm the adaptive mechanism, the interrelation of other contextual factors like gender, clothing insulation, airspeed, metabolic activities, etc. to thermal comfort expectations of subjects were also studied.
BACKGROUND: Studies have documented a significant association between temperature and all-cause mortality for various cities but such data are unavailable for Hyderabad City. OBJECTIVE: The objective of this work was to assess the association between the extreme heat and all-cause mortality for summer months (March to June) from 2006 to 2015 for Hyderabad city population. METHODS: We obtained the data on temperature and all-cause mortality for at least ten years for summer months. Descriptive and Bivariate analysis were conducted. Pearson correlation coefficient was used to study the relationship between heat and all-cause mortality for lag time effect. RESULTS: A total of 122,117 deaths for 1,220 summer days (2006 to 2015) were analyzed with mean daily all-cause mortality was 100.1±21.5. There is an increase of 16% and 17% per day mean all-cause mortality at the maximum temperature of less than or equal to 40 degrees C and for extreme danger days (Heat Index greater than 54 degrees C) respectively. The mean daily all-cause mortality shows a significant association with maximum temperature (P < 0.001) and Heat Index from caution to extreme danger risk days (P<0.0183). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at peak on same day of the maximum temperature (r = 0.273 at p<0.01). CONCLUSION: The study concludes that the impact of ambient heat in the rise of all-cause mortality is clearly evident (16% mean deaths/day). There was no lag effect from the effect of extreme heat on all-cause mortality as the peak period was the same as the maximum temperature. Hence heat action plans are needed. However, extreme heat-related mortality merits further analysis.
The present paper is an attempt to study the heat waves associated fatalities over space and time in India. For this, ‘Disastrous Weather Events’ reports statistics have been used for the period 1978-2014. The analysis has shown that a total of 660 heat wave events have caused 12,273 fatalities (about 332 fatalities every year). Only five states namely, Andhra Pradesh (42%), Rajasthan (17%), Odisha (10%), Uttar Pradesh (7%) and Bihar (7%) have accounted more than 80% of the heat wave fatalities, although nine states namely, Arunachal Pradesh, Nagaland, Manipur, Meghalaya, Tripura, Sikkim, Mizoram, Uttarakhand and Goa have never reported heat wave events and fatalities during 1978-2014. Interestingly, each event has resulted about 104 fatalities in Andhra Pradesh state. Further, fatality and density rates have been witnessed to the tune of 0.35 and 3.81 respectively. Temporally, heat wave events have displayed large differences with a significant increasing trend (P < 0.01), whereas no trend could be noticed in fatalities. Majority of events have been witnessed in May and June months. It has been observed that men have been more harshly affected compared to women and children. Finally, it is believed that this study may provide new insight towards making better disaster management guidelines for minimizing the shocks of harsh temperature.
Heat waves are often termed as the silent killer and have become even more important as recent studies suggest that the heat wave have become second most devastating extreme weather events in terms of human deaths and losses. It is also been largely realised by scientific community that it is not just the high temperatures which are responsible for the gruesome effect of heat waves but several other meteorological parameters play a vital role in aggravating the impact and causing much more damages. In view of the above the attention of scientific community, weather forecasters as well as disaster managers has shifted to also take into account the different meteorological parameters like maximum and minimum temperatures, relative humidity, wind speed, duration/spell of heat waves and its intensity which are aggravating the impact of heat stress. In this background, this study is undertaken as an attempt to quantify the effect of different meteorological parameters on heat wave on different regions of India for different summer months (March, April, May and June). In this study the impact of individual meteorological parameter as well their cumulative effect is studied based on data of 30 years (1981-2010) for 300 stations. The effect of different meteorological parameters is identified for different months for different regions of the country. Also the cumulative scores are calculated for different regions considering different meteorological parameters, as a first initiative to perform heat hazard analysis and zonation over the entire country. This could serve as initial step for planning mitigation and adaptation strategies throughout the country. These scores as thresholds for different regions may be also useful for operational forecaster’s for early impact based warning services as well as for the disaster managers, for taking effective and timely actions.
The heatwave is a disastrous hazard having significant impacts on health and society. This study analyses the heatwave hazards and risk for India’s current and future scenarios using socioeconomic vulnerability and temperature datasets during the summer (April-June) season. The Census of India (CoI) 2011 datasets were considered to assess current vulnerability and projected from the SocioEconomic Data And Application Center (SEDAC) population at Shared Socioeconomic Pathway (SSP) 4 for future vulnerability. Whereas IMD temperature data used for hazard assessment for the present scenario (1958-2005) while projected temperature data from regional earth system model REMO-OASIS-MPIOM (ROM) were used for the future (2006-2099) scenario. The study exhibited the most hazardous, vulnerable, and risk-prone regions identified as the south-eastern coast and Indo-Gangetic plains and some populous districts with metropolitan regions (Mumbai, Delhi, and Kolkata) under the current scenario. The coupled model ROM has efficiently captured the critical districts with higher and lower risk, showing its future projection capability. The study highlighted that the heatwave hazard-risk would significantly worsen in future scenarios in all districts under enhanced global warming and largely affecting the districts in the eastern and middle Indo-Gangetic plains and Malabar region. The present study will provide sufficient insights into designing mitigation strategies and future adaptive planning for the heatwave risk, which is one of the targets under Sustainable Development Goal 13 (Goal 13: Climate Action).
A considerable association between temperature and all-cause mortality has been documented in various studies. Further insights can be obtained from studying the impact of temperature and heat index (HI) for Jaipur city’s all-cause mortality. The objective of this work was to assess the association between the extreme heat (daily maximum temperature, daily minimum temperature, daily mean temperature, relative humidity and HI) and all-cause mortality for summer months (March to June) from 2006 to 2015 for urban population of Jaipur. For summer months, we collected the data on various temperature and all-cause mortality parameters for at least 10 years. The student’s t-test and ANOVA were used to analyse variations in mean temperature, maximum temperature and HI. The Pearson correlation coefficient was used to study the relationship between ambient heat and lag time effect all-cause mortality. A total of 75,571 deaths (all-cause mortality) for 1,203 summer days (2006-2015) were analysed in relation to temperature and relative humidity. The mean daily all-cause mortality has been estimated at 62.8 +/- 15.2 for the study period. There is a significant increase of 39% per day all-cause mortality at the maximum temperature of 45 degrees C and above. However only 10% rise per day all-cause mortality for extreme danger days (HI > 54 degrees C). The mean daily all-cause mortality shows a significant association with daily maximum temperature (F = 34.6, P < .0001) and HI (discomfort index) from caution to extreme danger risk days (F = 5.0, P < .0019). The lag effect of extreme heat on all-cause mortality for the study period (2006 to 2015) was at a peak period on the same day of the maximum temperature (r = 0.245 at P < .01) but continues up to four days. The study concludes that the effect of ambient heat on all-cause mortality increase is clearly evident (rise of 39% deaths/day). Accordingly, focus should be put on developing adaptation measures against ambient heat. This analysis may satisfy policy makers' needs. Extreme heat-related mortality needs further study to reduce adverse effects on health among Jaipur's urban population.
Heat waves are quite frequent over the Indian subcontinent during the summer season (April-July) owing to an increase in anthropogenic activities and global temperatures. These extreme heat conditions induce a high level of outdoor discomfort, adverse health effects and mortality, depending on the degree of thermal stress. The present study investigates the climatology of thermal stress and its trends over northwest (NW) India during the summer. The Universal Thermal Climate Index (UTCI) derived from Human thErmAl comforT (ERAS-HEAT) dataset was used for the period of 1981-2019. The monthly and seasonal climatological mean of UTCI exhibits moderate to strong thermal stress over NW India (ranges from 27 to 34.5 degrees C) than in the rest of the country (below 25.5 degrees C), with a peak during the months of June (34.5 degrees C) and July (33.5 degrees C) months. The seasonal mean UTCI shows significant rising trends (0.9 degrees C per 39 years) over NW India and entire India (0.6 degrees C per 39 years), indicating that the thermal discomfort amplifies at a faster pace compared to the rest of India. Similar rising trends are also noticed in the major cities of the study region. Surface temperature and relative humidity also exhibit a substantial increasing trend, which resulted in the intensification of thermal discomfort over NW India. Furthermore, the number of thermal discomfort days over NW India exhibits an increasing trend during 1981-2019. The composite analysis of UTCI greater than 32 degrees C (referred to as strong heat stress) depicts the highest thermal discomfort conditions in NW India. During summer, strong soil temperatures and high sensible heat fluxes over the study region may enhance the warming at the surface during UTCI (> 32 degrees C) days as it depends on surface radiative fluxes through the mean radiant temperature. In addition to high temperatures, a substantial amount of moisture transported by strong westerly wind from the Arabian Sea towards the NW India during strong thermal stress days seems to have contributed to high thermal stress conditions in the region.
BACKGROUND: Record-breaking temperatures have occurred more frequently worldwide under the trend of climate change. It has increased the number of people at heat related medical conditions resulting in both mortality and morbidity from heat stress. This study aimed to assess factors associated with vulnerability to heat stress, its health effects among people of Nepalgunj Sub-metropolitan, and identify various coping strategies adopted. METHODS: Cross-sectional analytical study was conducted among 366 research participants selected through multi-stage random sampling technique in Nepalgunj Sub-metropolitan. Heat Index was assessed using secondary analysis of meteorological data of Nepalgunj (Airport) station. Chi-square test was done to analyze the primary data. RESULTS: Out of 366 participants, 224 (61.2%) participants had heat related symptoms in the past 6 months (April to September) from the date of the interview. Sex, education, income, roof construction, Cross-ventilation, working hour per day, presence of chronic disease, and medications use had a significant association with heat related symptoms among the participants (p<0.05) The most common coping strategies adopted to manage heat stress were the use of cooling methods, wearing light clothing, and bathing by cold water. The average monthly heat index was highest in August (42 °C) and lowest in April (29°C). CONCLUSIONS: The majority of the participants had heat related symptoms in the study area. In order to mitigate the heat stress in the urban town like Nepalgunj, measures such as tree plantation, reducing vehicle smoke emissions, and developing proper housing ventilation can be applied.
As a result of global climate change, the frequency and intensity of heat waves have increased significantly. According to the World Meteorological Organization (WMO), extreme temperatures in southwestern Pakistan have exceeded 54 degrees C in successive years. The identification and assessment of heat-health vulnerability (HHV) are important for controlling heat-related diseases and mortality. At present, heat waves have many definitions. To better describe the heat wave mortality risk, we redefine the heat wave by regarding the most frequent temperature (MFT) as the minimum temperature threshold for HHV for the first time. In addition, different indicators that serve as relevant evaluation factors of exposure, sensitivity and adaptability are selected to conduct a kilometre-level HHV assessment. The hesitant analytic hierarchy process (H-AHP) method is used to evaluate each index weight. Finally, we incorporate the weights into the data layers to establish the final HHV assessment model. The vulnerability in the study area is divided into five levels, high, middle-high, medium, middle-low and low, with proportions of 3.06%, 46.55%, 41.85%, 8.53% and 0%, respectively. Health facilities and urbanization were found to provide advantages for vulnerability reduction. Our study improved the resolution to describe the spatial heterogeneity of HHV, which provided a reference for more detailed model construction. It can help local government formulate more targeted control measures to reduce morbidity and mortality during heat waves.
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.
BACKGROUND: Extreme heat exposure is a growing public health concern. In this trial, we tested the impact of a community health worker (CHW) led heat education programme on all-cause mortality, unplanned hospital visits and changes in knowledge and practices in Karachi, Pakistan. METHODS: The Heat Emergency Awareness and Treatment trial was a community-based, open-label, two-group, unblinded cluster-randomised controlled trial that implemented a CHW-led educational intervention between March and May 2018 in Karachi, Pakistan. We randomly assigned (1:1) 16 clusters, each with ~185 households or 1000 population, to the intervention or usual care (control group). We collected data on all-cause mortality, unplanned hospital visits, evidence of heat illness through surveillance and a knowledge and practice survey during the summer months of 2017 (preintervention) and 2018 (postintervention). FINDINGS: We recruited 18 554 participants from 2991 households (9877 individuals (1593 households) in the control group and 8668 individuals (1398 households) in the intervention group). After controlling for temporal trends, there was a 38% (adjusted OR 0.62, 95% CI 0.49 to 0.77) reduction in hospital visits for any cause in the intervention group compared with the control group. In addition, there was an improvement in many areas of knowledge and practices, but there was no significant difference in all-cause mortality. INTERPRETATION: A CHW-led community intervention was associated with decreased unscheduled hospital visits, improved heat literacy and practices but did not impact all-cause mortality. CHWs could play an essential role in preparing communities for extreme heat events. TRIAL REGISTRATION NUMBER: NCT03513315.
Heat waves are the second leading cause of weather-related morbidity and mortality affecting millions of individuals globally, every year. The aim of this study was to understand the perceptions and practices of community residents and healthcare professionals with respect to identification and treatment of heat emergencies. A qualitative study was conducted using focus group discussions and in-depth interviews, with the residents of an urban squatter settlement, community health workers, and physicians and nurses working in the emergency departments of three local hospitals in Karachi. Data was analyzed using content analysis. The themes that emerged were (1) perceptions of the community on heat emergencies; (2) recognition and early treatment at home; (3) access and quality of care in the hospital; (4) recognition and treatment at the health facility; (5) facility level plan; (6) training. Community members were able to recognize dehydration as a heat emergency. Males, elderly, and school-going children were considered at high risk for heat emergencies. The timely treatment of heat emergencies was widely linked with availability of financial resources. Limited availability of water, electricity, and open public spaces were identified as risk factors for heat emergencies. Home based remedies were reported as the preferred practice for treatment by community members. Both community members and healthcare professionals were cognizant of recognizing heat related emergencies.
The objective of this paper is to model and study the impact of high temperature on mortality in Pakistan. For this purpose, we have used mortality and climate data consisting of maximum temperature, variation in monthly temperature, average rainfall, humidity, dewpoint, as well as average air pressure in the country over the period from 2000 to 2019. We have used the Generalized Linear Model with Quasi-Poisson link function to model the number of deaths in the country and to assess the impact of maximum temperature on mortality. We have found that the maximum temperature in the country has a significant impact on mortality. The number of deaths in Pakistan increases as the maximum temperature increases. We found that, as the maximum temperature increase beyond 30 degrees C, mortality increases significantly. Our results indicate that mortality increases by 27% when the maximum temperature in the country increases from medium category to a very high level. Similarly, the number of deaths in the country increases by 11% when the temperature increases from medium temperature to high level. Furthermore, our study found that when the maximum temperature in the country decreases from a medium level to a low level, the number of deaths in the country decreases by 23%. This study does not consider the impact of other factors on mortality, such as age, medical conditions, gender, geographical location, as well as variability of temperature across the country.
Internally displaced people (IDP) due to conflict and violence were estimated as 41.3 million in 55 countries as the end of the year 2019, the highest figure ever recorded. Sri Lanka has not yet prioritized the health and wellbeing of households in building designing, with the emerging heat island effect making the lives more desperate for IDP. This study focused on the effect of energy poverty on occupant comfort in determining the quality of life of people and adaptive behaviors to manage heat strain in overheated interiors of rehabilitated residences in Jaffna, Sri Lanka. Field investigations consisted of personal monitoring, questionnaire surveying and physical measurements in four clusters of rehabilitation residence programmes in four regions. The study found that IDP were suffering from hidden energy poverty, with mean electricity consumption of 52 kWh per household per month. Residents have marginal (29%) access to clean fuels for cooking and accountable for an abnormal particulate matter count of 360 951 particles per cubic centimeter. Findings explicitly revealed the presence of overheated spaces with mean thermal preference of-0.6 conveying the need of cooler indoor environment. People tend to exhibit behavioral adjustments to cope up with prevailing extreme temperatures. Severity of heat stress informed by modified wet bulb globe temperature (WBGT) reporting 90% (28-31 degrees C) of households facing higher risk of heat strain while remaining 10% (>31 degrees C) are in hazardous situation. Predicted mean vote (PMV) was 1.29 explains warm sensation with predicted percentage of dissatisfied (PPD) 44.1% not complying to ASHRAE 55 standards. This detrimental combination of fuel poverty, lack of thermal comfort, and unacceptable indoor air quality has been a significant factor for 62% of the residences reporting at least one type of illness and being more prone to cardiovascular and respiratory disorders (37%). Thus, the study evidenced the presence of energy poverty and overheated interiors in the IDP’s residences in hot tropics of Sri Lanka. (c) 2021 Elsevier B.V. All rights reserved.
Extreme heat is an increasing climate risk due to climate change and the urban heat island (UHI) effect and can jeopardize points of dispensing (PODs) for COVID-19 vaccination distribution and broader public health emergency preparedness (PHEP) response operations. These PODs were often located on large parking lot sites with high heat severity and did not take heat mitigation or management strategies into account for unacclimated workers and volunteers. To investigate the personal heat exposure of workers, volunteers, and clients at three PODs in Tucson, Arizona, we collected ambient air temperatures, wet bulb globe temperatures (WBGT), surface temperatures, and thermal images. We also made qualitative observations and compared data against daily meteorological records. Ambient air temperatures at all three PODs exceeded the meteorological recorded high. WBGT on average were 8°F (4.4 °C) higher in full sun locations than shaded locations such as tents. Evaporative cooling decreased ambient air temperatures by 2°F (1.2 °C) when placed one per tent, but decreased ambient air temperatures by 7°F (3.9 °C) when placed en masse in a larger tent. Vehicle surface temperatures exceeded recommended safe limits of 140°F (60 °C) at all three sites, with a maximum temperature recorded at 170.9°F (77.2 °C). Public health professionals should consider heat resilience, including heat mitigation and management measures, in POD and PHEP response operations to reduce exposure. This includes considering the UHI effect in the siting of PODs, applying heat mitigation strategies in the design of PODs such as the adaptive use of solar panels for shading, and improving heat safety guidance for workers and volunteers.
The thermal adaptation of buildings and their residents is important in extreme cold climates for energy saving building design. A thermal measurement and a thermal comfort survey were conducted in traditional houses during the winter in the extreme cold climate of the Himalayan region of Nepal. Measurements were taken in 9 houses over 7 days to assess the thermal environment. Thermal comfort surveys were conducted over 4 days, and a total of 1,584 thermal responses were gathered from 36 residents. Passive heating effects were found in houses with thick brick walls and mud roofs. Residents of these houses were highly satisfied with the thermal environment, with 10.7 degrees C being the mean comfort temperature, which was related to the indoor temperature of the investigated indoor spaces. It can be concluded from these findings that people are well adapted to the thermal environment of traditional vernacular houses, as a result of which the comfort temperature is lower than the thermal comfort standards. Consequently, a significant amount of energy can be saved by passive building design and lowering the indoor temperature setting for heating. (C) 2020 The Author. Published by Elsevier B.V.
We provide the first estimates of the impacts of prenatal exposure to extreme temperatures on infant health at birth using the latest national birth data from 2009 to 2018 from all U.S. states. We consistently find that an additional day with mean temperature greater than 80°F or less than 10°F increases preterm births and low birthweight. Strikingly, the adverse effects are borne disproportionately by Black and Hispanic mothers, suggesting that the projected increase in extreme temperatures may further exacerbate the existing birth health disparities across different race/ethnicity groups. We also contribute by investigating the impact of deviations from the normal weather pattern, to identify the extreme weather events after accounting for the adaptation response. We find that prenatal exposure to extreme heat two standard deviations above county’s historic average induces preterm births and NICU admissions, particularly for mothers whose pregnancies overlap with summer months. These results are timely and policy relevant, considering the recent weather trends with rising temperatures and frequent extreme weather events.
This study is an assessment of the effects of outdoor air pollution and extreme weather events on the health of outdoor workers in Delhi, including auto rickshaw drivers, street vendors, and sweepers. To carry it out, a cross-sectional and perception-based epidemiological research design was used, and the primary tool used for data collection was a questionnaire. Two hundred twenty-eight people participated in the survey, and a pulmonary function test (PFT) was performed on 63 participants. Most of the respondents from different occupational groups complained about headaches/giddiness, nausea, and muscular cramps during extreme heat events due to the physically demanding nature of their jobs in the outdoor environment. Furthermore, autorickshaw drivers reported the highest prevalence of ophthalmic symptoms, such as eye redness (44%) and eye irritation (36%). In comparison, vendors reported a higher prevalence of headaches (43%) and eye redness (40%) due to increased exposure to vehicular emissions. Among sweepers, musculoskeletal problems like joint pain (40%), backache (38%), and shoulder pain (35%) were most prevalent due to occupation-related ergonomic factors. In addition, the majority of autorickshaw drivers (47%), vendors (47%), and sweepers (48%) considered that air quality had a severe impact on their health. PFT results showed that most respondents had restricted lung function. Binary logistic regression analysis showed that lung function impairment had a significant association with smoking (p = 0.023) and age (0.019). The odds ratio for smoking, which was around 4, indicated that respondents who smoked had a nearly four times greater risk of developing lung impairment. The study also highlighted the need for using personal protective equipment and developing guidelines to reduce their exposure level.
BACKGROUND: Exposure to high and low ambient temperatures is associated with morbidity and mortality across the globe. Most of these studies assessing the effects of non-optimum temperatures on health and have been conducted in the developed world, whereas in India, the limited evidence on ambient temperature and health risks and has focused mostly on the effects of heat waves. Here we quantify short term association between all temperatures and mortality in urban Pune, India. METHODS: We applied a time series regression model to derive temperature-mortality associations based on daily mean temperature and all-cause mortality records of Pune city from year January 2004 to December 2012. We estimated high and low temperature-mortality relationships by using standard time series quasi-Poisson regression in conjunction with a distributed lag non-linear model (DLNM). We calculated temperature attributable mortality fractions for total heat and total cold. FINDINGS: The analysis provides estimates of the total mortality burden attributable to ambient temperature. Overall, 6∙5% [95%CI 1.76-11∙43] of deaths registered in the observational period were attributed to non-optimal temperatures, cold effect was greater 5.72% [95%CI 0∙70-10∙06] than heat 0∙84% [0∙35-1∙34]. The gender stratified analysis revealed that the highest burden among men both for heat and cold. CONCLUSION: Non-optimal temperatures are associated with a substantial mortality burden. Our findings could benefit national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately due to climate change.
In the Indian subcontinent, the annual average extreme weather events (EWEs) are reported to be increasing during the last few decades. The impact of increased EWEs on mortality has become a key issue in terms of minimizing it, even with the increasing population. In the present study, based on 50 years’ data (1970-2019) of India Meteorological Department, mortality rates of different EWEs viz., floods, tropical cyclones, heat waves, cold waves, lightning, etc. were analysed, both at the national and state level. The analysis was done based on different periods, i.e. annual, decadal and twenty-year slice periods. Various statistical analyses were carried out. Out of these EWEs, floods accounted for maximum mortality of 46.1%, followed by tropical cyclones with 28.6% mortality. Over the decades, despite a significant rise in EWEs (except for tropical cyclones), there has been a decrease in the mortality rate (mortalities per year per million population). The number of mortalities per event had a significant negative trend for heatwaves and floods, during the last 50 years. The total EWEs had a mortality rate of 3.86 during 1980-1999 and it reduced to 2.14 during 2000-2019. The mortality rate of tropical cyclones reduced by 94% in the past 20 years, whereas for heatwaves and lightning it increased by 62.2% and 52.8%, respectively. However, the change in mortality rate was not found to be statistically significant due to high year to year variability in mortality associated with floods, lightning, and tropical cyclones in the last two decades as compared to earlier decades. In India, among the major states, Odisha, Andhra Pradesh, Assam, Bihar, Kerala, and Maharashtra were found to be having maximum mortality rates due to EWEs in the last two decades and thus there is a need to consider these states with priority for developing disaster management action plans.
The Intergovernmental Panel on Climate Change (IPCC) report highlights the projected increase in heat wave (HW) frequency, intensity, and duration. Globally, HW events have caused massive deaths in the past. India has also experienced severe HWs and thousands have reportedly died during the past decade. The study uses the Local Climate Zone (LCZ) classification developed by Stewart and Oke (2012) for evaluating heat stress at the city level during the summer period. Stationery surveys were conducted to collect micro-meteorological data in different LCZs. The study analyses the unique behaviour of mapped LCZs in Nagpur, a tropical landlocked Indian city using widely adopted heat indices (heat index and humidex). It investigates two kinds of probabilities, the distribution of heat stress levels in a particular LCZ and how vulnerable are various LCZs to a given heat stress level. It adopts a statistical approach fitting a predictive logit model to estimate the probability of heat stress in various LCZs. The results show that temperature regimes differ significantly across the LCZs. Secondly, heat stress varies greatly depending upon the LCZs. The mapping scheme and the corresponding heat stress provides indispensable information for targeted heat response planning and heat stress mitigation strategies in heat-prone areas.
