BACKGROUND:Climate change threatens global health, particularly among vulnerable populations such as pregnant individuals and their newborns. Evidence linking heat to premature birth is largely based on single-location studies or heterogeneous meta-analyses, leaving important gaps regarding underrepresented regions, preterm subgroups, and the role of maternal and infant characteristics. OBJECTIVES:To quantify the association between heat and preterm birth (PTB) across multiple countries, assess gestational-age-specific effects, and identify maternal vulnerability factors. METHODS:We analysed 36.6 million births occurring during the warm season from 250 locations in 13 countries to assess heat effects on PTB. Distributed lag non-linear models (DLNM) with quasi-Poisson regression estimated heat-PTB associations and the fraction of PTB attributable to heat. Gestational-age subcategories (extreme, very, late, and at-term) and socio-economic vulnerability profiles were also examined. RESULTS:Overall, 1.4% (95% CI: 1.3-1.5) of PTB were attributable to heat (855 PTB per million births), with national burdens from 628 to 1,347 PTB per million. Higher susceptibility was suggested for younger, single, non-primiparous, less-educated, and socio-economically deprived mothers, and among female fetuses. Late PTB showed the largest risk; at-term births also displayed a small but consistent heat-related increase. CONCLUSIONS:This large analysis of heat-related PTB using harmonized individual-level data indicates that heat increases PTB risk, with variations across countries and climates. It also shows that heat can trigger labour beyond the typical PTB window, affecting pregnancies not usually considered clinically vulnerable. Overall, these findings underscore the need for strategies to mitigate heat-related risks during pregnancy, particularly among socio-economically vulnerable populations.

Climate change is increasingly affecting natural, societal and economic systems in Switzerland, requiring a better understanding of cross-sectoral risks and their interactions. This challenge is addressed by the programme “NCCS-Impacts” of the Swiss National Centre for Climate Services (NCCS), in which five interlinked projects cover (1) socioeconomic scenarios, (2) human and animal health, (3) ecosystem services, (4) supply chains, and (5) economic costs. The projects are closely connected and generate strong synergies. Results will be released progressively until the end of 2026.In addition to generating new scientific insights, NCCS-Impacts places strong emphasis on developing actionable, user-oriented climate services. These are co-produced by researchers, practitioners, stakeholders and communication experts to maximise their usability and relevance for climate adaptation and mitigation. At the programme level, a key objective is to synthesise results across sectors and disciplines in a consistent and structured way making complex and heterogeneous findins more accessible, comparable and relevant for decision-making.The presentation provides a synthesis of key results from the projects, including new socioeconomic pathways for Switzerland and associated greenhouse gas emissions, projections of heat-related mortality and vulnerability risks, climate risks for supply chains, and impacts on agricultural yields. It will also showcase selected web-based tools tailored to user needs, such as a hospital management tool for forecasting heat-related emergency visits, an interactive map for identifying supply chain risks, and a dashboard for exploring cross-sectoral impacts on ecosystem services. In addition, the presentation will introduce the overarching synthesis concept developed within NCCS-Impacts, illustrating how cross-sectoral findings can be integrated, structured and communicated to support informed decision-making.

Background Rising temperatures are associated with increased psychiatric morbidity, although the mechanisms behind this remain poorly understood. This study investigates the role of psychotropic medications in the relationship between ambient heat and urgent psychiatric hospitalisations in a Swiss psychiatric clinic. Methods We applied a case-time series design with distributed lag models to examine the short-term association (0–3 lag) between mean temperature and the risk of urgent hospitalisations using individual-level data from the private psychiatric clinic (2017–2024). We evaluated the role of medications as effect modifiers for all and by sub-diagnosis. Results The risk of urgent psychiatric hospitalisation increased by 20% for each 10-degree rise in daily mean temperature (1.20, 95% Confidence Interval (CI) 1.04; 1.40), with higher risks in patients aged 65 years and older and those aged 30 years and younger (1.56 (1.12–2.16); 1.35 (1.07–1.72)). Regardless of the diagnosis, patients taking antipsychotics (1.18 (1.02–1.23)) and anxiolytics (1.15 (1.05–1.24)) showed higher vulnerability to heat, whereas no effect was found in antidepressants and antipsychotics. Conclusion Our results confirm that psychiatric patients are vulnerable to increasing temperatures, and this risk may be modulated by psychotropic medication use. This research contributes to a better understanding of the mechanisms behind the heat sensitivity of certain mental health conditions and supports the development of targeted public health measures.

