Disparities in the adverse health effects due to ambient environmental exposures have long been documented in the environmental epidemiology literature. A growing body of environmental epidemiology literature has focused on how detrimental aspects of the physical environment (e.g., poor housing quality) and social environment (e.g., chronic social stressors) can exacerbate the adverse health effects of environmental exposures (e.g., air pollution, heat). However, the literature on protective factors which might mitigate adverse health effects of environmental exposure is more limited. We borrow from the climate resilience and disaster preparedness literature to discuss how protective community assets may be identified, operationalized, and understood in environmental epidemiologic research. We outline two major pathways through which community assets may protect environmental health: by reducing overall exposure (mediation) and by reducing susceptibility (effect modification). This framework can help environmental epidemiologists and other public health researchers select and understand appropriate community assets to test as effect modifiers or mediators of associations between environmental exposures and adverse health outcomes. We present examples of community assets organized into five domains and highlight pragmatic challenges that may arise when considering assets in large-scale epidemiologic research-for example, limitations on availability of publicly available data at meaningful spatial scales, and challenges interpreting available community asset data. Finally, we posit that research focused on community assets can inform scalable, impactful health-promoting interventions.
Early Relational Health (ERH)-a foundational determinant of lifelong mental and physical health-is emerging as a critical component of paediatric practice. However, its integration into Canadian paediatric residency training remains poorly defined. This study conducted an environmental scan of Canadian paediatric residency programs to examine the current state of ERH education, as reported by Program Directors (PDs). PDs from Canadian paediatric residency programs were invited to complete an anonymous survey (September-December 2023). The survey explored PDs' definitions of ERH, existing training opportunities, perceptions of how well ERH is addressed, and motivators for incorporating structured curricula. Data were analyzed using descriptive statistics. Ten PDs completed the survey (37% response rate). All (100%) General Pediatrics PDs reported their program teaches positive parenting and early child development "Not Very Well," compared with 20% of subspecialty PDs. Sixty per cent of General Pediatrics PDs and all Subspecialty PDs rated an ERH curriculum as "Very Important" for their learners. Nearly all respondents expressed interest in implementing a structured, evidence-based, self-guided ERH curriculum to improve resident knowledge and skills. This is the first study to evaluate ERH training within Canadian paediatric residency programs. While some subspecialty programs have integrated ERH content, most General Pediatrics programs identified clear training gaps. All PDs recognized ERH as an essential topic despite limited formal education opportunities. Development of a structured, competency-based ERH curriculum represents a key next step in advancing paediatric training and care quality in Canada.
Early childhood development forms the cornerstone for a healthy, fulfilling, and productive life. Research in health psychology and longevity highlights that social relationships are the most significant determinant of lifelong health and development. Among these, early attachment between children and caregivers, bolstered by positive experiences and nurturing environments, is pivotal for optimal growth, development, and well-being. This highlights the need for holistic approaches in healthcare, particularly during the critical first 1000 days of life. To address these needs, comprehensive evaluations must include assessments of childcaregiver interactions alongside biological, psychological, social, and environmental factors. Recognizing this, the American Academy of Pediatrics has embraced the Early Relational Health (ERH) framework, focusing on fostering healthy relationships during this crucial period. The framework encompasses all caregivers, including parents, extended family, and peers. The ERH framework emphasizes a broad assessment of factors affecting health-biological, psychological, interactional, economic, and environmental-within the child and caregivers' living contexts. The primary objective is not to teach parenting skills but to cultivate safe, stable, nurturing relationships supporting lifelong well-being. The ERH underscores the critical importance of assessing relational health as a "fifth vital sign," alongside traditional measures such as respiratory rate, heart rate, temperature, and blood pressure, in the first 1000 days. Integrating this framework into health systems can enhance the well-being of children and caregivers, ensuring a robust foundation for lifelong development.
As temperatures defy heat records, it is difficult to ignore the implications of climate change for public health, including impacts on population health more specifically. In short, climate change is happening now and presents an immediate hazard to human health on a global scale. Age-related health effects are an inalienable truth; physiology is relatively universal, and so are the ways in which our bodies respond to different types and levels of exposures to environmental stressors at different lifestages. Children are uniquely vulnerable to climate change stressors not only due to their physical and developmental immaturity, but also because they generally rely on adult caretakers for the fundamentals of survival. This article is the summary piece accompanying a special issue of Environmental Research: Health. It compiles new studies on children's vulnerability to climate change as well as studies exploring climate adaptation strategies to promote and protect child health. In this special issue, we see how these concepts are reflected repeatedly in empirical data domestically and internationally. For example, the special issue includes articles investigating linkages between climate change and health hazards such as asthma, injuries, and malnutrition. While local context is extremely important, many of the health effects may be extrapolated to other communities around the world.
