Associations between High Temperature, Heavy Rainfall, and Diarrhea among Young Children in Rural Tamil Nadu, India: A Prospective Cohort Study

Matching actions to needs: shifting policy responses to the changing health needs of Chinese children and adolescents

China is home to the second largest population of children and adolescents in the world. Yet demographic shifts mean that the government must manage the challenge of fewer children with the needs of an ageing population, while considering the delicate tension between economic growth and environmental sustainability. We mapped the health problems and risks of contemporary school-aged children and adolescents in China against current national health policies. We involved multidisciplinary experts, including young people, with the aim of identifying actionable strategies and specific recommendations to promote child and adolescent health and wellbeing. Notwithstanding major improvements in their health over the past few decades, contemporary Chinese children and adolescents face distinct social challenges, including high academic pressures and youth unemployment, and new health concerns including obesity, mental health issues, and sexually transmitted infections. Inequality by gender, geography, and ethnicity remains a feature of health risks and outcomes. We identified a mismatch between current health determinants, risks and outcomes, and government policies. To promote the health of children and adolescents in China, we recommend a set of strategies that target government-led initiatives across the health, education, and community sectors, which aim to build supportive and responsive families, safe communities, and engaging and respectful learning environments. TRANSLATION: For the Chinese translation of the abstract see Supplementary Materials section.

Influence of hydrometeorological risk factors on child diarrhea and enteropathogens in rural Bangladesh

BACKGROUND

A number of studies have detected relationships between weather and diarrhea. Few have investigated associations with specific enteric pathogens. Understanding pathogen-specific relationships with weather is crucial to inform public health in low-resource settings that are especially vulnerable to climate change.

OBJECTIVES

Our objectives were to identify weather and environmental risk factors associated with diarrhea and enteropathogen prevalence in young children in rural Bangladesh, a population with high diarrheal disease burden and vulnerability to weather shifts under climate change.

METHODS

We matched temperature, precipitation, surface water, and humidity data to observational longitudinal data from a cluster-randomized trial that measured diarrhea and enteropathogen prevalence in children 6 months-5.5 years from 2012-2016. We fit generalized additive mixed models with cubic regression splines and restricted maximum likelihood estimation for smoothing parameters.

RESULTS

Comparing weeks with 30°C versus 15°C average temperature, prevalence was 3.5% higher for diarrhea, 7.3% higher for Shiga toxin-producing Escherichia coli (STEC), 17.3% higher for enterotoxigenic E. coli (ETEC), and 8.0% higher for Cryptosporidium. Above-median weekly precipitation (median: 13mm; range: 0-396mm) was associated with 29% higher diarrhea (adjusted prevalence ratio 1.29, 95% CI 1.07, 1.55); higher Cryptosporidium, ETEC, STEC, Shigella, Campylobacter, Aeromonas, and adenovirus 40/41; and lower Giardia, sapovirus, and norovirus prevalence. Other associations were weak or null.

DISCUSSION

Higher temperatures and precipitation were associated with higher prevalence of diarrhea and multiple enteropathogens; higher precipitation was associated with lower prevalence of some enteric viruses. Our findings emphasize the heterogeneity of the relationships between hydrometeorological variables and specific enteropathogens, which can be masked when looking at composite measures like all-cause diarrhea. Our results suggest that preventive interventions targeted to reduce enteropathogens just before and during the rainy season may more effectively reduce child diarrhea and enteric pathogen carriage in rural Bangladesh and in settings with similar meteorological characteristics, infrastructure, and enteropathogen transmission.

Floods and Diarrhea Risk in Young Children in Low- and Middle-Income Countries

Importance

Climate change is associated with more frequent and intense floods. Current research on the association between flood exposure and diarrhea risk is limited mainly to short-term and event-specific analyses. Moreover, how prior drought or water, sanitation, and hygiene (WaSH) practices influence this association remains largely unknown.

Objective

To examine the association between flood exposure and diarrhea risk among children younger than 5 years and to evaluate the compounding influence of prior drought and effect modification by WaSH.

Design, Setting, and Participants

This cross-sectional study included multicluster surveys conducted by the Demographic and Health Surveys Program in 43 low- and middle-income countries during 2009 through 2019. This study included children younger than 5 years in all households from each survey cluster. Collected data were analyzed between September 1 and December 31, 2022.

Exposures

Historical flood events during 2009 through 2019 were obtained from the Dartmouth Flood Observatory.

Main Outcome and Measures

The main outcome was diarrhea prevalence among children younger than 5 years in the 2 weeks before the survey was conducted. Results were analyzed by binomial generalized linear mixed-effects logistic regression models with nested random intercepts for country and survey cluster.

Results

Among 639 250 children making up the complete data series (excluding 274 847 children with missing values for diarrhea or baseline characteristics), 6365 (mean [SD] age, 28.9 [17.2] months; 3214 boys [50.5%]; 3151 girls [49.5%]) were exposed to floods during the 8 weeks after a flood started. The prevalence of diarrhea was 13.2% (n = 839) among exposed children and 12.7% (n = 80 337) among unexposed children. Exposure to floods was associated with increased diarrhea risk, with the highest odds ratio (OR) observed during the second to fourth weeks after floods started (OR, 1.35; 95% CI, 1.05-1.73). When floods were stratified by severity and duration, significant associations were observed only for extreme floods (OR during the third to fifth weeks, 2.07; 95% CI, 1.37-3.11) or floods lasting more than 2 weeks (OR during the second to fourth weeks, 1.47; 95% CI, 1.13-1.92), with significantly stronger associations than for less extreme floods or shorter-duration floods, respectively. The OR during the first 4 weeks after the start of floods was significantly higher for floods preceded by a 6-month or longer drought (12-month drought OR, 1.96; 95% CI, 1.53-2.52) than for floods not preceded by a 6-month or longer drought (12-month drought OR, 1.00; 95% CI, 0.79-1.27).