The unplanned and uncontrolled urbanization of Indian cities has put them under different ecological and environmental threats. Urban heat island (UHI) is one such critical ecological hazard, whereby an urban area is experiencing higher land surface temperature (LST) as compared to the surrounding rural area. In the present study, the relationship of LST and surface urban heat island (SUHI) with the degree of impervious surface (IS) and green spaces (GS) in four rapidly growing Indian cities is presented. This study utilizes different geospatial techniques, including urban-rural gradient analysis, surface urban heat island estimation using Landsat OLI/TIRS data. The results signify a strong negative correlation of LST with the IS for Ahmedabad, Jodhpur, and Nagpur, while a positive correlation is seen over Guwahati. The negative correlation is the manifestation of the urban cool island, pertaining to higher LST over rural areas. On the other hand, Guwahati is surrounded by green vegetation, which provides natural cooling and thus lowers the LST, resulting in positive SUHI. The density of GS is found to be a significant contributor of SUHI in Guwahati city, whereas in the other three cities, its impact is insignificant due to its presence in very less amount in rural surroundings.
In a rapidly warming world, sustainable cooling is directly related to the protection of fresh and nutritious food, medicines, and the population from extreme heat for work conditions, the economic productivity of the working population, and income generation. This study aimed to understand how rural communities are meeting their nutrition, livelihood, health, living space, and mobility requirements regarding the role of cooling. We selected three villages as case studies in Maharashtra, India and conducted household surveys, in-depth interviews of key informants, focus group discussions (FGDs), and social mapping building typology study. The objective was to assess the rural community cooling to propose a community cooling hub (CCH) framework that could be economically, environmentally, and socially sustainable for the three villages. Our study showed that agriculture, dairy, buildings (domestic and commercial), and healthcare require cooling intervention in the studied communities. Based on the needs assessment for cooling, we proposed a CCH framework to provide cooling solutions in an integrated system for rural contexts.
Extreme heat and heat waves have been established as disasters which can lead to a great loss of life. Several studies over the years, both within and outside of India, have shown how extreme heat events lead to an overall increase in mortality. However, the impact of extreme heat, similar to other disasters, depends upon the vulnerability of the population. This study aims to assess the extreme heat vulnerability of the population of four cities with different characteristics across India. This cross-sectional study included 500 households from each city across the urban localities (both slum and non-slum) of Ongole in Andhra Pradesh, Karimnagar in Telangana, Kolkata in West Bengal and Angul in Odisha. Twenty-one indicators were used to construct a household vulnerability index to understand the vulnerability of the cities. The results have shown that the majority of the households fell under moderate to high vulnerability level across all the cities. Angul and Kolkata were found to be more highly vulnerable as compared to Ongole and Karimnagar. Further analysis also revealed that household vulnerability is more significantly related to adaptive capacity than sensitivity and exposure. Heat Vulnerability Index can help in identifying the vulnerable population and scaling up adaptive practices.
Climate change and rapid urbanization currently pose major challenges for equitable development in megacities of the Global South, such as Delhi, India. This study considers how urban social inequities are distributed in terms of burdens and benefits by quantifying exposure through an urban heat risk index (UHRI), and proximity to greenspace through the normalized difference vegetation index (NDVI), at the ward level in Delhi. Landsat derived remote sensing imagery for May and September 2011 is used in a sensitivity analysis of varying seasonal exposure. Multivariable models based on generalized estimating equations (GEEs) reveal significant statistical associations (p < 0.05) between UHRI/NDVI and several indicators of social vulnerability. For example, the proportions of children (β = 0.922, p = 0.024) and agricultural workers (β = 0.394, p = 0.016) are positively associated with the May UHRI, while the proportions of households with assets (β = -1.978, p = 0.017) and households with electricity (β = -0.605, p = 0.010) are negatively associated with the May UHRI. In contrast, the proportions of children (β = 0.001, p = 0.633) and agricultural workers (β = 0.002, p = 0.356) are not significantly associated with the May NDVI, while the proportions of households with assets (β = 0.013, p = 0.010) and those with electricity (β = 0.008, p = 0.006) are positively associated with the May NDVI. Our findings emphasize the need for future research and policies to consider how socially vulnerable groups are inequitably exposed to the impact of climate change-related urban heat without the mitigating effects of greenspace.
The combined effects of global warming, urbanization, and demographic change influence climate risk for urban populations, particularly in metropolitan areas with developing economies. To inform climate change adaptation and spatial planning, it is important to study urban climatic hazards and populations at risk in relation to urban growth trends and development patterns. However, this relationship has not been adequately investigated in studies dedicated to climate vulnerability. This study identifies the typologies of development patterns within Lahore, Pakistan, investigates the heat vulnerability of residents at a neighborhood scale, and establishes a relationship between both of these factors. We identified urban clusters with diverse development patterns. Fourteen context- and site-specific indicators were selected to construct a human heat vulnerability index. Weighted sum, cluster analysis, and ANOVA test of variance were conducted to analyze the data. Our results demonstrate that development patterns significantly influence human vulnerability to heat stress, e.g., vulnerability is higher in older cities and undeveloped neighborhoods with less diverse land uses. These findings are essential for informing policy-makers, decision-makers and spatial planners about proactive adaptation planning in dynamic urban environments.
Heat waves are expected to intensify around the globe in the future, with a potential increase in heat stress and heat-induced mortality in the absence of adaptation measures. India has high current exposure to heat waves, and with limited adaptive capacity, impacts of increased heat waves might be quite severe. This paper presents a comparative analysis of urban heat stress/heatwaves by combining temperature and vapour pressure through two heat stress indices, i.e., Wet Bulb Globe Temperature (WBGT) and humidex index. For the years 1970-2000 (historical) and 2041-2060 (future), these two indicators were estimated in Jaipur. Another goal of this research is to better understand Jaipur land use changes and urban growth. For the land use study, Landsat 5 TM and Landsat 8 OLI satellite data from the years 1993, 2010, and 2015 were examined. During the research period, urban settlement increased and the majority of open land is converted to urban settlements. In the coming term, all months except three, namely July to September, have seen an increase in the WBGT index values; however, these months are classified as dangerous. Humidex’s historical value has been 21.4, but in RCP4.5 and RCP8.5 scenarios, it will rise to 25.5 and 27.3, respectively, and slip into the danger and extreme danger categories. The NDVI and SAVI indices are also used to assess the city’s condition during various periods of heat stress. The findings suggest that people’s discomfort levels will rise in the future, making it difficult for them to work outside and engage in their usual activities.
Urban climate changes and the warming of the cities are serious issues that cannot be overlooked. One of the most common inferences for these changes is unprecedented and unplanned urbanization, which further causes a rise in local, regional, and even global temperatures. Although the rate of urbanisation defines and greatly influences the city’s socioeconomic worth and GDP per capita, if the urban expansion is hap-hazardous, it can cause serious environmental harm.There has been a steep rise in global urban population over the past three decades, and the highest growth rates have been observed in Asian and African cities. These two continents have been predicted to contribute to almost 90% of the total urban growth from the present to 2050. India is one of the few highly susceptible countries to the harsh effects of climate change in terms of rise in temperatures. After 1990s’, India has observed substantial changes in the landscape due to urbanization, which has led to a significant rise in the surface and ambient air temperatures, further affecting the planet’s health. Elevated temperature drastically affects the health of urban dwellers leading to a rise in stress and discomfort levels. Estimation of Land Surface Temperature (LST) can play a vital role in understanding the region-specific alterations in temperatures as it uses satellite data that captures the entire region and provides the information in the form of pixels. Traditionally, the temperature was measured at meteorological stations and extrapolated for the entire region,whichinduces inaccuracies. This ambiguity can be amended by developing a relationship between LST and ambient air temperature. This communication focuses on LST estimation using Radiative Transfer Equation algorithm corresponding to various Landuse categories. The study also attempts to create a relationship between the LST and the ambient air temperature observed at two meteorological stations. An overall assessment of the number of days under stress for the residents was also performed over several years. Kolkata Metropolitan Area was considered the study area to represent the results and understand the complete analysis. A rise of 6.77 degrees C was observed in LST over the study period (2000-2019) due to an increment of 200% in the urban area. Analysis of the number of days under stress showed an increasing trend for the study area due to alterations in urban temperatures. These results and the suggestions from the scientific community, urban planners, and climate experts will help develop or modify the current policy frameworks for creating a balance between development and the environment, thus creating sustainable urban development.
We investigated the time evolution of heat waves and warm nights over the 7 agroclimatic zones of Tamil Nadu, India, during the period 1951-2016, including the spatiotemporal patterns of concurrent hot day and hot night (CHDHN) episodes and the concurrent warm spells in daytime temperature and drought (CWD) episodes. The research relied upon gridded temperature and rainfall observations from the India Meteorological Department. We used the Heat-Wave Magnitude Index daily to study the warm spells in daytime and nighttime temperature, while the analysis of droughts was based on the Standardized Precipitation Evapotranspiration Index. We observed a considerable increase in the count, intensity and duration of heat waves and warm night episodes across Tamil Nadu between the periods 1951-1983 and 1984-2016. Particularly, the number of heat wave events almost doubled in the second half of the study period. We observed a west-east gradient in the severity of heat waves. The intensity and duration of warm night events increased up to 3-fold in the second half of the study period, especially over central Tamil Nadu. The study recorded a multi-fold increase in the number and frequency of CHDHN episodes and the number of CWD episodes during 1984-2016 compared to the base period 1951-1983. More importantly, the incidence of compound events that coexisted with anomalous phases of sea surface temperatures registered a statistically significant spike in many locations. These changes in temperature-induced extremes pose an exceptional public health threat that can increase morbidity and mortality, disproportionately affecting vulnerable sections of Tamil Nadu’s populace engaged in outdoor work.
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.
The impact of heat stress among the elderly in India-particularly the elderly poor-has received little or no attention. Consequently, their susceptibility to heat-related illnesses is virtually unknown, as are the strategies they use to avoid, or deal with, the heat. This study examined perceptions of comfort, heat-related symptoms, and coping behaviors of 130 elderly residents of Kolkata slums and 180 elderly residents of rural villages south of Kolkata during a 90-day period when the average 24-h heat indexes were between 38.6 °C and 41.8 °C. Elderly participants in this study reported being comfortable under relatively warm conditions-probably explained by acclimatization to the high level of experienced heat stress. The prevalence of most heat-related symptoms was significantly greater among elderly women, who also were more likely to report multiple symptoms and more severe symptoms. Elderly women in the rural villages were exposed to significantly hotter conditions during the day than elderly men, making it likely that gender differences in symptom frequency, number and severity were related to gender differences in heat stress. Elderly men and elderly village residents made use of a greater array of heat-coping behaviors and exhibited fewer heat-related symptoms than elderly women and elderly slum residents. Overall, heat measurements and heat-related symptoms were less likely to be significant predictors of most coping strategies than personal characteristics, building structures and location. This suggests that heat-coping behaviors during hot weather were the result of complex, culturally influenced decisions based on many different considerations besides just heat stress.
Cities are becoming hotter day-by-day because heat is trapped near the earth’s surface due to a decrease in green cover, rapid urbanization, energy-intensity activities, and concrete structures. The four major metropolitan cities of India, i.e. Kolkata, Chennai, Delhi and Mumbai, have experienced heat waves and heat stress frequently during the summer season. This study analyses heat wave and heat stress patterns in these cities using 30 years of data from 1990 to 2019 during the summer season. We used daily maximum temperature, relative humidity, wind speed and solar radiation datasets for the above mentioned period in this study. To understand the episode of a heat wave, we have used the 95th percentile method. Furthermore, we have also used Humidity Index (HD) to evaluate the degree of discomfort and the Universal Thermal Climate Index (UTCI) to categorize the level of heat stress. The analysis indicates that the number of heat wave events in the Delhi region is 26.31%, 31.58% and 63.16% higher than Kolkata, Chennai, and Mumbai regions respectively. It is also seen that the risks of extreme heat stress and dangerous-heat stroke events in the Chennai region during heat wave periods are higher than that experienced in other metropolitan cities because of high temperature with higher values of relative humidity. The risk of extreme heat stress is less in Delhi because of lower relative humidity compared to other metropolitan cities although temperature is higher in this region. However, the risk of extreme heat stress is lower in Mumbai region because of relatively lower temperature than Chennai during summer season. The likelihood of experiencing great discomfort during heat wave periods in Kolkata city is higher than that experienced in other metropolitan cities in India, however, during non-heat wave periods the probability of extreme discomfort is higher in Chennai.
Extreme heat events (EHEs) have been linked to increased mortality rates, rendering them a valuable research topic in both climate and public health. Early warning systems are highly impactful in prevention and management of heat-related illnesses. We aimed to determine the preliminary maximum temperature thresholds for Nagpur and Rajkot city of India by analyzing the meteorological and mortality data to enable the heat-health response system based on the heat wave disaster risk of a particular state and city. We conducted a trend analysis with daily maximum temperature and all-cause mortality data of Nagpur and Rajkot (2003-2017) cities, also city-specific thresholds evaluated for both cities. There was a significant association between all-cause mortality and extreme heat events and it was more profound when temperatures were above 40.1 degrees C, but V-shaped relationship of mortality-temperature was noted only for Nagpur city. The dose-response relationship between maximum temperatures and deaths alert thresholds to activate heat health response for red alert set at 46 degrees C and 44 degrees C for Nagpur and Rajkot city respectively. This study suggests that determining local thresholds is important for developing and implementing scientific early warning systems to prevent heat-related illnesses.
BACKGROUND: Diarrhea and typhoid, ancient water-borne diseases which are highly connected to rainfall are serious public health challenges in the blocks of Kalahandi district of Odisha, India. OBJECTIVES: Corroboration of rainfall and waterborne diseases are available in abundance; therefore, the objective of this article is to calculate the climate and disease vulnerability index (CDVI) value for each block of Kalahandi. METHODS: We have applied the livelihood vulnerability index with some modifications and classify the three major categories, i.e., exposure, sensitivity, and adaptive capacity into six subcategories. These six subcategories are further divided into 26 vulnerability indicators based on a detailed literature review. RESULTS: The result indicated that the Thuamul Rampur block, the southernmost part of the district is highly exposed to the annual and seasonal mean rainfall, and the Madanpur Rampur block lies in the northernmost part of the district is highly exposed to diarrhea and typhoid. Based on the calculation of the final CDVI value, nearly 50% of blocks of the Kalahandi district fall in the category of very high to high vulnerable zones. Furthermore, it has been observed that factors such as rainfall and disease distribution, vulnerable population and infrastructure, and education and health-care capacities had a notable influence on vulnerability. CONCLUSION: It is rare to find a health vulnerability-related study in India at this microlevel based on the suitable indicators selected for a tribal and backward region.
Melioidosis is a seasonal infectious disease in tropical and subtropical areas caused by the soil bacterium Burkholderia pseudomallei. In many parts of the world, including South West India, most cases of human infections are reported during times of heavy rainfall, but the underlying causes of this phenomenon are not fully understood. India is among the countries with the highest predicted melioidosis burden globally, but there is very little information on the environmental distribution of B. pseudomallei and its determining factors. The present study aimed (i) to investigate the prevalence of B. pseudomallei in soil in South West India, (ii) determine geochemical factors associated with B. pseudomallei presence and (iii) look for potential seasonal patterns of B. pseudomallei soil abundance. Environmental samplings were performed in two regions during the monsoon and post-monsoon season and summer from July 2016 to November 2018. We applied direct quantitative real time PCR (qPCR) together with culture protocols to overcome the insufficient sensitivity of solely culture-based B. pseudomallei detection from soil. A total of 1,704 soil samples from 20 different agricultural sites were screened for the presence of B. pseudomallei. Direct qPCR detected B. pseudomallei in all 20 sites and in 30.2% (517/1,704) of all soil samples, whereas only two samples from two sites were culture-positive. B. pseudomallei DNA-positive samples were negatively associated with the concentration of iron, manganese and nitrogen in a binomial logistic regression model. The highest number of B. pseudomallei-positive samples (42.6%, p < 0.0001) and the highest B. pseudomallei loads in positive samples [median 4.45 × 10(3) genome equivalents (GE)/g, p < 0.0001] were observed during the monsoon season and eventually declined to 18.9% and a median of 1.47 × 10(3) GE/g in summer. In conclusion, our study from South West India shows a wide environmental distribution of B. pseudomallei, but also considerable differences in the abundance between sites and within single sites. Our results support the hypothesis that nutrient-depleted habitats promote the presence of B. pseudomallei. Most importantly, the highest B. pseudomallei abundance in soil is seen during the rainy season, when melioidosis cases occur.
Climate change is adversely impacting the burden of diarrheal diseases. Despite significant reduction in global prevalence, diarrheal disease remains a leading cause of morbidity and mortality among young children in low- and middle-income countries. Previous studies have shown that diarrheal disease is associated with meteorological conditions but the role of large-scale climate phenomena such as El Niño-Southern Oscillation (ENSO) and monsoon anomaly is less understood. We obtained 13 years (2002-2014) of diarrheal disease data from Nepal and investigated how the disease rate is associated with phases of ENSO (El Niño, La Niña, vs. ENSO neutral) monsoon rainfall anomaly (below normal, above normal, vs. normal), and changes in timing of monsoon onset, and withdrawal (early, late, vs. normal). Monsoon season was associated with a 21% increase in diarrheal disease rates (Incident Rate Ratios [IRR]: 1.21; 95% CI: 1.16-1.27). El Niño was associated with an 8% reduction in risk while the La Niña was associated with a 32% increase in under-5 diarrheal disease rates. Likewise, higher-than-normal monsoon rainfall was associated with increased rates of diarrheal disease, with considerably higher rates observed in the mountain region (IRR 1.51, 95% CI: 1.19-1.92). Our findings suggest that under-5 diarrheal disease burden in Nepal is significantly influenced by ENSO and changes in seasonal monsoon dynamics. Since both ENSO phases and monsoon can be predicted with considerably longer lead time compared to weather, our findings will pave the way for the development of more effective early warning systems for climate sensitive infectious diseases.
Introduction: The incidence of diarrhea, a leading cause of morbidity and mortality in low-income countries such as Nepal, is temperature-sensitive, suggesting it could be associated with climate change. With climate change fueled increases in the mean and variability of temperature and precipitation, the incidence of water and food-borne diseases are increasing, particularly in sub-Saharan Africa and South Asia. This national-level ecological study was undertaken to provide evidence linking weather and climate with diarrhea incidence in Nepal. Method: We analyzed monthly diarrheal disease count and meteorological data from all districts, spanning 15 eco-development regions of Nepal. Meteorological data and monthly data on diarrheal disease were sourced, respectively, from the Department of Hydrology and Meteorology and Health Management Information System (HMIS) of the Government of Nepal for the period from 2002 to 2014. Time-series log-linear regression models assessed the relationship between maximum temperature, minimum temperature, rainfall, relative humidity, and diarrhea burden. Predictors with p-values < 0.25 were retained in the fitted models. Results: Overall, diarrheal disease incidence in Nepal significantly increased with 1 °C increase in mean temperature (4.4%; 95% CI: 3.95, 4.85) and 1 cm increase in rainfall (0.28%; 95% CI: 0.15, 0.41). Seasonal variation of diarrheal incidence was prominent at the national level (11.63% rise in diarrheal cases in summer (95% CI: 4.17, 19.61) and 14.5% decrease in spring (95% CI: −18.81, −10.02) compared to winter season). Moreover, the effects of temperature and rainfall were highest in the mountain region compared to other ecological regions of Nepal. Conclusion: Our study provides empirical evidence linking weather factors and diarrheal disease burden in Nepal. This evidence suggests that additional climate change could increase diarrheal disease incidence across the nation. Mountainous regions are more sensitive to climate variability and consequently the burden of diarrheal diseases. These findings can be utilized to allocate necessary resources and envision a weather-based early warning system for the prevention and control of diarrheal diseases in Nepal.
Surface water quality is among the significant challenges in the Sutlej River basin, passing through Pakistan’s most densely populated province. Currently, the overall surface water quality is grossly polluted, mainly due to the direct discharge of wastewater from the urban areas to the Sutlej River directly or through stream networks. Escherichia coli concentrations vary under extreme weather events like floods and droughts and socioeconomic circumstances like urbanization, population growth, and treatment options. This paper assesses the future E. coli load and concentrations using the Soil and Water Assessment Tool (SWAT) along with scenarios based on Shared Socioeconomic Pathways (SSPs) and Representative Concentration Pathways (RCPs) developed by the Intergovernmental Panel on Climate Change (IPCC). E. coli concentrations according to a more polluted scenario disclose a near and mid future increase by 108% and 173%, and far future increases up to 251% compared to the reference period (baseline) concentrations. The E. coli concentration is reduced by - 54%, - 68%, and - 81% for all the projected time steps compared to the baseline concentrations. While highly improved sewerage and manure management options are adapted, the concentration is further reduced by - 96%, - 101%, and - 105%, respectively, compared to the baseline. Our modeling and scenario matrix study shows that reducing microbiological concentrations in the surface water is possible. Still, it requires rigorous sanitation and treatment options, and socioeconomic variables play an essential role besides climate change to determine the microbiological concentration of water resources and be included in future studies whenever water quality and health risks are considered.
In tropical countries such as Sri Lanka, where leptospirosis-a deadly disease with a high mortality rate-is endemic, prediction is required for public health planning and resource allocation. Routinely collected meteorological data may offer an effective means of making such predictions. This study included monthly leptospirosis and meteorological data from January 2007 to April 2019 from Sri Lanka. Factor analysis was first used with rainfall data to classify districts into meteorological zones. We used a seasonal autoregressive integrated moving average (SARIMA) model for univariate predictions and an autoregressive distributed lag (ARDL) model for multivariable analysis of leptospirosis with monthly average rainfall, temperature, relative humidity (RH), solar radiation (SR), and the number of rainy days/month (RD). Districts were classified into wet (WZ) and dry (DZ) zones, and highlands (HL) based on the factor analysis of rainfall data. The WZ had the highest leptospirosis incidence; there was no difference in the incidence between the DZ and HL. Leptospirosis was fluctuated positively with rainfall, RH and RD, whereas temperature and SR were fluctuated negatively. The best-fitted SARIMA models in the three zones were different from each other. Despite its known association, rainfall was positively significant in the WZ only at lag 5 (P = 0.03) but was negatively associated at lag 2 and 3 (P = 0.04). RD was positively associated for all three zones. Temperature was positively associated at lag 0 for the WZ and HL (P < 0.009) and was negatively associated at lag 1 for the WZ (P = 0.01). There was no association with RH in contrast to previous studies. Based on altitude and rainfall data, meteorological variables could effectively predict the incidence of leptospirosis with different models for different climatic zones. These predictive models could be effectively used in public health planning purposes.
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.
BACKGROUND: Pakistan has been experiencing intervals of sporadic cases and localized outbreaks in the last two decades. No proper study has been carried out in order to find out the environmental burden of toxigenic V. cholerae as well as how temporal and environmental factors associated in driving cholera across the country. METHODS: We tested waste water samples from designated national environment surveillance sites in Pakistan with RT-PCR assay. Multistage sampling technique were utilized for samples collection and for effective sample processing Bag-Mediated Filtration system, were employed. Results were analysed by district and month wise to understand the geographic distribution and identify the seasonal pattern of V. cholera detection in Pakistan. RESULTS: Between May 2019, and February 2020, we obtained and screened 160 samples in 12 districts across Pakistan. Out of 16 sentinel environmental surveillance sites, 15 sites showed positive results against cholera toxigenic gene with mostly lower CT value (mean, 34??2) and have significant difference (p < 0.05). The highest number of positive samples were collected from Sindh in month of November, then in June it is circulating in different districts of Pakistan including four Provinces respectively. CONCLUSION: V. cholera detection do not follow a clear seasonal pattern. However, the poor sanitation problems or temperature and rainfall may potentially influence the frequency and duration of cholera across the country. Occurrence of toxigenic V. cholerae in the environment samples showed that cholera is endemic, which is an alarming for a potential future cholera outbreaks in the country.
We examine the impact of flooding in Pakistan on child health using satellite data and two household datasets. Flooding may influence child health, as measured by weight-for-height z-score, through two key channels. First, excessive flood waters can catalyze the spread of diarrheal disease, negatively impacting child health. Second, excessive flood waters – even when damaging in some areas – provide water to rice paddies and other agriculture, increasing food availability in the post-flood period. This may positively influence child health. In Pakistan, we find evidence of both channels: floods increase incidence of morbidity (diarrhea and fever) as well as meal frequency in the post flood season. We also find that floods increase dietary diversity, but only in districts with high rice harvesting intensity where flooding may predict favorable growing conditions. Because these mechanisms (disease incidence and dietary adequacy) act against one another, we find weak overall impact of floods on child health. (c) 2021 Elsevier Ltd. All rights reserved.