To explore the associations of long-term exposure to air pollution with onset of all human health conditions. Prospective phenome-wide association study. Denmark. All Danish residents aged ≥30 years on 1 January 2000 were included (N=3 323 612). After exclusion of individuals with missing geocoded residential addresses, 3 111 988 participants were available for the statistical analyses. First registered diagnosis of every health condition according to the International Classification of Diseases, 10th revision, from 2000 to 2017. Long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were both positively associated with the onset of more than 700 health conditions (ie, >80% of the registered health conditions) after correction for multiple testing, while the remaining associations were inverse or insignificant. As regards the most common health conditions, PM2.5 and NO2 were strongest positively associated with chronic obstructive pulmonary disease (PM2.5: HR 1.06 (95% CI 1.05 to 1.07) per 1 IQR increase in exposure level; NO2: 1.14 (95% CI 1.12 to 1.15)), type 2 diabetes (PM2.5: 1.06 (95% CI 1.05 to 1.06); NO2: 1.12 (95% CI 1.10 to 1.13)) and ischaemic heart disease (PM2.5: 1.05 (95% CI 1.04 to 1.05); NO2: 1.11 (95% CI 1.09 to 1.12)). Furthermore, PM2.5 and NO2 were both positively associated with so far unexplored, but highly prevalent outcomes relevant to public health, including senile cataract, hearing loss and urinary tract infection. The findings of this study suggest that air pollution has a more extensive impact on human health than previously known. However, as this study is the first of its kind to investigate the associations of long-term exposure to air pollution with onset of all human health conditions, further research is needed to replicate the study findings.
Assessing the health impacts of climate stressors is challenging due to the inherently interdisciplinary nature of the effort and the complexity of data, methods, and software involved. We surveyed researchers who published in the climate and health space to identify major barriers to using and sharing climate and health data and code resources. Participants were identified using a PubMed query to return articles related to research in the field of climate and health. Using the PubMed API, we scraped email addresses for authors of matching published articles. 9195 authors were emailed a link to the online survey instrument, which took approximately 7 min to complete. We had an 11.8% response rate resulting in 1041 useable responses. Respondents were from over 75 different countries with only 16.4% working with US populations and were evenly represented between early, mid, and established career. The most desired resources were analysis-ready datasets and educational materials on data management and analysis. Personal constraints such as lack of time were a major barrier to sharing data or code. Our survey results suggest that investment in data creation as a professional service, knowledge sharing and collaboration, and research infrastructure will be enthusiastically adopted and help to accelerate the pace of research to practice.
Climate change-driven temperature increases worsen air quality in places where coal combustion powers electricity for air conditioning. Climate solutions that substitute clean and renewable energy in place of polluting coal and promote adaptation to warming through reflective cool roofs can reduce cooling energy demand in buildings, lower power sector carbon emissions, and improve air quality and health. We investigate the air quality and health co-benefits of climate solutions in Ahmedabad, India-a city where air pollution levels exceed national health-based standards-through an interdisciplinary modeling approach. Using a 2018 baseline, we quantify changes in fine particulate matter (PM2.5) air pollution and all-cause mortality in 2030 from increasing renewable energy use (mitigation) and expanding Ahmedabad's cool roofs heat resilience program (adaptation). We apply local demographic and health data and compare a 2030 mitigation and adaptation (M&A) scenario to a 2030 business-as-usual (BAU) scenario (without climate change response actions), each relative to 2018 pollution levels. We estimate that the 2030 BAU scenario results in an increase of PM2.5 air pollution of 4.13 µg m-3 from 2018 compared to a 0.11 µg m-3 decline from 2018 under the 2030 M&A scenario. Reduced PM2.5 air pollution under 2030 M&A results in 1216-1414 fewer premature all-cause deaths annually compared to 2030 BAU. Achievement of National Clean Air Programme, National Ambient Air Quality Standards, or World Health Organization annual PM2.5 Air Quality Guideline targets in 2030 results in up to 6510, 9047, or 17 369 fewer annual deaths, respectively, relative to 2030 BAU. This comprehensive modeling method is adaptable to estimate local air quality and health co-benefits in other settings by integrating climate, energy, cooling, land cover, air pollution, and health data. Our findings demonstrate that city-level climate change response policies can achieve substantial air quality and health co-benefits. Such work can inform public discourse on the near-term health benefits of mitigation and adaptation.
