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The authors would like to acknowledge the participation of 4 additional authors to this article. They contributed to the processing of the Japanese dataset used in the study. The corrected authorship, the corrected Acknowledgements and the corrected Contributors and Declaration of interests sections are presented below. H.M.C. and W.L. performed data analysis. W.L., D.R., A.U., A.E., A.M.V., A.Z., A.G., A.Z., A.T., B.A., B.F., C.Í., C.Å., C.F.S.N., E.I., E.L., F.M., F.A., F.S., H.O. H.K., J.K., J.M., J.S., J.J., K.K., M.H.D., M.S.R., M.H., M.P., N.R., N.S., S.O., S.T., X.S., Y.H., Y.K., YL.G., Y.G., and M.L.B. provided essential data resources. H.M.C. drafted the first version. H.M.C. and M.L.B. performed writing and editing the manuscript. H.M.C., W.L., A.U., A.G., A.T., B.A., E.L., F.S., S.T., and M.L.B. conducted reviewing. H.M.C. and D.R. have developed the figures. All authors have read and acknowledged the final manuscript., This publication was developed under Assistance Agreement No. RD83587101 awarded by the U.S. Environmental Protection Agency to Yale University. It has not been formally reviewed by EPA. The views expressed in this document are solely those of the authors and do not necessarily reflect those of the Agency. EPA does not endorse any products or commercial services mentioned in this publication. Research reported in this publication was also supported by the National Institute on Minority Health and Health Disparities of the National Institutes of Health under Award Number R01MD012769. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Also, this work has been supported by the National Research Foundation of Korea (2021R1A6A3A03038675), Medical Research Council-UK (MR/V034162/1 and MR/R013349/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), Academy of Finland (Grant ID: 310372), European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655 and 874990), Czech Science Foundation (22-24920S), Emory University’s NIEHS-funded HERCULES Center (Grant ID: P30ES019776), and Grant CEX2018-000794-S funded by MCIN/AEI/10.13039/501100011033. The funders had no role in the design, data collection, analysis, interpretation of results, manuscript writing, or decision to publication.

Rationale: The associations between ambient coarse particulate matter (PM2.5-10) and daily mortality are not fully understood on a global scale. Objectives: To evaluate the short-term associations between PM2.5-10 and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide. Methods: We collected daily mortality (total, cardiovascular, and respiratory) and air pollution data from 205 cities in 20 countries/regions. Concentrations of PM2.5-10 were computed as the difference between inhalable and fine PM. A two-stage time-series analytic approach was applied, with overdispersed generalized linear models and multilevel meta-analysis. We fitted two-pollutant models to test the independent effect of PM2.5-10 from copollutants (fine PM, nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide). Exposure-response relationship curves were pooled, and regional analyses were conducted. Measurements and Main Results: A 10 μg/m3 increase in PM2.5-10 concentration on lag 0-1 day was associated with increments of 0.51% (95% confidence interval [CI], 0.18%-0.84%), 0.43% (95% CI, 0.15%-0.71%), and 0.41% (95% CI, 0.06%-0.77%) in total, cardiovascular, and respiratory mortality, respectively. The associations varied by country and region. These associations were robust to adjustment by all copollutants in two-pollutant models, especially for PM2.5. The exposure-response curves for total, cardiovascular, and respiratory mortality were positive, with steeper slopes at lower exposure ranges and without discernible thresholds. Conclusions: This study provides novel global evidence on the robust and independent associations between short-term exposure to ambient PM2.5-10 and total, cardiovascular, and respiratory mortality, suggesting the need to establish a unique guideline or regulatory limit for daily concentrations of PM2.5-10., Supported by the National Natural Science Foundation of China (92043301, 82030103 [H.K. and C.L.] and 92143301 [R.C.]); the Ministry of Science and Technology, Taiwan (MOST 110–2314-B-002–083 [Y.-L.L.G.]); the Medical Research Council-UK (MR/R013349/1 [A.G.]); Fundação para a Ciência e a Tecnologia through the grant SFRH/BPD/115112/2016 (J.M.); the Australian Research Council (DP210102076 [Y.G.]); the European Union’s Horizon 2020 Project Exhaustion (820655 [A.G., S.R., A.D.-L.P., and A.S.]); the Natural Environment Research Council UK (NE/R009384/1 [A.G.]); the Australian National Health and Medical Research Council (APP2000581, APP1163693, and APP2008813 [Y.G.]); and an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (APP2009866 [S.L.]).

The question of whether, how, and to what extent climate change is affecting health is central to many climate and health studies. We describe a set of formal methods, termed detection and attribution, used by climatologists to determine whether a climate trend or extreme event has changed and to estimate the extent to which climate change influenced that change. We discuss events where changing weather patterns were attributed to climate change and extend these analyses to include health impacts from heat waves in 2018 and 2019 in Europe and Japan, and we show how such impact attribution could be applied to melting ice roads in the Arctic. Documenting the causal chain from emissions of greenhouse gases to observed human health outcomes is important input into risk assessments that prioritize health system preparedness and response interventions and into financial investments and communication about potential risk to policy makers and to the public.

Background: The association between fine particulate matter (PM2.5) and mortality widely differs between as well as within countries. Differences in PM2.5 composition can play a role in modifying the effect estimates, but there is little evidence about which components have higher impacts on mortality. Methods: We applied a 2-stage analysis on data collected from 210 locations in 16 countries. In the first stage, we estimated location-specific relative risks (RR) for mortality associated with daily total PM2.5 through time series regression analysis. We then pooled these estimates in a meta-regression model that included city-specific logratio-transformed proportions of seven PM2.5 components as well as meta-predictors derived from city-specific socio-economic and environmental indicators. Results: We found associations between RR and several PM2.5 components. Increasing the ammonium (NH4+) proportion from 1% to 22%, while keeping a relative average proportion of other components, increased the RR from 1.0063 (95% confidence interval [95% CI] = 1.0030, 1.0097) to 1.0102 (95% CI = 1.0070, 1.0135). Conversely, an increase in nitrate (NO3-) from 1% to 71% resulted in a reduced RR, from 1.0100 (95% CI = 1.0067, 1.0133) to 1.0037 (95% CI = 0.9998, 1.0077). Differences in composition explained a substantial part of the heterogeneity in PM2.5 risk. Conclusions: These findings contribute to the identification of more hazardous emission sources. Further work is needed to understand the health impacts of PM2.5 components and sources given the overlapping sources and correlations among many components.