BACKGROUND: Chengannur, a town in the south Indian state of Kerala, was 1 of the worst affected towns during the floods of 2018. Post-flood, Kerala state was under the threat of many infectious diseases including leptospirosis, but did not report any leptospirosis infections. OBJECTIVES: This study was conducted with the following objectives: (1) Assess the knowledge, attitude and practices regarding the prevention of leptospirosis among the flood affected population and Accredited Social Health Activists (ASHAs) of Chengannur; and (2) Analyze the factors responsible for and contributing to leptospirosis control in the area post flood. METHODOLOGY: A cross-sectional questionnaire based observational study was conducted among 2 groups: the flood affected population, and ASHA. The questionnaire was divided into 3 parts. Part A contained the socio-demographic information. Part B contained questions on assessment of knowledge, attitude, and practices regarding the prevention, and control of leptospirosis. Part C was only for the ASHA involved. RESULTS: The final sample size was 331 (244 from the general population and 87 ASHAs). With respect to knowledge, attitude, and practice, the responses were dichotomized into correct and wrong responses. The mean knowledge score was 9.01 ± 1.08 (maximum score of 10), mean attitude score was of 3.61 ± 0.55 (maximum score of 4) and the mean practice score was 4.12 ± 1.05 (maximum score of 5). CONCLUSION: Knowledge and attitude scores did not significantly differ between the general population and ASHA, but the practice score showed a higher score among the ASHA, all of which could have probably contributed to the prevention of a leptospirosis outbreak in the region.
Neonates and children are more vulnerable to the negative impact of flood-related changes and may have a variety of detrimental negative impacts on their health. They are more prone to get various infectious diseases. They are also more vulnerable to malnutrition during floods. Flooding limits access to clean water as sewage overflows and contaminates nearby water sources. The polluted setting in the flood-affected area makes it difficult to ensure the hygiene of feeding equipment used to prepare infant formula. Breastfeeding may also become less effective due to the lack of privacy for women to breastfeed their kids while living in temporary shelters with other flood victims. In addition, milk production decreases and might even cease due to mothers’ reduced food intake and increased stress levels. Flooding may also cause supplemental feeding to deteriorate. The mothers and other primary caregivers usually lack the resources in affected areas to prepare supplemental diets for their kids, which further harm the babies. There is mounting evidence that children are more likely to develop clogged noses, itchy eyes, hoarseness, skin complications, and sneezing while living in humid areas.
The recent monsoon rains in Pakistan were unprecedented and caused flooding all over Pakistan, especially in Sindh and Balochistan. Following this national disaster, various water-borne and contagious diseases started erupting all over the country. In such a calamity-struck city of Jacobabad, we started receiving cases with a peculiar set of ocular complaints mimicking viral keratoconjunctivitis. Failure to respond to traditional treatment and the unique appearance of these corneal opacities led to a rare diagnosis of Microsporidial Keratoconjunctivitis, which was later confirmed by microscopy and staining of corneal scrapings of the most affected case. In line with published literature, all cases were treated with topical fluoroquinolone and topical anti-fungal therapy, following which the disease was cleared within a week. The disease has seen an upward trend the world over, especially among Asia. To the best of our knowledge, no such cases have been reported in Pakistan as yet. In this case series, we highlight the strong correlation of emergence of microsporidial keratitis in patients following exposure to pooled water bodies after the monsoon rainy season and floods. Moreover, this report will help create awareness in eye professionals regarding the prevention, timely diagnosis and treatment of these rare and emerging cases. Key Words: Keratitis, Spores, Water-borne diseases, Microsporidia.
BACKGROUND: Current literatures seem devoted only on relating climate change with malaria. Overarching all possible environmental determinants of malaria prevalence addressed by scanty literature in Nepal is found apposite research at this moment. This study aims to explore the environmental determinants of malaria prevalence in western Nepal. METHODS: Cross-sectional data collected from community people were used to identify the environmental determinants of malaria prevalence in western Nepal. Probit and logistic regressions are used for identifying determinants. RESULTS: The results reveal that environmental variables: winter temperature (aOR: 2.14 [95% CI: 1.00-4.56]), flooding (aOR: 2.45 [CI: 1.28-4.69]), heat waves (aOR: 3.14 [CI: 1.16-8.46]) and decreasing river water level (aOR: 0.25 [CI: 0.13-0.47]) are found major factors to influence malaria prevalence in western Nepal. Besides, pipeline drinking water (aOR: 0.37 [0.17-0.81]), transportation facility (aOR: 1.18 [1.07-1.32]) and awareness programs (aOR: 2.62 [0.03-6.65]) are exigent social issues to influence malaria prevalence in Nepal. To be protected from disease induced by environmental problems, households have used extra season specific clothes, iron nets and mosquito nets, use of insecticide in cleaning toilet and so on. CONCLUSIONS: Adaptation mechanism against these environmental issues together with promoting pipeline drinking water, transportation facility and awareness programs are the important in malaria control in Nepal. Government initiation with incentivized adaptation mechanism for the protection of environment with caring household attributes possibly help control malaria in western Nepal.
This paper investigates the extent to which in-utero exposure to droughts influences the health outcomes of Bangladeshi children in early childhood. Exploiting the plausibly exogenous deviations of rainfall from the location-specific norms, we find that deficient rainfall during the prenatal period is harmful to child health. Specifically, in-utero exposure to droughts decreases the height-for-age, weight-for-height, and weight-for-age z-scores by 0.10, 0.11, and 0.11 standard deviations among children under five years old, respectively. Our heterogeneity analyses reveal that the adverse health setbacks fall disproportionately on children of disadvantaged backgrounds. Exploring the differential effects by trimesters of exposure, we further show that experiencing droughts during the second and the third trimesters leaves injurious effects on early childhood health.
BACKGROUND: Drought has been a considerable problem for many years in northern Bangladesh. However, the health impacts of drought in this region are not well understood. METHODS: This study analyzed the impact of drought duration and severity on select causes of mortality in northern Bangladesh. Rainfall data from three meteorological stations (Rangpur, Dinajpur and Nilphamari) in northern Bangladesh were used to assess drought and non-drought periods, and the Standardized Precipitation Index was used to categorize mild, moderate, severe, and extreme drought. Mortality data from 2007 to 2017 for the three areas were collected from the Sample Vital Registration System, which is a survey of 1 million people. The generalized linear model with Poisson regression link was used to identify associations between mortality and the drought severity and 1-month preceding SPI. RESULTS: Only severe and extreme drought in the short-term drought periods affected mortality. Long-term drought was not associated with natural cause mortality in Rangpur and Nilphamari. In Dinajpur, mild and moderate drought was associated with circulatory- and respiratory-related mortality. CONCLUSION: The impact of drought on mortality varied by region. This study improves our understanding of how droughts affect specific causes of mortality and will help policy makers to take appropriate measures against drought impacts on selected cause of mortality. Future research will be critical to reduce drought-related risks of health.
Climate change has increased the frequency of drought occurrence in various parts of the world. Drought as a complex phenomenon causes severe impacts on ecological and socio-economic status. Short-term and long-term occurrences of drought have made many regions vulnerable globally. This paper makes an attempt to assess drought vulnerability in Godavari Middle Sub-basin of India. Twenty-four site specific socio-economic and environmental factors were identified based on the extensive literature review. Drought frequency was assessed using standardized precipitation index (SPI). These datasets were divided into training (70%) and testing (30%) data. Frequency ratio (FR) model was utilized to establish relationship among drought conditioning factors and drought frequency. Weights obtained from the FR model were used as input to the adaptive neuro-fuzzy inference systems (ANFIS) model. Drought vulnerability results were validated using the testing data and receiver operating characteristic (ROC). The accuracy of ANFIS models for 1-month (0.957), 3-months (0.882), 6-months (0.964) and 12-months (0.938) showed high suitability of ANFIS model for the assessment of drought vulnerability. The findings revealed that very low normalized difference vegetation index (NDVI) and increasing trend of highest maximum and mean maximum temperature were major environmental factors which influenced high drought vulnerability in the sub-basin. High proportion of area under fallow land, high infant mortality rate (IMR) and moderate literacy rate were identified as major socio-economic factors making watersheds vulnerable during short and long-term droughts. Largest area of the sub-basin was found under high vulnerability for 3-months, followed by 6-months and 12-months droughts. Thus, the study calls for policy intervention towards lessening the impact of drought in highly vulnerable watersheds.
The Indian summer monsoon rainfall (ISMR) is vital for the livelihood of millions of people in the Indian region; droughts caused by monsoon failures often resulted in famines. Large volcanic eruptions have been linked with reductions in ISMR, but the responsible mechanisms remain unclear. Here, using 145-year (1871-2016) records of volcanic eruptions and ISMR, we show that ISMR deficits prevail for two years after moderate and large (VEI > 3) tropical volcanic eruptions; this is not the case for extra-tropical eruptions. Moreover, tropical volcanic eruptions strengthen El Niño and weaken La Niña conditions, further enhancing Indian droughts. Using climate-model simulations of the 2011 Nabro volcanic eruption, we show that eruption induced an El Niño like warming in the central Pacific for two consecutive years due to Kelvin wave dissipation triggered by the eruption. This El Niño like warming in the central Pacific led to a precipitation reduction in the Indian region. In addition, solar dimming caused by the volcanic plume in 2011 reduced Indian rainfall.
Climate change threatens global sustainability, especially in rural communities of developing countries. In Pakistan, severe impacts of climate change have become evident in the recent past. Large-scale floods in the Indus river system have caused massive damages in the past decade. Also, frequent droughts and heatwaves are among other consequences of the changing climate in the country. Understanding the perspective of local communities regarding climate change adaptation strategies is pivotal to effective policymaking. We surveyed the rural community in the Indus Basin, in southern Punjab, Pakistan, to assess the climate change adaptations currently practiced. We found that the respondents perceive droughts, floods, and disease outbreaks (which are frequently followed by flooding events) as major climate change-induced threats. The respondents used flood and drought-resistant crop varieties, field boundaries (spate irrigation), migration to safe places, and loans as key adaptation strategies. We also assessed the socioeconomic determinants of climate change adaptation behaviour using a binary logistic regression model. Gender, occupation, and education influenced the adaptations to climate change. The present study highlights the need for monetary support to flood-prone communities, better medical facilities, provision of drought and flood-resistant crop varieties, and awareness campaigns to enhance adaptive capacity in the study area.
The 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: Personnel deployed at an altitude ranging from 9000 ft to 23,000 ft are exposed to sub-zero temperatures up to -40 degrees C. These conditions lead to the development of various cold injuries which presents in varying grades and severity. Aim: The aim of this study is to study the epidemiological trends and assess risk factors/conditions those are contributing to the development of cold weather injuries (CWI) at extreme cold climate in high altitude areas. Methodology: This is a retrospective, observational study on cold injury cases evacuated from the northern glaciers of India. The data were collected and tabulated in MS-Excel sheets, and analysis was done using percentage, mean, median, linear regression, and P value calculation. SPSS statistical analysis software version 23 was employed for generating the results. P < 0.05 was considered for statistically significant. Results: The annual incidence of cold injuries calculated for troops deployed at high altitude (>9000 feet) with extreme cold climate is 6.4/1000/year. The average duration of exposure for the development of CWI was found to be 4.85 h with a standard deviation = 2.88 h. Statistically significant association was found between the median temperatures and number of cold injury cases evacuated monthly with a strong negative coefficient of correlation (Pearson’s) value r = -0.8214, and P = 0.001063. No correlation was found between the severity of frostbites and duration of exposure as the coefficient of correlation r (Pearson’s) was weakly positive with a value of 0.19 and statistically not significant with P = 0.127. Conclusion: This study highlights the magnitude of problem, high risk zones, and predisposing activities. Statistical association has been drawn between altitude, temperature and duration of exposure with burden of cold injury. This study provides an insight with respect to associations and risk factors for the development of CWI, in Indian perspective and may be beneficial for better planning and preventive measures to reduce burden of CWI.
The Uttarakhand State, known for its Himalayan Mountains, is a territory in Northern India that is extremely vulnerable to earthquakes, landslides, and floods. Currently, due to the COVID-19 outbreak, India is facing the dual challenge of containing a pandemic and responding to natural disasters. This situation can have a negative impact on the health and the economic development of the region, leading to a long-lasting humanitarian crisis that can disrupt even more, the already overburdened health service. In addition, it can pose serious threats to the wellbeing of the population as it complicates physical distancing and other COVID-19 prevention measures. It is of utmost importance to analyse the impact of floods, landslides, and COVID-19 pandemic on the health system of the Uttarakhand State, and how these crises interact with each other.
Cyclone Amphan battered the coastal communities in the southwestern part of Bangladesh in 2020 during the COVID-19 pandemic. These coastal communities were experiencing such a situation for the first time and faced the dilemma of whether to stay at home and embrace the cyclone or be exposed to the COVID-19 virus in the cyclone shelters by evacuating. This article intends to explore individuals’ decisions regarding whether to evacuate in response to cyclone Amphan and in light of the risks of the COVID-19 pandemic. Consequently, this study investigated evacuation behaviors among the households and explored the impacts of COVID-19 during the evacuation procedures. We conducted household surveys to collect primary information and undertook 378 samples for interviews at a precision level of 0.05 in fourteen villages. Despite the utmost effort of the government, the results demonstrated that 96.6% of people in the coastal area received a cyclone evacuation order before the cyclone’s landfall, and only 42% of people followed the evacuation order. The majority of households chose to stay at home because of fear of COVID-19 exposure in the crowded shelters. Although half of the evacuees were housed in cyclone shelters, COVID-19 preventive measures were apparently not set in place. Thus, this study will assist in crafting future government policies to enhance disaster evacuation plans by providing insights from the pandemic that can inform disaster management plans in the Global South.
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.
BACKGROUND: In the climate change discourse, a body of scholarship focusing on how people perceive climate change and its impact is increasing. However, in the Indian context, such scholarship is limited. OBJECTIVE: This paper aims to describe the perceptions of people on climate change and its health impacts, which were captured as part of a larger study. METHODOLOGY: A cross-sectional study was conducted in randomly selected 983 households in four districts spread across Madhya Pradesh and Jammu and Kashmir. A semi-structured questionnaire was used to collect the data. RESULTS: For 72% of respondents, the perception was not related to climate change per se. Their perceptions were contextual and were based on the anomalies which are observed in the immediate weather conditions. The health impacts of climate change were also not understood at the first place, but with probing 64% of respondents were able to report seasonal diseases. CONCLUSION: Perceptions of the people regarding climate change are more linked to their own experiences with their local weather conditions rather than the overall concept. This also explains their lack of comprehension about the health impact of climate change, but a sound understanding of seasonal diseases.
OBJECTIVES: Dakshina Kannada is one of the districts of Karnataka state of India with high incidences of mosquito-borne diseases, especially malaria and dengue. The larval stages of the mosquitoes are very important in determining the prevalence of adult mosquitoes and associated diseases. Hence, the occurrence of mosquito species was investigated by sampling different water bodies present in the Dakshina Kannada district from June 2014 to May 2017. METHODS: Random sampling was carried out from permanent and temporary, artificial and natural water bodies belonging to 11 types of microhabitats using dippers and suction pumps. RESULTS: A maximum of 37 mosquito species belonging to 12 genera were recorded with the dominant genera being Culex. Most species have been recorded from temporary bodies of water with the highest number of species in receptacles. Monsoon is the most productive season, both in terms of occurrence and abundance followed by post-monsoon and pre-monsoon. The abundance of mosquito larvae was significantly higher in temporary water bodies compared to the permanent. INTERPRETATION & CONCLUSION: Abundant rainfall in the study area which produces many natural and domestic temporary water bodies accounts for mosquito breeding throughout the year.
BACKGROUND & OBJECTIVES: In India, Kyasanur Forest Disease has been reported from the states of Karnataka, Kerala, Goa, and Maharashtra. The relationship between climatic factors and transmission of KFD remains untouched, therefore, the present study was undertaken. METHODS: Based on the occurrence of cases, Shivamogga district (Karnataka) and Wayanad district in Kerala and northern Goa (Goa state) were selected for the study. Data on the incidence of KFD and climate factors were collected from concerned authorities. To determine the relationship between dependent and independent variables, spearman’s correlation was calculated for monthly as well as with lag months. RESULTS: KFD cases and temperature (°C) were found significantly correlated up to 1 months’ lag period (p<0.05) while with precipitation relationship was found negatively significant for 0-3 months' lag. The range of suitable temperature for KFD in Shivamogga, Goa and Wayanad was found as 20-31°C, 25-29°C and 27-31°C respectively. The cumulative precipitation during transmission months (November-May) ranged from <150-500mm, while in non-transmission months (June-October) from >1100-2400mm. INTERPRETATION & CONCLUSION: The analysis of three sites revealed that with the increase in temperature, the intensity of KFD transmission decreases as corroborated by the seasonal fluctuations in Shivamogga, Goa and Wayanad. High precipitation from June to October rovides suitable ecology to tick vector and sets in transmission season from November to May when cumulative precipitation is <500 mm.
The effects of climate change on infectious diseases are a topic of considerable interest and discussion. We studied West Nile virus (WNV) in New York (NY) and Connecticut (CT) using a Weather Research and Forecasting (WRF) model climate change scenario, which allows us to examine the effects of climate change and variability on WNV risk at county level. We chose WNV because it is well studied, has caused over 50,000 reported human cases, and over 2200 deaths in the United States. The ecological impacts have been substantial (e.g., millions of avian deaths), and economic impacts include livestock deaths, morbidity, and healthcare-related expenses. We trained two Random Forest models with observational climate data and human cases to predict future levels of WNV based on future weather conditions. The Regional Model used present-day data from NY and CT, whereas the Analog Model was fit for states most closely matching the predicted future conditions in the region. Separately, we predicted changes to mosquito-based WNV risk using a trait-based thermal biology approach (Mosquito Model). The WRF model produced control simulations (present day) and pseudo-global warming simulations (future). The Regional and Analog Models predicted an overall increase in human cases of WNV under future warming. However, the Analog Model did not predict as strong of an increase in the number of human cases as the Regional Model, and predicted a decrease in cases in some counties that currently experience high numbers of WNV cases. The Mosquito Model also predicted a decrease in risk in current high-risk areas, with an overall reduction in the population-weighted relative risk (but an increase in area-weighted risk). The Mosquito Model supports the Analog Model as making more realistic predictions than the Regional Model. All three models predicted a geographic increase in WNV cases across NY and CT.
Vector-borne disease risk assessment is crucial to optimize surveillance, preventative measures (vector control), and resource allocation (medical supplies). High arthropod abundance and host interaction strongly correlate to vector-borne pathogen transmission. Increasing host density and movement increases the possibility of local and long-distance pathogen transmission. Therefore, we developed a risk-assessment framework using climate (average temperature and rainfall) and host demographic (host density and movement) data, particularly suitable for regions with unreported or underreported incidence data. This framework consisted of a spatiotemporal network-based approach coupled with a compartmental disease model and nonhomogeneous Gillespie algorithm. The correlation of climate data with vector abundance and host-vector interactions is expressed as vectorial capacity-a parameter that governs the spreading of infection from an infected host to a susceptible one via vectors. As an example, the framework is applied for dengue in Bangladesh. Vectorial capacity is inferred for each week throughout a year using average monthly temperature and rainfall data. Long-distance pathogen transmission is expressed with human movement data in the spatiotemporal network. We have identified the spatiotemporal suitability of dengue spreading in Bangladesh as well as the significant-incidence window and peak-incidence period. Analysis of yearly dengue data variation suggests the possibility of a significant outbreak with a new serotype introduction. The outcome of the framework comprised spatiotemporal suitability maps and probabilistic risk maps for spatial infection spreading. This framework is capable of vector-borne disease risk assessment without historical incidence data and can be a useful tool for preparedness with accurate human movement data.
Introduction: Dengue is a mosquito borne viral disease. found in tropical and subtropical countries. Dengue virus (DENV) infected mosquitoes of Aedes species are crucial for the transmission of disease. It has emerged as a threat to the public health systems. Dengue is endemic in many parts of India but still the status of dengue cases in Rewa Madhya Pradesh is not reported convincingly. Aim: To investigate the presence of dengue in Rewa district of Madhya Pradesh. Materials and Methods: This cross-sectional study was conducted in the Department of Microbiology at Shyam Shah Medical college Rewa under National Vector Borne Disease Control Programme (NVBDCP), Rewa, Madhya Pradesh, India, including 1113 Outpatient/Inpatient Department samples received during March 2021 to October 2021. Blood samples were collected from patients having febrile illness and after serum separation, serum were subjected to NS1 Enzyme Linked Immunosorbent Assay (ELISA) test. Descriptive statistics and Chi-square tests were applied for data analysis. Results: A total of 1113 sample were received and tested for dengue NS1 out of that 108 sample were found NS1 positive by ELISA. The cases of dengue started from the month of July 2021. But in the month of October dengue positivity was highest in number. Dengue cases reported were 297 (6.73%) in the rainy season (July-August), but the dengue positivity increased (713, 9.3%) in the post rainy season (September-October). Overall prevalence of dengue was higher in the 21-30 years (34.3%) age group followed by 11-20 years (24.1%), 31-40 years (18.5%), 41-50 years (18.5%), 51-60 years (7.4%) and >60 years (3.70%) age groups with respect to total positive cases. The prevalence of dengue was higher in male (12.94%) in comparison to females (5.54%). Conclusion: This study warrants the dengue virus infection as one of the important causes of fever during rainy and post rainy season in this region. Early diagnosis and reporting of cases are important for the better management of disease.
In recent decades, dengue has been expanding rapidly in the tropical cities. Even though environmental factors and landscape features profoundly impact dengue vector abundance and disease epidemiology, significant gaps exist in understanding the role of local environmental heterogeneity on dengue epidemiology in India. In this study, we assessed the role of remotely sensed climatic factors (rainfall, temperature and humidity) and landscape variables (land use pattern, vegetation and built up density) on dengue incidence (2012-2019) in Bhopal city, Central India. Dengue hotspots in the city were assessed through geographical information system based spatial statistics. Dengue incidence increased from 0.59 cases in 2012 to 9.11 cases in 2019 per 10,000 inhabitants, and wards located in Southern Bhopal were found to be dengue hotspots. Distributed lag non-linear model combined with quasi Poisson regression was used to assess the exposure-response association, relative risk (RR), and delayed effects of environmental factors on dengue incidence. The analysis revealed a non-linear relationship between meteorological variables and dengue cases. The model shows that the risk of dengue cases increases with increasing mean temperature, rainfall and absolute humidity. The highest RR of dengue cases (~2.0) was observed for absolute humidity ≥60 g/m3 with a 5-15 week lag. Rapid urbanization assessed by an increase in the built-up area (a 9.1% increase in 2020 compared to 2014) could also be a key factor driving dengue incidence in Bhopal city. The study sheds important insight into the synergistic effects of both the landscape and climatic factors on the transmission dynamics of dengue. Furthermore, the study provides key baseline information on the climatic variables that can be used in the micro-level dengue prediction models in Bhopal and other cities with similar climatic conditions.
INTRODUCTION: The study aimed to develop a reproducible, open-source, and scalable framework for extracting climate data from satellite imagery, understanding dengue’s decadal trend in India, and estimating the relationship between dengue occurrence and climatic factors. MATERIALS AND METHODS: A framework was developed in the Open Source Software, and it was empirically tested using reported annual dengue occurrence data in India during 2010-2019. Census 2011 and population projections were used to calculate incidence rates. Zonal statistics were performed to extract climate parameters. Correlation coefficients were calculated to estimate the relationship of dengue with the annual average of daily mean and minimum temperature and rainy days. RESULTS: Total 818,973 dengue cases were reported from India, with median annual incidence of 6.57 per lakh population; it was high in 2019 and 2017 (11.80 and 11.55 per lakh) and the Southern region (8.18 per lakh). The highest median annual dengue incidence was observed in Punjab (24.49 per lakh). Daily climatic data were extracted from 1164 coordinate locations across the country for the decadal period (4,249,734 observations). The annual average of daily temperature and rainy days positively correlated with dengue in India (r = 0.31 and 0.06, at P < 0.01 and 0.30, respectively). CONCLUSION: The study provides a reproducible algorithm for bulk climatic data extraction from research-level satellite imagery. Infectious disease models can be used to understand disease epidemiology and strengthen disease surveillance in the country.
India has witnessed a five-fold increase in dengue incidence in the past decade. However, the nation-wide distribution of dengue vectors, and the impacts of climate change are not known. In this study, species distribution modeling was used to predict the baseline and future distribution of Aedine vectors in India on the basis of biologically relevant climatic indicators. Known occurrences of Aedes aegypti and Aedes albopictus were obtained from the Global Biodiversity Information Facility database and previous literature. Bio-climatic variables were used as the potential predictors of vector distribution. After eliminating collinear and low contributing predictors, the baseline and future prevalence of Aedes aegypti and Aedes albopictus was determined, under three Representative Concentration Pathway scenarios (RCP 2.6, RCP 4.5 and RCP 8.5), using the MaxEnt species distribution model. Aedes aegypti was found prevalent in most parts of the southern peninsula, the eastern coastline, north eastern states and the northern plains. In contrast, Aedes albopictus has localized distribution along the eastern and western coastlines, north eastern states and in the lower Himalayas. Under future scenarios of climate change, Aedes aegypti is projected to expand into unsuitable regions of the Thar desert, whereas Aedes albopictus is projected to expand to the upper and trans Himalaya regions of the north. Overall, the results provide a reliable assessment of vectors prevalence in most parts of the country that can be used to guide surveillance efforts, despite minor disagreements with dengue incidence in Rajasthan and the north east, possibly due to behavioral practices and sampling efforts. Plain Language Summary Climatic parameters derived from temperature and humidity affect the development and survival of mosquitoes that spread diseases. In the past decade, India has witnessed an alarming rise in dengue, a viral disease that spreads through the bite of the mosquitoes Aedes aegypti and Aedes albopictus. We used machine learning based modeling algorithm to predict the present and future abundance of these mosquitoes in India, based on biologically relevant climatic factors. The results project expansion of Aedes aegypti in the hot arid regions of the Thar Desert and Aedes albopictus in cold upper Himalayas as a result of future climatic changes. The results provide a useful guide for strengthening efforts for entomological and dengue surveillance.