Ozone (O3) and nitrogen dioxide (NO2) are two common gaseous pollutants that both possess oxidizing properties with consequences for human health and have an inextricable chemical relationship that could have distinct public health impacts when considered in combination. We examined the short-term associations of the combined oxidative capacity of O3 and NO2 (represented by Oxwt, the average of O3 and NO2 concentrations weighted by their standard electrode potential) with total, cardiovascular and respiratory mortality in 380 cities across 23 countries or regions between 1985 and 2020. Over 2 days (LAG01), a 10-ppb increase in Oxwt concentration was associated with an increase of 0.82% (95% confidence interval (CI): 0.55%, 1.10%) in total mortality, 1.09% (95% CI: 0.83%, 1.35%) in cardiovascular mortality and 0.88% (95% CI: 0.31%, 1.45%) in respiratory mortality. We also observed variations in this association by geographic region and study period. More deaths were attributable to Oxwt than to either O3 or NO2 but fewer than the sum of the two. Thus, Oxwt might be a valuable indicator for use in public health efforts to capture the combined effects of O3 and NO2.

Epidemiological evidence on the effects of droughts on human health is limited and heterogeneous, and drivers of vulnerability are still uncertain. The IGIA-SETH project aims to address these research gaps by using advanced epidemiological models and unique health and climate datasets. In particular, the present study aims to estimate drought-related mortality risks and identify vulnerability patterns on a global scale, using a robust and common approach and a large multi-location mortality dataset.We analyse mortality data from 832 locations distributed around the world with a wide range of climatic, demographic and socioeconomic characteristics over the period 1969-2019. We use a two-stage time series analytical design with a quasi-Poisson regression and a threshold function to model the association between droughts and mortality. Droughts at short and long- time scales are defined using the Standardized Precipitation Evaporation Index (SPEI) computed at one- and twelve-month accumulation periods. Potential effect modification by climatic, demographic, socioeconomic and environmental factors are also evaluated.Our findings suggest that extreme short-term and long-term drought events are associated with an increased mortality risk at 1% (95% confidence interval: 0.7%-1.2%) and 0.7% (0.01%-1.3%), respectively, at a SPEI=-2 vs. SPEI=0. Countries with higher mean temperatures and lower annual precipitation show a higher vulnerability to short-term droughts, while for long-term droughts, higher vulnerability is mostly found in countries with lower temperature range, lower annual average precipitation, and with a higher Gross Domestic Product per Capita.To our knowledge, this study represents the first comprehensive quasi-global analysis providing robust evidence of increased mortality risk associated with different drought exposures. Different mechanisms interacting at different levels, as well as different distribution of climatic, socioeconomic and demographic vulnerability factors between countries can driver disparities in drought-related mortality risks worldwide.

Climate change and evolving of population dynamics, including ageing and changes in population size, are reshaping temperature-attributable mortality patterns. However, there is limited evidence on the prospective trajectory of heat- and cold-attributable mortality in Oslo, particularly under combined scenarios of global warming and population development. This study aims to project heat- and cold-attributable mortality in Oslo and assess the distinct contributions of each of these drivers, utilising high-resolution data. We conducted a two-step approach with time series analysis with distributed lag non-linear models to estimate heat- and cold-attributable mortality relationship based on mean daily ambient temperature. Then, we performed a health impact assessment to compute the attributable mortality to heat and cold in the baseline period (2010–2019) and by the end of the century using regional population projections, mortality rates and projected daily temperature under two climate scenarios: RCP4.5 and RCP8.5. For the RCP4.5/Medium Road scenario, the attributable mortality fractions for heat and cold are projected to increase over time, with values ranging from 9.05