Conclusions

These findings suggest that floods, especially severe floods, long-duration floods, and floods preceded by drought, are associated with an increased risk of diarrhea among children younger than 5 years living in low- and middle-income countries. With the projected increasing frequency and intensity of floods and drought under climate change, greater collective efforts are needed to protect children's health from these compounding events.

Understanding diarrhoeal diseases in response to climate variability and drought in Cape Town, South Africa: a mixed methods approach

BACKGROUND

The climate of southern Africa is expected to become hotter and drier with more frequent severe droughts and the incidence of diarrhoea to increase. From 2015 to 2018, Cape Town, South Africa, experienced a severe drought which resulted in extreme water conservation efforts. We aimed to gain a more holistic understanding of the relationship between diarrhoea in young children and climate variability in a system stressed by water scarcity.

METHODS

Using a mixed-methods approach, we explored diarrhoeal disease incidence in children under 5 years between 2010 to 2019 in Cape Town, primarily in the public health system through routinely collected diarrhoeal incidence and weather station data. We developed a negative binomial regression model to understand the relationship between temperature, precipitation, and relative humidity on incidence of diarrhoea with dehydration. We conducted in-depth interviews with stakeholders in the fields of health, environment, and human development on perceptions around diarrhoea and health-related interventions both prior to and over the drought, and analysed them through the framework method.

RESULTS

From diarrhoeal incidence data, the diarrhoea with dehydration incidence decreased over the decade studied, e.g. reduction of 64.7% in 2019 [95% confidence interval (CI): 5.5-7.2%] compared to 2010, with no increase during the severe drought period. Over the hot dry diarrhoeal season (November to May), the monthly diarrhoea with dehydration incidence increased by 7.4% (95% CI: 4.5-10.3%) per 1 °C increase in temperature and 2.6% (95% CI: 1.7-3.5%) per 1% increase in relative humidity in the unlagged model. Stakeholder interviews found that extensive and sustained diarrhoeal interventions were perceived to be responsible for the overall reduction in diarrhoeal incidence and mortality over the prior decade. During the drought, as diarrhoeal interventions were maintained, the expected increase in incidence in the public health sector did not occur.

CONCLUSIONS

We found that that diarrhoeal incidence has decreased over the last decade and that incidence is strongly influenced by local temperature and humidity, particularly over the hot dry season. While climate change and extreme weather events especially stress systems supporting vulnerable populations such as young children, maintaining strong and consistent public health interventions helps to reduce negative health impacts.

Short-Term Effects of Climate Variability on Childhood Diarrhoea in Bangladesh: Multi-Site Time-Series Regression Analysis

The aim of this study was to estimate the effects of climate on childhood diarrhoea hospitalisations across six administrative divisions in Bangladesh and to provide scientific evidence for local health authorities for disease control and prevention. Fortnightly hospital admissions (August/2013-June/2017) for diarrhoea in children under five years of age, and fortnightly average maximum temperature, relative humidity and rainfall recordings for six administrative divisions were modelled using negative binomial regression with distributed lag linear terms. Flexible spline functions were used to adjust models for seasonality and long-term trends. During the study period, 25,385 diarrhoea cases were hospitalised. Overall, each 1 °C rise in maximum temperature increased diarrhoea hospitalisations by 4.6% (IRR = 1.046; 95% CI, 1.007-1.088) after adjusting for seasonality and long-term trends in the unlagged model. Using lagged effects of maximum temperature, and adjusting for relative humidity and rainfall for each of the six administrative divisions, the relationship between maximum temperature and diarrhoea hospitalisations varied between divisions, with positive and negative effect estimates. The temperature-diarrhoea association may be confounded by seasonality and long-term trends. Our findings are a reminder that the effects of climate change may be heterogeneous across regions, and that tailored diarrhoea prevention strategies need to consider region-specific recommendations rather than relying on generic guidelines.

Artificial intelligence in wastewater treatment: A data-driven analysis of status and trends

Wastewater treatment is a complex process that involves many uncertainties, leading to fluctuations in effluent quality and costs, and environmental risks. Artificial intelligence (AI) can handle complex nonlinear problems and has become a powerful tool for exploring and managing wastewater treatment systems. This study provides a summary of the current status and trends in AI research as applied to wastewater treatment, based on published papers and patents. Our results indicate that, at present, AI is primarily used to evaluate removal of pollutants (conventional, typical, and emerging contaminants), optimize models and process parameters, and control membrane fouling. Future research will likely continue to focus on removal of phosphorus, organic pollutants, and emerging contaminants. Moreover, analyzing microbial community dynamics and achieving multi-objective optimization are promising directions of research. The knowledge map shows that there may be future technological innovation related to predicting water quality under specific conditions, integrating AI with other information technologies and utilizing image-based AI and other algorithms in wastewater treatment. In addition, we briefly review development of artificial neural networks (ANNs) and explore the evolutionary path of AI in wastewater treatment. Our findings provide valuable insights into potential opportunities and challenges for researchers applying AI to wastewater treatment.