Fermentation plays a pivotal role in shaping the flavor and overall quality of Pu-erh tea, a microbially fermented dark tea. Here, we monitored physicochemical properties, chemical constituents, and microbial succession at 15 fermentation time points. Amplicon sequencing identified Staphylococcus, Bacillus, Kocuria, Aspergillus, Blastobotrys, Thermomyces, and Rasamsonia as dominant genera, with prokaryotic communities showing greater richness and diversity than eukaryotic ones. Beta diversity and clustering analyses revealed stable microbial structures during late fermentation stages. Non-targeted metabolomics detected 347 metabolites, including 56 significantly differential compounds enriched in caffeine metabolism and unsaturated fatty acid biosynthesis. Fermentation phases exhibited distinct metabolic patterns, with volatile aroma compounds (2-acetyl-1-pyrroline, 2,5-dimethylpyrazine) and health-beneficial fatty acids (linoleic acid, arachidonic acid) accumulating in later stages. OPLS-DA and KEGG PATHWAY analyses confirmed significant shifts in metabolite profiles relevant to flavor and biofunctionality. RDA revealed strong correlations between microbial taxa, environmental parameters, and representative metabolites. To functionally verify microbial contributions, 17 bacterial and 10 fungal strains were isolated. Six representative strains, mainly Bacillus and Aspergillus, exhibited high enzymatic activity on macromolecules, confirming their roles in polysaccharide and protein degradation. This integrative multi-omics investigation provides mechanistic insights into Pu-erh tea fermentation and offers a scientific basis for microbial community optimization in tea processing.
The development of innovative tools for real-time monitoring and forecasting of environmental health impacts is central to effective public health interventions and resource allocation strategies. Though a need for such generic tools has been previously echoed by public health planners and regional authorities responsible for issuing anticipatory alerts, a comprehensive, robust and scalable real-time system for predicting temperature-related excess deaths at a local scale has not been developed yet. Filling this gap, we propose a flexible operational framework for coupling publicly available weather forecasts with temperature-mortality risk functions specific to small census-based zones, the latter derived using state-of-the-art environmental epidemiological models. Utilising high-resolution temperature data forecast by a leading European meteorological centre, we demonstrate a real-time application to forecast the excess mortality during the July 2022 heatwave over England and Wales. The output, consisting of expected temperature-related excess deaths at small geographic areas on different lead times, can be automated to generate maps at various spatio-temporal scales, thus facilitating preventive action and allocation of public health resources in advance. While the real-case example discussed here demonstrates an application for predicting (expected) heat-related excess deaths, the framework can also be adapted to other weather-related health risks and to different geographical areas, provided data on both meteorological exposure and the underlying health outcomes are available to calibrate the associated risk functions. The proposed framework addresses an urgent need for predicting the short-term environmental health burden on public health systems globally, especially in low- and middle-income regions, where rapid response to mitigate adverse exposures and impacts to extreme temperatures are often constrained by available resources.
Diabetes is one of the major non-communicable diseases whose physiological complications are linked with a higher risk of mortality amongst the adult age group of people living globally. This review article documents updated pharmacological evidence and insights into the antidiabetic mechanisms of green, black, white, oolong, and pu-erh teas via reported experimental and clinical models toward encouraging their use as a complementary nutraceutical in managing the biochemical alterations found in the onset and progression of diabetes. Peer-reviewed articles published in "PubMed", "Google Scholar", and "ScienceDirect" from 2010 and beyond that reported the antidiabetic, antilipidemic, and digestive enzyme inhibitory effects of the selected tea types were identified. The keywords used for the literature search comprise the common or scientific names of the tea and their corresponding bioactivity. Although teas portrayed different antidiabetic pharmacological properties linked to their bioactive components, including polyphenols, polysaccharides, and amino acids, the type of phytochemical found in each tea type depends on their processing. Green tea's strong carbohydrate digestive enzyme inhibitory effect was linked with Ellagitannins and catechins, whereas theaflavin, a main ingredient in black tea, increases insulin sensitivity via enhancing GLUT4 translocation. Theabrownin in pu-erh tea improves FBG and lipid metabolism, while chemical components in white tea attenuate prediabetes-mediated reproductive dysfunctions by improving testicular tissue antioxidant capabilities. Based on the body of findings presented in this article, it is evident that integrating tea intake into daily food consumption routines could offer a promising practical solution to support human health and well-being against diabetes disease.