Dengue fever is a mosquito-borne viral disease caused by the dengue virus of the Flaviviridae family and is responsible for colossal health and economic burden worldwide. This study aimed to investigate the effect of environmental, seasonal, and spatial variations on the spread of dengue fever in Sri Lanka. The study used secondary data of monthly dengue infection and the monthly average of environmental parameters of 26 Sri Lankan regions from January 2015 to December 2019. Besides the descriptive measurements, Kendall’s tau_b, Spearman’s rho, and Kruskal-Wallis H test have been performed as bivariate analyses. The multivariate generalized linear negative binomial regression model was applied to determine the impacts of meteorological factors on dengue transmission. The aggregate negative binomial regression model disclosed that precipitation (odds ratio: 0.97, p < 0.05), humidity (odds ratio: 1.05, p < 0.01), and air pressure (odds ratio: 1.46, p < 0.01) were significantly influenced the spread of dengue fever in Sri Lanka. The bioclimatic zone is the vital factor that substantially affects the dengue infection, and the wet zone (odds ratio: 6.41, p < 0.05) was more at-risk than the dry zone. The climate season significantly influenced dengue fever transmission, and a higher infection rate was found (odds ratio: 1.46, p < 0.01) in the northeast monsoon season. The findings of this study facilitate policymakers to improve the existing dengue control strategies focusing on the meteorological condition in the local as well as global perspectives.
BACKGROUND: Dengue, transmitted by Aedes mosquitoes, is a major public health problem in Sri Lanka. Weather affects the abundance, feeding patterns, and longevity of Aedes vectors and hence the risk of dengue transmission. We aimed to quantify the effect of weather variability on dengue vector indices in ten Medical Officer of Health (MOH) divisions in Kalutara, Sri Lanka. METHODS: Monthly weather variables (rainfall, temperature, and Oceanic Niño Index [ONI]) and Aedes larval indices in each division in Kalutara were obtained from 2010 to 2018. Using a distributed lag non-linear model and a two-stage hierarchical analysis, we estimated and compared division-level and overall relationships between weather and premise index, Breteau index, and container index. FINDINGS: From Jan 1, 2010, to Dec 31, 2018, three El Niño events (2010, 2015-16, and 2018) occurred. Increasing monthly cumulative rainfall higher than 200 mm at a lag of 0 months, mean temperatures higher than 31·5°C at a lag of 1-2 months, and El Niño conditions (ie, ONI >0·5) at a lag of 6 months were associated with an increased relative risk of premise index and Breteau index. Container index was found to be less sensitive to temperature and ONI, and rainfall. The associations of rainfall and temperature were rather homogeneous across divisions. INTERPRETATION: Both temperature and ONI have the potential to serve as predictors of vector activity at a lead time of 1-6 months, while the amount of rainfall could indicate the magnitude of vector prevalence in the same month. This information, along with knowledge of the distribution of breeding sites, is useful for spatial risk prediction and implementation of effective Aedes control interventions. FUNDING: None.
Dengue is endemic in Bangladesh and is an important cause of morbidity and mortality. Suppressing the mosquito vector activity at the optimal time annually is a practical strategy to control dengue outbreaks. The objective of this study was to estimate the monthly growth factor (GF) of dengue cases over the past 12 years as a means to identify the optimal time for a vector-control programme in Bangladesh. We reviewed the monthly cases reported by the Institute of Epidemiology, Disease Control and Research of Bangladesh during the period of January 2008-December 2019. We calculated the GF of dengue cases between successive months during this period and report means and 95% confidence intervals (CI). The median number of patients admitted to the hospital with dengue fever per year was 1554 (range: 375-101,354). The mean monthly GF of dengue cases was 1.2 (95% CI: 0.4-2.4). The monthly GF lower CI between April and July was > 1, whereas from September to November and January the upper CI was <1. The highest GF of dengue was recorded in June (mean: 2.4; 95% CI: 1.7-3.5) and lowest in October (mean: 0.43; 95% CI: 0.24-0.73). More than 81% (39/48) months between April and July for the period 2008-2019 had monthly GF >1 compared to 20% (19/96) months between August and March of the same period. The monthly GF was significantly correlated with monthly rainfall (r = 0.39) and monthly mean temperature (r = 0.30). The growth factor of the dengue cases over the last 12 years appeared to follow a marked periodicity linked to regional rainfall patterns. The increased transmission rate during the months of April-July, a seasonally determined peak suggests the need for strengthening a range of public health interventions, including targeted vector control efforts and community education campaigns.
Numerous studies on climate change and variability have revealed that these phenomena have noticeable influence on the epidemiology of dengue fever, and such relationships are complex due to the role of the vector—the Aedes mosquitoes. By undertaking a step-by-step approach, the present study examined the effects of climatic factors on vector abundance and subsequent effects on dengue cases of Dhaka city, Bangladesh. Here, we first analyzed the time-series of Stegomyia indices for Aedes mosquitoes in relation to temperature, rainfall and relative humidity for 2002–2013, and then in relation to reported dengue cases in Dhaka. These data were analyzed at three sequential stages using the generalized linear model (GLM) and generalized additive model (GAM). Results revealed strong evidence that an increase in Aedes abundance is associated with the rise in temperature, relative humidity, and rainfall during the monsoon months, that turns into subsequent increases in dengue incidence. Further we found that (i) the mean rainfall and the lag mean rainfall were significantly related to Container Index, and (ii) the Breteau Index was significantly related to the mean relative humidity and mean rainfall. The relationships of dengue cases with Stegomyia indices and with the mean relative humidity, and the lag mean rainfall were highly significant. In examining longitudinal (2001–2013) data, we found significant evidence of time lag between mean rainfall and dengue cases.
This study investigated the influence of climate factors on malaria incidence in the Sundargarh district, Odisha, India. The WEKA machine learning tool was used with two classifier techniques, Multi-Layer Perceptron (MLP) and J48, with three test options, 10-fold cross-validation, percentile split, and supplied test. A comparative analysis was carried out to ascertain the superior model among malaria prediction accuracy techniques in varying climate contexts. The results suggested that J48 had exhibited better skill than MLP with the 10-fold cross-validation method over the percentile split and supplied test options. J48 demonstrated less error (RMSE = 0.6), better kappa = 0.63, and higher accuracy = 0.71), suggesting it as most suitable model. Seasonal variation of temperature and humidity had a better association with malaria incidents than rainfall, and the performance was better during the monsoon and post-monsoon when the incidents are at the peak.
Meeting global and national malaria elimination targets requires identifying challenges as early as possible so that strategies can be modified to stay on track. This qualitative study of stakeholders who have a major influence on malaria programs across the Southeast Asian region, including those at a state level in India and at a national level in Cambodia, Myanmar, Thailand and Vietnam, shows that most believe Plasmodium falciparum malaria elimination targets are attainable, but are less optimistic for meeting Plasmodium vivax targets. Across these countries, stakeholders reported large variations in access to malaria diagnosis and treatment; the effectiveness of strategies for reaching migrants and hardto-serve populations; and securing sufficient numbers of skilled workers for both diagnosis and compliance with artemisinin-combination treatments and the need to optimise use of insecticides. Additionally, there was optimism about coordinated surveillance and response, but this was counterbalanced with a sense that national and regional collaboration opportunities have been missed. Climate change impacts were seen as a potential threat by all stakeholders in this study and in need of further research.
BACKGROUND: Climate and climate change affect the spatial pattern and seasonality of malaria risk. Season lengths and spatial extents of mapped current and future malaria transmission suitability predictions for Nepal were assessed for a combination of malaria vector and parasites: Anopheles stephensi and Plasmodium falciparum (ASPF) and An. stephensi and Plasmodium vivax (ASPV) and compared with observed estimates of malaria risk in Nepal. METHODS: Thermal bounds of malaria transmission suitability for baseline (1960-1990) and future climate projections (RCP 4.5 and RCP 8.5 in 2030 and 2050) were extracted from global climate models and mapped for Nepal. Season length and spatial extent of suitability between baseline and future climate scenarios for ASPF and ASPV were compared using the Warren’s I metric. Official 2010 DoHS risk districts (DRDs) and 2021 DoHS risk wards (DRWs), and spatiotemporal incidence trend clusters (ITCs) were overlaid on suitability season length and extent maps to assess agreement, and potential mismatches. RESULTS: Shifts in season length and extent of malaria transmission suitability in Nepal are anticipated under both RCP 4.5 and RCP 8.5 scenarios in 2030 and 2050, compared to baseline climate. The changes are broadly consistent across both future climate scenarios for ASPF and ASPV. There will be emergence of suitability and increasing length of season for both ASPF and ASPV and decreasing length of season for ASPV by 2050. The emergence of suitability will occur in low and no-risk DRDs and outside of high and moderate-risk DRWs, season length increase will occur across all DRD categories, and outside of high and moderate-risk DRWs. The high and moderate risk DRWs of 2021 fall into ITCs with decreasing trend. CONCLUSIONS: The study identified areas of Nepal where malaria transmission suitability will emerge, disappear, increase, and decrease in the future. However, most of these areas are anticipated outside of the government’s current and previously designated high and moderate-risk areas, and thus outside the focus of vector control interventions. Public health officials could use these anticipated changing areas of malaria risk to inform vector control interventions for eliminating malaria from the country, and to prevent malaria resurgence.
Increased levels of CO(2) and various greenhouse gases cause global warming and, in combination with pollutants from fossil fuel combustion and vehicular and industrial emissions, have been driving increases in noncommunicable diseases across the globe, resulting a higher mortality and morbidity. Respiratory diseases and associated allergenic manifestations have increased worldwide, with rates higher in developing countries. Pollen allergy serves as a model for studying the relationship between air pollution and respiratory disorders. Climate changes affect the quality and amount of airborne allergenic pollens, and pollutants alter their allergenicity, resulting in greater health impacts, especially in sensitized individuals.
RATIONALE: To date, there is no published local epidemiological evidence documenting the respiratory health effects of source specific air pollution in South Asia, where PM2.5 composition is different from past studies. Differences include more biomass and residue crop-burning emissions, which may have differing health implications. OBJECTIVES: We assessed PM2.5 associations with respiratory emergency department (ED) visits in a biomass-burning dominated high pollution region, and evaluated their variability by pollution source and composition. METHODS: Time-series regression modeling was applied to daily ED visits from January 2014 through December 2017. Air pollutant effect sizes were estimated after addressing long-term trends and seasonality, day-of-week, holidays, relative humidity, ambient temperature, and the effect modification by season, age, and sex. RESULTS: PM2.5 yielded a significant association with increased respiratory ED visits [0.84% (95% CI: 0.33%, 1.35%)] per 10 μg/m3 increase. The PM2.5 health effect size varied with season, the highest being during monsoon season, when fossil-fuel combustion sources dominated exposures. Results from a source-specific health effect analysis was also consistent with fossil-fuel PM2.5 having a larger effect size per 10 μg/m3 than PM2.5 from other sources [fossil-fuel PM2.5: 2.79% (0.33% to 5.31%), biomass-burning PM2.5: 1.27% (0% to 2.54%), and other-PM2.5: 0.95% (0.06% to 1.85%)]. Age-specific associations varied, with children and older adults being disproportionately affected by the air pollution, especially by the combustion-related particles. CONCLUSIONS: This study provided novel and important evidence that respiratory health in Dhaka is significantly affected by particle air pollution, with a greater health impact by fossil-fuel combustion derived PM2.5.
A large concern with estimates of climate and health co-benefits of “clean” cookstoves from controlled emissions testing is whether results represent what actually happens in real homes during normal use. A growing body of evidence indicates that in-field emissions during daily cooking activities differ substantially from values obtained in laboratories, with correspondingly different estimates of co-benefits. We report PM(2.5) emission factors from uncontrolled cooking (n = 7) and minimally controlled cooking tests (n = 51) using traditional chulha and angithi stoves in village kitchens in Haryana, India. Minimally controlled cooking tests (n = 13) in a village kitchen with mixed dung and brushwood fuels were representative of uncontrolled field tests for fine particulate matter (PM(2.5)), organic and elemental carbon (p > 0.5), but were substantially higher than previously published water boiling tests using dung or wood. When the fraction of nonrenewable biomass harvesting, elemental, and organic particulate emissions and modeled estimates of secondary organic aerosol (SOA) are included in 100 year global warming commitments (GWC(100)), the chulha had a net cooling impact using mixed fuels typical of the region. Correlation between PM(2.5) emission factors and GWC (R(2) = 0.99) implies these stoves are climate neutral for primary PM(2.5) emissions of 8.8 ± 0.7 and 9.8 ± 0.9 g PM(2.5)/kg dry fuel for GWC(20) and GWC(100), respectively, which is close to the mean for biomass stoves in global emission inventories.
Despite low per capita emissions, with over a billion population, India is pivotal for climate change mitigation globally, ranking as the third largest emitter of greenhouse gases. We linked a previously published multidimensional population projection with emission projections from an integrated assessment model to quantify the localised (i.e. state-level) health benefits from reduced ambient fine particulate matter in India under global climate change mitigation scenarios in line with the Paris Agreement targets and national scenarios for maximum feasible air quality control. We incorporated assumptions about future demographic, urbanisation and epidemiological trends and accounted for model feedbacks. Our results indicate that compared to a business-as-usual scenario, pursuit of aspirational climate change mitigation targets can avert up to 8.0 million premature deaths and add up to 0.7 years to life expectancy (LE) at birth due to cleaner air by 2050. Combining aggressive climate change mitigation efforts with maximum feasible air quality control can add 1.6 years to LE. Holding demographic change constant, we find that climate change mitigation and air quality control will contribute slightly more to increases in LE in urban areas than in rural areas and in states with lower socio-economic development.
This research was carried out to analyze variations in indoor and outdoor ozone concentrations and their health impact on local communities of megacities in Pakistan. For indoor ozone measurements, industrial units of an economic zone, Hattar Industrial Estate, Haripur, KPK, Pakistan, were selected. For outdoor ozone measurements, maximum and minimum peaks from different selected stations of three megacities (Islamabad, Abbottabad, and Haripur Hattar) in Pakistan were analyzed for paired comparisons. The tropospheric ozone levels were measured with the help of a portable SKY 2000-WH-O-3 meter from December 2018 to November 2019. According to the findings of this investigation, the indoor ozone concentrations at Hattar Industrial Estate exceeded the permissible limit devised by the WHO. The highest concentration (0.37 ppm) was recorded in the month of May in the food industry, while the lowest concentration (0.00 ppm) was recorded in the cooling area of the steel industry in the month of December. For outdoor ozone concentrations, the maximum concentration (0.23 ppm) was detected in Islamabad in the month of March 2019, whereas the rest of year showed comparatively lower concentrations. In Haripur, the maximum concentration (0.22 ppm) was detected in the month of February 2019 and a minimum concentration (0.11 ppm) was found in the month of November 2019. In Abbottabad, the maximum concentration (0.21 ppm) was detected in the month of March 2019 and the minimum concentration was 0.082 ppm. Increasing tropospheric ozone levels might be harmful for local communities and industrial laborers in the winter season because of the foggy weather. In the Abbottabad and Hattar regions, since COVID infection is indirectly related to low temperature and high emission of gases may compromise the respiratory systems of humans. The results of the present study were shared with industrialists to set precautions for ambient air quality and support the adoption of low emission techniques in industries for the safety of labour and nearby residents.
Pakistan ranks third in the world in terms of mortality attributable to air pollution, with aerosol mass concentrations (PM2.5) consistently well above WHO (World Health Organization) air quality guidelines (AQG). However, regulation is dependent on a sparse network of air quality monitoring stations and insufficient ground data. This study utilizes long-term observations of aerosols and trace gases to characterize and rank the air pollution scenarios and pollution characteristics of 80 selected cities in Pakistan. Datasets used include (1) the Aqua and Terra (AquaTerra) MODIS (Moderate Resolution Imaging Spectmradiometer) Level 2 Collection 6.1 merged Dark Target and Deep Blue (DTB) aerosol optical depth (AOD) retrieval products; (2) the CAMS (Copernicus Atmosphere Monitoring Service) reanalysis PM1, PM2.5, and PM10 data; (3) the MERRA-2 (Modern-Era Retrospective analysis for Research and Applications, Version 2) reanalysis PM2.5 data, (4) the OMI (Ozone Monitoring Instrument) tropospheric vertical column density (TVCD) of nitrogen dioxide (NO2), and VCD of sulfur dioxide (SO2) in the Planetary Boundary Layer (PBL), (5) the VIIRS (Visible Infrared Imaging Radiometer Suite) Nighttime Lights data, (6) MODIS Collection 6 Version 2 global monthly fire location data (MCD14ML), (7) population density, (8) MODIS Level 3 Collection 6 land cover types, (9) AERONET (AErosol RObotic NETwork) Version 3 Level 2.0 data, and (10) ground-based PM2.5 concentrations from air quality monitoring stations. Potential Source Contribution Function (PSCF) analyses were performed by integrating with ground-based PM2.5 concentrations and the NOAA (National Oceanic and Atmospheric Administration) HYSPLIT (Hybrid Single-Particle Lagrangian Integrated Trajectory) air parcel back trajectories to identify potential pollution source areas which are responsible for extreme air pollution in Pakistan. Results show that the ranking of the top polluted cities depends on the type of pollutant considered and the metric used.For example, Jhang, Multan, and Vehari were characterized as the top three polluted cities in Pakistan when considering AquaTerra DTB AOD products; for PM1, PM2.5, and PM10 Lahore, Gujranwala, and Okara were the top three; for tropospheric NO2 VCD Lahore, Rawalpindi, and Islamabad and for PBL SO2 VCD Lahore, Mirpur, and Gujranwala. The results demonstrate that Pakistan’s entire population has been exposed to high PM2.5 concentrations for many years, with a mean annual value of 54.7 mu g/m(3), over all Pakistan from 2003 to 2020.This value exceeds Pakistan’s National Environmental Quality Standards (Pak-NEQS, i.e., <15 mu g/m(3) annual mean) for ambient air defined by the Pakistan Environmental Protection Agency (Pak-EPA) as well as the WHO Interim Target-1 (i.e., mean annual PM2.5 < 35 mu g/m(3)).The spatial analyses of the concentrations of aerosols and trace gases in terms of population density, nighttime lights, land cover types, and fire location data, and the PSCF analysis indicate that Pakistan's air quality is strongly affected by anthropogenic sources inside of Pakistan, with contributions from surrounding countries.Statistically significant positive (increasing) trends in PM1, PM2. 5, PM10, tropospheric NO2 VCD, and SO2 VCD were observed in similar to 89%, similar to 67%, similar to 48%, 91%, and similar to 88% of the Pakistani cities (80 cities), respectively. This comprehensive analysis of aerosol and trace gas levels, their characteristics in spatio-temporal domains, and their trends over Pakistan, is the first of its kind. Results will be helpful to the Ministry of Climate Change (Government of Pakistan), Pak-EPA, SUPARCO (Pakistan Space and Upper Atmosphere Research Commission), policymakers, and the local research community to mitigate air pollution and its effects on human health.
This paper examines the effect of biomass burning on adolescent health in India. The biomass burning problem is quite acute especially in North India, with some states experiencing forest fires and few states actively engaging in crop burning practice. We combine remote sensing data on biomass burning events with a pan-India survey on teenage girls (TAG survey). We exploit regional and temporal variation in our data to establish the link between occurrence of extremely high levels of biomass burning during early life and adolescent height for girls in India. Our results indicate that exposure to extremely high level of biomass burning during prenatal and postnatal period is associated with lower height (by 0.7 percent or 1.07 cm) later in life. Girls from North India are found to be especially vulnerable to the harmful effects of exposure to biomass burning. (c) 2021 Elsevier B.V. All rights reserved.
Smoke from wildfires is a growing health risk across the US. Understanding the spatial and temporal patterns of such exposure and its population health impacts requires separating smoke-driven pollutants from non-smoke pollutants and a long time series to quantify patterns and measure health impacts. We develop a parsimonious and accurate machine learning model of daily wildfire-driven PM(2.5) concentrations using a combination of ground, satellite, and reanalysis data sources that are easy to update. We apply our model across the contiguous US from 2006 to 2020, generating daily estimates of smoke PM(2.5) over a 10 km-by-10 km grid and use these data to characterize levels and trends in smoke PM(2.5). Smoke contributions to daily PM(2.5) concentrations have increased by up to 5 μg/m(3) in the Western US over the last decade, reversing decades of policy-driven improvements in overall air quality, with concentrations growing fastest for higher income populations and predominantly Hispanic populations. The number of people in locations with at least 1 day of smoke PM(2.5) above 100 μg/m(3) per year has increased 27-fold over the last decade, including nearly 25 million people in 2020 alone. Our data set can bolster efforts to comprehensively understand the drivers and societal impacts of trends and extremes in wildfire smoke.
Amid worsening climate change, the recurrent wildfires have substantially worsened air quality in the Western United States (U.S.). Understanding the knowledge, attitudes, perception, and practices (KAPP) over time in response to natural disasters such as wildfires is crucial for public health interventions and disaster preparedness. This is the first study to investigate the change in air quality KAPP over time in response to natural disasters. Previous studies have only assessed KAPP at a fixed time point. Using a two-wave panel survey (during and post-wildfires), we assessed the association between KAPP and respiratory health indicators as well as the changes over time in 212 participants in the U.S. Between the two waves, we found a significant 8% increase in knowledge, which was mainly driven by participants in areas unaffected by the wildfires. In addition, we found differential associations between KAPP and respiratory health indicators between areas affected and unaffected by the wildfires. These findings suggest that experiencing wildfires may affect KAPP and more longitudinal studies are warranted, particularly during periodic air quality crises.
The common cold is a leading cause of morbidity and contributes significantly to the health costs in Bhutan. The study utilized multivariate Zero-inflated Poisson regression in a Bayesian framework to identify climatic variability and spatial and temporal patterns of the common cold in Bhutan. There were 2,480,509 notifications of common cold between 2010 and 2018. Children aged < 15 years were twice (95% credible interval [CrI] 2.2, 2.5) as likely to get common cold than adults, and males were 12.4% (95 CrI 5.5%, 18.7%) less likely to get common cold than females. A 10 mm increase in rainfall lagged one month, and each 1 °C increase of maximum temperature was associated with a 5.1% (95% CrI 4.2%, 6.1%) and 2.6% (95% CrI 2.3%, 2.8%) increase in the risk of cold respectively. An increase in elevation of 100 m and 1% increase in relative humidity lagged three months were associated with a decrease in risk of common cold by 0.1% (95% CrI 0.1%, 0.2%) and 0.3% (95% CrI 0.2%, 0.3%) respectively. Seasonality and spatial heterogeneity can partly be explained by the association of common cold to climatic variables. There was statistically significant residual clustering after accounting for covariates. The finding highlights the influence of climatic variables on common cold and suggests that prioritizing control strategies for acute respiratory infection program to subdistricts and times of the year when climatic variables are associated with common cold may be an effective strategy.
This study examines point and non-point sources of air pollution and particulate matter and their associated socioeconomic and health impacts in South Asian countries, primarily India, China, and Pakistan. The legislative frameworks, policy gaps, and targeted solutions are also scrutinized. The major cities in these countries have surpassed the permissible limits defined by WHO for sulfur dioxide, carbon monoxide, particulate matter, and nitrogen dioxide. As a result, they are facing widespread health problems, disabilities, and causalities at extreme events. Populations in these countries are comparatively more prone to air pollution effects because they spend more time in the open air, increasing their likelihood of exposure to air pollutants. The elevated level of air pollutants and their long-term exposure increases the susceptibility to several chronic/acute diseases, i.e., obstructive pulmonary diseases, acute respiratory distress, chronic bronchitis, and emphysema. More in-depth spatial-temporal air pollution monitoring studies in China, India, and Pakistan are recommended. The study findings suggest that policymakers at the local, national, and regional levels should devise targeted policies by considering all the relevant parameters, including the country’s economic status, local meteorological conditions, industrial interests, public lifestyle, and national literacy rate. This approach will also help design and implement more efficient policies which are less likely to fail when brought into practice.