Effects of High Temperature and Heavy Precipitation on Drinking Water Quality and Child Hand Contamination Levels in Rural Kenya

Climate change may impact human health through the influence of weather on environmental transmission of diarrhea. Previous studies have found that high temperatures and heavy precipitation are associated with increased diarrhea prevalence, but the underlying causal mechanisms have not been tested and validated. We linked measurements of Escherichia coli in source water (n = 1673), stored drinking water (n = 9692), and hand rinses from children <2 years old (n = 2634) with publicly available gridded temperature and precipitation data (at ≤0.2 degree spatial resolution and daily temporal resolution) by the GPS coordinates and date of sample collection. Measurements were collected over a 3-year period across a 2500 km² area in rural Kenya. In drinking water sources, high 7-day temperature was associated with a 0.16 increase in log₁₀ E. coli levels (p < 0.001, 95% CI: 0.07, 0.24), while heavy 7-day total precipitation was associated with a 0.29 increase in log₁₀ E. coli levels (p < 0.001, 95% CI: 0.13, 0.44). In household stored drinking water, heavy 7-day precipitation was associated with a 0.079 increase in log₁₀ E. coli levels (p = 0.042, 95% CI: 0.07, 0.24). Heavy precipitation did not increase E. coli levels among respondents who treated their water, suggesting that water treatment can mitigate effects on water quality. On child hands, high 7-day temperature was associated with a 0.39 decrease in log₁₀ E. coli levels (p < 0.001, 95% CI: -0.52, -0.27). Our findings provide insight on how climate change could impact environmental transmission of bacterial pathogens in Kenya. We suggest water treatment is especially important after heavy precipitation (particularly when preceded by dry periods) and high temperatures.

The impact of temperature and precipitation on all-infectious-, bacterial-, and viral-diarrheal disease in Taiwan

BACKGROUND

The ongoing climate change will elevate the incidence of diarrheal in 2030-2050 in Asia, including Taiwan. This study investigated associations between meteorological factors (temperature, precipitation) and burden of age-cause-specific diarrheal diseases in six regions of Taiwan using 13 years of (2004-2016) population-based data.

METHODS

Weekly cause-specific diarrheal and meteorological data were obtained from 2004 to 2016. We used distributed lag non-linear model to assess age (under five, all age) and cause-specific (viral, bacterial) diarrheal disease burden associated with extreme high (99th percentile) and low (5th percentile) of climate variables up to lag 8 weeks in six regions of Taiwan. Random-effects meta-analysis was used to pool these region-specific estimates.

RESULTS

Extreme low temperature (15.30 °C) was associated with risks of all-infectious and viral diarrhea, with the highest risk for all-infectious diarrheal found at lag 8 weeks among all age [Relative Risk (RR): 1.44; 95 % Confidence Interval (95 % CI): 1.24-1.67]. The highest risk of viral diarrheal infection was observed at lag 2 weeks regardless the age. Extreme high temperature (30.18 °C) was associated with risk of bacterial diarrheal among all age (RR: 1.07; 95 % CI: 1.02-1.13) at lag 8 weeks. Likewise, extreme high precipitation (290 mm) was associated with all infectious diarrheal, with the highest risk observed for bacterial diarrheal among population under five years (RR: 2.77; 95 % CI: 1.60-4.79) at lag 8 weeks. Extreme low precipitation (0 mm) was associated with viral diarrheal in all age at lag 1 week (RR: 1.08; 95 % CI: 1.01-1.15)].

CONCLUSION

In Taiwan, extreme low temperature is associated with an increased burden of viral diarrheal, while extreme high temperature and precipitation elevated burden of bacterial diarrheal. This distinction in cause-specific and climate-hazard specific diarrheal disease burden underscore the importance of incorporating differences in public health preparedness measures designed to enhance community resilience against climate change.

Uncovering social and environmental factors that increase the burden of climate-sensitive diarrheal infections on children

Climate-sensitive infectious diseases are an issue of growing concern due to global warming and the related increase in the incidence of extreme weather and climate events. Diarrhea, which is strongly associated with climatic factors, remains among the leading causes of child death globally, disproportionately affecting populations in low- and middle-income countries (LMICs). We use survey data for 51 LMICs between 2000 and 2019 in combination with gridded climate data to estimate the association between precipitation shocks and reported symptoms of diarrheal illness in young children. We account for differences in exposure risk by climate type and explore the modifying role of various social factors. We find that droughts are positively associated with diarrhea in the tropical savanna regions, particularly during the dry season and dry-to-wet and wet-to-dry transition seasons. In the humid subtropical regions, we find that heavy precipitation events are associated with increased risk of diarrhea during the dry season and the transition from dry-to-wet season. Our analysis of effect modifiers highlights certain social vulnerabilities that exacerbate these associations in the two climate zones and present opportunities for public health intervention. For example, we show that stool disposal practices, child feeding practices, and immunizing against the rotavirus modify the association between drought and diarrhea in the tropical savanna regions. In the humid subtropical regions, household's source of water and water disinfection practices modify the association between heavy precipitation and diarrhea. The evidence of effect modification varies depending on the type and duration of the precipitation shock.

The Association Between Rainfall, Temperature, and Reported Drinking Water Source: A Multi-Country Analysis

Climate change may alter access to safe drinking water, with important implications for health. We assessed the relationship between temperature and rainfall and utilization of basic drinking water (BDW) in The Gambia, Mozambique, Pakistan, and Kenya. The outcomes of interest were (a) whether the reported drinking water source used in the past 2 weeks met the World Health Organization definition of BDW and (b) use of a BDW source that was always available. Temperature and precipitation data were compiled from weather stations and satellite data and summarized to account for long- and short-term weather patterns and lags. We utilized random forests and logistic regression to identify key weather variables that predicted outcomes by site and the association between important weather variables and BDW use. Higher temperatures were associated with decreased BDW use at three of four sites and decreased use of BDW that is always available at all four sites. Increasing rainfall, both in the long- and short-term, was associated with increased BDW use in three sites. We found evidence for interactions between household wealth and weather variables at two sites, suggesting lower wealth populations may be more sensitive to weather-driven changes in water access. Changes in temperature and precipitation can alter safe water use in low-resource settings-investigating drivers for these relationships can inform efforts to build climate resilience.