Global warming, the increase in average global temperatures, is one of the most impactful consequences of recent human activities, particularly the burning of fossil fuels. This rise in temperatures is associated with individuals’ mental health in a range of ways (e.g., by triggering or exacerbating symptoms, altering the severity and frequency of symptoms) and through a variety of different pathways (e.g., through heat-related sleep disruption, irritability, cognitive changes). This detrimental impact appears to be unevenly distributed, with evidence hinting at a heightened impact on young people, older individuals, those living in lower socio-economic regions, and those living in the Global South. The aim of this living systematic review is to evaluate any causal effect of heat exposure on depressive, anxious, and psychotic symptoms, or suicidality, and if a causal effect exists, to evaluate the potential mediators of this effect. We will search electronic databases for longitudinal observational studies that measure exposure to heat and its effect on mental health outcomes, intervention studies that experimentally test the effects of heat exposure or cooling interventions, and qualitative studies that report mechanisms and pathways of the impact of heat on mental health outcomes. We will include studies in the general population or in populations diagnosed with depression, anxiety, schizophrenia, or suicidal tendencies. We will also include experimental studies of extreme heat exposure in non-human endothermic, terrestrial animals, which report behavioural outcomes relevant to human mental health. At least two reviewers will use pre-defined tools to select studies, extract data, and assess risk of bias. We will summarise evidence using qualitative meta-synthesis with a critical realist epistemology for qualitative studies, and random-effects meta-analyses or synthesis without meta-analysis for quantitative studies. We will conduct the review in a living mode, and we will re-run database searches every six months to identify potential new evidence. We will present the summary of evidence (SoE) across the different sources of evidence and apply triangulation methods to integrate findings and strengthen causal inference. This project is part of GALENOS, and we co-produce this review with members of the global lived experience advisory board. N/A N/A N/A

Rising temperatures have raised concerns about impacts on mental health, including suicide. However, how climate change will affect global temperature-related suicide remains unclear. Using data from 751 locations across 26 countries, combined with climate projections under 3 emissions scenarios, we estimated temperature-suicide associations and projected temperature-related suicide mortality through the 2050s, assuming no adaptation, demographic shifts or changes in suicide rate. Here we show that climate change is projected to increase suicide mortality attributable to temperature across all studied regions, with the magnitude depending on both the emissions scenario and geographic location. Warmer regions-including Central and South America, South Europe, Southeast Asia and South Africa-show larger increases, while temperate and colder regions such as North America, North Europe, East Asia and Australia show smaller but meaningful rises. These findings highlight the potential of climate change to exacerbate suicide and underscore the importance of adaptive mitigation strategies.

BACKGROUND:Ambient PM10 is associated with mortality; however, potential changes in this association over time and the factors explaining such changes are unclear. Therefore, we aimed to examine whether mortality risk associated with PM10 has changed from 1979 to 2019 and whether changes in socioeconomic or environmental conditions can explain any temporal variation in the association between PM10 and mortality. METHODS:We applied an extended two-stage time-series design to assess temporal change in the association between PM10 and all-cause mortality across 143 cities in 26 countries from 1979 to 2019. In the first stage, city-specific and time-specific associations between PM10 and mortality were estimated using quasi-Poisson regression after each city time series was divided into non-overlapping 3-year segments. In the second stage, these estimates were pooled by use of longitudinal random-effects meta-regression with calendar year as a predictor. We further investigated whether selected socioeconomic and environmental factors explained observed temporal trends by including these variables in the second-stage model. FINDINGS:Totally, 23·2 million deaths were analysed. The overall association between PM10 and mortality had increased from 1979 to 2019, indicating a stronger association at a given PM10 concentration over time. A 10 μg/m3 increase in daily PM10 was associated with a 0·23% increase in all-cause mortality in 1979 (95% CI 0·05-0·41), and this association increased to 0·51% in 2019 (0·36-0·65). Temporal patterns in the PM10-mortality association varied across cities and were positively associated with population ageing over time and negatively associated with annual mean PM10 concentrations. INTERPRETATION:The findings of this study suggest that the effect of a given increment of PM10 on mortality has increased over time. Applying historical risk estimates could underestimate the current health burden. Continuous updating of evidence on the health impacts of air pollution is essential to ensure accurate and valid estimates. FUNDING:Wellcome Trust.