Mountainous regions are highly hazardous, and these hazards often lead to loss of human life. The Hindu Kush Himalaya (HKH), like many mountainous regions, is the site of multiple and overlapping natural hazards, but the distribution of multi-hazard risk and the populations exposed to it are poorly understood. Here, we present high-resolution transboundary models describing susceptibility to floods, landslides, and wildfires to understand population exposure to multi-hazard risk across the HKH. These models are created from historical remotely sensed data and hazard catalogs by the maximum entropy (Maxent) machine learning technique. Our results show that human settlements in the HKH are disproportionately concentrated in areas of high multi-hazard risk. In contrast, low-hazard areas are disproportionately unpopulated. Nearly half of the population in the region lives in areas that are highly susceptible to more than one hazard. Warm low-altitude foothill areas with perennially moist soils were identified as highly susceptible to multiple hazards. This area comprises only 31% of the study region, but is home to 49% of its population. The results also show that areas susceptible to multiple hazards are also major corridors of current migration and urban expansion, suggesting that current rates and patterns of urbanization will continue to put more people at risk. This study establishes that the population in the HKH is concentrated in areas susceptible to multiple hazards and suggests that current patterns of human movement will continue to increase exposure to multi-hazards in the HKH.
Several countries have been affected by natural hazards during the COVID-19 pandemic. The combination of the pandemic and natural hazards has led to serious challenges that include financial losses and psychosocial stress. Additionally, this compound disaster affected evacuation decision making, where to evacuate, volunteer participation in mitigation and recovery, volunteer support acceptance, and interest in other hazard risks. This study investigated the impact of COVID-19 on disaster response and recovery from various types of hazards, with regard to preparedness, evacuation, volunteering, early recovery, awareness and knowledge of different types of hazards, and preparedness capacity development. This study targets hazards such as Cyclone Amphan in India, the Kumamoto flood in Japan, Typhoon Rolly in the Philippines, and the California wildfires in the U.S. This study made several recommendations, such as the fact that mental health support must be taken into consideration during COVID-19 recovery. It is necessary to improve the genral condition of evacuation centers in order to encourage people to act immediately. A pandemic situation necessitates a strong communication strategy and campaign with particular regard to the safety of evacuation centers, the necessity of a lockdown, and the duration required for it to reduce the psychological impact. Both national and local governments are expected to strengthen their disaster risk reduction (DRR) capacity, which calls for the multi-hazard management of disaster risk at all levels and across all sectors.
In the present scenario, tick-borne diseases (TBDs) are well known for their negative impacts on humans as well as animal health in India. The reason lies in their increased incidences due to global warming, environmental and ecological changes, and availability of suitable habitats. On a global basis, they are now considered a serious threat to human as well as livestock health. The major tick-borne diseases in India include Kyasanur forest disease (KFD), Crimean-congo hemorrhagic fever (CCHF), Lyme disease (LD), Q fever (also known as coxiellosis), and Rickettsial infections. In recent years, other tick-borne diseases such as Babesiosis, Ganjam virus (GANV), and Bhanja virus (BHAV) infections have also been reported in India. The purpose of this paper is to review the history and the current state of knowledge of tick-borne diseases in the country. The conclusion of this review is extending the requirement of greater efforts in research and government management for the diagnosis and treatment and as well as prevention of these diseases so that tick-borne disease burden should be minimizing in India.
Climate change is expected to have severe consequences for the world, some of which are already being felt. According to projections, in some regions, droughts will be more frequent and intense in the 21st century. This calls for purposeful interventions by governments to mitigate the impacts. Drought-affected communities are more vulnerable to famine. The effects of drought are felt in people’s education levels, nutrition, health, sanitation, and women and the safety of children in these communities. The impact of drought can be seen in the livelihoods of people affected by it. Against this backdrop, there is the need to document the effects of drought on women and children’s health in the affected communities. Such a study calls for a systematic approach. This study explores the various dimensions of the effects of droughts. It accessed electronic databases, including Google Scholar, Scopus, Pub-Med, JSTOR to identify a substantial number of studies using key words and expressions. To begin with, the word drought was kept constant in all combinations of keywords and phrases. The search was then refined by using the word drought with keywords, such as livelihood, vulnerability, sustainable development, adaption and mitigation, migration, health impact, and risk management to search the required articles. Only studies conducted in the period 2000 – 2019 were considered for this review. The review’s findings show that due to a lack of water during a drought, the burden of work on women and children increased considerably. Most faced severe health issues like malnutrition and anemia. The livelihoods of women were also affected because of which they were forced to adopt various strategies to overcome the problems posed by droughts. Droughts occur every year in different parts of India. Actions are required to mitigate the effects of drought, including the provision of drinking water, food, aid and relief aid to distressed farmers, employment support, support for changes in livelihoods, water security, and drought-proofing. State policies and actions must give particular attention to women and children because they are the most vulnerable. Employment-generation actions should also include youth by providing appropriate training for developing appropriate skills.
Bangladesh’s unique climate vulnerability is well-investigated but the mental health impacts of climate change remain relatively unexplored. Three databases were searched for English primary qualitative studies published between 2000 and 2020. Out of 1202 publications, 40 met the inclusion criteria. This systematic review applies a systems approach to further understand Bangladesh’s ‘climate-wellbeing’ network. The literature indicates diverse factors linking environmental stress and mental ill-health including four key themes: (1) post-hazard mental health risks, (2) human (im)mobility, (3) social tension and conflict, and (4) livelihood loss and economic hardship. This systems analysis also revealed that people’s mental wellbeing is strongly mediated by socio-economic status and gender. The article illustrates how multiple pathways may amplify stress, anxiety, violence, and psychological damage. Greater recognition of the ‘climate-wellbeing’ connections, and incorporation of mental health in current climate action and policy frameworks, will be an effective way to achieve a more sustainable future.
Kerala is one of India’s most vulnerable states in India when it comes to climate-induced disasters. Kerala’s public health department grappled with a flood of unprecedented magnitude in August 2018. Situating the flood in the context of Kerala’s state and society, this paper addresses three questions: What was the level of flood-prevention preparedness? What were the public health effects and how were they managed? Finally, what policy lessons were learned? Drawing from reports of relevant national and state agencies responsible for disaster management as well as first-hand accounts of nongovernmental organizations and media coverage, this paper argues that while Kerala’s flood-prevention preparedness was far from ideal, its postflood response in mounting a rapid and effective rescue and relief operation as well as in preventing a public health crisis was commendable. The paper also shows that impressive achievements in climate-disaster health management can be achieved through a decentralized and participatory public health system in which coordinated public action is managed by a capacious state with the active collaboration of civil society.
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.
The Nepali population is among those most vulnerable to the health impacts of climate change. We conducted a systematic literature review to document the health effects of climate change in Nepal and identify knowledge gaps by examining vulnerability categories related to health. Three databases were searched for journal articles that addressed health and vulnerability related to climate change in Nepal from 2010 onwards. Of the 1063 articles identified, 37 were eligible for inclusion. The findings suggested the health of the population was affected mostly by food insecurity, floods, droughts, and reduced water levels. Studies revealed both morbidity and mortality increased due to climate change, with the most impacted populations being women, children, and the elderly. At greatest risk for impacts from climate change were those from poor and marginal populations, especially impoverished women. The public health sector, healthcare, and potable water sources were some of the least mentioned vulnerability subcategories, indicating more research is needed to better understand their adaptation capacities. We propose that identifying vulnerabilities and areas of limited research are critical steps in the prioritization of health policy and interventions for the most vulnerable populations in Nepal.
To protect public health, heat-related policies are increasingly being adopted by city authorities to address the unequal impact of heatwaves. Ahmedabad’s Heat Action Plan (HAP) is an acclaimed and successful policy response in India and beyond. While the pilot evaluation of the initiative suggests that almost a thousand deaths were avoided annually after its implementation, it is not yet clear whose lives were saved, and to what extent this statistic was due to the HAP, rather than other factors. By reviewing the published and grey literature centering on the HAP target groups, outreach strategies, and impacts on urban services, this paper points out major knowledge gaps concerning the potentials and impacts of the HAP, which may lead to the systematical exclusion of vulnerable and disadvantaged groups from the intended benefits. In this paper, it is argued that the effectiveness and inclusiveness of the HAP predominantly depend on its integration into urban development projects, which is a challenging task given the existing horizontal and vertical fragmentation in the planning of city projects. Moreover, urban plans and policies, including the HAP, are shown to be overly focused on technology, and as a consequence, they do not realize their limited scope in addressing the associated issues, which are fundamentally social, deep, and structural, such as spatial inequality in Indian cities.
Although Nepal is a country rich in natural beauty, along with an abundance of natural resources, the children of this diverse nation still face several serious health issues arising from their own environment (water pollution, air pollution, chemical pollution, solid waste issues and drainage issues). Nepal also ranks as a highly vulnerable country to the adverse impacts of climate change. Children are more vulnerable to various infections for immunological, physiological and social reasons. Their inherent immunity diminishes within months after birth. There are risk factors for the development of various diseases, e.g. unsafe drinking water and lack of sanitation, which contribute to diarrheal diseases, trachoma, hookworm and amoebic dysentery; another risk factor is indoor air pollution. The infant mortality rate (IMR) is higher in rural areas with 55 per 1000 live births, compared to urban areas with 38 per 1000 live births. Likewise, the under-5-year-old mortality rate (MR) in rural areas is 64 and that in urban areas is 45 per 1000 live births. Around 12% of the population suffer from chronic respiratory diseases, according to a recent study exploring the situation in Kathmandu. Pneumonia is a leading cause of mortality among children under 5 years of age in Nepalese hospitals. Children under 5 are more prone to the ill effects of polluted environments because of their less well-developed immune system. In addition, the school environment is not sufficiently healthy due to the distribution of unsafe drinking water and poor sanitation supply systems. In Nepal, mainly in the 20 Terai districts, arsenic contamination of groundwater is a public health problem. Underground water is used as drinking water in those areas, but without purification – the estimate is that around 0.5 million people live at the risk of arsenic poisoning. Within a span of 200 km from north to south, the climate of Nepal varies from arctic to tropical. The annual average air pollution concentration is 5 times above the World Health Organization (WHO) air quality guidelines, which poses a serious health risk to hundreds of thousands of Nepalese people: 133 out of 1,000,000 deaths each year are related to air pollution. Dramatically, Kathmandu city is a silent killer to walk around due to air pollution, and its air quality is ranked as the worst out of 180 countries, according to the 2018 Environmental Performance Index. However, insufficient studies have been conducted to explore children’s environmental health issues. It is therefore essential to carry out more scientific studies to explore the issues of children’s environmental health as environmental health problems in children are serious in the Nepalese context.
Climate variability is heavily impacting human health all around the globe, in particular, on residents of developing countries. Impacts on surface water and groundwater resources and water-related illnesses are increasing, especially under changing climate scenarios such as diversity in rainfall patterns, increasing temperature, flash floods, severe droughts, heatwaves and heavy precipitation. Emerging water-related diseases such as dengue fever and chikungunya are reappearing and impacting on the life of the deprived; as such, the provision of safe water and health care is in great demand in developing countries to combat the spread of infectious diseases. Government, academia and private water bodies are conducting water quality surveys and providing health care facilities, but there is still a need to improve the present strategies concerning water treatment and management, as well as governance. In this review paper, climate change pattern and risks associated with water-related diseases in developing countries, with particular focus on Pakistan, and novel methods for controlling both waterborne and water-related diseases are discussed. This study is important for public health care, particularly in developing countries, for policy makers, and researchers working in the area of climate change, water quality and risk assessment.
As the world deals with COVID-19, there is increasing attention to the threat of emerging and re-emerging infectious diseases. India is especially vulnerable to climate-induced health risks and a hotspot for infectious diseases. In this study we use a scoping review to synthesize evidence on the impact of climate on infectious diseases. We use this to uncover gaps and understand the implications for policymaking and health system preparedness. There is a strong evidence base linking climate change to disease outbreaks, both directly and indirectly. Socio-economic factors are the modifiers that determine disease severity in different populations and locations.
Efforts have been made to quantify the spatio-temporal malaria transmission intensity over India using the dynamical malaria model, namely, Vector-borne Disease Community Model of International Centre for Theoretical Physics Trieste (VECTRI). The likely effect of climate change in the variability of malaria transmission intensity over different parts of India is also investigated. The Historical data and future projection scenarios of the rainfall and temperature derived from the Coupled Model Intercomparison Project Phase 5 (CMIP5) model output are used for this purpose. The Entomological Inoculation Rate (EIR) and Vector are taken as quantifiers of malaria transmission intensity. It is shown that the maximum number of malaria cases over India occur during the Sept-Oct months, whereas the minimum during the Feb-Apr months. The malaria transmission intensity as well as length of transmission season over India is likely to increase in the future climate as a result of global warming.
Over the last decade, several flood early warning systems have been established in Nepal, helping reduce the number of people affected and killed by floods. However, there are still challenges in communicating flood warning to the most vulnerable. The unavailability of real-time monitoring in smaller streams and tributaries has created challenges for communicating early warning. The ongoing restructuring process of the multilevel governance system in the country also presents challenges, specifically institutional such as insufficient coordination among relevant agencies, lack of adequate personnel, limited budget, and unclear roles and responsibilities. This study uses the Alexander framework (2015) to identify gaps in flood early warning communication in relation to their technical, institutional and socio-cultural components. Qualitative research methods in the form of key informant interviews and on-site focus group discussions were conducted at the national, district and local levels to collect data, taking Ratu watershed as a case study. Based on our analysis, we conclude that, first, while progress has been made in the monitoring and forecasting of floods, integration of socio-cultural aspects that can make early warning information accessible to the most vulnerable has to be strengthened. Second, warning messages need to be co-designed with communities and tailored to meet their diverse needs for proper dissemination and timely protective action. Finally, for flood risk communication to bridge ‘the last mile’ in terms of reaching the most vulnerable in the community must take account of their distinct social, economic and political experiences in both content and delivery of the information.
Poverty and discrimination compound vulnerability to disasters. Yet, people who experience these are some of the least involved groups in Disaster Risk Reduction (DRR) dialogue and research. This study aims to fill that gap by narrating the lived experience of underprivileged flood-affected communities. We conducted in-depth interviews (N = 48) with community members (n = 36) and staff members of collaborating non-governmental organisations (n = 12). We also conducted focus group discussions with staff members of the same NGOs. The results describe how systemic issues entrenched with socio-economic and cultural factors impact a community?s ability to prepare for floods. These communities received no warning or timely evacuation messages, and perceived the received support as inadequate and unfair. Communities recovered through their resourcefulness and thoughtfulness. They resented the government for its lack of action throughout the disaster cycle. Priorities for future efforts involve actively engaging these vulnerable groups and tailoring DRR activities for them.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease represents the causative agent with a potentially fatal risk which is having great global human health concern. Earlier studies suggested that air pollutants and meteorological factors were considered as the risk factors for acute respiratory infection, which carries harmful pathogens and affects the immunity. The study intended to explore the correlation between air pollutants, meteorological factors, and the daily reported infected cases caused by novel coronavirus in India. The daily positive infected cases, concentrations of air pollutants, and meteorological factors in 288 districts were collected from January 30, 2020, to April 23, 2020, in India. Spearman’s correlation and generalized additive model (GAM) were applied to investigate the correlations of four air pollutants (PM(2.5), PM(10), NO(2), and SO(2)) and eight meteorological factors (Temp, DTR, RH, AH, AP, RF, WS, and WD) with COVID-19-infected cases. The study indicated that a 10 ?g/m(3) increase during (Lag0-14) in PM(2.5), PM(10), and NO(2) resulted in 2.21% (95%CI: 1.13 to 3.29), 2.67% (95% CI: 0.33 to 5.01), and 4.56 (95% CI: 2.22 to 6.90) increase in daily counts of Coronavirus Disease 2019 (COVID 19)-infected cases respectively. However, only 1 unit increase in meteorological factor levels in case of daily mean temperature and DTR during (Lag0-14) associated with 3.78% (95%CI: 1.81 to 5.75) and 1.82% (95% CI: -1.74 to 5.38) rise of COVID-19-infected cases respectively. In addition, SO(2) and relative humidity were negatively associated with COVID-19-infected cases at Lag0-14 with decrease of 7.23% (95% CI: -10.99 to -3.47) and 1.11% (95% CI: -3.45 to 1.23) for SO(2) and for relative humidity respectively. The study recommended that there are significant correlations between air pollutants and meteorological factors with COVID-19-infected cases, which substantially explain the effect of national lockdown and suggested positive implications for control and prevention of the spread of SARS-CoV-2 disease.
INTRODUCTION: Enteric Fever (EF) affects over 14.5 million people every year globally, with India accounting for the largest share of this burden. The water-borne nature of the disease makes it prone to be influenced as much by unsanitary living conditions as by climatic factors. The detection and quantification of the climatic effect can lead to improved public health measures which would in turn reduce this burden. METHODOLOGY: We obtained a list of monthly Widal positive EF cases from 1995 to 2017 from Ahmedabad and Surat Municipalities. We obtained population data, daily weather data, and Oceanic Niño Index values from appropriate sources. We quantified the association between extreme weather events, phases of El Niño Southern Oscillations (ENSO) and incidence of EF. RESULTS: Both cities showed a seasonal pattern of EF, with cases peaking in early monsoon. Risk of EF was affected equally in both cities by the monsoon season — Ahmedabad (35%) and Surat (34%). Extreme precipitation was associated with 5% increase in EF in Ahmedabad but not in Surat. Similarly, phases of ENSO had opposite effects on EF across the two cities. In Ahmedabad, strong El Niño months were associated with 64% increase in EF risk while strong La Niña months with a 41% reduction in risk. In Surat, strong El Niño was associated with 25% reduction in risk while moderate La Niña with 21% increase in risk. CONCLUSIONS: Our results show that the risk of EF incidence in Gujarat is highly variable, even between the two cities only 260 kms apart. In addition to improvements in water supply and sewage systems, preventive public health measures should incorporate variability in risk across season and phases of ENSO. Further studies are needed to characterize nationwide heterogeneity in climate-mediated risk, and to identify most vulnerable populations that can benefit through early warning systems.
The surface water is a significant feature in the hydrological system and is a vital compound for life growth. Assessment of trace elements in the water bodies is essential since it poses huge threats to aquatic organisms and humans if present in high concentrations. This study was carried out to assess the seasonal changes in the dissolved trace elements concentration in Bhavani river, which is one of the major rivers of Tamil Nadu, southern India and also to assess the human health risk due to its consumption. A total of 46 surface water samples were collected along the river during pre-monsoon and post-monsoon of 2018 and were analyzed for various trace elements such as Zn, Cu, Fe, Ni, and Pb. The variation in trace element concentration is observed spatially, where higher concentration is found in samples from agricultural and urban areas than the samples from the undisturbed natural-mountain terrains. The results highlighted that the concentrations of trace elements differ temporally where the concentration is greater during the monsoon due to increased discharge of sewage and agricultural run off to the river. Multivariate statistical analysis indicates stronger relationship between trace elements and other physio-chemical parameters hinting that natural and anthropogenic sources alters the riverine chemistry. Thus, the rainfall-runoff characteristics along with lithology, topography, and landuse of the basin plays a dominant role in the seasonal variation of dissolved trace elements. The water quality index value shows “good/excellent” during pre-monsoon and “marginal/fair” during monsoon season and the Heavy Metal Pollution Index values were also low during both the seasons. The river water samples which defy these indices were found to be either from urban or agricultural lands. The oral and dermal ingestion health risk to adults was assessed, which indicates that the risks posed to humans by consumption of water were minimal. The trace metal concentration of the river was then compared with the other rivers of world and India, where it shows that Zn, Cu, and Ni concentration was higher in Bhavani than in most of the rivers. Thus, the study highlighted that the urban settlements and agricultural lands have a considerable influence on river quality thereby triggering the increase in trace element concentrations. Therefore, the study necessitates on the continuous monitoring of river along with adoption of stringent discharge protocols.
Secure potable water is indispensable to life. The presence of salinity in potable water has become a serious problem worldwide and it is essential to ensure secure potable water, particularly in the coastal areas of Bangladesh. In this work, 48 (forty-eight) harvested rainwater samples were assessed from Upazila (sub-district) of Mongla and Sarankhola, Bagerhat district, Bangladesh during the monsoon (May) and post-monsoon (October) periods. The objective was to examine the effect of seasonal variations on the quality of harvested rainwater. The harvested rainwater was analyzed for fecal coliform, total coliform, lead (Pb), zinc (Zn), pH, and turbidity. The mean pH in monsoon and post-monsoon periods was 6.93 and 7.24, respectively, which was within both the WHO guideline and Bangladesh Drinking Standard. In the monsoon season, turbidity levels in samples met the Bangladesh water quality standard but 10% of the harvested rainfall samples had Pb levels that exceeded the WHO drinking water limit. The turbidity of harvested rainwater in post-monsoon exceeded the WHO and Bangladesh Drinking Standard by 21% (10 out of 48) and 6% (3 out of 48), respectively. The fecal coliform of harvested rainwater exceeded both WHO and Bangladesh Drinking Standard by 56% (27 out of 48) and 67% (32 out of 48) in the monsoon and post-monsoon, correspondingly. Conversely, total coliform of harvested rainwater exceeded both the WHO and Bangladesh Drinking Standard by 67% (32 out of 48) and 79% (38 out of 48), accordingly in the monsoon and post-monsoon seasons. The Zn was below the WHO and Bangladesh Drinking Standard but Pb exceeded the WHO guideline in the monsoon and post-monsoon by 15% (7 out of 48) and 17% (8 out of 48), respectively. Pb is toxic to humans and children are especially vulnerable. The harvested rainwater should be treated effectively to reduce the toxicity and danger posed by Pb, fecal coliform, and total coliform before it is fit for drinking purposes.
Urban green spaces (UGS) are known for providing a cooling effect by evapotranspiration, shade, and by altering the albedo. Heat mitigation by UGS reduces the space cooling demand, provides comfort, and enhances productivity. Rapid urbanization in developing countries has resulted in dwindling green spaces and their protective role is often neglected. We have quantified the heat mitigation by UGS using the InVEST model (Integrated Valuation of Ecosystem Services and Trade-offs) for present and future scenarios of Nagpur City which is situated in a heatwave-affected zone. Four future plausible scenarios were generated with a combination of drivers-economic development and commitment to promoting UGS, using the two-axis scenario analysis method. The simulated UGS in each future scenario (by allowing 10% variation in the land use) is utilized for quantification of heat mitigation and energy conserved. In comparison with the present situation, 21-29% less space cooling energy is conserved in scenarios driven by economic development (least commitment to UGS), whereas 17% more energy is conserved when UGS are promoted. In similar lines, the average temperature is increased by 0.5-0.7 degrees C when UGS are neglected, while the temperature dropped by 0.5 degrees C when UGS are promoted in Nagpur City. The methodology presents an integration of scenario analysis with heat mitigation modeling which can enable urban planners and researchers to improve their understanding of the ecological structure of urban centers and can aid in appreciating the potential of UGS in heat mitigation for human wellbeing.
Globally, mountain systems are unevenly exposed to risks of extreme precipitation. Within the Himalayan region, precipitation extremes are a rising concern, but their current understanding is limited. In this study, we use 113?years of precipitation data to rank and characterize precipitation extremes in the Indian Western Himalayas (IWH). Our statistical ranking method integrates precipitation spatial extent and its intensity across different durations for determining the severity of extreme events. The proposed ranking method accounts for multi-day duration ranking method to capture persistent precipitation episodes. Results show that the method accurately detects and ranks the most extreme precipitation events that occurred in the IWH and indicate locations of these events. Our results highlight that critical long duration events in the region (e.g., 10?days) are missed at ranks at shorter duration (e.g., 2–3?days), thereby highlighting the importance to multi-day precipitation extremes ranking. In addition, the proposed ranking method provides information about the event duration that will be associated with the highest impact on society, carrying high significance. Our findings are valuable for flood risk management and disaster risk reduction.
BACKGROUND: 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.
Cryptosporidium is a water-borne zoonotic parasite worldwide, usually found in lakes and rivers contaminated with sewage and animal wastes, causing outbreaks of cryptosporidiosis. In this study, 300 water samples were collected from four designated places of flood-affected district Nowshera consist of different water sources to find out the prevalence of Cryptosporidium via polymerase chain reaction (PCR). The overall prevalence of Cryptosporidium was 30.33% (91/300) with more prevalent 44% in drain water and low 5% in bore/tube well water. The prevalence in open well and tap water was recorded 33% and 20%, respectively. The highest prevalence was recorded in summer (June-September). The result of this study ensures enormous contamination of drinking water that requires appropriate treatment, cleaning and filtration to provide safe drinking water. Preventing water-borne disease and proper treatment of water supplies is essential to public health.