Extreme heat events (EHEs) are the deadliest weather hazards in the United States (U.S.). Local health jurisdictions (LHJs) in the U.S. are frontline responders during EHEs and other public health emergencies. This study aims to clarify the factors influencing EHE preparedness and response implementation. From January to March 2023, we conducted and thematically analyzed four focus group discussions with 17 representatives from U.S. LHJs. The Consolidated Framework for Implementation Research was used to guide the discussion. Participants described barriers, facilitators, and needs surrounding extreme heat preparedness and response implementation. The focus group discussions identified four factors that influence EHE preparedness and response implementation: local conditions (environmental, political, planning); engaging communities and tailoring strategies; partnerships and relational connections; and available resources. Focus group discussions emphasized the need for EHE preparedness and response activities to be targeted and scaled to the unique climate, population, and needs of the implementing jurisdiction. Local conditions, community engagement, partnerships, and available resources shape LHJ priorities. The study emphasizes the need for scalable resources and comprehensive plans, and identifies research gaps to be addressed in the future.
Microbial-induced corrosion costs billions of dollars, including replacing plastics degraded by fungi. Fungal growth is moisture dependent, but we need to better understand how equilibrium relative humidity (ERH) affects plastic degradation. The goal of this project was to measure how ERH impacts degradation of polyester polyurethane foam by Aureobasidium pullulans and identify potential genetic pathways. We incubated three environmental strains of A. pullulans on foam at 50%, 85%, and 100% ERH and evaluated degradation through foam weight loss, Scanning Electron Microscopy (SEM), external nutrient availability, RNA sequencing, and proxy Impranil clearing. Higher ERH after 1 week of incubation corresponded to greater weight loss in foam (p = 0.002), with percent weight loss ranging from 0.11% to 5.1%. SEM foam imaging shows signs of fungal growth and degradation at high ERH while nutrient data suggests that, beyond the foam, additional carbon is not required. We identified 10 cutinases among the three strains. In one strain, two cutinases were 2.5 to 100-fold upregulated at 85% and 100% ERH compared to 50% (p < 0.05) and the cutinase with the highest upregulation demonstrated clearing of Impranil. Our results demonstrate that increased relative humidity can increase fungal degradation of polyurethane foams as relevant for biodegradation prevention or promotion.
Fine particulate air pollution (PM2.5) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities.
Climate change will increase the frequency of extreme weather events. This means climate-driven events like wildfires and power outages will likely co-occur more often, potentially magnifying their health risks. We characterized three types of climate-driven events-anomalously warm temperatures, wildfire burn zone disasters, and long power outages-in 58 California counties during 2018-2019. We defined county-day anomalously warm temperatures when daily average temperatures exceeded 24 °C and the 85th percentile of the long-term county average. We defined county-day wildfire burn zone disasters when an active wildfire burn zone intersected a county, burned 1+ structures, killed a civilian, or received a Federal Emergency Management Agency Fire Management Declaration, and overlapped with a community. For a subset of the 38 counties (66%), long power outage county days were identified using PowerOutage.us data when an outage affected >0.5% of county customers for 8+ h. Co-occurring events were when 2+ of these events occurred on the same county day. Using the CDC/ATSDR Social Vulnerability Index (SVI), we determined whether co-occurring events disproportionately affected vulnerable populations. Nearly every county (97%) experienced at least one day of anomalously warm temperatures, 57% had at least one wildfire burn zone disaster day, and 63% (24/38 counties with available data) had at least one long power outage day. The most common co-occurring events (anomalously warm temperatures and wildfire burn zone disasters) impacted 24 (41%) counties for 144 total county-days. We did not find a clear connection between co-occurring events and social vulnerability. We observed an inverse correlation between co-occurring wildfire burn zone disasters and long power outage days with SVI, and a positive correlation between co-occurring anomalously warm and long power outage days with SVI. This analysis can inform regional resource allocation and other state-wide planning and policy objectives to reduce the adverse effects of climate-driven events.