Abstract Background Vector-borne diseases (VBDs) are an evolving public health concern in Switzerland, where endemic tick-borne infections coexist with emerging mosquito-borne threats linked to climate and ecological change. Public preparedness depends on population knowledge, risk perception, and preventive behaviour alongside institutional capacity. We assessed knowledge, attitudes, and practices (KAP) regarding VBDs among adults in the canton of Bern, interpreted alongside a complementary national stakeholder survey. Methods We analysed a 2025 cross-sectional web-based survey embedded in the BEready cohort. After validity screening, we derived a latent knowledge score using a two-parameter logistic item response theory (IRT) model fitted to knowledge items. Multivariable linear regression examined associations between participant characteristics and latent knowledge. We identified KAP profiles through partitioning-around-medoids clustering based on block-weighted Gower dissimilarities. A parallel survey of cantonal and Liechtenstein authorities in human health, animal health, and environment departments provided institutional context. Results Among 1,847 respondents, 1,337 met validity criteria. Knowledge was strongest for tick-related content: 98% matched tick-borne encephalitis to ticks, 87% did so for Lyme disease. Mosquito-borne knowledge was markedly weaker, with only 36% correctly classifying chikungunya and 43% West Nile fever as mosquito-borne, despite 53% reporting at least weekly summer mosquito exposure. Tick checks were reported by 79% of participants versus 30% for mosquito standing-water removal. The IRT model indicated that mosquito-borne items were both hardest and most discriminating. Higher knowledge was associated with educational attainment, female sex, residence history, tick-bite frequency, and travel history, alongside a non-linear age effect peaking in mid-adulthood. Clustering identified six KAP profiles distinguishing knowledge gaps, low perceived relevance, and weak translation of knowledge into practice. The stakeholder survey (n=55) showed institutional engagement was considerably more developed for mosquito-borne than tick-borne diseases, although about half of authorities reported no dedicated human resources (49%) or budget (55%). Conclusions Public knowledge and practice remain stronger for tick-borne than mosquito-borne diseases, despite frequent mosquito exposure, revealing a communication gap. Institutional preparedness shows the opposite pattern, being more developed for mosquito-borne threats. Public health strategies should sustain effective tick-prevention messaging while strengthening mosquito-borne disease communication, household source reduction, and support for community-level surveillance and control.

Introduction Heat significantly impacts human health by causing heat strain or exacerbating pre-existing conditions. Hospitals may suffer a higher healthcare demand during intense heat periods, especially if climate change continues to increase the severity and frequency of heatwaves. Anticipating episodes of higher hospital demand would allow better resource planning and quality of care. Methods We developed a real-time forecasting tool of daily hospital demand (specifically, all-cause emergency room visits (ERVs)), which accounts for the impact of heat. Our tool is based on a regression model integrating temperature-ERV function with autoregressive terms and other temporal trends. The model can (1) quantify the association between the number of hospital visits and temperature based on historical data and (2) provide accurate short-term forecasts of the daily ERV based on temperature values expected for the upcoming days. As a case study, we used data from Bern University Hospital for the summers of 2014–2022, and mean temperature per day as an indicator of heat exposure. Results Temperature–ERV relationship exhibited a non-linear shape. We found that, with respect to the mean temperature of minimum risk of 15 °C, there were approximately 6 (95% CI 2 to 10) additional ERVs when mean temperature was around 25°C, corresponding to a 3% increase in summer 2022. The estimated variation increased for mean temperature above 25 °C but with large uncertainty. We also found that our model showed higher accuracy at forecasting hospital demand during periods with particularly hot days, compared with a model neglecting temperature. Our forecasting tool is implemented in a user-friendly R Shiny app, allowing for application to new datasets. Conclusions We found a robust association between ambient temperature and visits to the emergency department in a Swiss hospital. Our findings suggest that including temperature can increase the accuracy of predictions for hospital demand during summer.