Climate change impacts on the health of South Asian children and women subpopulations - A scoping review

Background and objectives

Climate change impacts are felt unequally worldwide; populations that experience geographical vulnerability, those living in small island states and densely populated coastal areas, and children and women are affected disproportionately. This scoping review aims to synthesize evidence from relevant studies centred on South Asia, identify research gaps specifically focused on children and women's health, and contribute to knowledge about South Asia's existing mitigation and adaptation strategies.

Methods

A research librarian executed the search on six databases using controlled vocabulary (e.g., MeSH, Emtree, etc.) and keywords representing the concepts “vulnerable populations” and “climate change” and “health impacts” and “South Asia.” Databases were searched from January 2010 to May 2020. Papers were screened independently by two researchers.

Results

Forty-two studies were included, of which 23 were based in India, 14 in Bangladesh, and five in other South Asian countries. Nineteen studies focused on meteorological factors as the primary exposure. In contrast, thirteen focused on extreme weather events, nine on air pollution, and one on salinity in coastal areas. Thirty-four studies focused on the health impacts on children related to extreme weather events, meteorological factors, and air pollution, while only eight studies looked at health impacts on women. Undernutrition, ARI (acute respiratory infection), diarrheal diseases, low birth weight, and premature mortality were the major health impacts attributed to extreme weather events, meteorological factors, and air pollution exposure in children and women in the region.

Conclusion

Extreme weather events, meteorological factors and air pollution have affected the health of children and women in South Asia. However, the gap in the literature across the South Asian countries concerning relationships between exposure to extreme weather events, meteorological factors, air pollution and health effects, including mental health problems in children and women, are opportunities for future work.

Bottled and Well Water Quality in a Small Central Appalachian Community: Household-Level Analysis of Enteric Pathogens, Inorganic Chemicals, and Health Outcomes in Rural Southwest Virginia

Consumption of unsafe drinking water is associated with a substantial burden of disease globally. In the US, ~1.8 million people in rural areas lack reliable access to safe drinking water. Our objective was to characterize and assess household-level water sources, water quality, and associated health outcomes in Central Appalachia. We collected survey data and water samples (tap, source, and bottled water) from consenting households in a small rural community without utility-supplied water in southwest Virginia. Water samples were analyzed for physicochemical parameters, total coliforms, E. coli, nitrate, sulfate, metals (e.g., arsenic, cadmium, lead), and 30+ enteric pathogens. Among the 69% (n = 9) of households that participated, all had piped well water, though 67% (n = 6) used bottled water as their primary drinking water source. Total coliforms were detected in water samples from 44.4% (n = 4) of homes, E. coli in one home, and enteric pathogens (Aeromonas, Campylobacter, Enterobacter) in 33% (n = 3) of homes. Tap water samples from 11% (n = 1) of homes exceeded the EPA MCL for nitrate, and 33% (n = 3) exceeded the EPA SMCL for iron. Among the 19 individuals residing in study households, reported diarrhea was 25% more likely in homes with measured E. coli and/or specific pathogens (risk ratio = 1.25, cluster-robust standard error = 1.64, p = 0.865). Although our sample size was small, our findings suggest that a considerable number of lower-income residents without utility-supplied water in rural areas of southwest Virginia may be exposed to microbiological and/or chemical contaminants in their water, and many, if not most, rely on bottled water as their primary source of drinking water.

Estimating the seasonally varying effect of meteorological factors on the district-level incidence of acute watery diarrhea among under-five children of Iran, 2014-2018: a Bayesian hierarchical spatiotemporal model

Under-five years old acute watery diarrhea (U5AWD) accounts for most diarrheal diseases' burden, but little is known about the adjusted effect of meteorological and socioeconomic determinants. A dataset containing the seasonal numbers of U5AWD cases at the district level of Iran is collected through MOHME. Accordingly, the district-level standardized incidence ratio and Moran's I values are calculated to detect the significant clusters of U5AWD over sixteen seasons from 2014 to 2018. Additionally, the author tested twelve Bayesian hierarchical models in order to determine which one was the most accurate at forecasting seasonal number of incidents. Iran features a number of U5AWD hotspots, particularly in the southeast. An extended spatiotemporal model with seasonally varying coefficients and space-time interaction outperformed other models, and so became the paper's proposal in modeling U5AWD. Temperature demonstrated a global positive connection with seasonal U5AWD in districts (IRR: 1.0497; 95% CrI: 1.0254-1.0748), owing to its varying effects during the winter ((IRR: 1.0877; 95% CrI: 1.0408-1.1375) and fall (IRR: 1.0866; 95% CrI: 1.0405-1.1357) seasons. Also, elevation (IRR: 0.9997; 95% CrI: 0.9996-0.9998), piped drinking water (IRR: 0.9948; 95% CrI: 0.9933-0.9964), public sewerage network (IRR: 0.9965; 95% CrI: 0.9938-0.9992), years of schooling (IRR: 0.9649; 95% CrI: 0.944-0.9862), infrastructure-to-household size ratio (IRR: 0.9903; 95% CrI: 0.986-0.9946), wealth index (IRR: 0.9502; 95% CrI: 0.9231-0.9781), and urbanization (IRR: 0.9919; 95% CrI: 0.9893-0.9944) of districts were negatively associated with seasonal U5AWD incidence. Strategically, developing geoinformation alarm systems based on meteorological data might help predict U5AWD high-risk areas. The study also anticipates increased rates of U5AWD in districts with poor sanitation and socioeconomic level. Therefore, governments should take appropriate preventative actions in these sectors.