Studies have investigated the effects of heat and temperature variability (TV) on mortality. However, few assessed whether TV modifies the heat-mortality association. Data on daily temperature and mortality in the warm season were collected from 717 locations across 36 countries. TV was calculated as the standard deviation of the average of the same and previous days' minimum and maximum temperatures. We used location-specific quasi-Poisson regression models with an interaction term between the cross-basis term for mean temperature and quartiles of TV to obtain heat-mortality associations under each quartile of TV, and then pooled estimates at the country, regional, and global levels. Results show the increased risk in heat-related mortality with increments in TV, accounting for 0.70% (95% confidence interval [CI]: -0.33 to 1.69), 1.34% (95% CI: -0.14 to 2.73), 1.99% (95% CI: 0.29-3.57), and 2.73% (95% CI: 0.76-4.50) of total deaths for Q1-Q4 (first quartile-fourth quartile) of TV. The modification effects of TV varied geographically. Central Europe had the highest attributable fractions (AFs), corresponding to 7.68% (95% CI: 5.25-9.89) of total deaths for Q4 of TV, while the lowest AFs were observed in North America, with the values for Q4 of 1.74% (95% CI: -0.09 to 3.39). TV had a significant modification effect on the heat-mortality association, causing a higher heat-related mortality burden with increments of TV. Implementing targeted strategies against heat exposure and fluctuant temperatures simultaneously would benefit public health., This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). Y.W and B.W. were supported by the China Scholarship Council (nos. 202006010044 and 202006010043); S.L. was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (no. APP2009866); Y.G. was supported by Career Development Fellowship (no. APP1163693) and Leader Fellowship (no. APP2008813) of the Australian National Health and Medical Research Council; J.K. and A.U. were supported by the Czech Science Foundation (project no. 20–28560S); N.S. was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (no. P30ES019776); Y.H. was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency; M.d.S.Z.S.C. and P.H.N.S. were supported by the São Paulo Research Foundation (FAPESP); H.O. and E.I. were supported by the Estonian Ministry of Education and Research (IUT34–17); J.M. was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016); A.G. and F.S. were supported by the Medical Research Council UK (grant ID MR/R013349/1), the Natural Environment Research Council UK (grant ID NE/R009384/1), and the EU’s Horizon 2020 project, Exhaustion (grant ID 820655); A.S. and F.d.D. were supported by the EU’s Horizon 2020 project, Exhaustion (grant ID 820655); V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046); and A.T. by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). Statistics South Africa kindly provided the mortality data, but had no other role in the study.

Minimum mortality temperature (MMT) is an important indicator to assess the temperature-mortality association, indicating long-term adaptation to local climate. Limited evidence about the geographical variability of the MMT is available at a global scale.

Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PMFor this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000-16. Daily concentrations of wildfire-related PM65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/mShort-term exposure to wildfire-related PMAustralian Research Council, Australian National HealthMedical Research Council.

Urban air pollutant emissions and concentrations vary throughout the year due to various factors, e.g., meteorological conditions and human activities. In this study, seasonal variations in daily mortality associated with increases in the concentrations of PM10 (particulate matter), PM2.5–10 (coarse particles), BC (black carbon), NO2 (nitrogen dioxide), and O3 (ozone) were calculated for Stockholm during the period from 2000 to 2016. The excess risks in daily mortality are presented in single and multi-pollutant models during the whole year and divided into four different seasons, i.e., winter (December–February), spring (March–May), summer (June–August), and autumn (September–November). The excess risks in the single-pollutant models associated with an interquartile range (IQR) increase for a lag 02 during the whole year were 0.8% (95% CI: 0.1–1.4) for PM10, 1.1% (95% CI: 0.4–1.8) for PM2.5–10, 0.5% (95% CI: −0.5–1.5) for BC, −1.5% (95% CI: −0.5–−2.5) for NO2, and 1.9% (95% CI: 1.0–2.9) for O3. When divided into different seasons, the excess risks for PM10 and PM2.5–10 showed a clear pattern, with the strongest associations during spring and autumn, but with weaker associations during summer and winter, indicating increased risks associated with road dust particles during these seasons. For BC, which represents combustion-generated particles, the pattern was not very clear, but the strongest positive excess risks were found during autumn. The excess risks for NO2 were negative during all seasons, and in several cases even statistically significantly negative, indicating that NO2 in itself was not harmful at the concentrations prevailing during the measurement period (mean values &lt, 20 µg m−3). For O3, the excess risks were statistically significantly positive during “all year” in both the single and the multi-pollutant models. The excess risks for O3 in the single-pollutant models were also statistically significantly positive during all seasons.

Background: Exposure to cold or hot temperatures is associated with premature deaths. We aimed to evaluate the global, regional, and national mortality burden associated with non-optimal ambient temperatures. Methods: In this modelling study, we collected time-series data on mortality and ambient temperatures from 750 locations in 43 countries and five meta-predictors at a grid size of 0·5° × 0·5° across the globe. A three-stage analysis strategy was used. First, the temperature–mortality association was fitted for each location by use of a time-series regression. Second, a multivariate meta-regression model was built between location-specific estimates and meta-predictors. Finally, the grid-specific temperature–mortality association between 2000 and 2019 was predicted by use of the fitted meta-regression and the grid-specific meta-predictors. Excess deaths due to non-optimal temperatures, the ratio between annual excess deaths and all deaths of a year (the excess death ratio), and the death rate per 100 000 residents were then calculated for each grid across the world. Grids were divided according to regional groupings of the UN Statistics Division. Findings: Globally, 5 083 173 deaths (95% empirical CI [eCI] 4 087 967–5 965 520) were associated with non-optimal temperatures per year, accounting for 9·43% (95% eCI 7·58–11·07) of all deaths (8·52% [6·19–10·47] were cold-related and 0·91% [0·56–1·36] were heat-related). There were 74 temperature-related excess deaths per 100 000 residents (95% eCI 60–87). The mortality burden varied geographically. Of all excess deaths, 2 617 322 (51·49%) occurred in Asia. Eastern Europe had the highest heat-related excess death rate and Sub-Saharan Africa had the highest cold-related excess death rate. From 2000–03 to 2016–19, the global cold-related excess death ratio changed by −0·51 percentage points (95% eCI −0·61 to −0·42) and the global heat-related excess death ratio increased by 0·21 percentage points (0·13–0·31), leading to a net reduction in the overall ratio. The largest decline in overall excess death ratio occurred in South-eastern Asia, whereas excess death ratio fluctuated in Southern Asia and Europe. Interpretation: Non-optimal temperatures are associated with a substantial mortality burden, which varies spatiotemporally. Our findings will benefit international, national, and local communities in developing preparedness and prevention strategies to reduce weather-related impacts immediately and under climate change scenarios. Funding: Australian Research Council and the Australian National Health and Medical Research Council.