Minimum mortality temperature (MMT) is an important feature of temperature-mortality relationship, defined as the temperature at which mortality risk is lowest. Although numerous studies have estimated MMT for all-cause mortality, few have explored differences by age or cause of death. We analyzed daily mean temperature and mortality data from 667 communities across 39 countries. Mortality was classified by age and cause of death (cardiovascular, respiratory, or non-cardiorespiratory). A two-stage meta-analytic approach was applied to estimate the MMT and its corresponding percentile (MMTP) by age and cause of death. In the overall population, MMT was the highest for cardiovascular mortality (22.1 °C, 95% CI: 20.9-23.4 °C), whereas respiratory and non-cardiorespiratory causes were 0.87 °C and 0.66 °C lower, respectively, than that for cardiovascular causes. Similar patterns were observed for MMTP, which was highest for cardiovascular mortality (75%, 95% CI: 73-78%) and lower by 5% and 4% for respiratory and non-cardiorespiratory causes, respectively. MMT increased with age for cardiovascular (0.19 °C per 10 years, 95% CI: 0.14-0.23) and non-cardiorespiratory causes (0.13 °C per 10 years, 95% CI: 0.09-0.16). These patterns were generally consistent across geographical regions. Overall, both MMT and MMTP differed by cause of death and age, indicating that the optimal temperature varies across population subgroups.

Several studies have explored the short-term effects of environmental stressors on coronavirus disease 2019 (COVID-19) transmission and severity. However, evidence on the interactive effects of meteorological conditions and air pollution remains limited and geographically variable. We therefore aimed to quantify the independent and interactive effects of short-term exposure to humidex, a composite index of temperature and relative humidity, and fine particulate matter ≤ 2.5 μm (PM2.5) on daily COVID-19 incidence across multiple cities and in multiple countries. Daily time-series data on confirmed COVID-19 cases, meteorological factors, and PM2.5 concentrations were collected from 439 cities in 22 countries during January 2020-August 2022 as part of the Multi-Country Multi-City Collaborative Research Network. A two-stage design was applied: first, city-specific quasi-Poisson models with distributed lag non-linear models estimated exposure-response associations; second, multilevel random-effects meta-analyses pooled city-specific estimates. Effect modification by PM2.5 was assessed using a product term between non-linear humidex function and linear PM2.5 function. Approximately 95.1 million confirmed COVID-19 cases were analyzed. Lower humidex values (0.1 °C versus 15.1 °C) were associated with increased daily cases (relative risk [RR]: 1.1192, 95% confidence interval [CI]: 1.0214-1.2262). A 10 μg/m3increase in PM2.5 over the current and preceding 2 days was associated with a modest increase in daily cases (RR: 1.0079, 95% CI: 1.0001-1.0161). No statistically significant interaction between humidex and PM2.5 was observed. Short-term exposure to cold-dry conditions and elevated PM2.5 independently increased COVID-19 incidence, highlighting the need to consider both thermal environment and air quality when designing climate-resilient public health responses. These findings enhance understanding of how climate-related environmental stressors influence COVID-19 transmission.

BACKGROUND:Older adults are highly vulnerable to heat, yet how individual characteristics modulate its effects remains unclear. We assessed heat-related emergency hospital admission (EHA) risk across subpopulations of older adults receiving home care services in Switzerland (2019-2022). METHODS:We analysed patient-level EHA data linked to daily maximum temperature by MedStat regions of residence. We employed a case time series design with quasi-Poisson regression and distributed lag non-linear models to examine heat-related EHA risk, stratifying by individual characteristics, including sociodemographic factors, pre-existing health conditions, primary diagnosis, and levels of dependency and social interaction. RESULTS:The overall heat-related EHA risk was 1.12 (95% confidence interval (CI): 1.04-1.20) (at 99th percentile vs minimum temperature percentile risk). Males (1.16; 1.04-1.29) generally showed higher heat-related EHA risk than females (1.09; 0.98-1.20), except among those aged ≥85 years (females 1.16; 1.00-1.34 vs males 1.06; 0.90-1.26). Regarding functional capacity, females requiring assistance with daily tasks had an increased heat-related EHA risk, whereas males showed the opposite trend, with higher risk among those who were independent. Sex-specific analyses revealed that anxiety and dementia/Alzheimer's disease were risk factors for females, whereas cancer, chronic obstructive pulmonary disease, and coronary heart disease were risk factors for males. Joint stratification by pre-existing health conditions and primary diagnosis showed that individuals with pre-existing cancer had higher risks of admission for circulatory, genitourinary, infectious, and endocrine/metabolic causes during heat exposure. CONCLUSION:Our results show that older individuals are not equally vulnerable to heat, underscoring the need for targeted public health interventions to protect high-risk older adults.