The effect and attributable risk of daily temperature on category C infectious diarrhea in Guangdong Province, China

Previous studies have explored the effect between ambient temperature and infectious diarrhea (ID) mostly using relative risk, which provides limited information in practical applications. Few studies have focused on the disease burden of ID caused by temperature, especially for different subgroups and cities in a multi-city setting. This study aims to estimate the effects and attributable risks of temperature on category C ID and explore potential modifiers among various cities in Guangdong. First, distributed lag non-linear models (DLNMs) were used to explore city-specific associations between daily mean temperature and category C ID from 2014 to 2016 in Guangdong and pooled by applying multivariate meta-analysis. Then, multivariate meta-regression was implemented to analyze the potential heterogeneity among various cities. Finally, we assessed the attributable burden of category C ID due to temperature, low (below the 5th percentile of temperature) and high temperature (above the 95th percentile of temperature) for each city and subgroup population. Compared with the 50th percentile of daily mean temperature, adverse effects on category C ID were found when the temperature was lower than 12.27 ℃ in Guangdong Province. Some city-specific factors (longitude, urbanization rate, population density, disposable income per capita, and the number of medical technicians and beds per thousand persons) could modify the relationship of temperature-category C ID. During the study period, there were 60,505 category C ID cases (17.14% of total cases) attributable to the exposure of temperature, with the attributable fraction (AF) of low temperature (4.23%, 95% empirical confidence interval (eCI): 1.79-5.71%) higher than high temperature (1.34%, 95% eCI: 0.86-1.64%). Males, people under 5 years, and workers appeared to be more vulnerable to temperature, with AFs of 29.40%, 19.25%, and 21.49%, respectively. The AF varied substantially at the city level, with the largest AF of low temperature occurring in Shaoguan (9.58%, 95% eCI: 8.36-10.09%), and that of high temperature occurring in Shenzhen (3.16%, 95% eCI: 2.70-3.51%). Low temperature was an important risk factor for category C ID in Guangdong Province, China. The exposure-response relationship could be modified by city-specific characteristics. Considering the whole population, the attributable risk of low temperature was much higher than that of high temperature, and males, people under 5 years, and workers were vulnerable populations.

Associations between climate variables and water quality in low- and middle-income countries: A scoping review

Understanding how climate change will affect water quality and therefore, health, is critical for building resilient water services in low- and middle-income countries (LMICs) where the effect of climate change will be felt most acutely. Evidence of the effect of climate variables such as temperate and rainfall on water quality can generate insights into the likely impact of future climate change. While the seasonal effects on water quality are known, and there is strong qualitative evidence that climate change will impact water quality, there are no reviews that synthesise quantitative evidence from LMICs on links between climate variables and water quality. We mapped the available evidence on a range of climate exposures and water quality outcomes and identified 98 peer-reviewed studies. This included observational studies on the impact of temperature and rainfall events (which may cause short-term changes in contaminant concentrations), and modelling studies on the long-term impacts of sea level rise. Evidence on links between antecedent rainfall and microbiological contamination of water supplies is strong and relatively evenly distributed geographically, but largely focused on faecal indicator bacteria and on untreated shallow groundwater sources of drinking water. The literature on climate effects on geogenic contaminants was sparse. There is substantial research on the links between water temperature and cyanobacteria blooms in surface waters, although most studies were from two countries and did not examine potential effects on water treatment. Similarly, studies modelling the impact of sea level rise on groundwater salinity, mostly from south-Asia and the Middle East, did not discuss challenges for drinking water supplies. We identified key future research priorities based on this review. These include: more studies on specific pathogens (including opportunistic pathogens) in water supplies and their relationships with climate variables; more studies that assess likely relationships between climate variables and water treatment processes; studies into the relationships between climate variables and geogenic contaminants, including risks from heavy metals released as glacier retreat; and, research into the impacts of wildfires on water quality in LMICs given the current dearth of studies but recognised importance.

Projecting Temperature-Attributable Mortality and Hospital Admissions due to Enteric Infections in the Philippines

BACKGROUND

Enteric infections cause significant deaths, and global projection studies suggest that mortality from enteric infections will increase in the future with warmer climate. However, a major limitation of these projection studies is the use of risk estimates derived from nonmortality data to project excess enteric infection mortality associated with temperature because of the lack of studies that used actual deaths.

OBJECTIVE

We quantified the associations of daily temperature with both mortality and hospital admissions due to enteric infections in the Philippines. These associations were applied to projections under various climate and population change scenarios.

METHODS

We modeled nonlinear temperature associations of mortality and hospital admissions due to enteric infections in 17 administrative regions of the Philippines using a two-stage time-series approach. First, we quantified nonlinear temperature associations of enteric infections by fitting generalized linear models with distributed lag nonlinear models. Second, we combined regional estimates using a meta-regression model. We projected the excess future enteric infections due to nonoptimal temperatures using regional temperature-enteric infection associations under various combinations of climate change scenarios according to representative concentration pathways (RCPs) and population change scenarios according to shared socioeconomic pathways (SSPs) for 2010-2099.

RESULTS

Regional estimates for mortality and hospital admissions were significantly heterogeneous and had varying shapes in association with temperature. Generally, mortality risks were greater in high temperatures, whereas hospital admission risks were greater in low temperatures. Temperature-attributable excess deaths in 2090-2099 were projected to increase over 2010-2019 by as little as 1.3% [95% empirical confidence intervals (eCI): -3.1%, 6.5%] under a low greenhouse gas emission scenario (RCP 2.6) or as much as 25.5% (95% eCI: -3.5%, 48.2%) under a high greenhouse gas emission scenario (RCP 8.5). A moderate increase was projected for temperature-attributable excess hospital admissions, from 0.02% (95% eCI: -2.0%, 1.9%) under RCP 2.6 to 5.2% (95% eCI: -12.7%, 21.8%) under RCP 8.5 in the same period. High temperature-attributable deaths and hospital admissions due to enteric infections may occur under scenarios with high population growth in 2090-2099.