Objective To evaluate the short term associations between nitrogen dioxide (NO2) and total, cardiovascular, and respiratory mortality across multiple countries/regions worldwide, using a uniform analytical protocol. Design Two stage, time series approach, with overdispersed generalised linear models and multilevel meta-analysis. Setting 398 cities in 22 low to high income countries/regions. Main outcome measures Daily deaths from total (62.8 million), cardiovascular (19.7 million), and respiratory (5.5 million) causes between 1973 and 2018. Results On average, a 10 μg/m3 increase in NO2 concentration on lag 1 day (previous day) was associated with 0.46% (95% confidence interval 0.36% to 0.57%), 0.37% (0.22% to 0.51%), and 0.47% (0.21% to 0.72%) increases in total, cardiovascular, and respiratory mortality, respectively. These associations remained robust after adjusting for co-pollutants (particulate matter with aerodynamic diameter ≤10 μm or ≤2.5 μm (PM10 and PM2.5, respectively), ozone, sulfur dioxide, and carbon monoxide). The pooled concentration-response curves for all three causes were almost linear without discernible thresholds. The proportion of deaths attributable to NO2 concentration above the counterfactual zero level was 1.23% (95% confidence interval 0.96% to 1.51%) across the 398 cities. Conclusions This multilocation study provides key evidence on the independent and linear associations between short term exposure to NO2 and increased risk of total, cardiovascular, and respiratory mortality, suggesting that health benefits would be achieved by tightening the guidelines and regulatory limits of NO2., HaK was supported by the National Natural Science Foundation of China (92043301, 82030103, and 91843302) and China Medical Board Collaborating Program (16-250). AG and FS were supported by the Medical Research Council, UK (MR/M022625/1), the Natural Environment Research Council, UK (NE/R009384/1), and the European Union’s Horizon 2020 Project Exhaustion (820655). VH was supported by the Spanish Ministry of Science and Innovation (PCIN-2017-046), and the German Federal Ministry of Education and Research (01LS1201A2). YH and MH were supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency, Japan. JK and AU were supported by the Czech Science Foundation (18-22125S). ST was supported by the Shanghai Municipal Science and Technology Commission (18411951600). Y-LLG was supported by a Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). SL was supported by an Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). JJKJJ and NR were supported by the Academy of Finland (310372). The funders had no role in considering the study design or in the collection, analysis, interpretation of data, writing of the report, or decision to submit the article for publication.

Summary Background Many regions of the world are now facing more frequent and unprecedentedly large wildfires. However, the association between wildfire-related PM2·5 and mortality has not been well characterised. We aimed to comprehensively assess the association between short-term exposure to wildfire-related PM2·5 and mortality across various regions of the world. Methods For this time series study, data on daily counts of deaths for all causes, cardiovascular causes, and respiratory causes were collected from 749 cities in 43 countries and regions during 2000–16. Daily concentrations of wildfire-related PM2·5 were estimated using the three-dimensional chemical transport model GEOS-Chem at a 0·25° × 0·25° resolution. The association between wildfire-related PM2·5 exposure and mortality was examined using a quasi-Poisson time series model in each city considering both the current-day and lag effects, and the effect estimates were then pooled using a random-effects meta-analysis. Based on these pooled effect estimates, the population attributable fraction and relative risk (RR) of annual mortality due to acute wildfire-related PM2·5 exposure was calculated. Findings 65·6 million all-cause deaths, 15·1 million cardiovascular deaths, and 6·8 million respiratory deaths were included in our analyses. The pooled RRs of mortality associated with each 10 μg/m3 increase in the 3-day moving average (lag 0–2 days) of wildfire-related PM2·5 exposure were 1·019 (95% CI 1·016–1·022) for all-cause mortality, 1·017 (1·012–1·021) for cardiovascular mortality, and 1·019 (1·013–1·025) for respiratory mortality. Overall, 0·62% (95% CI 0·48–0·75) of all-cause deaths, 0·55% (0·43–0·67) of cardiovascular deaths, and 0·64% (0·50–0·78) of respiratory deaths were annually attributable to the acute impacts of wildfire-related PM2·5 exposure during the study period., Australian Research Council, Australian National Health & Medical Research Council.

Background Epidemiological evidence on short-term association between ambient carbon monoxide (CO) and mortality is inconclusive and limited to single cities, regions, or countries. Generalisation of results from previous studies is hindered by potential publication bias and different modelling approaches. We therefore assessed the association between short-term exposure to ambient CO and daily mortality in a multicity, multicountry setting. Methods We collected daily data on air pollution, meteorology, and total mortality from 337 cities in 18 countries or regions, covering various periods from 1979 to 2016. All included cities had at least 2 years of both CO and mortality data. We estimated city-specific associations using confounder-adjusted generalised additive models with a quasi-Poisson distribution, and then pooled the estimates, accounting for their statistical uncertainty, using a random-effects multilevel meta-analytical model. We also assessed the overall shape of the exposure–response curve and evaluated the possibility of a threshold below which health is not affected. Findings Overall, a 1 mg/m3 increase in the average CO concentration of the previous day was associated with a 0·91% (95% CI 0·32–1·50) increase in daily total mortality. The pooled exposure–response curve showed a continuously elevated mortality risk with increasing CO concentrations, suggesting no threshold. The exposure–response curve was steeper at daily CO levels lower than 1 mg/m3, indicating greater risk of mortality per increment in CO exposure, and persisted at daily concentrations as low as 0·6 mg/m3 or less. The association remained similar after adjustment for ozone but was attenuated after adjustment for particulate matter or sulphur dioxide, or even reduced to null after adjustment for nitrogen dioxide. Interpretation This international study is by far the largest epidemiological investigation on short-term CO-related mortality. We found significant associations between ambient CO and daily mortality, even at levels well below current air quality guidelines. Further studies are warranted to disentangle its independent effect from other traffic-related pollutants., EU Horizon 2020, UK Medical Research Council, and Natural Environment Research Council