Background: Pregnancy is a critical window of heightened vulnerability to heat stress which has been linked to adverse birth outcomes, including preterm birth (PTB). However, existing evidence is largely derived from high-income countries and may underestimate the burden in settings with higher exposure, limited adaptive capacity and less health system resilience. Methods: This prospective observational cohort study utilised PRECISE Network data from The Gambia, Kenya, and Mozambique. We geo-coded maternal location of residency to daily maximum Universal Thermal Climate Index (UTCI) data from ERA-5-Heat stress. A distributed lag non-linear Cox proportional hazard model was used to estimate the association between UTCI (defined by individualised percentiles) and PTB. This time-to-event analyses, stratified by gestational week, estimated the lag-specific hazard ratios (HR), at 0-6 and 0-27 days preceding delivery, comparing the 95th to the 50th percentile heat stress exposure. Models were adjusted for potential confounders, and interactions by maternal age, country and fetal growth status were explored. Findings: A total of 838 PTBs were recorded out of 4,750 pregnancies (17.6%). Heat-stress exposure was associated with significantly increased risk for PTB, with a cumulative HR of 1.55 (95% CI 1.35–1.78) for days 0-6 and 1.22, 1.12-1.32 for 0-27 days. Significant effect modification was identified by fetal growth status but not by maternal age or country. There was a higher risk of PTB in those exposed to heat stress for infants born large-for-gestational-age compared with those born small-for-gestational-age, hazard ratios of 1.99, (95% CI 1.57-2.54) and 1.03 (95% CI 0.73, 1.47) respectively. Findings remained consistent on sensitivity analyses. Interpretation: Heat stress substantially increases PTB risk in Sub-Saharan Africa, with LGA infants particularly vulnerable and effect size estimates exceeding those reported in high-income settings. These findings underscore the urgent need for targeted heat-health interventions to protect maternal and neonatal health.

Background: Heat is widely acknowledged as one of the most hazardous climate-related risk factors affecting human health. Increasing urban development has led to an amplification of its health impacts due to the Urban Heat Island (UHI) effect. However, our understanding of neighbourhood-level vulnerability to the UHI effect remains limited. This information can be crucial for policymakers to identify high-risk areas in cities and develop more targeted public health interventions. Thus, we propose a comprehensive approach to map the vulnerability to UHI in the city of Bern (Switzerland) by (1) assessing the demographic and socio-economic factors contributing to increased UHI exposure and (2) analysing the spatial distribution of vulnerability to the UHI effect.Methods: We collected population and household statistics at the individual level from 2012 to 2021 from the Federal Statistical Office of Switzerland. Firstly, we calculated the intensity of UHI (representing the temperature difference between the inner city and the rural surroundings) in each district of Bern using high-resolution (50mx50m) modelled urban temperature data. Next, we performed univariate logistic regression models to estimate the association between UHI exposure and population characteristics, reporting odds ratio (OR) and 95% confidence intervals (CI). We defined UHI exposure as individuals being exposed to UHI intensity exceeding the city-mean for the corresponding census year. Subsequently, we established the Heat Vulnerability Index (HVI) by selecting key determinants: 1) the elderly population (aged ≥65 years), 2) females, and 3) individuals with low socio-economic status. The overall percentile ranks for districts were calculated by summing variable rankings.Result: First, our study identified several factors contributing to increased UHI exposure, in particular, single individuals had 60% higher odds of UHI exposure (OR:1.60; CI:1.59-1.62) compared to married individuals, and individuals aged 26-44 (1.71; 1.70-1.74) compared to those aged 0-17. Also, wealthier individuals appeared to have higher odds of UHI exposure (medium: 2.32; 2.30-2.35, high: 1.66; 1.64-1.67) compared to the lowest group. In the context of the work environment, individuals in large-size companies (≥250 employees) had an increased risk (1.85; 0.77-6.05) of UHI exposure compared to those in micro-size companies (

Previous health impact assessments of temperature-related mortality in Europe indicated that the mortality burden attributable to cold is much larger than for heat. Questions remain as to whether climate change can result in a net decrease in temperature-related mortality. In this study, we estimated how climate change could affect future heat-related and cold-related mortality in 854 European urban areas, under several climate, demographic and adaptation scenarios. We showed that, with no adaptation to heat, the increase in heat-related deaths consistently exceeds any decrease in cold-related deaths across all considered scenarios in Europe. Under the lowest mitigation and adaptation scenario (SSP3-7.0), we estimate a net death burden due to climate change increasing by 49.9