DISCUSSION

In the Philippines, futures with hotter temperatures and high population growth may lead to a greater increase in temperature-related excess deaths than hospital admissions due to enteric infections. Our results highlight the need to strengthen existing primary health care interventions for diarrhea and support health adaptation policies to help reduce future enteric infections. https://doi.org/10.1289/EHP9324.

Biodigester Cookstove Interventions and Child Diarrhea in Semirural Nepal: A Causal Analysis of Daily Observations

BACKGROUND

Hundreds of thousands of biodigesters have been constructed in Nepal. These household-level systems use human and animal waste to produce clean-burning biogas used for cooking, which can reduce household air pollution from woodburning cookstoves and prevent respiratory illnesses. The biodigesters, typically operated by female caregivers, require the handling of animal waste, which may increase domestic fecal contamination, exposure to diarrheal pathogens, and the risk of enteric infections, especially among young children.

OBJECTIVE

We estimated the effect of daily reported biogas cookstove use on incident diarrhea among children < 5 y old in the Kavrepalanchok District of Nepal. Secondarily, we assessed effect measure modification and statistical interaction of individual- and household-level covariates (child sex, child age, birth order, exclusive breastfeeding, proof of vaccination, roof type, sanitation, drinking water treatment, food insecurity) as well as recent 14-d acute lower respiratory infection (ALRI) and season.

METHODS

We analyzed 300,133 person-days for 539 children in an observational prospective cohort study to estimate the average effect of biogas stove use on incident diarrhea using cross-validated targeted maximum likelihood estimation (CV-TMLE).

RESULTS

Households reported using biogas cookstoves in the past 3 d for 23% of observed person-days. The adjusted relative risk of diarrhea for children exposed to biogas cookstove use was 1.31 (95% confidence interval (CI): 1.00, 1.71) compared to unexposed children. The estimated effect of biogas stove use on diarrhea was stronger among breastfed children (2.09; 95% CI: 1.35, 3.25) than for nonbreastfed children and stronger during the dry season (2.03; 95% CI: 1.17, 3.53) than in the wet season. Among children exposed to biogas cookstove use, those with a recent ALRI had the highest mean risk of diarrhea, estimated at 4.53 events (95% CI: 1.03, 8.04) per 1,000 person-days.

DISCUSSION

This analysis provides new evidence that child diarrhea may be an unintended health risk of biogas cookstove use. Additional studies are needed to identify exposure pathways of fecal pathogen contamination associated with biodigesters to improve the safety of these widely distributed public health interventions. https://doi.org/10.1289/EHP9468.

Hospitalization Rates and Direct Medical Costs for Fever in a Pediatric Cohort in South India

Background

Primary data on causes and costs of hospitalization are necessary for costing and cost-effectiveness analysis. Data on incidence and causes of hospitalization and consequent expenses among Indian children are limited.

Methods

A cohort of 6000 children aged 0.5–15 years residing in urban Vellore was followed for 3 years, under the Vellore Typhoid Study, 2016–2017, and later under the Surveillance for Enteric Fever project, 2017–2019. Data on hospitalization events and associated antibiotic use, and direct medical costs for fever-related hospitalization of study children were obtained from caregivers through weekly follow-up by study field workers.

Results

The incidence of hospitalization was 33 per 1000 child-years of observation. Children aged 0.5–5 years had the highest incidence of hospitalization. The top 5 infectious causes for hospitalization were acute undifferentiated fevers, respiratory tract infections, acute gastroenteritis, enteric fever, and dengue. The overall median cost of hospitalization for fever was 4243 (interquartile range, 2502–7215) Indian rupees (INR). An episode of dengue had a median cost of 5627 INR, followed by acute undifferentiated fevers and enteric fever with median costs of 3860 and 3507 INR, respectively.

Conclusions

Hospitalization for fever is common in young children and impacts household finances in low-income Indian households.

Association between climate and infectious diseases among children in Varanasi city, India: A prospective cohort study

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/m³) 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.

Effect of ambient temperatures on category C notifiable infectious diarrhea in China: An analysis of national surveillance data

BACKGROUND

Many studies have explored the association between meteorological factors and infectious diarrhea (ID) transmission but with inconsistent results, in particular the roles from temperatures. We aimed to explore the effects of temperatures on the transmission of category C ID, to identify its potential heterogeneity in different climate zones of China, and to provide scientific evidence to health authorities and local communities for necessary public health actions.

METHODS

Daily category C ID counts and meteorological variables were collected from 270 cities in China over the period of 2014-16. Distributed lag non-linear models (DLNMs) were applied in each city to obtain the city-specific temperature-disease associations, then a multivariate meta-analysis was implemented to pool the city-specific effects. Multivariate meta-regression was conducted to explore the potential effect modifiers. Attributable fraction was calculated for both low and high temperatures, defined as temperatures below the 5th percentile of temperature or above the 95th percentile of temperature.

RESULTS

A total of 2,715,544 category C ID cases were reported during the study period. Overall, a M-shaped curve relationship was observed between temperature and category C ID, with a peak at the 81st percentile of temperatures (RR = 1.723, 95% CI: 1.579-1.881) compared to 50th percentile of temperatures. The pooled associations were generally stronger at high temperatures compared to low ambient temperatures, and the attributable fraction due to heat was higher than cold. Latitude was identified as a possible effect modifier.