Bangladesh stands out as a climate change hot spot due to its unique geography, climate, high population density, and limited adaptation capacity. Mounting evidence suggests that the country is already suffering from the effects of climate change which may get worse without aggressive action. Here, we use an ensemble of high-resolution (10 km) regional climate model simulations to project near-term change in climate extremes, mainly heat waves and intense rainfall, for the period (2021–2050). Near-term climate projections represent a valuable input for designing sound adaptation policies. Our climate projections suggest that heatwaves will become more frequent and severe in Bangladesh under the business-as-usual scenario (RCP8.5). In particular, extremes of wet-bulb temperature (a temperature and humidity metric important in evaluating humid heat stress) in the western part of Bangladesh including Bogra, Ishurdi, and Jessore are likely to exceed the extreme danger threshold (according to U.S. National Weather Service criterion), which has rarely been observed in the current climate. The return periods of extreme heat waves are also significantly shortened across the country. In addition, country-averaged rainfall is projected to increase by about 6% during the summer months, with the largest increases (above 10%) in the eastern mountainous areas, such as Sylhet and Chittagong. Meanwhile, insignificant changes in extreme rainfall are simulated. Our results suggest that Bangladesh is particularly susceptible to climate extremes in the near future, in the form of extreme heat waves over the western part of the country.
Bangladesh is a country of natural disasters and climatic hazards, which frequently affect its inhabitants’ lives and livelihoods. Among the various risks and disasters, floods are the most frequent hazard that makes haor households vulnerable. Therefore, this study was undertaken to estimate livelihood vulnerability to flooding within the flood-prone haor ecosystem in Bangladesh. Primary data were collected from 100 haor households each from Kishoreganj, Netrokona, and Sunamganj districts (N?=?300) by applying a multistage random sampling technique. Data were collected through face-to-face interviews using a pretested structured questionnaire. The Livelihood Vulnerability Index (LVI) and the Intergovernmental Panel on Climate Change (IPCC) framework of vulnerability were applied to compare vulnerabilities among the selected haor-based communities. The empirical results revealed that haor households in Sunamganj district were more vulnerable to flood hazard and natural disaster in terms of food, water, and health than households in the other two districts. Taking into account the major components of the LVI, the IPCC framework of vulnerability indicated that households in Sunamganj district were the most vulnerable due to their lowest adaptive capacity and highest sensitivity and exposure. These findings enable policymakers to formulate and implement effective strategies and programs to minimize vulnerability and enhance resilience by improving the livelihoods of the vulnerable haor households of Bangladesh, especially those in Sunamganj district.
Non-migration is an adaptive strategy that has received little attention in environmental migration studies. We explore the leveraging factors of non-migration decisions of communities at risk in coastal Bangladesh, where exposure to both rapid- and slow-onset natural disasters is high. We apply the Protection Motivation Theory (PMT) to empirical data and assess how threat perception and coping appraisal influences migration decisions in farming communities suffering from salinization of cropland. This study consists of data collected through quantitative household surveys (n?=?200) and semi-structured interviews from four villages in southwest coastal Bangladesh. Results indicate that most respondents are unwilling to migrate, despite better economic conditions and reduced environmental risk in other locations. Land ownership, social connectedness, and household economic strength are the strongest predictors of non-migration decisions. This study is the first to use the PMT to understand migration-related behaviour and the findings are relevant for policy planning in vulnerable regions where exposure to climate-related risks is high but populations are choosing to remain in place.
This study aims to explore the impact of climate change on health, including local adaptation strategies. A mixed-method approach has been used in this study. The results reveal that increasing the frequency of flooding, severity of riverbank erosion and drought, and rising disease outbreak are the highest indicators of climate change perceived by riverine island (char) dwellers, which is similar to the observed data. It also uncovers, approximately all respondents encounter several health-related issues during different seasons where prevailing cold and cough with fever, skin diseases, and diarrhoea are the leading ailments. Several adaptation strategies are accommodated by char inhabitants in order to enhance resilience against the climate change health impacts, but the paucity of money, disrupted communication, lack of formal health-care centre are the most obstacles to the sustainability of adaptation. This research recommends that healthcare-associated project should be performed through proper monitoring for exterminating char dwellers’ health issues.
Soaring temperatures cause deaths in large numbers in various parts of India. The number of deaths vary with region and are influenced by the demographics and socioeconomic characteristics of the region. This study tried to estimate the number of deaths associated with exposure to heat in the different states of India. Secondary data was used, which was collected from the website data.gov.in, an Open Government Data (OGD) Platform of the Indian government. Descriptive statistics were applied using Microsoft Excel-10. It was found that there 3014 men died from heat-related causes in 2001-05, which increased to 5157 in the period 2011-15. For women the number of deaths in the corresponding periods were 849 and 1254 respectively. Deaths caused by heatwaves were found to be higher than those resulting from avalanches, exposure to cold, cyclone, tornado, starvation due to natural calamity, earthquake, epidemic, flood, landslide, torrential rain and forest fire. The study revealed that there are regional variations in the number deaths due to heatstroke. From the perspective of disaster preparedness, it is important to note that deaths from heat strokes occur every year. With rising temperatures, the numbers are likely to increase. The findings of the study highlight this concern. Therefore, there is a need for targeted region-specific interventions for reducing the number of deaths due to heatwaves.
Households’ vulnerability assessment is considered an essential step towards reducing the harmful consequences of disaster risks. Adaptation helps in reducing their future vulnerability. The aims of this study are to (1) assess the different components of vulnerability, (2) compare the individual components and the composite vulnerability between the two regions and (3)assess the households’ adaptation to floods. Data were collected from 382 households and statistical tests were applied for comparison among these households living in two regions. A total of 32 and 17 indicators were used for vulnerability and adaptation assessment respectively. Results revealed that social, economic, physical and institutional components of vulnerability were found higher in Region 1 than Region 2. Except for social and attitudinal vulnerability, all the other vulnerability components had significant differences. Similarly, the overall composite vulnerability was higher in Region 1 than Region 2 and statistically significant. Moreover, in both regions, informal adaptation was mostly practiced compared to formal adaptation. Thus, it is recommended that the government and non-governmental stakeholders provide options and facilitation for formal adaptation at the community level.
As the world’s population is expected to be over 2/3rd urban by 2050, climate action in cities is a growing area of interest in the inter-disciplines of development policy, disaster mitigation and environmental governance. The climate impacts are expected to be quite severe in the developing world, given its urban societies are densely packed, vastly exposed to natural elements while possessing limited capabilities. There is a notable ambiguity and complexity that inhibits a methodical approach in identifying urban resilience measures. The complexity is due to intersection of large number of distinct variables in climate geoscience (precipitation and temperature anomalies at different locations, RCPs, timeline), adaptation alternatives (approach, priority, intervention level) and urban governance (functional mandate, institutional capacity, and plans & policies). This research examines how disparate and complex knowledge and information in these inter-disciplines can be processed for systematic ‘negotiation’ to situate, ground and operationalize resilience in cities. With India as a case, we test this by simulating mid-term and long-run climate scenarios (2050 & 2080) to map regional climate impacts that shows escalation in the intensity of climate events like heat waves, urban flooding, landslides and sea level rise. We draw on suitable adaptation measures for five key urban sectors- water, infrastructure (including energy), building, urban planning, health and conclude a sleuth of climate resilience building measures for policy application through national/ state policies, local urban plans and preparation of city resilience strategy, as well as advance the research on ‘negotiated resilience’ in urban areas.
Rural communities inhabited on riverbank areas are frequently facing the ever-increasing psychological, social and economic distress due to negative effects of riverbank erosion. This study focused to investigate the impact of climate-based hazards particularly riverbank erosion on human displacement, food security and livelihood of rural riverine households and how vulnerable households act in response. The survey data of 398 households of erosion-prone riverbank area were collected, and group discussions connecting household heads from this area were also used for this study. In human displacement scenario of the last ten years due to riverbank erosion, almost 60% households lost their homestead once while 38% more than three times and forced to displaced. Empirical estimates of households’ food security status indicated the value of Food Security Index 2.11, highlighting households face issue of food security all over the year. Food security issue of vulnerable households is highly related with migration because these households have insufficient employment chances, and coupled with limited or no farming land, they are highly prone to migration. In conclusion, this study estimated that riverbank erosion risk is a co-exist reason of population displacement, increasing rural environmental vulnerability and obstacles to psychological, cultural and socioeconomic development. Implications of local-based proper policy interventions such as developing advance research regarding infusion of agro-based technology packages for emerging Bait areas for developing resilience, human capital development, credit access and institution service are necessary for improving livelihood and food security of these riverbank erosion households. State-based institutions and local community mutually need to focus increasing forestry specifically in riverbank areas to save fertile land from riverbank erosion and reducing environmental pollution. Convalescing livelihood and food security for erosion riverbank households, more employment opportunity needs to provided, investing more in training and education programmes to promoting income-generating activities that subsequently will develop livelihood and food security of households.
Floods are the most common hazard in Bangladesh adversely affecting the lives and livelihoods of millions of riverine people. Flood-affected households adopt a variety of post-disaster mitigation measures, to the best of their ability, in recognition that similar events are likely to occur again in the future. However, little is known about what drives a household to adopt risk mitigation measures after experiencing a severe flood. The objective of this study was to investigate the determinants of households’ decisions on the implementation of flood risk mitigation measures, following the severe flood in 2017 in northern Bangladesh. The data used for this study were collected from the right bank of the Teesta River in Bangladesh through a survey of 377 households and six key informant interviews. Most of the households (83.3%) adopted at least one risk mitigation measure from either structural or nonstructural categories after the 2017 flood. Binary logistic regression models provide useful insights into the determinants of the implementation of mitigation measures and intention to implement mitigation measures in future. The results showed that the perceived probability of flood, perceived preparedness, flood experience, exposure to flood, membership, household head’s sex, income source, and landownership significantly influenced households to implement mitigation measures in the post-disaster period. Additionally, the intention to implement mitigation measures was influenced by the membership and education of households. This study contributes in terms of useful information about the determinants of post-disaster mitigation measures in riverine areas of Bangladesh. These findings can be used to target specific households to promote disaster risk reduction interventions.
The present study explored the association between daily ambient air pollution and daily emergency room (ER) visits due to acute respiratory symptoms in children of Delhi. The daily counts of ER visits (ERV) of children (?15 years) having acute respiratory symptoms were obtained from two hospitals of Delhi for 21 months. Simultaneously, data on daily concentrations of particulate matter (PM(10) and PM(2.5)), nitrogen dioxide (NO(2)), sulfur dioxide (SO(2)), carbon monoxide (CO), and ozone (O(3)) and weather variables were provided by the Delhi Pollution Control Committee. K-means clustering with time-series approach and multi-pollutant generalized additive models with Poisson link function was used to estimate the 0-6-day lagged change in daily ER visits with the change in multiple pollutants levels. Out of 1,32,029 children screened, 19,120 eligible children having acute respiratory symptoms for ?2 weeks and residing in Delhi for the past 4 weeks were enrolled. There was a 29% and 21% increase in ERVs among children on high and moderate level pollution cluster days, respectively, compared to low pollution cluster days on the same day and previous 1-6 days of exposure to air pollutants. There was percentage increase (95% CI) 1.50% (0.76, 2.25) in ERVs for acute respiratory symptoms for 10 ?g/m(3) increase of NO(2) on previous day 1, 46.78% (21.01, 78.05) for 10 ?g/m(3) of CO on previous day 3, and 13.15% (9.95, 16.45) for 10 ?g/m(3) of SO(2) on same day of exposure. An increase in the daily ER visits of children for acute respiratory symptoms was observed after increase in daily ambient air pollution levels in Delhi.
India has reported a high prevalence of Intimate Partner Violence (IPV) against women over the years. Previous Western research has found an increased IPV risk among women in the aftermath of natural disasters, underscoring the need for such studies in India. We could not locate any study focusing on the impact of slow-onset versus rapid-onset disasters, which might have differing impacts on the vulnerable, especially on the incidence of IPV in India. Using data on ever-married women from the National Family Health Survey-4 (2015-16), we investigated the association of residing in districts exposed to a drought (N = 31,045), and separately, to two cyclones (N = 8469), with three forms of self-reported IPV against women (emotional, physical, and sexual). Survey-adjusted logistic regression models showed that exposure to cyclone was positively associated with emotional IPV (AOR: 1.59, 95% CI: 1.20, 2.10) after adjusting for sociodemographic covariates. Although not statistically significant, exposure to cyclone was also positively associated with physical and sexual IPV, and drought with physical IPV. However, we did not find an association of drought with emotional and sexual violence. We corroborated previous findings that women from wealthier households, with greater education, and whose husbands had no history of alcohol consumption, were less likely to experience any form of IPV independent of the influence of other factors. These results highlight the potential increased risk of IPV following natural disasters. In patriarchal societies such as India vulnerable to climate-change, these sobering results highlight the need to prepare for the social disasters that might accompany natural disasters.
Mountain ecosystems are considered vulnerable to early impacts of climate change. Whether and how local residents of these areas perceive these changes, however, remain under-studied questions. By conducting a household survey in the Khumbu region of Nepal, this study assessed local residents’ experience-based perception of changes in climate trends and patterns, perceived risk, and attitudes towards climate issues. Multivariate cluster analysis based on residents’ climate change beliefs revealed three segments: “Cautious,” “Disengaged,” and “Alarmed.” A comparison of these segments along key psychosocial constructs of Protection Motivation Theory (PMT) revealed significant inter-segment differences in residents’ perception of severity, vulnerability, response efficacy, self-efficacy, and response cost associated with engaging in mitigating behavior. Results shed light on how residents of high elevation areas that are considered to be exposed to early impacts of climate change perceive the risk and intend to respond. These findings could also assist stakeholders working in other similar mountain ecosystems in understanding vulnerability and in working towards climate readiness.
Pakistan is home to a wide range of geographical landscapes, each of which faces different climate change impacts and challenges. This article presents findings from a National Geographic Society funded project, which employed a people-centered, narratives-based approach to study climate impacts and adaptation strategies of people in 19 rural study sites in four provinces of Pakistan (N = 108). The study looked at six climate-related stressors-changes in weather patterns, floods, Glacial Lake Outburst Floods, drought, heat waves, and sea-level rise-in the coastal areas of Sindh, the desert of Thar, the plains of Punjab, and the mountains of Hunza, Gilgit, and Chitral. Speaking to people at these frontlines of climate change revealed much about climate suffering and trauma. Not only is the suffering induced by losses and damages to property and livelihood, but climate impacts also take a heavy toll on people’s psycho-social wellbeing, particularly when they are displaced from their homes. The findings further demonstrate that people try to adapt in various ways, for instance by altering their agricultural practices, but they face severe barriers to effective adaptation action. Understanding people’s perceptions of climate change and incorporating their recommendations in adaptation planning can help policy-makers develop a more participatory, inclusive, and holistic climate resilience framework for the future.
Soil-transmitted helminthiasis is a major disease burden in developing countries, with a considerable share borne by India. Currently, the principal strategy of the World Health Organization for the control of soil-transmitted helminths (STHs) is mass deworming in the high-risk population based on the prevalence and intensity of infection in a region. However, the disease load of STH remains unknown in many regions. A cross-sectional study was conducted in 2017 among children in the age group of 5-13 years in Barpeta, Assam, to ascertain the prevalence of STH infection in school-aged children and its probable risk factors. Socio-demographic and epidemiologic data were gathered using a piloted questionnaire. Geohelminths were identified by the Kato-Katz method. Association with probable risk-factors was analyzed by binomial logistic regression. Overall, 16.3% [95% confidence interval (CI) = 12.9-19.8] of children were found to be infected with one or more of the three STHs. Ascaris, hookworm, and Trichuris infections were observed in 9.4%, 7.4%, and 5.3%, respectively. The strongest predictors for the presence of any STH with multivariable analysis were open defecation (habitual or occasional), lack of proper handwashing, living in homes affected by flood, and age group of 8-10 years. The availability of proper handwashing stations in schools was found to be protective against Trichuris. Awareness among the people regarding sanitation and personal hygiene, particularly in the post-flood scenario, is imperative for sustainable control of STH infections. Preventive deworming should be continued; however, the time and frequency must be adjusted according to the prevailing climatic conditions in the region under study.
BACKGROUND: Climate change influences patterns of human mobility and health outcomes. While much of the climate change and migration discourse is invested in quantitative predictions and debates about whether migration is adaptive or maladaptive, less attention has been paid to the voices of the people moving in the context of climate change with a focus on their health and wellbeing. This qualitative research aims to amplify the voices of migrants themselves to add nuance to dominant migration narratives and to shed light on the real-life challenges migrants face in meeting their health needs in the context of climate change. METHODS: We conducted 58 semi-structured in-depth interviews with migrants purposefully selected for having moved from rural Bhola, southern Bangladesh to an urban slum in Dhaka, Bangladesh. Transcripts were analysed using thematic analysis under the philosophical underpinnings of phenomenology. Coding was conducted using NVivo Pro 12. FINDINGS: We identified two overarching themes in the thematic analysis: Firstly, we identified the theme “A risk exchange: Exchanging climate change and health risks at origin and destination”. Rather than describing a “net positive” or “net negative” outcome in terms of migration in the context of climate change, migrants described an exchange of hazards, exposures, and vulnerabilities at origin with those at destination, which challenged their capacity to adapt. This theme included several sub-themes-income and employment factors, changing food environment, shelter and water sanitation and hygiene (WaSH) conditions, and social capital. The second overarching theme was “A changing health and healthcare environment”. This theme also included several sub-themes-changing physical and mental health status and a changing healthcare environment encompassing quality of care and barriers to accessing healthcare. Migrants described physical and mental health concerns and connected these experiences with their new environment. These two overarching themes were prevalent across the dataset, although each participant experienced and expressed them uniquely. CONCLUSION: Migrants who move in the context of climate change face a range of diverse health risks at the origin, en route, and at the destination. Migrating individuals, households, and communities undertake a risk exchange when they decide to move, which has diverse positive and negative consequences for their health and wellbeing. Along with changing health determinants is a changing healthcare environment where migrants face different choices, barriers, and quality of care. A more migrant-centric perspective as described in this paper could strengthen migration, climate, and health governance. Policymakers, urban planners, city corporations, and health practitioners should integrate the risk exchange into practice and policies.
Air pollution has become a threat to human health in urban settlements, ultimately leading to negative impacts on overall economic system as well. Already developed nations and still developing countries both are at the risk of air pollution globally. In this scenario, this work aims to investigate the associations of asthma (AS) and acute upper respiratory infection (ARI) patients with satellite-based aerosol optical depth (AOD) and meteorological factors, i.e., relative humidity (RH), temperature (TEMP), and wind speed (WS). We applied second-generation unit root tests to provide empirical evidence. Two sets of unit root tests confirmed mix order of integration, and the other Westerlund co-integration test further showed strong linkages between estimated variables. Fully modified ordinary least square (FMOLS) and dynamic ordinary least square (DOLS) tests were applied, only to explore that TEMP and WS lower the number of AS and ARI patients, but RH and AOD increase the number of patients. Therefore, in accordance with these findings, our study provides some important policy instruments to improve the health status in megacities of Pakistan.
INTRODUCTION: Global climate change has produced growing natural disasters across the world especially in Global South. Different countries experience varied vulnerabilities depending on their geographical location, economic status and ability of management. In a highly disaster susceptible developing country like Bangladesh, many individuals experience a greater rate of natural disasters with devastating health effects. Compare with men, women have a higher incidence of mortality and health effects following natural disasters. The study aims to explore women’s experience of physical and psychological health vulnerabilities with primary causes in natural disaster-affected areas of Bangladesh. METHODS AND ANALYSIS: This is an exploratory mixed-method study comprising survey and in-depth interviews with equal priority to identify physical and psychological health vulnerabilities of women living in natural disaster-affected areas of Bangladesh. Quantitative data will be collected using self-administered sociodemographic and perceived severity instrument, 12-item Short-Form, Impact of Event Scale-Revised and Brief Coping Scale, while specific open-ended guidelines will be used for the qualitative part. The instruments will be translated into Bangla following the Brislin (1970) model of translation. The survey will be administered in paper copies, with at least 384 respondents, whereas 30 participants will be in-depth interviewed using an audio recorder. Survey data will be analysed using SPSS V.25 following descriptive and inferential statistics as required. The recorded open-ended responses will be transcribed and analysed using thematic analysis. Finally, both data sets will be integrated and synthesised according to the sequential mixed-method approach. ETHICS AND DISSEMINATION: The study has been reviewed and approved by the Human Research Ethics Committee of the University of New England. The results will be actively disseminated through peer-reviewed journals, conference presentations, social media, the internet and various community engagement activities.
Existing efforts to ensure safe water access in coastal Bangladesh are challenged by increasing freshwater salinity. This research explored/explores safe water consumption choices in coastal Bangladesh, which data are scarce to date, using a mixed-methods approach. In 2014, a cross-sectional survey was conducted in southwestern coastal Bangladesh (n=261) and data was generated on water supply and consumption. Data collection also involved 29 in-depth interviews of household care givers and focus group discussions were performed with three community groups. Descriptive statistics were applied to analyse quantitative data and thematic analysis was used for qualitative data. The survey showed that 60% of the study population used tube well water while 40% used pond water for drinking. It was observed that for cooking purposes, the use of pond water was slightly higher than the tube well water. Only 13% of the respondents mentioned that their drinking water tasted salty whereas 6% of the respondents reported health problem (diarrhoea, dysentery, gastric issues and skin problems) after using these water sources. The qualitative data reveals that water available for drinking and cooking is causing a serious threat to this coastal community, particularly during the dry season. In-depth assessments indicated that drinking water choices were less driven by concerns for health than practical issues such as travel distance and time taken and taste. The palatability of water was an important determinant of choice for drinking and other domestic uses. Furthermore, the utility of alternative options for safe drinking water is driven by beliefs and traditions and source maintenance. Given the increasing salinisation of freshwaters in many low-lying countries and likely exacerbation related to climate change-induced sea level rise, therefore, promotion of low saline drinking water along with salt reducing interventions consider that community beliefs and practices must be a made priority.
To curb the staggering health burden attributed to air pollution, the sustainable solution for India would be to reduce emissions in future. Here we project ambient fine particulate matter (PM2.5) exposure in India for the year 2030 under two contrasting air pollution emission pathways for two different climate scenarios based on Representative Concentration Pathways (RCP4.5 and RCP8.5). All-India average PM2.5 is expected to increase from 41.4 +/- 26.5 mu g m(-3) in 2010 to 61.1 +/- 40.8 and 58.2 +/- 37.5 mu g m(-3) in 2030 under RCP8.5 and RCP4.5 scenarios, respectively if India follows the current legislation (baseline) emission pathway. In contrast, ambient PM2.5 in 2030 would be 40.2 +/- 27.5 (for RCP8.5) and 39.2 +/- 25.4 (for RCP4.5) mu g m(-3) following the short-lived climate pollutant (SLCP) mitigation emission pathway. We find that the lower PM2.5 in the mitigation pathway (34.2% and 32.6%, respectively for RCP8.5 and RCP4.5 relative to the baseline emission pathway) would come at a cost of 0.3-0.5 degrees C additional warming due to the direct impact of aerosols. The premature mortality burden attributable to ambient PM2.5 exposure is expected to rise from 2010 to 2030, but 381,790 (5-95% confidence interval, CI 275,620-514,600) deaths can be averted following the mitigation emission pathway relative to the baseline emission pathway. Therefore, we conclude that given the expected large health benefit, the mitigation emission pathway is a reasonable tradeoff for India despite the meteorological response. However, India needs to act more aggressively as the World Health Organization (WHO) annual air quality guideline (10 mu g m(-3)) would remain far off.
Based on spatial variation and time, climate change has various levels of impacts on different communities and sometime with the state of development as well. The rural mountainous households that depend on natural resources for subsistence livelihoods and agriculture are particularly vulnerable with changing climate. Livelihood vulnerability assessment at local level is imperative to formulate appropriate adaptation policy and programs to address their livelihood challenges. This paper explored two vulnerability assessment indices, livelihood vulnerability index and IPCC vulnerability index by surveying 150 households from three village development committees (VDCs) in Lamjung district, Nepal. Data related to climate variables, natural disasters, water and food security, health, socio-demographics, livelihood strategies, and social network were collected and combined into indices. Both indices differed based on well-being status, gender of the household head and location across the households of three VDCs. The analysis was based on indices constructed from selected indicators measuring exposure, sensitivity, and adaptive capacity. Results indicated that very poor and poor households, and female-headed households were more vulnerable than medium, well-off and male-headed households. The availability of livelihood diversified strategies, education, establishment of early warning system to climate extreme will help to reduce vulnerability to climate change in the study areas. The findings help in designing priority areas of intervention for adaptation plan to reduce vulnerability and enhance the resilience of the mountainous households to climate change.