The question of whether, how, and to what extent climate change is affecting health is central to many climate and health studies. We describe a set of formal methods, termed detection and attribution, used by climatologists to determine whether a climate trend or extreme event has changed and to estimate the extent to which climate change influenced that change. We discuss events where changing weather patterns were attributed to climate change and extend these analyses to include health impacts from heat waves in 2018 and 2019 in Europe and Japan, and we show how such impact attribution could be applied to melting ice roads in the Arctic. Documenting the causal chain from emissions of greenhouse gases to observed human health outcomes is important input into risk assessments that prioritize health system preparedness and response interventions and into financial investments and communication about potential risk to policy makers and to the public.

Background While the COVID-19 outbreak in China now appears suppressed, Europe and the USA have become the epicentres, both reporting many more deaths than China. Responding to the pandemic, Sweden has taken a different approach aiming to mitigate, not suppress, community transmission, by using physical distancing without lockdowns. Here we contrast the consequences of different responses to COVID-19 within Sweden, the resulting demand for care, intensive care, the death tolls and the associated direct healthcare related costs. Methods We used an age-stratified health-care demand extended SEIR (susceptible, exposed, infectious, recovered) compartmental model for all municipalities in Sweden, and a radiation model for describing inter-municipality mobility. The model was calibrated against data from municipalities in the Stockholm healthcare region. Results Our scenario with moderate to strong physical distancing describes well the observed health demand and deaths in Sweden up to the end of May 2020. In this scenario, the intensive care unit (ICU) demand reaches the pre-pandemic maximum capacity just above 500 beds. In the counterfactual scenario, the ICU demand is estimated to reach ∼20 times higher than the pre-pandemic ICU capacity. The different scenarios show quite different death tolls up to 1 September, ranging from 5000 to 41 000, excluding deaths potentially caused by ICU shortage. Additionally, our statistical analysis of all causes excess mortality indicates that the number of deaths attributable to COVID-19 could be increased by 40% (95% confidence interval: 0.24, 0.57). Conclusion The results of this study highlight the impact of different combinations of non-pharmaceutical interventions, especially moderate physical distancing in combination with more effective isolation of infectious individuals, on reducing deaths, health demands and lowering healthcare costs. In less effective mitigation scenarios, the demand on ICU beds would rapidly exceed capacity, showing the tight interconnection between the healthcare demand and physical distancing in the society. These findings have relevance for Swedish policy and response to the COVID-19 pandemic and illustrate the importance of maintaining the level of physical distancing for a longer period beyond the study period to suppress or mitigate the impacts from the pandemic.

BackgroundWhile the COVID-19 outbreak in China now appears surpressed, Europe and the US have become the epicenters, both reporting many more deaths than China. Responding to the pandemic, Sweden has taken a different approach aiming to mitigate, not suppressing community transmission, by using physical distancing without lock-downs. Here we contrast consequences of different responses to COVID-19 within Sweden, the resulting demand for care, intensive care, the death tolls, and the associated direct healthcare related costs.MethodsWe use an age stratified health-care demand extended SEIR compartmental model calibrated to the municipality level for all municipalities in Sweden, and a radiation model describing inter-municipality mobility.ResultsOur model fit well with the observed deaths in Sweden up to 20th of April, 2020. The intensive care unit (ICU) demand is estimated to reach almost 10,000 patients per day by early May in an unmitigated scenario, far above the pre-pandemic ICU capacity of 526 beds. In contrast, a scenario with moderate physical distancing and shielding of elderly in combination with more effective isolation of infectious individuals would reduce numbers to below 500 per day. This would substantially flatten the curve, extend the epidemic period, but a risk resurgence is expected if measures are relaxed. The different scenarios show quite different death tolls up to the 1th of September, ranging from 5,000 to 41,000 deaths, exluding deaths potentially caused by ICU shortage. Further, analyses of the total all-cause mortality in Stockholm indicate that a confirmed COVID-19 death is associated with a additional 0.40 (95% Cl: 0.24, 0.57) all-cause death.ConclusionThe results of this study highlight the impact of different combinations of non-pharmaceutical interventions, especially moderate physical distancing and shielding of elderly in combination with more effective isolation of infectious individuals, on reducing deaths and lower healthcare costs. In less effective mitigation scenarios, the demand on ICU beds would rapidly exceed capacity, showing the tight interconnection between the healthcare demand and physical distancing in the society. These findings have relevance for Swedish policy and response to the COVID-19 pandemic and illustrate the importance of maintaining the level of physical distancing for a longer period to suppress or mitigate the impacts from the pandemic.Key messagesWe find physical distancing and isolation of infectious individuals without lockdown is effective in mitigating much of the negative direct health impact from the COVID-19 pandemic in Sweden, but has a higher death toll compared to other Scandinavian countries who did implement a lockdownBetween the start of the Swedish model of physical distancing and shiedling the elderly in March to late April, it appears Sweden has managed to ensure that ICU demands do not exceed ICU capacities and that deaths are substantially reduced compared to a counterfactual scenario.In the counterfactual scenario (eg no public health interventions), the intensive care unit demand is estimated to be almost 20 times higher than the intensive care capacity in Sweden and the number of deaths would be between 40,000 to 60,000Under current mitigation strategies, the death toll, health care need, and its associated cost are, however, still substantial, and it is likely to continue to rise unless the virus is suppressed, or eliminated. In the stronger mitigation and suppression scenarios, including the scenario fitting best to data from Sweden by late April 2020, there is an obvious risk of resurgence of the epidemic unless physical distancing, shielding of the elderly, and home isolation are effectively sustained.Additional analyses indicate all-cause non COVID-19 excess mortality rises with 0.4 deaths per every reported COVID-19 death in the Stockholm area.