CONCLUSIONS

The overall positive pooled associations between temperature and category C ID in China suggest the increasing temperature could bring about more category C infectious diarrhea cases, which warrants further public health measurements.

Boiled or Bottled: Regional and Seasonal Exposures to Drinking Water Contamination and Household Air Pollution in Rural China

BACKGROUND

Inadequate access to safe drinking water remains a global health problem, particularly in rural areas. Boiling is the most commonly used form of point-of-use household water treatment (HWT) globally, although the use of bottled water in low- and middle-income countries (LMICs) is increasing rapidly.

OBJECTIVES

We assessed the regional and seasonal prevalence of HWT practices (including bottled water use) in low-income rural areas in two Chinese provinces, evaluated the microbiological safety of drinking water and associated health outcomes, and estimated the air pollution burden associated with the use of solid fuels for boiling.

METHODS

We conducted cross-sectional surveys and collected drinking water samples from 1,033 rural households in Guangxi and Henan provinces. Temperature sensors affixed to pots and electric kettles were used to corroborate self-reported boiling frequencies and durations, which were used to model household air pollution (HAP) in terms of estimated particulate matter ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 ) concentrations.

RESULTS

Based on summer data collection in both provinces, after controlling for covariates, boiling with electric kettles was associated with the largest log reduction in thermotolerant coliforms (TTCs) (- 0.66 log 10 TTC most probable number/ 100 mL ), followed by boiling with pots (- 0.58 ), and bottled water use (- 0.39 ); all were statistically significant (p < 0.001 ). Boiling with electric kettles was associated with a reduced risk of TTC contamination [risk ratio ( RR ) = 0.25 , p < 0.001 ] and reported diarrhea (RR = 0.80 , p = 0.672 ). TTCs were detected in 51% (n = 136 ) of bottled water samples. For households boiling with biomass, modeled PM 2.5 concentrations averaged 79   μ g / m 3 (standard deviation = 21 ).

DISCUSSION

Our findings suggest that where boiling is already common and electricity access is widespread, the promotion of electricity-based boiling may represent a pragmatic stop-gap means of expanding safe water access until centralized, or decentralized, treated drinking water is available; displacing biomass use for water boiling could also reduce HAP concentrations and exposures. Our results also highlight the risks of increasing bottled water use in rural areas, and its potential to displace other sources of safe drinking water, which could in turn hamper efforts in China and other LMICs toward universal and affordable safe water access. https://doi.org/10.1289/EHP7124.

Effects of heavy rainfall on waterborne disease hospitalizations among young children in wet and dry areas of New Zealand

Heavy rainfall is associated with increased risk of waterborne disease. However, it is not known whether the risk increment differs between wet and dry regions. We examined this question in New Zealand, which has a wide geographical variation of annual rainfall totals (10^th-90^th percentile difference ≥3000 mm). We conducted a nested case-crossover study within a prospective child cohort (born in 2009-2010) for assessing transient health effects when modified by longitudinal exposures to rainfall. Short-term heavy rainfall effects on hospitalizations due to enteric bacterial and viral infectious causes at lag of 0-14 days were assessed using a Cox regression model adjusted for daily temperature, relative humidity and evapotranspiration. We derived quantiles of time-weighted long-term rainfall levels at the children's homes and these were added as an interaction term to the short-term effect model. Hospitalization risks were higher two days after heavy rainfall days (hazard ratio [95% confidence interval]: 1.73 [1.10-2.70]). The lowest-observable-adverse-effect-level was detected at the 94^th percentile of daily rainfall total. Hospital admissions 1-2 days after heavy rainfall increased most in locations with the lowest and highest long-term rainfall. An interaction of this kind between short-term weather and long-term climate has not been reported previously. It is relevant to climate change risk assessments given global projections of increasing intensity of precipitation, against a background of more severe, and possibly more frequent, droughts and flooding.

Understanding the Impact of Rainfall on Diarrhea: Testing the Concentration-Dilution Hypothesis Using a Systematic Review and Meta-Analysis

BACKGROUND

Projected increases in extreme weather may change relationships between rain-related climate exposures and diarrheal disease. Whether rainfall increases or decreases diarrhea rates is unclear based on prior literature. The concentration-dilution hypothesis suggests that these conflicting results are explained by the background level of rain: Rainfall following dry periods can flush pathogens into surface water, increasing diarrhea incidence, whereas rainfall following wet periods can dilute pathogen concentrations in surface water, thereby decreasing diarrhea incidence.

OBJECTIVES

In this analysis, we explored the extent to which the concentration-dilution hypothesis is supported by published literature.

METHODS

To this end, we conducted a systematic search for articles assessing the relationship between rain, extreme rain, flood, drought, and season (rainy vs. dry) and diarrheal illness.

RESULTS

A total of 111 articles met our inclusion criteria. Overall, the literature largely supports the concentration-dilution hypothesis. In particular, extreme rain was associated with increased diarrhea when it followed a dry period [incidence rate ratio ( IRR ) = 1.26 ; 95% confidence interval (CI): 1.05, 1.51], with a tendency toward an inverse association for extreme rain following wet periods, albeit nonsignificant, with one of four relevant studies showing a significant inverse association (IRR = 0.911 ; 95% CI: 0.771, 1.08). Incidences of bacterial and parasitic diarrhea were more common during rainy seasons, providing pathogen-specific support for a concentration mechanism, but rotavirus diarrhea showed the opposite association. Information on timing of cases within the rainy season (e.g., early vs. late) was lacking, limiting further analysis. We did not find a linear association between nonextreme rain exposures and diarrheal disease, but several studies found a nonlinear association with low and high rain both being associated with diarrhea.