The COVID-19 pandemic and climate change are both urgent global health concerns. However, their impact on human lives has not been compared on the same scale. In this study, we compared mortality due to heat with COVID-19 in 38 cities worldwide, considering different levels of global warming (+1°C, +1.5°C, +2°C, and +3°C). Our findings reveal that even at a global warming level of +1.0ºC, 6 cities are already at a point where heat-related deaths could equal COVID-19 deaths within 15 years. Regardless of high or low COVID-19 mortality in the cities, the number of years to reach the level of COVID-19 mortality decreases with higher global warming levels. In 18.4% to 47.4% of the cities, heat-related mortality is projected to equal COVID-19 mortality within 15 years, ranging from +1.0ºC to +3.0ºC of global warming. The vulnerability to climate change varies among regions, with European, Mediterranean, and North American cities experiencing a significant rise in heat-related mortality with higher global warming levels. It is important to note that the given number of years represents the time required to reach COVID-19 mortality. However, unlike the peak and decline of COVID-19, climate change-driven heat-related deaths will persistently worsen unless substantial adaptation measures are taken. This emphasizes the crucial need to integrate climate change into public health discourse and policy.

BACKGROUND:The rise in hot nights over recent decades and projections of further increases due to climate change underscores the critical need to understand their impact. This knowledge is essential for shaping public health strategies and guiding adaptation efforts. Despite their significance, research on the implications of hot nights remains limited. OBJECTIVE:This study estimated the association between hot-night excess (the sum of excess heat during the nighttime above a threshold) and duration (the percent of nighttime with a positive excess) based on hourly ambient temperatures and daily mortality in the warm season over multiple locations worldwide. METHODS:We fitted time series regression models to mortality in 178 locations across 44 countries using a distributed lag non-linear model over lags of 0-3 days, controlling for daily maximum temperature and daily mean absolute humidity. Next, we used a multivariate meta-regression model to pool results and estimated attributable burdens. RESULTS:We found a positive, increasing mortality risk with hot-night excess and duration. Assuming 0 as a reference, the pooled relative risks of death associated with extreme excess and duration, defined as the 90th percentile in each index, were both similar at 1.026 (95 % CI, 1.017; 1.036) and 1.026 (95 % CI, 1.013; 1.040). The overall estimated attributable fractions were also observed to be closely similar at 0.60 % (95 % CI, 0.09; 1.10 %) and 0.62 % (95 % CI, 0.00; 1.23 %), respectively. DISCUSSION:This study provides new evidence that hot nights have a specific contribution to heat-related mortality risk. Modeling thermal characteristics' sub-hourly impact on mortality during the night could improve decision-making for long-term adaptions and preventive public health strategies.

More than 61,000 heat-related deaths were associated with the record-breaking temperatures in Europe during the summer of 2022. In this study, we quantify the number of heat-related deaths that would have been avoided in the absence of anthropogenic warming.For this study, we utilize epidemiological models calibrated for the period 2015–2019 to estimate the heat-related mortality burden in the summer of 2022 for the factual and counterfactual scenario. We derive a counterfactual scenario by removing the regional summer mean warming that arises in response to rising global mean temperatures from the factual temperatures. We use ERA5-Land temperature data and mortality counts from the Eurostat database to estimate the heat-related deaths across 823 distinct administrative regions spanning 35 European countries. At 1.15 °C of global warming since pre-industrial times, we obtain a population-weighted median increase over all regions in Europe of more than 2 °C in summer mean temperatures, with the Mediterranean regions being most affected by the increase. By comparing the factual and counterfactual heat-related mortality, we estimate that approx. 70% [95th CI 53.33%– 82.17%] of the total heat-related deaths would not have occurred without anthropogenic warming. Southern Europe has been the most affected by dangerous heat and consequently features the highest number of heat-related deaths attributable to climate change [64.19% of the climate change-attributable deaths]. In relative terms, however, the impact of anthropogenic warming is strongest in Central Europe where approx. 78% of the heat-related deaths are attributable to anthropogenic warming.