Objective To assess short term mortality risks and excess mortality associated with exposure to ozone in several cities worldwide. Design Two stage time series analysis. Setting 406 cities in 20 countries, with overlapping periods between 1985 and 2015, collected from the database of Multi-City Multi-Country Collaborative Research Network. Population Deaths for all causes or for external causes only registered in each city within the study period. Main outcome measures Daily total mortality (all or non-external causes only). Results A total of 45 165 171 deaths were analysed in the 406 cities. On average, a 10 µg/m3 increase in ozone during the current and previous day was associated with an overall relative risk of mortality of 1.0018 (95% confidence interval 1.0012 to 1.0024). Some heterogeneity was found across countries, with estimates ranging from greater than 1.0020 in the United Kingdom, South Africa, Estonia, and Canada to less than 1.0008 in Mexico and Spain. Short term excess mortality in association with exposure to ozone higher than maximum background levels (70 µg/m3) was 0.26% (95% confidence interval 0.24% to 0.28%), corresponding to 8203 annual excess deaths (95% confidence interval 3525 to 12 840) across the 406 cities studied. The excess remained at 0.20% (0.18% to 0.22%) when restricting to days above the WHO guideline (100 µg/m3), corresponding to 6262 annual excess deaths (1413 to 11 065). Above more lenient thresholds for air quality standards in Europe, America, and China, excess mortality was 0.14%, 0.09%, and 0.05%, respectively. Conclusions Results suggest that ozone related mortality could be potentially reduced under stricter air quality standards. These findings have relevance for the implementation of efficient clean air interventions and mitigation strategies designed within national and international climate policies., Funding: This work was primarily supported by the UK Medical Research Council (MR/M022625/1 and MR/R013349/1) and by the UK Natural Environment Research Council (NE/R009384/1). HaK was supported by the National Natural Science Foundation of China (91843302 and 91643205) and China Medical Board Collaborating Program (16-250). JM was supported by the Fundação para a Ciência e a Tecnologia (FCT) through the scholarship SFRH/BPD/115112/2016. VH was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO, PCIN-2017-046) and the German Federal Ministry of Education and Research (BMBF, 01LS1201A2). AU and JK were supported by the Czech Science Foundation (18-22125S). HO and EI were supported by the Estonian Ministry of Education and Research (IUT34-17). AT was supported by the Japanese Society for the Promotion of Science invitational fellowships for research in Japan (S18149). YG was supported by the career development fellowship of the Australian National Health and Medical Research Council (APP1107107 and APP1163693). ST was supported by the Science and Technology Commission of Shanghai Municipality (18411951600). HoK was supported by the Global Research Laboratory (#K21004000001-10A0500-0710) through the National Research Foundation of Korea and by the Future Planning and Korea Ministry of Environment as the “Climate Change Correspondence R&D Program” (2013001310002). RMG was supported by a CSIR parliamentary grant. NS is supported by the National Institute of Environmental Health Sciences funded HERCULES Centre (P30ES019776). The sponsors had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; and preparation, review, or approval of this manuscript.

Background While the COVID-19 outbreak in China now appears suppressed, Europe and the USA have become the epicentres, both reporting many more deaths than China. Responding to the pandemic, Sweden has taken a different approach aiming to mitigate, not suppress, community transmission, by using physical distancing without lockdowns. Here we contrast the consequences of different responses to COVID-19 within Sweden, the resulting demand for care, intensive care, the death tolls and the associated direct healthcare related costs. Methods We used an age-stratified health-care demand extended SEIR (susceptible, exposed, infectious, recovered) compartmental model for all municipalities in Sweden, and a radiation model for describing inter-municipality mobility. The model was calibrated against data from municipalities in the Stockholm healthcare region. Results Our scenario with moderate to strong physical distancing describes well the observed health demand and deaths in Sweden up to the end of May 2020. In this scenario, the intensive care unit (ICU) demand reaches the pre-pandemic maximum capacity just above 500 beds. In the counterfactual scenario, the ICU demand is estimated to reach ∼20 times higher than the pre-pandemic ICU capacity. The different scenarios show quite different death tolls up to 1 September, ranging from 5000 to 41 000, excluding deaths potentially caused by ICU shortage. Additionally, our statistical analysis of all causes excess mortality indicates that the number of deaths attributable to COVID-19 could be increased by 40% (95% confidence interval: 0.24, 0.57). Conclusion The results of this study highlight the impact of different combinations of non-pharmaceutical interventions, especially moderate physical distancing in combination with more effective isolation of infectious individuals, on reducing deaths, health demands and lowering healthcare costs. In less effective mitigation scenarios, the demand on ICU beds would rapidly exceed capacity, showing the tight interconnection between the healthcare demand and physical distancing in the society. These findings have relevance for Swedish policy and response to the COVID-19 pandemic and illustrate the importance of maintaining the level of physical distancing for a longer period beyond the study period to suppress or mitigate the impacts from the pandemic.

An increase in the global health burden of temperature was projected for 459 locations in 28 countries worldwide under four representative concentration pathway scenarios until 2099. We determined that the amount of temperature increase for each 100 ppm increase in global CO2 concentrations is nearly constant, regardless of climate scenarios. The overall average temperature increase during 2010–2099 is largest in Canada (1.16 °C/100 ppm) and Finland (1.14 °C/100 ppm), while it is smallest in Ireland (0.62 °C/100 ppm) and Argentina (0.63 °C/100 ppm). In addition, for each 1 °C temperature increase, the amount of excess mortality is increased largely in tropical countries such as Vietnam (10.34%p/°C) and the Philippines (8.18%p/°C), while it is decreased in Ireland (−0.92%p/°C) and Australia (−0.32%p/°C). To understand the regional variability in temperature increase and mortality, we performed a regression-based modeling. We observed that the projected temperature increase is highly correlated with daily temperature range at the location and vulnerability to temperature increase is affected by health expenditure, and proportions of obese and elderly population. © 2019, This study was supported by the Global Research Lab (# K21004000001-10A0500-00710 ) through the National Research Foundation of Korea (NRF), funded by the Ministry of Science, ICT (Information and Communication Technologies), and Future Planning. JL was supported by the National Research Foundation of Korea as NRF-SNSF Researcher Exchange Program ( NRF-2018K2A9A1A06086694 ). AG was supported by Medical Research Council UK (Grant ID: MR/M022625/1 ) and Natural Environment Research Council UK (Grant ID: NE/R009384/1 ). JK and AU were supported by the Czech Science Foundation , project no. 18-22125S . HO and EI were supported by the Estonian Ministry of Education and Research (Grant no IUT34-17 ). JJKJ and NRIR were supported by the Research Council for Health, Academy of Finland (Grant no 266314 and 310372 ). MH and YH were supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency . AT was supported by the Japan Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan ( S18149 ). Appendix A