DISCUSSION

Our meta-analysis suggests that the effect of rainfall depends on the antecedent conditions. Future studies should use standard, clearly defined exposure variables to strengthen understanding of the relationship between rainfall and diarrheal illness. https://doi.org/10.1289/EHP6181.

Systems Science Approaches for Global Environmental Health Research: Enhancing Intervention Design and Implementation for Household Air Pollution (HAP) and Water, Sanitation, and Hygiene (WASH) Programs

BACKGROUND

Two of the most important causes of global disease fall in the realm of environmental health: household air pollution (HAP) and poor water, sanitation, and hygiene (WASH) conditions. Interventions, such as clean cookstoves, household water treatment, and improved sanitation facilities, have great potential to yield reductions in disease burden. However, in recent trials and implementation efforts, interventions to improve HAP and WASH conditions have shown few of the desired health gains, raising fundamental questions about current approaches.

OBJECTIVES

We describe how the failure to consider the complex systems that characterize diverse real-world conditions may doom promising new approaches prematurely. We provide examples of the application of systems approaches, including system dynamics, network analysis, and agent-based modeling, to the global environmental health priorities of HAP and WASH research and programs. Finally, we offer suggestions on how to approach systems science.

METHODS

Systems science applied to environmental health can address major challenges by a) enhancing understanding of existing system structures and behaviors that accelerate or impede aims; b) developing understanding and agreement on a problem among stakeholders; and c) guiding intervention and policy formulation. When employed in participatory processes that engage study populations, policy makers, and implementers, systems science helps ensure that research is responsive to local priorities and reflect real-world conditions. Systems approaches also help interpret unexpected outcomes by revealing emergent properties of the system due to interactions among variables, yielding complex behaviors and sometimes counterintuitive results.

DISCUSSION

Systems science offers powerful and underused tools to accelerate our ability to identify barriers and facilitators to success in environmental health interventions. This approach is especially useful in the context of implementation research because it explicitly accounts for the interaction of processes occurring at multiple scales, across social and environmental dimensions, with a particular emphasis on linkages and feedback among these processes. https://doi.org/10.1289/EHP7010.

Poultry Ownership Associated with Increased Risk of Child Diarrhea: Cross-Sectional Evidence from Uganda

Domestic animals have been associated with enteric infections in young children and can also be carriers of respiratory viruses. We conducted a cross-sectional assessment of health outcomes in children aged < 5 years associated with animal presence among 793 rural households in Uganda. We recorded the 2-week prevalence of diarrhea and respiratory infections in children, and the number of cows, poultry, sheep/goats, and pigs in the household. We used generalized linear models with robust standard errors to estimate the prevalence ratio (PR) for diarrhea and respiratory infections associated with households owning the above- versus below-median number of animals. We conducted unadjusted and adjusted analyses controlling for socioeconomic, water, sanitation, and hygiene indicators. Children in households with the above-median number (> 5) of poultry had 83% higher diarrhea prevalence than those with ≤ 5 poultry (adjusted PR = 1.83 [1.04, 3.23], P = 0.04). Children in households with the above-median number (> 2) of cows had 48% lower prevalence of respiratory infection than those with ≤ 2 cows (adjusted PR = 0.52 [0.35, 0.76], P < 0.005). There were no other significant associations between domestic animals and child health. Studies should assess if barring chickens from indoor living quarters and sanitary disposal of chicken and other animal feces can reduce childhood zoonotic infections.

Precipitation and Salmonellosis Incidence in Georgia, USA: Interactions between Extreme Rainfall Events and Antecedent Rainfall Conditions

BACKGROUND

The southeastern United States consistently has high salmonellosis incidence, but disease drivers remain unknown. Salmonella is regularly detected in this region's natural environment, leading to numerous exposure opportunities. Rainfall patterns may impact the survival/transport of environmental Salmonella in ways that can affect disease transmission.

OBJECTIVES

This study investigated associations between short-term precipitation (extreme rainfall events) and longer-term precipitation (rainfall conditions antecedent to these extreme events) on salmonellosis counts in the state of Georgia in the United States.

METHODS

For the period 1997-2016, negative binomial models estimated associations between weekly county-level extreme rainfall events (≥90th percentile of daily rainfall) and antecedent conditions (8-week precipitation sums, categorized into tertiles) and weekly county-level salmonellosis counts.

RESULTS

In Georgia's Coastal Plain counties, extreme and antecedent rainfall were associated with significant differences in salmonellosis counts. In these counties, extreme rainfall was associated with a 5% increase in salmonellosis risk (95% CI: 1%, 10%) compared with weeks with no extreme rainfall. Antecedent dry periods were associated with a 9% risk decrease (95% CI: 5%, 12%), whereas wet periods were associated with a 5% increase (95% CI: 1%, 9%), compared with periods of moderate rainfall. In models considering the interaction between extreme and antecedent rainfall conditions, wet periods were associated with a 13% risk increase (95% CI: 6%, 19%), whereas wet periods followed by extreme events were associated with an 11% increase (95% CI: 5%, 18%). Associations were substantially magnified when analyses were restricted to cases attributed to serovars commonly isolated from wildlife/environment (e.g., Javiana). For example, wet periods followed by extreme rainfall were associated with a 34% risk increase (95% CI: 20%, 49%) in environmental serovar infection.

CONCLUSIONS

Given the associations of short-term extreme rainfall events and longer-term rainfall conditions on salmonellosis incidence, our findings suggest that avoiding contact with environmental reservoirs of Salmonella following heavy rainfall events, especially during the rainy season, may reduce the risk of salmonellosis. https://doi.org/10.1289/EHP4621.