Microorganisms are present in all occupied indoor environments, including homes on Earth and within specialized systems like the International Space Station (ISS). Microbes when exposed to excess moisture, such as from an unexpected ventilation system failure, can undergo growth that is associated with material degradation and negative health effects. However, we do not yet understand how exposure of these microbes to excess moisture alters their function. A de novo metatranscriptomic study was performed using dust collected from the US air filtration system of the ISS and incubated in laboratory chambers on Earth at different equilibrium relative humidity (ERH) levels. Changes in fungal function (gene expression) were significantly associated with moisture (adonis2 p = 0.0001). Secondary metabolism and fungal growth genes were upregulated (FDR-adjusted p ≤ 0.001, log2FC ≥ 2) at elevated ERH compared to 50% ERH. Elevated moisture conditions showed upregulation of aflatoxin and fungal allergen genes such as Asp f 4 (log2FC = 26.4, upregulated at 85% ERH compared to 50%) and Alt a 7 (log2FC = 2.98, upregulated at 100% ERH compared to 50%). Our results demonstrate that understanding microbial functional changes in response to elevated moisture will help develop more robust microbial monitoring standards for spacecraft environments to protect astronaut health and spacecraft integrity in low-Earth orbit and beyond.
Indoor nitrogen dioxide (NO2) and fine particulate matter (PM2.5) are concerns in U.S. households, especially those that cook using gas or propane stoves. Exposures to these and other indoor pollutants are linked to a variety of adverse health outcomes, including asthma morbidity, that disproportionately affect low-income households. We conducted a cross-sectional study of 138 homes in four low-income rural communities in California's San Joaquin Valley, comparing air pollutant concentrations between households that participated in a state electrification program and households using propane or natural gas for cooking. In each home, pollutants were monitored for approximately one month using personal air monitors and for 48 h using reference-grade instruments. Median 48-h average indoor NO2 concentrations were 63% lower in electric stove homes (electric: 6.0 ppb, gas: 16.0 ppb, p < 0.001). No electric stove homes had 48-h indoor NO2 concentrations exceeding the California annual guideline of 30 ppb, while 17% of gas homes did. Additionally, no electric stove homes had 1-h rolling-average NO2 concentrations exceeding the 100-ppb level deemed unhealthy for sensitive groups by the U.S. Environmental Protection Agency, whereas 41% of gas homes exceeded this threshold. PM2.5 concentrations were similar across groups, indicating that cooking-related emissions from food were the dominant contributor to PM2.5 mass concentrations rather than particles generated from gas combustion. Our evaluation of monitoring durations showed that two to four days of NO2 data and one week of PM2.5 data provided reliable estimates of longer-term averages, suggesting that shorter campaigns may yield robust estimates of indoor air quality. These results support the provision of electric cooking technologies as a strategy to address air quality-related health risks in rural, low-income communities and provide new evidence from an understudied population that can inform future indoor air quality research and energy transition policies.
The threats to human health from wildfires and wildfire smoke (WFS) in the United States (US) are increasing due to continued climate change. A growing body of literature has documented important adverse health effects of WFS exposure, but there is insufficient evidence regarding how risk related to WFS exposure varies across individual or community level characteristics. To address this evidence gap, we utilized a large nationwide database of healthcare utilization claims for emergency department (ED) visits in California across multiple wildfire seasons (May through November, 2012-2019) and quantified the health impacts of fine particulate matter <2.5 μm (PM2.5) air pollution attributable to WFS, overall and among subgroups of the population. We aggregated daily counts of ED visits to the level of the Zip Code Tabulation Area (ZCTA) and used a time-stratified case-crossover design and distributed lag non-linear models to estimate the association between WFS and relative risk of ED visits. We further assessed how the association with WFS varied across subgroups defined by age, race, social vulnerability, and residential air conditioning (AC) prevalence. Over a 7 day period, PM2.5 from WFS was associated with elevated risk of ED visits for all causes (1.04% (0.32%, 1.71%)), non-accidental causes (2.93% (2.16%, 3.70%)), and respiratory disease (15.17% (12.86%, 17.52%)), but not with ED visits for cardiovascular diseases (1.06% (-1.88%, 4.08%)). Analysis across subgroups revealed potential differences in susceptibility by age, race, and AC prevalence, but not across subgroups defined by ZCTA-level Social Vulnerability Index scores. These results suggest that PM2.5 from WFS is associated with higher rates of all cause, non-accidental, and respiratory ED visits with important heterogeneity across certain subgroups. Notably, lower availability of residential AC was associated with higher health risks related to wildfire activity.