During the summer of 2018 large parts of Sweden experienced a record-breaking heatwave regarding temperatures and duration. Previous studies from Sweden with less extreme heat have shown that daily mortality is expected to increase during periods with high temperatures. Between the 2nd of July and 5th of August, the period in 2018 with the highest temperatures, 635 more deaths were observed in Sweden compared to the same period in 2017. This corresponds to an 8,2% increase over the entire heatwave, and a 13,5% increase during the warmest week, the 16th to 22nd of July. When using temperature data from four weather stations and relative risks from the models established for the Swedish heatwave early warning system, the heat episode in the summer of 2018 could be expected to result in 601-746 excess deaths, depending on model choice. Comparison with the observed mortality data therefore confirm the ability of the risk models to predict the expected increase in mortality also during longer periods with higher temperatures than ever studied before in Sweden.

BACKGROUND The systematic evaluation of the results of time-series studies of air pollution is challenged by differences in model specification and publication bias. METHODS We evaluated the associations of inhalable particulate matter (PM) with an aerodynamic diameter of 10 μm or less (PM10) and fine PM with an aerodynamic diameter of 2.5 μm or less (PM2.5) with daily all-cause, cardiovascular, and respiratory mortality across multiple countries or regions. Daily data on mortality and air pollution were collected from 652 cities in 24 countries or regions. We used overdispersed generalized additive models with random-effects meta-analysis to investigate the associations. Two-pollutant models were fitted to test the robustness of the associations. Concentration–response curves from each city were pooled to allow global estimates to be derived. RESULTS On average, an increase of 10 μg per cubic meter in the 2-day moving average of PM10 concentration, which represents the average over the current and previous day, was associated with increases of 0.44% (95% confidence interval [CI], 0.39 to 0.50) in daily all-cause mortality, 0.36% (95% CI, 0.30 to 0.43) in daily cardiovascular mortality, and 0.47% (95% CI, 0.35 to 0.58) in daily respiratory mortality. The corresponding increases in daily mortality for the same change in PM2.5 concentration were 0.68% (95% CI, 0.59 to 0.77), 0.55% (95% CI, 0.45 to 0.66), and 0.74% (95% CI, 0.53 to 0.95). These associations remained significant after adjustment for gaseous pollutants. Associations were stronger in locations with lower annual mean PM concentrations and higher annual mean temperatures. The pooled concentration–response curves showed a consistent increase in daily mortality with increasing PM concentration, with steeper slopes at lower PM concentrations. CONCLUSIONS Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.) Copyright © 2019 Massachusetts Medical Society., Funding text #1 Our data show independent associations between short-term exposure to PM10 and PM2.5 and daily all-cause, cardiovascular, and respiratory mortality in more than 600 cities across the globe. These data reinforce the evidence of a link between mortality and PM concentration established in regional and local studies. (Funded by the National Natural Science Foundation of China and others.) Funding text #2 Supported by the National Natural Science Foundation of China (grants 91843302 and 91643205, to Dr. Kan); the China Medical Board Collaborating Program (grant 16-250); the Medical Research Council, United Kingdom (grants MR/R013349/1 and MR/M022625/1, to Drs. Gasparrini, Sera, and Vicedo-Cabrera); the Career Development Fellowship of the Australian National Health and Medical Research Council (grants APP1107107 and APP1163693, to Dr. Guo); the Ministry of Education of Spain (grant PRX17/00705, to Dr. Tobias); the National Plan for I+D+I (grant PI15/00515), cofunded by the Instituto de Salud Carlos III Directorate General for Evaluation and the European Regional Development Fund (FEDER); the Global Research Laboratory (grant K21004000001-10A0500-00710 from the National Research Foundation of Korea, funded by the Ministry of Science, Information and Communication Technologies, to Dr. Kim); the Academy of Finland (grants 310372 and 310373, to Drs. Jaakkola and Ryti); the Estonian Ministry of Education and Research (grant IUT34-17, to Drs. Orru and Indermitte); the Czech Science Foundation (grant 18-22125S, to Drs. Kyselý and Urban); and a Professional Services Agreement with the Health Effects Institute, United States (to Dr. Cohen).View less Funding text #3 The authors’ affiliations are as follows: the School of Public Health, Key Laboratory of Public Health Safety of the Ministry of Education and National Health Commission Key Laboratory of Health Technology Assessment (C.L., R.C., H. Kan), the Department of Environmental Science and Engineering (J. Chen), Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (R.C., H. Kan), Fudan University, Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine (S.T.), and Children’s Hospital of Fudan University, National Center for Children’s Health (H. Kan), Shanghai, the School of Public Health and Management, Binzhou Medical University, Yantai (Y.G.), the School of Public Health, Institute of Environment and Population Health, Anhui Medical University, Hefei (S.T.), and the Key Laboratory of Environment and Health, Ministry of Education, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan (T.W.) — all in China; the Department of Public Health, Environments and Society (F.S., A.M.V.-C., A.M., A.G.) and the Centre for Statistical Methodology (A.G.), London School of Hygiene and Tropical Medicine, and the School of Population Health and Environmental Sciences, King’s College London (K.K.), London; the Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC (Y.G.), and the School of Public Health and Social Work, Queensland University of Technology, Brisbane (S.T.) — both in Australia; the Institute of Advanced Studies, University of São Paulo, São Paulo (M.S.Z.S.C., P.H.N.S.); the Air Health Science Division, Health Canada, and the School of Epidemiology and Public Health, University of Ottawa, Ottawa, ON (E.L.); the Department of Public Health (P.M.) and the School of Nursing and Obstetrics (N.V.O.), Universidad de los Andes, Santiago, Chile; Hospital Vista Hermosa, Bogota, Colombia (S.O.G.); Santé Publique France, French National Public Health Agency, Saint Maurice, France (M.P.); the Department of Epidemiology, Lazio Regional Health Service–ASL Roma 1, Rome (M. Stafoggia, M. Scortichini); Karolinska Institute, Institute of Environmental Medicine, Stockholm (M. Stafoggia), and the Department of Public Health and Clinical Medicine, Umeå University, Umeå (B.F., C.Å., H.O.) — both in Sweden; the Department of Pediatric Infectious Diseases, Institute of Tropical Medicine, Nagasaki University, Nagasaki (M.H.), and the Faculty of Health and Sport Sciences, University of Tsukuba, Tsukuba (Y.H.) — both in Japan; the Department of Environmental Health, National Institute of Pub