Major heat waves are occurring over India during the hottest months of May and June. Since the temperature extremes have major impact on human health and agriculture, better understanding the dynamics behind its evolution and propagation will help us to develop effective mitigation strategies. Understanding the spatio-temporal distribution, evolution and dynamics associated with heat waves is lacking over this region, due to the lack of high-resolution weather information. Here, we developed a high-resolution (4 x 4 km) dynamically downscaled hourly climate data for April to June during period of 2001-2016. The downscaled daily surface temperature is in good agreement with station observations, which is also in agreement with the observed features of temperature distribution during this period. Based on the Indian meteorological department definition, intensity of the heat waves is identified and re-classified into minor and severe category. The spatio-temporal distribution of each heat wave shows variation in its spatial coverage and also in its intensity. The distributions of heat waves are mainly over central India, North-West India and states such as Odisha, Andhra Pradesh and Telangana during pre-monsoon season. Results show that the increase in meridional heat transport is higher than the zonal advection component, and intensification of heat waves is linked with heat accumulation over a particular region associated with weakening of heat transport. The further amplification associated with depletion of soil moisture will result in the reduction in evaporative cooling, and it will further amplify the surface air temperature.
Levees protect floodplain areas from frequent flooding, but they can paradoxically contribute to more severe flood losses. The construction or reinforcement of levees can attract more assets and people in flood-prone area, thereby increasing the potential flood damage when levees eventually fail. Moreover, structural protection measures can generate a sense of complacency, which can reduce preparedness, thereby increasing flood mortality rates. We explore these phenomena in the Jamuna River floodplain in Bangladesh. In this study area, different levels of flood protection have co-existed alongside each other since the 1960s, with a levee being constructed only on the right bank and its maintenance being assured only in certain places. Primary and secondary data on population density, human settlements, and flood fatalities were collected to carry out a comparative analysis of two urban areas and two rural areas with different flood protection levels. We found that the higher the level of flood protection, the higher the increase of population density over the past decades as well as the number of assets exposed to flooding. Our results also show that flood mortality rates associated with the 2017 flooding in Bangladesh were lower in the areas with lower protection level. This empirical analysis of the unintended consequences of structural flood protection is relevant for the making of sustainable policies of disaster risk reduction and adaptation to climate change in rapidly changing environments.
Exposure to extreme climate events causes population displacement and adversely affects the health of mothers and children in multiple ways. This paper investigates the effects of displacement on whether a child is delivered at a health center, as opposed to at home, and on postnatal care service utilization in Bangladesh. Using cross-sectional survey data from 599 mothers who gave birth in the three years prior to the date of interview, including 278 from households which had previously been displaced and 231 from households which had not been displaced, we use multivariate logistic regression to identify the factors associated with maternal healthcare service utilization. The results show that displaced households’ mothers are only about a quarter as likely to deliver at a health center as mothers from non-displaced households. The use of health center-based delivery decreases as the numbers of past displacements increases. Higher number of previous children, lower use of antenatal care during pregnancy, lower household income, and lack of access to radio/television also significantly reduce a mother’s likelihood of delivery at a health center. Displaced mothers are also substantially less likely to use postnatal care services for their neonates, especially those supplied by trained providers. Use of health facilities for delivery, use of antenatal care services, and previous number of children are other important predictors of postnatal care service utilization for neonates. In light of these findings, relocation of local health facilities with basic and emergency care provisions to areas in which the displaced have resettled, reinforcement of Family Planning services, and extension of coverage of the Maternity Allowance benefits in the displacement-prone mainland riverine areas are recommended policy responses.
The coal-dominated electricity system poses major challenges for India to tackle air pollution and climate change. Although the government has issued a series of clean air policies and low-carbon energy targets, a key barrier remains enforcement. Here, we quantify the importance of policy implementation in India’s electricity sector using an integrated assessment method based on emissions scenarios, air quality simulations, and health impact assessments. We find that limited enforcement of air pollution control policies leads to worse future air quality and health damages (e.g., 14?200 to 59?000 more PM(2.5)-related deaths in 2040) than when energy policies are not fully enforced (5900 to 8700 more PM(2.5)-related deaths in 2040), since coal power plants with end-of-pipe controls already emit little air pollution. However, substantially more carbon dioxide will be emitted if low-carbon and clean coal policies are not successfully implemented (e.g., 400 to 800 million tons more CO(2) in 2040). Thus, our results underscore the important role of effectively implementing existing air pollution and energy policy to simultaneously achieve air pollution, health, and carbon mitigation goals in India.
Thermal comfort standards are essential to ensure comfortable and enjoyable indoor conditions, and they also help in optimizing energy use. Thermal comfort studies, either climate chamber-based or field investigation, are conducted across the globe in order to ascertain the comfort limits as per the climatic and other adaptive features. However, very few studies are conducted when the occupants are subjected to a stressed condition, like the COVID-19 lockdown, which may not only have the health impacts but also have psychological impacts on the adaptation. In this paper, we present the results of the online study conducted regarding the status of thermal comfort during the COVID-19 lockdown in India. A total of 406 complete responses were collected from subjects located across 3 different climatic regions of India, that is, cold climate, composite climate, and hot and humid climate. Variations in clothing insulation, thermal sensation, and preference were noted across the different climatic regions. We also present the variation in opening of windows and running of fans with the variation in outdoor mean air temperature. The self-judged productivity, comfort, desire to go outdoors, and effectiveness of working from home were seen to vary with the increase in the days of lockdown.
Dengue is an important emerging vector-borne disease in Bhutan. This study aimed to quantify the spatial and temporal patterns of dengue and their relationship to environmental factors in dengue-affected areas at the sub-district level. A multivariate zero-inflated Poisson regression model was developed using a Bayesian framework with spatial and spatiotemporal random effects modelled using a conditional autoregressive prior structure. The posterior parameters were estimated using Bayesian Markov Chain Monte Carlo simulation with Gibbs sampling. A total of 708 dengue cases were notified through national surveillance between January 2016 and June 2019. Individuals aged ?14 years were found to be 53% (95% CrI: 42%, 62%) less likely to have dengue infection than those aged >14 years. Dengue cases increased by 63% (95% CrI: 49%, 77%) for a 1°C increase in maximum temperature, and decreased by 48% (95% CrI: 25%, 64%) for a one-unit increase in normalized difference vegetation index (NDVI). There was significant residual spatial clustering after accounting for climate and environmental variables. The temporal trend was significantly higher than the national average in eastern sub-districts. The findings highlight the impact of climate and environmental variables on dengue transmission and suggests prioritizing high-risk areas for control strategies.
OBJECTIVES: Indian agriculture is mostly dependent on monsoon. Poor and irregular rainfall may result in crop failure and food shortage among the vulnerable population. This study examined the variations in drought condition and its association with under age 5 child malnutrition across the districts of India. METHODS: Using remote sensing and National Family Health Survey (NFHS-4) data, univariate Moran’s I and bivariate local indicator of spatial autocorrelation (LISA) maps were generated to assess the spatial autocorrelation and clustering. To empirically check the association, we applied multivariate ordinary least square and spatial autoregressive models. RESULTS: The study identified highly significant spatial dependence of drought followed by underweight, stunting, and wasting. Bivariate LISA maps showed negative spatial autocorrelation between drought and child malnutrition. Regression results suggest agricultural drought is substantially associated with stunting. An increasing value of drought showed statistical association with the decreasing (??=?-?8.251; p value?
Vector control is one of the main aspects to reach the target of eliminating visceral leishmaniasis from Indian sub-continent as set by the World Health Organisation. Data on different aspects of vector like ecology, behaviour, population dynamics and their association with environmental factors are very important for formulating an effective vector control strategy. The present work was designed to study the species abundance and impact of environmental factors on population dynamics of vector P. argentipes in a visceral leishmaniasis endemic area of Malda district, West Bengal. Adult sand flies were collected using light traps and mouth aspirators from twelve kala-azar affected villages of Habibpur block of Malda district, on a monthly basis from January to December, 2018. Morphological and molecular methods were used for species identification. Population dynamics were assessed by man hour density and per night per trap collection. Data were analysed using SPSS software to determine the impact of environmental factors on vector population P. argentipes was found to the predominant species and prevalent throughout the year. A significantly higher number of sand flies were collected from cattle sheds than human dwellings and peri-domestic vegetation. A portion of the P. argentipes population was exophilic and exophagic as evidenced by their collection from peri-domestic vegetation. The highest population density was recorded during April to September. Population dynamics were mostly influenced by average temperature along humidity and rain fall. Resting behaviour of sand flies was not restricted to the lower portion of the wall but equally distributed throughout the wall and ceiling. Programme officials should consider management of outdoor populations of the sand flies and timings of indoor residual spray for chemical control purpose.
Summertime heat stress future projections from multi-model mean of 18 CMIP5 models show unprecedented increasing levels in the RCP 4.5 and RCP 8.5 emission scenarios over India. The estimated heat stress is found to have more impact on the coastal areas of India having exposure to more frequent days of extreme caution to danger category along with the increased probability of occurrence. The explicit amount of change in temperature, increase in the duration and intensity of warm days along with the modulation in large scale circulation in future are seemingly connected to the increasing levels of heat stress over India. A decline of 30 to 40% in the work performance is projected over India by the end of the century due to the elevated heat stress levels which pose great challenges to the country policy makers to design the safety mechanisms and to protect people working under continuous extreme hot weather conditions.
BACKGROUND: Often quoted as “heaven on earth,” Kashmir forms one of the two divisions of the Union territory of Jammu and Kashmir. A high-altitude region with abundant precipitation and snowfall, the people of Kashmir experience peculiar dermatoses not commonly seen in the majorly tropical subcontinent of India. In this study, we focussed on cold dermatoses as a comprehensive cluster and attempted to study them as a group. AIMS: To determine the prevalence of cold dermatoses in Kashmir valley and study their epidemiological characteristics. METHODS: This observational, cross-sectional community-based study was conducted on native Kashmiri population in three districts of the valley, exclusively during the winter season of the year 2016-17 and 2017-18. The data were tabulated and analyzed with Chi-square test for discrete variables and t-test for continuous variables, using OpenEpi. A P value of less than 0.05 was taken as significant. RESULTS: The study included a total of 1200 cases with 602 males and 598 females. Perniosis was most commonly encountered dermatoses in our study with a prevalence of 12.2%. Frostbite had a prevalence of 0.83%. Raynaud’s phenomenon and asteatotic eczema were seen in 1.5% and 1.67% of the population, respectively. Cold panniculitis, cold urticaria, and livedo reticularis were each seen in 0.08% of the population. CONCLUSIONS: Cold dermatoses form an important source of morbidity among the native population of Kashmir. These can be easily prevented by ensuring adequate protection against cold. Creating awareness regarding these disorders and probable association with connective tissue disorders is also imperative.
BACKGROUND AND AIMS: As, the COVID-19 has been deemed a pandemic by World Health Organization (WHO), and since it spreads everywhere throughout the world, investigation in relation to this disease is very much essential. Investigation of pattern in the occurrence of COVID-19, to check the influence of different meteorological factors on the incidence of COVID-19 and prediction of incidence of COVID-19 are the objectives of this paper. METHODS: For trend analysis, Sen’s Slope and Man-Kendall test have been used, Generalized Additive Model (GAM) of regression has been used to check the influence of different meteorological factors on the incidence and to predict the frequency of COVID-19, and Verhulst (Logistic) Population Model has been used. RESULTS: Statistically significant linear trend found for the daily-confirmed cases of COVID-19. The regression analysis indicates that there is some influence of the interaction of average temperature (AT) and average relative humidity (ARH) on the incidence of COVID-19. However, this result is not consistent throughout the study area. The projections have been made up to 21st May, 2020. CONCLUSIONS: Trend and regression analysis give an idea of the incidence of COVID-19 in India while projection made by Verhulst (Logistic) Population Model for the confirmed cases of the study area are encouraging as the sample prediction is as same as the actual number of confirmed COVID-19 cases.
We analyze the combined effect of political violence and adverse climatic and health shocks on child nutrition using longitudinal data from Andhra Pradesh, India. The paper shows three key results using two-stage least square (2SLS) models: (i) the presence of political violence reduces the mean height-for-age z-scores of children by between 0.4 and 0.9 standard deviations and reduces the mean weight-for-age z-scores of children by between 0.3 and 0.6 standard deviations; (ii) political violence generates such a large negative effect on the long-term nutrition of children (measured by height-for-age z-scores) through a reduction of the ability of households to cope with drought and illness; and (iii) drought and illness have an adverse effect on child nutrition in Andhra Pradesh only in violence-affected communities. The 2SLS results are robust to a wide range of robustness tests. Potential mechanisms explaining the strong joint welfare effect of conflict and adverse shocks are the failure of economic coping strategies in areas of violence and restricted access to public goods and services.
INTRODUCTION: In August 2018, India’s southern state of Kerala experienced its worst flooding in over a century. This report describes the relief efforts in Kozhikode, a coastal region of Kerala, where Operation Navajeevan was initiated. SOURCES: Data were collected from a centralized database at the command center in the District Medical Office as well as first-hand accounts from providers who participated in the relief effort. OBSERVATIONS: From August 15 through September 8, 2018, 36,846 flood victims were seen at 280 relief camps. The most common cause for presentation was exacerbation of an on-going chronic medical condition (18,490; 50.2%). Other common presentations included acute respiratory infection (7,451; 20.2%), traumatic injuries (3,736; 10.4%), and psychiatric illness (5,327; 14.5%). ANALYSIS: The prevalence of chronic disease exacerbation as the primary presentation during Operation Navajeevan represents an epidemiologic shift in disaster relief in India. It is foreseeable that as access to health care improves in low- and middle-income countries (LMICs), and climate change increases the prevalence of extreme weather events around the world, that this trend will continue.
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.
Mountains are characterized by their specificities such as fragility, marginality and remoteness. They are prone to various hazards such as drought, flood, forest fire, landslide and therefore physical, ecological and social systems of the mountains are at risk. Climate change adds to intensifying the magnitude of multi-hazard risk in mountains. The present study attempts to evaluate risk induced by multi-hazard and climate change in the Indian Himalayan Region (IHR) using the Intergovernmental Panel on Climate Change (IPCC) framework. The proposed multi-hazard risk index was based on indicators from a broader domain and applied on 109 administrative districts of IHR. Exposure, sensitivity, adaptive capacity, and coping capacity were defined using comprehensive and sub-regional indicators identified through inductive and deductive approaches. The result showed that the differential risks among the districts of IHR were governed by the multiplicity of the factor such as demography, amenities, natural capital, partnership, technology and spatial specificities of the districts. The result highlighted the need of inclusion of spatial specificities for the risk mitigation in the IHR and therefore a Mountain Specific Risk Management Framework (MSMRMF) was proposed for sustaining the mountainous communities. The proposed MSMRMF contained two broad components as risk assessment and risk addressal. The framework detailed the risk mitigation and coping strategies (based on adjustment of internal and external strengths) for addressing risks. Risk mitigation was proposed to achieved through habitation resilience, natural capital enhancement, external partnerships, climate change adaptation, and technological interventions. The framework would provide an insight of risk and risk management strategies for the multi-hazard prone mountain regions for the sustainable development under the global change.
INTRODUCTION: This study aimed to investigate the effects of temperature variability on rotavirus infections among children under 5 years of age in Kathmandu, Nepal. Findings may inform infection control planning, especially in relation to the role of environmental factors in the transmission of rotavirus infection. METHODS: Generalized linear Poisson regression equations with distributed lag non-linear model were fitted to estimate the effect of temperature (maximum, mean and minimum) variation on weekly counts of rotavirus infections among children under 5 years of age living in Kathmandu, Nepal, over the study period (2013 to 2016). Seasonality and long-term effects were adjusted in the model using Fourier terms up to the seventh harmonic and a time function, respectively. We further adjusted the model for the confounding effects of rainfall and relative humidity. RESULTS: During the study period, a total of 733 cases of rotavirus infection were recorded, with a mean of 3 cases per week. We detected an inverse non-linear association between rotavirus infection and average weekly mean temperature, with increased risk (RR: 1.52; 95% CI: 1.08-2.15) at the lower quantile (10th percentile) and decreased risk (RR: 0.64; 95% CI: 0.43-0.95) at the higher quantile (75th percentile). Similarly, we detected an increased risk [(RR: 1.93; 95% CI: 1.40-2.65) and (RR: 1.42; 95% CI: 1.04-1.95)] of rotavirus infection for both maximum and minimum temperature at their lower quantile (10th percentile). We estimated that 344 (47.01%) cases of rotavirus diarrhoea among the children under 5 years of age were attributable to minimum temperature. The significant effect of temperature on rotavirus infection was not observed beyond lag zero week. CONCLUSION: An inverse non-linear association was estimated between rotavirus incidence and all three indices of temperature, indicating a higher risk of infection during the cooler times of the year, and suggesting that transmission of rotavirus in Kathmandu, Nepal may be influenced by temperature.
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.
BACKGROUND: More than 80,000 dengue cases including 215 deaths were reported nationally in less than 7 months between 2016 and 2017, a fourfold increase in the number of reported cases compared to the average number over 2010-2016. The region of Negombo, located in the Western province, experienced the greatest number of dengue cases in the country and is the focus area of our study, where we aim to capture the spatial-temporal dynamics of dengue transmission. METHODS: We present a statistical modeling framework to evaluate the spatial-temporal dynamics of the 2016-2017 dengue outbreak in the Negombo region of Sri Lanka as a function of human mobility, land-use, and climate patterns. The analysis was conducted at a 1?km?×?1?km spatial resolution and a weekly temporal resolution. RESULTS: Our results indicate human mobility to be a stronger indicator for local outbreak clusters than land-use or climate variables. The minimum daily temperature was identified as the most influential climate variable on dengue cases in the region; while among the set of land-use patterns considered, urban areas were found to be most prone to dengue outbreak, followed by areas with stagnant water and then coastal areas. The results are shown to be robust across spatial resolutions. CONCLUSIONS: Our study highlights the potential value of using travel data to target vector control within a region. In addition to illustrating the relative relationship between various potential risk factors for dengue outbreaks, the results of our study can be used to inform where and when new cases of dengue are likely to occur within a region, and thus help more effectively and innovatively, plan for disease surveillance and vector control.
Intensive irrigation in India has been demonstrated to decrease surface temperature, but the influence of irrigation on humidity and extreme moist heat stress is not well understood. Here we analysed a combination of in situ and satellite-based datasets and conducted meteorological model simulations to show that irrigation modulates extreme moist heat. We found that intensive irrigation in the region cools the land surface by 1 degrees C and the air by 0.5 degrees C. However, the decreased sensible heat flux due to irrigation reduces the planetary boundary layer height, which increases low-level moist enthalpy. Thus, irrigation increases the specific and relative humidity, which raises the moist heat stress metrics. Intense irrigation over the region results in increased moist heat stress in India, Pakistan, and parts of Afghanistan-affecting about 37-46 million people in South Asia-despite a cooler land surface. We suggest that heat stress projections in India and other regions dominated by semi-arid and monsoon climates that do not include the role of irrigation overestimate the benefits of irrigation on dry heat stress and underestimate the risks. Intensive irrigation in India cools the land surface, but increases the moist heat stress in South Asia, according to an analysis of observational datasets and meteorological models.
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.
Background: It is widely acknowledged that climate change will lead to more frequent natural disasters and extreme weather events. This is a matter of concern, especially for countries like India which is amongst the most vulnerable drought-prone countries in the world. In 2015 the Government of Maharashtra had declared a drought in state. The severe drought situation forced millions of people to migrate from the Marathwada region to the bigger cities. Objective: The objective of the study was to examine the sanitation, hygiene and living conditions of migrants who were forced to leave their homes because of the drought. The focus of the study was on the health problems of pregnant migrant women and children in their destinations. Methods: The study adopted a qualitative approach to explore this phenomena. Fifteen in-depth interviews were conducted which included ten pregnant women and five women who had children less than two years of age. Data analysis were carried out with thematic analysis using NVivo software. Results: The study shows that pregnant mothers and women with children are at greater risk of diseases at place of destination. In particular, the pregnant migrant mothers could not access the necessary antenatal care. Moreover, they could not sleep or rest during the day due to non-availability of place.
Short-lived climate pollutants (SLCPs) including black carbon (BC), methane (CH4), and tropospheric ozone (O-3) are major climate forcers after carbon dioxide (CO2). These SLCPs also have detrimental impacts on human health and agriculture. Studies show that the Hindu Kush Himalayan (HKH) region, which includes Nepal, has been experiencing the impacts of these pollutants in addition to greenhouse gases. In this study, we derive a national-level emission inventory for SLCPs, CO2, and air pollutants for Nepal and project their impacts under reference (REF) and mitigation policy (POL) scenarios. The impacts on human health, agriculture, and climate were then estimated by applying the following: (1) adjoint coefficients from the Goddard Earth Observing System (GEOS)-chemical transport model that quantify the sensitivity of fine particulate matter (PM2.5) and surface O-3 concentrations in Nepal, and radiative forcing in four latitudinal bands, to emissions in 2 x 2.5 degrees grids, and (2) concentration-response functions to estimate health and crop loss impacts in Nepal. With the mitigating measures undertaken, emission reductions of about 78% each of BC and CH4 and 87% of PM2.5 could be achieved in 2050 compared with the REF scenario. This would lead to an estimated avoidance of 29,000 lives lost and 1.7 million tonnes of crop loss while bringing an economic benefit in present value of 2.7 times more than the total cost incurred in its implementation during the whole period 2010-2050. The results provide useful policy insights and pathways for evidence-based decision-making in the design and effective implementation of SLCP mitigation measures in Nepal.
Malaria, a vector-borne disease, is a significant public health problem in Keonjhar district of Odisha (the malaria capital of India). Prediction of malaria, in advance, is an urgent need for reporting rolling cases of disease throughout the year. The climate condition do play an essential role in the transmission of malaria. Hence, the current study aims to develop and assess a simple and straightforward statistical model of an association between malaria cases and climate variates. It may help in accurate predictions of malaria cases given future climate conditions. For this purpose, a Bayesian Gaussian time series regression model is adopted to fit a relationship of the square root of malaria cases with climate variables with practical lag effects. The model fitting is assessed using a Bayesian version of R(2) (RsqB). Whereas, the predictive ability of the model is measured using a cross-validation technique. As a result, it is found that the square root of malaria cases with lag 1, maximum temperature, and relative humidity with lag 3 and 0 (respectively), are significantly positively associated with the square root of the cases. However, the minimum and average temperatures with lag 2, respectively, are observed as negatively (significantly) related. The considered model accounts for moderate amount of variation in the square root of malaria cases as received through the results for RsqB. We also present Absolute Percentage Errors (APE) for each of the 12 months (January-December) for a better understanding of the seasonal pattern of the predicted (square root of) malaria cases. Most of the APEs obtained corresponding to test data points is reasonably low. Further, the analysis shows that the considered model closely predicted the actual (square root of) malaria cases, except for some peak cases during the particular months. The output of the current research might help the district to develop and strengthen early warning prediction of malaria cases for proper mitigation, eradication, and prevention in similar settings.
Dengue is one of the most serious vector-borne infectious diseases in India, particularly in Kolkata and its neighbouring districts. Dengue viruses have infected several citizens of Kolkata since 2012 and it is amplifying every year. It has been derived from earlier studies that certain meteorological variables and climate change play a significant role in the spread and amplification of dengue infections in different parts of the globe. In this study, our primary objective is to identify the relative contribution of the putative drivers responsible for dengue occurrences in Kolkata and project dengue incidences with respect to the future climate change. The regression model was developed using maximum temperature, minimum temperature, relative humidity and rainfall as key meteorological factors on the basis of statistically significant cross-correlation coefficient values to predict dengue cases. Finally, climate variables from the Coordinated Regional Climate Downscaling Experiment (CORDEX) for South Asia region were input into the statistical model to project the occurrences of dengue infections under different climate scenarios such as Representative Concentration Pathways (RCP4.5 and RCP8.5). It has been estimated that from 2020 to 2100, dengue cases will be higher from September to November with more cases in RCP8.5 (872 cases per year) than RCP4.5 (531 cases per year). The present research further concludes that from December to February, RCP8.5 leads to suitable warmer weather conditions essential for the survival and multiplication of dengue pathogens resulting more than two times dengue cases in RCP8.5 than in RCP4.5. Furthermore, the results obtained will be useful in developing early warning systems and provide important evidence for dengue control policy-making and public health intervention.
National level floods affect large sections of the population, and in turn, receive attention from the government and international agencies. Localized natural disasters, including localized floods, do not get the attention of the government and policymakers because their impact is felt within limited geographical areas, despite the fact that these disasters severely affect the livelihood of rural communities. This study examines the impact of localized floods on the livelihood of farmers in Pakistan using a cross-sectional data set collected from 812 households. The empirical results show that localized floods severely affect rural livelihoods, and affected households have lowered cereal crop yields, less income, and reduced food security levels. Farmers adopt a number of strategies, including crop and livestock insurance, bund-making, land-leveling, and tree planting, to combat the impact of localized floods. Among all these mitigating strategies, the tree plantation is ranked as the best mitigating strategy followed by crop and livestock insurance, land leveling, and bund making, respectively. Education, wealth, access to non-governmental organizations (NGOs), extension services, and infrastructure, influence the adoption of measures to mitigate the effect of flood risks. National policy on localized flood risks needs to strengthen local institutions to provide support to families and extension services to train farmers to mitigate the impact of localized floods.
