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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.

Background: Increased mortality risk is associated with short-term temperature variability. However, to our knowledge, there has been no comprehensive assessment of the temperature variability-related mortality burden worldwide. In this study, using data from the MCC Collaborative Research Network, we first explored the association between temperature variability and mortality across 43 countries or regions. Then, to provide a more comprehensive picture of the global burden of mortality associated with temperature variability, global gridded temperature data with a resolution of 0·5° × 0·5° were used to assess the temperature variability-related mortality burden at the global, regional, and national levels. Furthermore, temporal trends in temperature variability-related mortality burden were also explored from 2000–19. Methods: In this modelling study, we applied a three-stage meta-analytical approach to assess the global temperature variability-related mortality burden at a spatial resolution of 0·5° × 0·5° from 2000–19. Temperature variability was calculated as the SD of the average of the same and previous days’ minimum and maximum temperatures. We first obtained location-specific temperature variability related-mortality associations based on a daily time series of 750 locations from the Multi-country Multi-city Collaborative Research Network. We subsequently constructed a multivariable meta-regression model with five predictors to estimate grid-specific temperature variability related-mortality associations across the globe. Finally, percentage excess in mortality and excess mortality rate were calculated to quantify the temperature variability-related mortality burden and to further explore its temporal trend over two decades. Findings: An increasing trend in temperature variability was identified at the global level from 2000 to 2019. Globally, 1 753 392 deaths (95% CI 1 159 901–2 357 718) were associated with temperature variability per year, accounting for 3·4% (2·2–4·6) of all deaths. Most of Asia, Australia, and New Zealand were observed to have a higher percentage excess in mortality than the global mean. Globally, the percentage excess in mortality increased by about 4·6% (3·7–5·3) per decade. The largest increase occurred in Australia and New Zealand (7·3%, 95% CI 4·3–10·4), followed by Europe (4·4%, 2·2–5·6) and Africa (3·3, 1·9–4·6). Interpretation: Globally, a substantial mortality burden was associated with temperature variability, showing geographical heterogeneity and a slightly increasing temporal trend. Our findings could assist in raising public awareness and improving the understanding of the health impacts of temperature variability. Funding: Australian Research Council, Australian National Health & Medical Research Council., This study was supported by the Australian Research Council (DP210102076) and the Australian National Health and Medical Research Council (APP2000581). YW was supported by the China Scholarship Council (number 202006010044). SL was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number APP2009866). QZ was supported by the Program of Qilu Young Scholars of Shandong University, Jinan, China. BW was supported by the China Scholarship Council (number 202006010043). JK and AU were supported by the Czech Science Foundation (project number 20–28560S). NS was supported by the National Institute of Environmental Health Sciences-funded HERCULES Center (P30ES019776). S-CP and YLG were supported by the Ministry of Science and Technology (Taiwan; MOST 109–2621-M-002–021). YH was supported by the Environment Research and Technology Development Fund (JPMEERF15S11412) of the Environmental Restoration and Conservation Agency. MdSZSC and PHNS were supported by the São Paulo Research Foundation (FAPESP). ST was supported by the Science and Technology Commission of Shanghai Municipality (grant number 18411951600). HO and EI were supported by the Estonian Ministry of Education and Research (IUT34–17). JM was supported by a fellowship of Fundação para a Ciência e a Tecnlogia (SFRH/BPD/115112/2016). AG and FS 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). AS, SR, and FdD were supported by the EU's Horizon 2020 project, Exhaustion (grant ID 820655). VH was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant ID PCIN-2017–046). AT was supported by MCIN/AEI/10.13039/501100011033 (grant CEX2018-000794-S). YG was supported by the Career Development Fellowship (number APP1163693) and Leader Fellowship (number APP2008813) of the Australian National Health and Medical Research Council. Statistics South Africa kindly provided the mortality data, but had no other role in the study. This Article is published in memory of Simona Fratianni, who helped to contribute the data for Romania.

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.

Climate change affects human health; however, there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change. Here, we use empirical data from 732 locations in 43 countries to estimate the mortality burdens associated with the additional heat exposure that has resulted from recent human-induced warming, during the period 1991–2018. Across all study countries, we find that 37.0% (range 20.5–76.3%) of warm-season heat-related deaths can be attributed to anthropogenic climate change and that increased mortality is evident on every continent. Burdens varied geographically but were of the order of dozens to hundreds of deaths per year in many locations. Our findings support the urgent need for more ambitious mitigation and adaptation strategies to minimize the public health impacts of climate change., We thank the participants of the ISIMIP Health workshop in Barcelona in November 2018 where this work was discussed for the first time. This study was supported by the Medical Research Council UK (grant no. MR/M022625/1), the Natural Environment Research Council UK (grant no. NE/R009384/1) and the European Union’s Horizon 2020 Project Exhaustion (grant no. 820655). N.S. was supported by the NIEHS-funded HERCULES Center (P30ES019776). Y.H. was supported by the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency, Japan (JPMEERF15S11412). J.J.J.K.J. was supported by Academy of Finland (grant no. 310372). V.H. was supported by the Spanish Ministry of Economy, Industry and Competitiveness (grant no. PCIN-2017-046) and the German Federal Ministry of Education and Research (grant no. 01LS1201A2). J.K. and A.U. were supported by the Czech Science Foundation (grant no. 20-28560S). J.M. was supported by the Fundação para a Ciência e a Tecnologia (FCT) (SFRH/BPD/115112/2016). S.R. and F.d.R. were supported by European Union’s Horizon 2020 Project EXHAUSTION (grant no. 820655). M.H. was supported by the Japan Science and Technology Agency as part of SICORP, grant no. JPMJSC20E4. Y.G. was supported by the Career Development Fellowship of the Australian National Health and Medical Research Council (APP1163693). S.L. was support by the Early Career Fellowship of the Australian National Health and Medical Research Council (APP1109193). Y.L.L.G. was supported by the Taiwan Ministry of Science and Technology (MOST110-2918-I-002-007) as a visiting academic at the University of Sydney.