Background The health burden associated with temperature is expected to increase due to a warming climate. Populations living in cities are likely to be particularly at risk, but the role of urban characteristics in modifying the direct effects of temperature on health is still unclear. In this contribution, we used a multi-country dataset to study effect modification of temperature–mortality relationships by a range of city-specific indicators. Methods We collected ambient temperature and mortality daily time-series data for 340 cities in 22 countries, in periods between 1985 and 2014. Standardized measures of demographic, socio-economic, infrastructural and environmental indicators were derived from the Organisation for Economic Co-operation and Development (OECD) Regional and Metropolitan Database. We used distributed lag non-linear and multivariate meta-regression models to estimate fractions of mortality attributable to heat and cold (AF%) in each city, and to evaluate the effect modification of each indicator across cities. Results Heat- and cold-related deaths amounted to 0.54% (95% confidence interval: 0.49 to 0.58%) and 6.05% (5.59 to 6.36%) of total deaths, respectively. Several city indicators modify the effect of heat, with a higher mortality impact associated with increases in population density, fine particles (PM2.5), gross domestic product (GDP) and Gini index (a measure of income inequality), whereas higher levels of green spaces were linked with a decreased effect of heat. Conclusions This represents the largest study to date assessing the effect modification of temperature–mortality relationships. Evidence from this study can inform public-health interventions and urban planning under various climate-change and urban-development scenarios., This work was primarily supported by the Medical Research Council—UK (MR/M022625/1). The following individual grants also supported this work: Y.G. was supported by the Career Development Fellowship of Australian National Health and Medical Research Council (APP1107107); A.T. was supported by the Ministry of Education of Spain (PRX17/00705); J.J.K.J. and N.R.I.R. were supported by the Research Council for Health, Academy of Finland (266314); Y.L.G. was supported by the National Health Research Institutes of Taiwan (NHRI-EM-106-SP03); M.L.B. was supported by a US Environmental Protection Agency Assistance Agreement awarded to Yale University (83587101).

Aims: The present study aimed to investigate if set thresholds in the Swedish heat-wave warning system are valid for all parts of Sweden and if the heat-wave warning system captures a potential increase in all-cause mortality and coronary heart disease (CHD) mortality. An additional aim was to investigate whether neighbourhood deprivation modifies the relationship between heat waves and mortality. Methods: From 1990 until 2014, in 14 municipalities in Sweden, we collected data on daily maximum temperatures and mortality for the five warmest months. Heat waves were defined according to the categories used in the current Swedish heat-wave warning system. Using a case-crossover approach, we investigated the association between heat waves and mortality in Sweden, as well as a modifying effect of neighbourhood deprivation. Results: On a national as well as a regional level, heat waves significantly increased both all-cause mortality and CHD mortality by approximately 10% and 15%, respectively. While neighbourhood deprivation did not seem to modify heat wave–related all-cause mortality, CHD mortality did seem to modify the risk. Conclusions: It may not be appropriate to assume that heat waves in Sweden will have the same impact in a northern setting as in a southern, or that the impact of heat waves will be the same in affluent and deprived neighbourhoods. When designing and implementing heat-wave warning systems, neighbourhood, regional and national information should be incorporated.

Background The association between heat and daily mortality and its temporal variation are well known. However, few studies have analyzed the inter-annual variations in both the risk estimates and impacts of heat. The aim is to estimate inter-annual variations in the effect of heat for a fixed temperature range, on mortality in 9 European cities included in the PHASE (Public Health Adaptation Strategies to Extreme weather events) project for the period 1990–2010. The second aim is to evaluate overall summer effects and heat–attributable deaths for each year included in the study period, considering the entire air temperature range (both mild and extreme temperatures). Methods A city-specific daily time-series analysis was performed, using a generalized additive Poisson regression model, restricted to the warm season (April–September). To study the temporal variation for a fixed air temperature range, a Bayesian Change Point analysis was applied to the relative risks of mortality for a 2 °C increase over the 90th percentile of the city-specific distribution. The number of heat attributable deaths in each summer were also calculated for mild (reference to 95th percentile) and extreme heat (95th percentile to maximum value). Results A decline in the effects of heat over time was observed in Athens and Rome when considering a fixed interval, while an increase in effects was observed in Helsinki. The greatest impact of heat in terms of attributable deaths was observed in the Mediterranean cities (Athens, Barcelona and Rome) for extreme air temperatures. In the other cities the impact was mostly related to extreme years with 2003 as a record breaking year in Paris (+ 1900 deaths) and London (+ 1200 deaths). Conclusions Monitoring the impact of heat over time is important to identify changes in population vulnerability and evaluate adaptation measures. Electronic supplementary material The online version of this article (10.1186/s12940-018-0411-0) contains supplementary material, which is available to authorized users.