We evaluated the implementation of local coalitions led in partnership with citizen scientists, community-based organizations, and public libraries in four rural communities to lower exposure to radon in the home. The objectives were to (1) describe the Reach-Effectiveness-Adoption-Implementation-Maintenance (RE-AIM) of four radon coalitions, and (2) compare RE-AIM factors among citizen scientists who participated in the coalitions and those who did not. A larger community-engaged research project embedded coalition building using a citizen science approach. Three of the four coalitions focused on health and wellness more broadly (18-34 members); one focused solely on radon (10 members). Coalition membership and activities varied from marketing a radon detector Library Loan Program, community events, and in-library tabling events to working with government officials to sign National Radon Action Month proclamations. We used mixed methods to evaluate coalition-building using the RE-AIM framework. The coalitions were most likely to reach local health departments, hospitals, and schools. Although these partners were highly supportive, they provided few to no resources. Four in 10 citizen scientists were at least moderately involved in the coalition regardless of whether they had high home radon. Citizen scientists reported low awareness of both how frequently radon received local media attention and how favorably radon awareness, testing, and mitigation was portrayed in local media, particularly among those uninvolved in the coalition. Citizen scientists involved in the coalition had the most experience disseminating scientific information on radon and educating the public. The coalitions fostered radon mitigation as 82% of library loan participants with high radon were likely to hire a radon mitigation professional, and all said financial assistance would help them mitigate. Multi-issue health coalitions that engage citizen scientists and partner with public libraries can increase radon testing and build demand for mitigation in rural areas.
High ambient temperatures have become more likely due to climate change and are linked to higher rates of heat-related illness, respiratory and cardiovascular diseases, mental health disorders, and other diseases. To date, far fewer studies have examined the effects of high temperatures on children versus adults, and studies including children have seldom been conducted on a national scale. Compared to adults, children have behavioral and physiological differences that may give them differential heat vulnerability. We acquired medical claims data from a large database of commercially insured US children aged 0-17 from May to September (warm-season) 2016-2019. Daily maximum ambient temperature and daily mean relative humidity estimates were aggregated to the county level using the Parameter-elevation Relationships on Independent Slopes dataset, and extreme heat was defined as the 95th percentile of the county-specific daily maximum temperature distribution. Using a case-crossover design and temperature lags 0-5 days, we estimated the associations between extreme heat and cause-specific emergency department visits (ED) in children aged <18 years, using the median county-specific daily maximum temperature distribution as the reference. Approximately 1.2 million ED visits in children from 2489 US counties were available during the study period. The 95th percentile of warm-season temperatures ranged from 71 °F to 112 °F (21.7 °C to 44.4 °C). Comparing 95th to the 50th percentile, extreme heat was associated with higher rates of ED visits for heat-related illness; endocrine, nutritional and metabolic diseases; and otitis media and externa, but not for all-cause admissions. Subgroup analyses suggested differences by age, with extreme heat positively associated with heat-related illness for both the 6-12 year (odds ratio [OR]: 1.34, 95% confidence interval [CI]: 1.16, 1.56) and 13-17 year age groups (OR: 1.55, 95% CI: 1.37, 1.76). Among children with health insurance across the US, days of extreme heat were associated with higher rates of healthcare utilization. These results highlight the importance of individual and population-level actions to protect children and adolescents from extreme heat, particularly in the context of continued climate change.
Visceral leishmaniasis (VL), a deadly neglected tropical disease, remains a persistent public health challenge in Brazil, where transmission is shaped by interacting climatic, environmental, and sociodemographic factors. Despite evidence that weather conditions influence VL dynamics, they remain underutilized for outbreak prediction. This study evaluates whether climate-informed machine learning can support early warnings for VL in Brazil. We developed machine learning models to forecast monthly VL case counts and classify outbreak risk using data from 2007 to 2024 across 113 Brazilian municipalities. A cutting-edge sliding window approach enabled models to capture both short- and long-term trends using lagged meteorological data combined with land-use and sociodemographic variables. Risk classification models were developed for a subset of 22 municipalities following the Brazilian Ministry of Health's prioritization framework to enable direct policy alignment. Predictive performance and variable importance were evaluated across locations. Weather patterns and indicators of human land-use pressure consistently ranked among the strongest predictors of VL risk. However, the relative importance of predictors varied across municipalities, reflecting local differences in transmission dynamics. Overall, forecasting models successfully captured long-term trends in observed case counts, and risk classification models, offering particularly timely and actionable signals for targeted intervention, achieved area under the curve scores above 0.80 in 86% of municipalities. Weather-informed machine learning models can provide timely, locally tailored predictions of VL risk in Brazil. As weather variability intensifies, integrating environmental data into existing surveillance systems may improve preparedness and reduce disease burden in vulnerable communities.