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.
In the freshwater environment of north India, cholera appears seasonally in form of clusters as well as sporadically, accounting for a significant piece of the puzzle of cholera epidemiology. We describe a number of cholera outbreaks with an average attack rate of 96.5/1000 but an overall low case fatality (0.17). Clinical cholera cases coincided with high rainfall and elevated temperatures, whereas isolation of V. cholerae non-O1 non-O139 from water was dependent on temperature (p??0.05). However, isolation from plankton samples correlated with increased temperature and pH (p?
OBJECTIVE: Floods are one of the most common types of disasters in Bangladesh and lead to direct and indirect impacts on health. The aim of the study was to assess the impact of floods on Maternal and Newborn Healthcare (MNH) utilization in Bangladesh between the years 2011 and 2014. METHODS: We used variables from the Bangladesh Demographic and Health Survey 2014 data and georeferenced data of floods between 2011 and 2014 from the Emergency Events Database. Multivariate logistic regression was used to determine whether the flood-affected exposures were significant in predicting differences in MNH utilization. RESULTS: The odds for the received antenatal care by skilled providers, institutional deliveries, deliveries by c-section, and postnatal care of the babies were significantly lower (Unadjusted OR?=?0.81, 0.88, 0.83, and 0.82 respectively; P?
OBJECTIVES: Pneumonia is a significant contributor to mortality and morbidity in children aged <5 years, and it is also one of the leading causes of hospitalisation for children in this age group. This study assessed the association between climate variability, patient characteristics (i.e. age, sex, weight, parental education, socio-economic status) and length of stay (LOS) in hospital for childhood pneumonia and its economic impact on rural Bangladesh. STUDY DESIGN: An ecological study design was used. METHODS: Data on daily hospitalisation for pneumonia in children aged <5 years (including patient characteristics) and daily climate data (temperature and relative humidity) between 1st January 2012 and 31st December 2016 were obtained from the Matlab Hospital (the International Centre for Diarrhoeal Disease Research, Bangladesh) and the Bangladesh Meteorological Department, respectively. A generalised linear model with Poisson link was used to quantify the association between climate factors, patient characteristics and LOS in hospital. RESULTS: The study showed that average temperature, temperature variation and humidity variation were positively associated with the LOS in hospital for pneumonia. A 1°C rise in average temperature and temperature variation during hospital stay increased the LOS in hospital by 1% (relative risk [RR]: 1.010, 95% confidence interval [CI]: 1.001-1.018) and 9.3% (RR: 1.093, 95% CI: 1.051-1.138), respectively. A 1% increase in humidity variation increased the LOS in hospital for pneumonia by 2.2% (RR: 1.022, 95% CI: 1.004-1.039). In terms of economic impact, for every 1° C temperature variation during the period of hospital stay, there is an addition of 0.81 USD/day/patient as a result of direct costs and 1.8 USD/day/patient for total costs. Annually, this results in an additional 443 USD for direct and 985 USD for total costs. CONCLUSIONS: Climate variation appears to significantly contribute to the LOS in hospital for childhood pneumonia. These findings may help policymakers to develop effective disease management and prevention strategies.
Background: Around 2-3% of hospitalizations have been reported due to dermatological adverse drug reactions. Recent studies suggest that climatic variations affect the skin barrier function and extreme conditions aggravate skin disorders.
Objective: The present study was designed to compare the impact of climatic variations on drug-induced skin reactions in the Northern and Eastern regions of India. Methods: We performed a one-year retrospective study to evaluate the impact of climatic variations (temperature and humidity) in Eastern (Kalyani, West Bengal) and Northern (Karnal, Haryana) regions on drug-induced skin reactions. Drug-induced skin reactions were reported month-wise in both the Eastern and Northern regions. Temperature and humidity level were also noted month-wise in both the regions. The direct correlation between climatic variations and number of drug reactions were assessed using Pearson’s correlation and quadratic regression analysis.
Results and Discussion: Overall, 99 and 81 dermatological adverse drug reactions were reported in tertiary care hospitals in the Northern and Eastern regions, respectively. During the summer season, the humidity level was found to be low in the Northern region as compared to the Eastern region. During this period, drug-induced skin reactions were reported significantly (p<0.05) more in the Northern region as compared to the Eastern region. Furthermore, quadratic regression analysis revealed that climatic variations contributed to drug reaction variability in the Northern region (68.5%) and Eastern region (23.5%).
Conclusion: Therefore, the difference in the prevalence of drug-induced skin reactions may be related to the different climatic conditions among these two regions. Further studies in controlled climatic conditions should be performed for definitive correlations and to look into possible solutions.
.The number of serious and extreme drought events is increasing, causing a serious threat to ecosystems, food security, livelihood security, social stability, and sustainable development. The Marathwada region of India is highly vulnerable to the impacts of drought and has been severely affected because of consecutive drought events from 2012 to 2016. This article aims to understand the rural farming household’s perceptions of the impacts of drought, their adaptation and mitigation measures, and also attempts to assess the level of satisfaction of rural households with government mitigation measures. This study is based on primary and secondary sources of data collected from 192 farming households following a structured questionnaire survey. The survey reveals that crop failure, livelihood insecurity, declines in livestock production, livestock loss, water conflicts, and problems in meeting agricultural expenses, increased school dropout rates of children, and both psychological and health problems, were the most immediate socio-economic impacts of drought. The various environmental impacts of drought perceived by farmers included depleted groundwater levels, poor groundwater quality, land degradation, a decrease in seasonal river flows, degradation of pastures and declines in soil fertility. It was found that small and medium sized farmers were highly affected by drought compared with marginal and large scale farmers because of their high dependency on agriculture and poor adaptation strategies.
Coronavirus Disease 2019 (COVID-19) pandemic poses extreme threat to public health and economy, particularly to the nations with higher population density. The disease first reported in Wuhan, China; later, it spreads elsewhere, and currently, India emerged as COVID-19 hotspot. In India, we selected 20 densely populated cities having infection counts higher than 500 (by 15 May) as COVID-19 epicenters. Daily COVID-19 count has strong covariability with local temperature, which accounts approximately 65-85% of the explained variance; i.e., its spread depends strongly on local temperature rise prior to community transmission phase. The COVID-19 cases are clustered at temperature and humidity ranging within 27-32°C and 25-45%, respectively. We introduce a combined temperature and humidity profile, which favors rapid COVID-19 growth at the initial phase. The results are highly significant for predicting future COVID-19 outbreaks and modeling cities based on environmental conditions. On the other hand, CO(2) emission is alarmingly high in South Asia (India) and entails high risk of climate change and extreme hot summer. Zoonotic viruses are sensitive to warming induced climate change; COVID-19 epicenters are collocated on CO(2) emission hotspots. The COVID-19 count distribution peaks at 31.0°C, which is 1.0°C higher than current (2020) and historical (1961-1990) mean, value. Approximately, 72% of the COVID-19 cases are clustered at severe to record-breaking hot extremes of historical temperature distribution spectrum. Therefore, extreme climate change has important role in the spread of COVID-19 pandemic. Hence, a strenuous mitigation measure to abate greenhouse gas (GHG) emission is essential to avoid such pandemics in future.
This paper aims to scrutinize in what way peri-urbanization triggers climate change vulnerabilities. By using spatial analysis techniques, the study undertakes the following tasks. First, the study demarcates Dhaka’s-the capital of Bangladesh-peri-urban growth pattern that took place over the last 24-year period (1992-2016). Afterwards, it determines the conformity of ongoing peri-urban practices with Dhaka’s stipulated planning documents. Then, it identifies Dhaka’s specific vulnerabilities to climate change impacts-i.e., flood, and groundwater table depletion. Lastly, it maps out the socioeconomic profile of the climate change victim groups from Dhaka. The findings of the study reveal that: (a) Dhaka lacks adequate development planning, monitoring, and control mechanisms that lead to an increased and uncontrolled peri-urbanization; (b) Dhaka’s explicitly undefined peri-urban growth boundary is the primary factor in misguiding the growth pockets-that are the most vulnerable locations to climate change impacts, and; (c) Dhaka’s most vulnerable group to the increasing climate change impacts are the climate migrants, who have been repeatedly exposed to the climate change-triggered natural hazards. These study findings generate insights into peri-urbanization-triggered climate change vulnerabilities that aid urban policymakers, managers, and planners in their development policy, planning, monitoring and control practices.
We examine the impact of extreme heat during pregnancy on infant mortality and check if public interventions can serve as effective adaptation strategies. We show that 2 children die as infants out of 1000 births in India for high temperature during pregnancy, tentatively due to reduced agricultural yields, wages, and greater disease prevalence like diarrhea. The heat-infant mortality relationship holds in rural India only. Using phased introduction of an employment guarantee program and partial introduction of a community health care worker program for identification, we find that only the health program is effective in modifying the temperature-infant mortality relationship in rural India.
BACKGROUND: Heat-related illness is a common medical emergency. There is failure of thermoregulatory mechanisms of the body resulting in multiple organ dysfunction syndrome which if not identified and treated urgently can result in high mortality rate and permanent neurological damage. This study provides description of clinical profile patients presenting with heat-related illness and identifies clinical and laboratory variables resulting in poor outcome. METHODS: This retrospective study was done identifying adult patients admitted with a diagnosis of heat-related illness from April to August 2019 in tertiary care center. Their clinical profile, laboratory investigations and outcome were extracted from medical records and variables associated with poor outcome were analyzed for statistical significance. RESULTS: Mean age of the patients in the study was 61 years with mean heat index of the localities being 39.6-degree C. 66% of patients had multiple organ dysfunction with central nervous system dysfunction (77%) followed by respiratory distress syndrome (61%) as the most common organ derangement. Evaporative cooling measures were incorporated in management of all patients, followed by cold saline infusion in 60%. Higher J-ERATO score at admission was found to be a predictor for underlying multiple organ dysfunction syndrome (P value < 0.029). The mortality rate associated with heat-related illness in this study was 11.1%. CONCLUSIONS: Multiple organ dysfunction is seen in majority of the patients and calculation of simple admission J-ERATO score helps in predicting the same. Declining mortality rate observed in our study as compared to the earlier studies could be attributed to increased awareness, prompt diagnosis and initiation of rapid cooling measures.
The need for healthcare workers (HCWs) to wear personal protective equipment (PPE) during the coronavirus disease 2019 (COVID-19) pandemic heightens their risk of thermal stress. We assessed the knowledge, attitudes, and practices of HCWs from India and Singapore regarding PPE usage and heat stress when performing treatment and care activities. One hundred sixty-five HCWs from India (n = 110) and Singapore (n = 55) participated in a survey. Thirty-seven HCWs from Singapore provided thermal comfort ratings before and after ice slurry ingestion. Differences in responses between India and Singapore HCWs were compared. A p-value cut-off of 0.05 depicted statistical significance. Median wet-bulb globe temperature was higher in India (30.2 °C (interquartile range [IQR] 29.1-31.8 °C)) than in Singapore (22.0 °C (IQR 18.8-24.8 °C)) (p < 0.001). Respondents from both countries reported thirst (n = 144, 87%), excessive sweating (n = 145, 88%), exhaustion (n = 128, 78%), and desire to go to comfort zones (n = 136, 84%). In Singapore, reports of air-conditioning at worksites (n = 34, 62%), dedicated rest area availability (n = 55, 100%), and PPE removal during breaks (n = 54, 98.2%) were higher than in India (n = 27, 25%; n = 46, 42%; and n = 66, 60%, respectively) (p < 0.001). Median thermal comfort rating improved from 2 (IQR 1-2) to 0 (IQR 0-1) after ice slurry ingestion in Singapore (p < 0.001). HCWs are cognizant of the effects of heat stress but might not adopt best practices due to various constraints. Thermal stress management is better in Singapore than in India. Ice slurry ingestion is shown to be practical and effective in promoting thermal comfort. Adverse effects of heat stress on productivity and judgment of HCWs warrant further investigation.
BACKGROUND: Although many studies have provided evidence for all-cause mortality attributed to extreme temperature across India, few studies have provided a systematic analysis of the association between all-cause mortality and temperature. OBJECTIVE: To estimate the risk associated with heat waves during two major heat waves of Nagpur occurred in 2010 and 2014. METHODS: The association between temperature and mortality was measured using a distributed lag non-linear model (DLNM) and the attributable deaths associated with the heat waves with forward perspective in the DLNM framework. RESULTS: From the ecological analysis, we found 580 and 306 additional deaths in 2010 and 2014, respectively. Moving average results also gave similar findings. DLNM results showed that the relative risk was 1.5 for the temperature above 45 °C; forward perspective analysis revealed that the attributable deaths during 2010 and 2014 were 505 and 376, respectively. Results from different methods showed that heat waves in different years had variable impacts for various reasons. However, all the results were consistent during 2010 and 2014; there were 30% and 14% extra-mortalities due to heat comparing to non-heat wave years. CONCLUSION: We strongly recommend the city Government to implement the action plans based on this research outcome to reduce the risk from the heat wave in future.
Drinking water quality is of vital importance for the healthy life of a community especially if consumer is a teenager. In order to compare groundwater profile of flooded area (FA) and non-flooded area (NFA) of district Sanghar, 120 water samples from public schools were collected and investigated for physico-chemical parameters, essential metals, trace elements and microbiological indicators. Analysis data revealed that 47% samples in FA were contaminated with faecal coliform bacteria as compared to only 8.3% in NFA. On the other hand, chemical indicators like TDS, Ca, Na, K, SO4, Mg and hardness were higher in FA. Comparison of trace elements content with WHO guidelines revealed that concentration of Fe, As and Zn was higher in 66.7%, 31.7% and 13.3% water samples, respectively in FA whereas content of these elements was also on higher side in 3.3%, 23.3% and 1.7% samples in NFA, respectively. Health risk assessment due to high concentration of Fe, As and Zn showed that As HRI>1, for children in 35 and 23% water samples in FA and NFA, respectively.
Limited evidence is available concerning the household-level costs of prevailing diseases and the potential cost of climate adaptation in Nepal. This study estimates these costs and assesses the relationships between prevalent diseases and climate adaptation at the household level using survey data from 420 households. An ingredients-based approach was used to estimate the cost of health and adaptation, and a Probit regression model was used to analyze the relationship between prevalent diseases and climate adaptation costs. Household direct curative costs are the highest among health cost components. Two-thirds of total health costs are direct costs for households. On average, 15.90% of household income is used for direct cost of health care. The climate hazard cost among afflicted households is estimated to be high. In addition, diseases like malaria, typhoid and jaundice, their costs, climate awareness program, droughts, family size and loss of per capita income are more likely to raise the cost of climate adaptation. The occurrence of gastritis, prevalence of diarrhea and cold waves are less likely to affect the cost. Policymakers should implement health financing schemes and adaptation strategies to prevent the loss of human health in western Nepal.
Malaria occurrence in the Chittagong Hill Tracts in Bangladesh varies by season and year, but this pattern is not well characterized. The role of environmental conditions on the occurrence of this vector-borne parasitic disease in the region is not fully understood. We extracted information on malaria patients recorded in the Upazila (sub-district) Health Complex patient registers of Rajasthali in Rangamati district of Bangladesh from February 2000 to November 2009. Weather data for the study area and period were obtained from the Bangladesh Meteorological Department. Non-linear and delayed effects of meteorological drivers, including temperature, relative humidity, and rainfall on the incidence of malaria, were investigated. We observed significant positive association between temperature and rainfall and malaria occurrence, revealing two peaks at 19 °C (logarithms of relative risks (logRR) = 4.3, 95% CI: 1.1-7.5) and 24.5 °C (logRR = 4.7, 95% CI: 1.8-7.6) for temperature and at 86 mm (logRR = 19.5, 95% CI: 11.7-27.3) and 284 mm (logRR = 17.6, 95% CI: 9.9-25.2) for rainfall. In sub-group analysis, women were at a much higher risk of developing malaria at increased temperatures. People over 50 years and children under 15 years were more susceptible to malaria at increased rainfall. The observed associations have policy implications. Further research is needed to expand these findings and direct resources to the vulnerable populations for malaria prevention and control in the Chittagong Hill Tracts of Bangladesh and the region with similar settings.
The present study explores the spatial and temporal pattern of cold wave related mortalities over India. The data for this study has been obtained from the annual reports pertaining to ‘Disastrous Weather Events’ published by India Meteorological Department, Pune for 37-years (1978-2014). The analysis reveals that a total of 8520 mortalities have been caused by 606 cold wave events, with an average of 230 mortalities per year. Only two states i.e. Bihar (44%) and Uttar Pradesh (31%) account for approximately 75% of total cold waves mortalities, while eleven states namely, Arunachal Pradesh, Assam, Goa, Karnataka, Kerala, Manipur, Mizoram, Nagaland, Sikkim, Tamil Nadu and Tripura have never experienced cold wave events and mortalities. Interestingly, each cold wave event has caused approximately 43 mortalities alone in Bihar state. Furthermore, mortality (standardized by population) and density rates (standardized by area) in India have been observed to be 0.24 and 2.65, respectively. In temporal terms, cold wave events and mortalities have shown large interannual variations without any significant increasing or decreasing trend. Most of the cold wave events and mortalities have been observed in January and December months. Males have been found to be more severely affected by the cold waves than females and children. Overall, the results of this research may provide an understanding to develop effective disaster management guidelines for temperature extremes safety and preparedness.
Sri Lanka is experiencing various social and environmental challenges, including drought, storms, floods, and landslides, due to climate change. One of Sri Lanka’s biggest cities, Kurunegala, is a densely populated city that is gradually turning into an economic revitalization area. This fast-growing city needs to establish an integrated urban plan that takes into account the risks of climate change. Thus, a climate change risk assessment was conducted for both the water and heat wave risks via discussions with key stakeholders. The risk assessment was conducted as a survey based on expert assessment of local conditions, with awareness surveys taken by residents, especially women. The assessment determined that the lack of drinking water was the biggest issue, a problem that has become more serious due to recent droughts caused by climate change and insufficient water management. In addition, the outbreak of diseases caused by heat waves was identified as a serious concern. Risk assessment is integral to developing an action plan for minimizing the damage from climate change. It is necessary to support education and awareness in developing countries so that they can perform risk assessment well and develop both problem-solving and policy-making abilities to adapt to a changing climate.
Background: Rotavirus diarrhea is often referred as “winter diarrheal disease” as it causes nearly 50% of the pediatric hospitalizations during winter season. This study was done with the objective of bringing out the epidemiological nexus of rotavirus cases with different seasonal parameters like maximum, minimum temperature, humidity, and average rainfall. Methods: This prospective observational study was conducted in a tertiary care teaching hospital of Eastern India from February 2016 to December 2018. Data on daily maximum and minimum temperature, relative humidity, and rainfall were collected. Result: Of 964 children admitted, 768 stool samples were collected for rotavirus assay. A total of 222 children (29%) were positive. The maximum, minimum temperature, average rainfall, and average humidity of 83.4 mm, 79.2%, 28.1, and 21.9, respectively, were significantly associated with positive rotaviral cases. Conclusions: The incidence of rotavirus positivity cases was found to be inversely associated with average temperature, humidity, and rainfall. The knowledge about the seasonal pattern in a particular geographical area would help in the reallocation of hospital services (staff and bed) to tackle the epidemic or emergency situations resulting from clustering of cases.
In India, a reduction in wheat crop yield would lead to a widespread impact on food security. In particular, the most vulnerable people are severely exposed to food insecurity. This study estimates the climate change vulnerability of wheat crops with respect to heterogeneities in time, space, and weighting methods. The study uses the Intergovernmental Panel on Climate Change (IPCC) framework of vulnerability while using composite indices of 27 indicators to explain exposure, sensitivity, and adaptive capacity. We used climate projections under current (1975-2005) conditions and two future (2021-2050) Representation Concentration Pathways (RCPs), 4.5 and 8.5, to estimate exposure to climatic risks. Consistency across three weighting methods (Analytical Hierarchy Process (AHP), Principal Component Analysis (PCA), and Equal Weights (EWs)) was evaluated. Results of the vulnerability profile suggest high vulnerability of the wheat crop in northern and central India. In particular, the districts Unnao, Sirsa, Hardoi, and Bathinda show high vulnerability and high consistency across current and future climate scenarios. In total, 84% of the districts show more than 75% consistency in the current climate, and 83% and 68% of the districts show more than 75% consistency for RCP 4.5 and RCP 8.5 climate scenario for the three weighting methods, respectively. By using different weighting methods, it was possible to quantify “method uncertainty” in vulnerability assessment and enhance robustness in identifying most vulnerable regions. Finally, we emphasize the importance of communicating uncertainties, both in data and methods in vulnerability research, to effectively guide adaptation planning. The results of this study would serve as the basis for designing climate impacts adjusted adaptation measures for policy interventions.
BACKGROUND: Dengue, a febrile illness, is caused by a Flavivirus transmitted by Aedes aegypti and Aedes albopictus mosquitoes. Climate influences the ecology of the vectors. We aimed to identify the influence of climatic variability on the occurrence of clinical dengue requiring hospitalization in Zone-5, a high incidence area of Dhaka City Corporation (DCC), Bangladesh. METHODS AND FINDINGS: We retrospectively identified clinical dengue cases hospitalized from Zone-5 of DCC between 2005 and 2009. We extracted records of the four major catchment hospitals of the study area. The Bangladesh Meteorological Department (BMD) provided data on temperature, rainfall, and humidity of DCC for the study period. We used autoregressive integrated moving average (ARIMA) models for the number of monthly dengue hospitalizations. We also modeled all the climatic variables using Poisson regression. During our study period, dengue occurred throughout the year in Zone-5 of DCC. The median number of hospitalized dengue cases was 9 per month. Dengue incidence increased sharply from June, and reached its peak in August. One additional rainy day per month increased dengue cases in the succeeding month by 6% (RR = 1.06, 95% CI: 1.04-1.09). CONCLUSIONS: Dengue is transmitted throughout the year in Zone-5 of DCC, with seasonal variation in incidence. The number of rainy days per month is significantly associated with dengue incidence in the subsequent month. Our study suggests the initiation of campaigns in DCC for controlling dengue and other Aedes mosquito borne diseases, including Chikunguniya from the month of May each year. BMD rainfall data may be used to determine campaign timing.
Floods are one of the greatest hazards in Bangladesh. It is assumed that people who reside in a riverine area have adapted to flood pulses. However, in most cases, household-level risk-reduction strategies are inadequate for ensuring a livelihood resilient to floods. This is because riverine people are exposed to recurrent floods, which increases their vulnerability to floods. In order to formulate effective risk-reduction policies and programs for riverine areas, it is crucial to measure flood risk at the local level. This study, therefore, aims to assess the flood risk of riverine households. A multi-dimensional integrated flood risk assessment framework was adopted to quantify household-level flood risk. Using a systematic random sampling technique, 377 respondents from the right bank of the Teesta River in Bangladesh were interviewed to characterize flood hazards, exposure to floods, and their vulnerability and capacity to absorb flood risk. The survey also includes key informant interviews. The collected data were aggregated using a composite index, while comparing the components of flood risk. Descriptive and analytical statistics were also computed. The results showed that flood risk was higher in downstream areas, followed by upstream areas and the midstream segments of the right bank of the Teesta River. The degree of flood risk in these three clusters was significantly different. A significant negative correlation was observed between vulnerability and capacity. No significant associations were found between the exposure and vulnerability components. The multivariate analysis suggested that households’ perceived preparedness was influenced by their ability to responds to floods. The empirical approach presented in this study could be used to assess flood risk in other regions, especially where data is scarce.
INTRODUCTION: Environmental factors such as wind, temperature, humidity, and sun exposure are known to affect influenza and viruses such as severe acute respiratory syndrome (SARS) and Middle East Respiratory Syndrome (MERS) transmissions. COVID-19 is a new pandemic with very little information available about its transmission and association with environmental factors. The goal of this paper is to explore the association of environmental factors on daily incidence rate, mortality rate, and recoveries of COVID-19. METHODS: The environmental data for humidity, temperature, wind, and sun exposure were recorded from metrological websites and COVID-19 data such as the daily incidence rate, death rate, and daily recovery were extracted from the government’s official website available to the general public. The analysis for each outcome was adjusted for factors such as lock down status, nationwide events, and the number of daily tests performed. Analysis was completed with negative binominal regression log link using generalised linear modelling. RESULTS: Daily temperature, sun exposure, wind, and humidity were not significantly associated with daily incidence rate. Temperature and nationwide social gatherings, although non-significant, showed trends towards a higher chance of incidence. An increase in the number of daily testing was significantly associated with higher COVID-19 incidences (effect size ranged from 2.17-9.96). No factors were significantly associated with daily death rates. Except for the province of Balochistan, a lower daily temperature was associated with a significantly higher daily recovery rate. DISCUSSION: Environmental factors such as temperature, humidity, wind, and daily sun exposure were not consistently associated with COVID-19 incidence, death rates, or recovery. More policing about precautionary measures and ensuring diagnostic testing and accuracy are needed.