The health burden from heatwaves is expected to increase with rising global mean temperatures and more extreme heat events over the coming decades. Health-related effects from extreme heat are more common in elderly populations. The population of Europe is rapidly aging, which will increase the health effects of future temperatures. In this study, we estimate the magnitude of adaptation needed to lower vulnerability to heat in order to prevent an increase in heat-related deaths in the 2050s; this is the Adaptive Risk Reduction (ARR) needed. Temperature projections under Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 from 18 climate models were coupled with gridded population data and exposure-response relationships from a European multi-city study on heat-related mortality. In the 2050s, the ARR for the general population is 53.5%, based on temperature projections under RCP 4.5. For the population above 65 years in Southern Europe, the ARR is projected to be 45.9% in a future with an unchanged climate and 74.7% with climate change under RCP 4.5. The ARRs were higher under RCP 8.5. Whichever emission scenario is followed or population projection assumed, Europe will need to adapt to a great degree to maintain heat-related mortality at present levels, which are themselves unacceptably high, posing an even greater challenge.

Climate change is expected to increase to extreme temperatures and lead to more intense formation of near-surface ozone. Higher temperatures can cause heat stress and ozone is a highly oxidative pollutant; both increase cardiorespiratory mortality. Using greenhouse gas and ozone precursor emission scenarios, global and regional climate and chemistry-transport models, epidemiological data, and population projections, we projected ozone- and heat-related health risks under a changing climate. European near-surface temperature was modelled with the regional climate model (RCA4), forced by the greenhouse gas emission scenario RCP4.5 and the global climate model EC-EARTH, and near-surface ozone was modelled with the Multi-scale Atmospheric Transport and Chemistry (MATCH) model. Two periods were compared: recent climate in 1991–2000 and future climate in 2046–2055, projecting around a 2° increase in global temperatures by that time. Projections of premature mortality considered future climate, future population, and future emissions separately and jointly to understand the relative importance of their contributions. Ozone currently causes 55 000 premature deaths annually in Europe due to long-term exposure, including a proportion of the estimated 26 000 deaths per year due to short-term exposures. When only taking into account the impact of a changing climate, up to an 11% increase in ozone-associated mortality is expected in some countries in Central and Southern Europe in 2050. However, projected decreases in ozone precursor emissions are expected to result in a decrease in ozone-related mortality (−30% as EU average). Due to aging and increasingly susceptible populations, the decrease in 2050 would be smaller, up to −24%. During summer months, ozone risks could combine with increasing temperatures, especially during the hottest periods and in densely populated urban areas. While the heat burden is currently of the same order of magnitude as ozone, due to increasing temperatures and decreasing ozone precursor emissions, heat-related mortality could be twice as large as ozone-related mortality in 2050.

Introduction Ozone is a highly oxidative pollutant, associated with increasing mortality. All else (e.g. ozone precursors) being equal, summertime ground-level ozone will increase as temperatures i...

The current global geographic distribution of malaria results from a complex interaction between climatic and non-climatic factors. Over the past century, socio-economic development and public health measures have contributed to a marked contraction in the distribution of malaria. Previous assessments of the potential impact of global changes on malaria have not quantified the effects of non-climate factors. In this paper, we describe an empirical model of the past, present and future-potential geographic distribution of malaria which incorporates both the effects of climate change and of socio-economic development. A logistic regression model using temperature, precipitation and gross domestic product per capita (GDPpc) identifies the recent global geographic distribution of malaria with high accuracy (sensitivity 85% and specificity 95%). Empirically, climate factors have a substantial effect on malaria transmission in countries where GDPpc is currently less than US$20,000. Using projections of future climate, GDPpc and population consistent with the IPCC A1B scenario, we estimate the potential future population living in areas where malaria can be transmitted in 2030 and 2050. In 2050, the projected population at risk is approximately 5.2 billion when considering climatic effects only, 1.95 billion when considering the combined effects of GDP and climate, and 1.74 billion when considering GDP effects only. Under the A1B scenario, we project that climate change has much weaker effects on malaria than GDPpc increase. This outcome is, however, dependent on optimistic estimates of continued socioeconomic development. Even then, climate change has important effects on the projected distribution of malaria, leading to an increase of over 200 million in the projected population at risk.

Over the last two decades a number of heatwaves have brought the need for heatwave early warning systems (HEWS) to the attention of many European governments. The HEWS in Europe are operating under the assumption that there is a high correlation between observed and forecasted temperatures. We investigated the sensitivity of different temperature mortality relationships when using forecast temperatures. We modelled mortality in Stockholm using observed temperatures and made predictions using forecast temperatures from the European Centre for Medium-range Weather Forecasts to assess the sensitivity. We found that the forecast will alter the expected future risk differently for different temperature mortality relationships. The more complex models seemed more sensitive to inaccurate forecasts. Despite the difference between models, there was a high agreement between models when identifying risk-days. We find that considerations of the accuracy in temperature forecasts should be part of the design of a HEWS. Currently operating HEWS do evaluate their predictive performance, this information should also be part of the evaluation of the epidemiological models that are the foundation in the HEWS. The most accurate description of the relationship between high temperature and mortality might not be the most suitable or practical when incorporated into a HEWS.

Objectives Respiratory diseases are ranked second in Europe in terms of mortality, prevalence and costs. Studies have shown that extreme heat has a large impact on mortality and morbidity, with a large relative increase for respiratory diseases. Expected increases in mean temperature and the number of extreme heat events over the coming decades due to climate change raise questions about the possible health impacts. We assess the number of heat-related respiratory hospital admissions in a future with a different climate. Design A Europe-wide health impact assessment. Setting An assessment for each of the EU27 countries. Methods Heat-related hospital admissions under a changing climate are projected using multicity epidemiological exposure–response relationships applied to gridded population data and country-specific baseline respiratory hospital admission rates. Times-series of temperatures are simulated with a regional climate model based on four global climate models, under two greenhouse gas emission scenarios. Results Between a reference period (1981–2010) and a future period (2021–2050), the total number of respiratory hospital admissions attributed to heat is projected to be larger in southern Europe, with three times more heat attributed respiratory hospital admissions in the future period. The smallest change was estimated in Eastern Europe with about a twofold increase. For all of Europe, the number of heat-related respiratory hospital admissions is projected to be 26 000 annually in the future period compared with 11 000 in the reference period. Conclusions The results suggest that the projected effects of climate change on temperature and the number of extreme heat events could substantially influence respiratory morbidity across Europe.