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.

Background: Increased atmospheric particulate matter (PM) concentrations are commonly observed during desert dust days in Iran, but there is still no evidence of their effects on human health. We aimed to evaluate the association between daily mortality and exposure to PM10 and PM2.5 during dust and non-dust days in Tehran and Ahvaz, two major Middle Eastern cities with different sources, intensity, and frequency of desert dust days. Methods: We identified desert dust days based on exceeding a daily PM10 concentration threshold of 150 µg/m3 between 2014 and 2017, checking for low PM2.5/PM10 ratio typical of dust days. We used a time-stratified case-crossover design to estimate the short-term effects of PM10 and PM2.5 concentrations on daily mortality during dust and non-dust days. Data was analyzed using conditional Poisson regression models. Results: Higher concentrations of PM and frequency of desert dust days were observed in Ahvaz rather than Tehran. In Ahvaz, the effect of PM10 at lag 0 was much higher during dust days, an increment of 10 μg/m3 was associated with 3.28% (95%CI = [2.42, 4.15]) increase of daily mortality, than non-dust days, 1.03% (95%CI = [−0.02, 2.08]), while in Tehran, was slightly higher during non-dust days, 0.72% (95%CI = [0.23, 1.23]), than in dust days, 0.49% (95%CI = [−0.22, 1.20]). No statistically significant associations were observed between PM2.5 and daily mortality in Ahvaz, while in Teheran the effect of PM2.5 increased significantly during non-dust days at lag 2, 1.89% (95%CI = [0.83, 1.2.95] and lag 3, 1.88% (95%CI = [0.83, 1.2.95]). Conclusion: The study provides evidence that exposure to PM during Middle East dust days is an important risk factor to human health in arid regions and areas affected by desert dust events. © 2019 The Authors, Funding text #1 Daily counts of all-natural cause mortality (ICD 10th revision: A00-R99) were collected for the cities of Ahvaz, from 21st March 2015 to 22nd September 2017, and Tehran, from 21st March 2014 to 20th March 2017. Mortality data were provided by the Iran Ministry of Health and Medical Education and the database of Tehran Municipality. 2.2.2 Funding text #2 This study was funded by Shahid Beheshti University of Medical Sciences (grant number #6649 ), the Environmental and Occupational Health Center of Ministry of Health and Medical Education , and the Generalitat de Catalunya ( AGAUR 2017 SGR41 ), Spain.

Background: Few studies have examined variation in the associations between heat waves and mortality in an international context. Objectives: We aimed to systematically examine the impacts of heat waves on mortality with lag effects internationally. Methods: We collected daily data of temperature and mortality from 400 communities in 18 countries/regions and defined 12 types of heat waves by combining community-specific daily mean temperature ≥90th, 92.5th, 95th, and 97.5th percentiles of temperature with duration ≥2, 3, and 4 d. We used time-series analyses to estimate the community-specific heat wave–mortality relation over lags of 0–10 d. Then, we applied meta-analysis to pool heat wave effects at the country level for cumulative and lag effects for each type of heat wave definition. Results: Heat waves of all definitions had significant cumulative associations with mortality in all countries, but varied by community. The higher the temperature threshold used to define heat waves, the higher heat wave associations on mortality. However, heat wave duration did not modify the impacts. The association between heat waves and mortality appeared acutely and lasted for 3 and 4 d. Heat waves had higher associations with mortality in moderate cold and moderate hot areas than cold and hot areas. There were no added effects of heat waves on mortality in all countries/regions, except for Brazil, Moldova, and Taiwan. Heat waves defined by daily mean and maximum temperatures produced similar heat wave–mortality associations, but not daily minimum temperature. Conclusions: Results indicate that high temperatures create a substantial health burden, and effects of high temperatures over consecutive days are similar to what would be experienced if high temperature days occurred independently. People living in moderate cold and moderate hot areas are more sensitive to heat waves than those living in cold and hot areas. Daily mean and maximum temperatures had similar ability to define heat waves rather than minimum temperature. Medical Research Council, UK