Search

Links between weather variability, influenza/acute respiratory infections (ARI), and human health are extremely complex in the cold season, and their explanation remains uncertain. It is not clear whether the winter mortality peak is related rather to low ambient temperatures or ARI, and how weather variability may modify transmission patterns of ARI and related mortality. This study investigates links between weather characteristics, influenza/ARI epidemics and all-cause mortality in the population of the Czech Republic (Central Europe), by employing long-term epidemiological and meteorological datasets over the 1982/83 to 2019/20 epidemics seasons. The links are analysed with respect to the predominant type of influenza virus in each season (A/H3N2 and A/H1N1 subtypes, and B lineages). We focus on i) identification of meteorological conditions associated with epidemics, ii) how timing of the epidemics and their magnitude are linked to weather characteristics, and iii) whether there are synergetic effects of cold weather and epidemics on the mortality impacts. Preliminary results suggest that high excess mortality during influenza epidemics was associated with low temperatures while above-average temperatures were linked to lower morbidity and mortality impacts. The role of other meteorological characteristics is less clear. Understanding weather conditions that increase the transmission and survival of influenza and respiratory viruses could help to better inform at-risk populations, implement preventive measures, and mitigate the negative impacts of influenza and ARI.

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.

Heat-related mortality has been identified as one of the key climate extremes posing a risk to human health. Current research focuses largely on how heat mortality increases with mean global temperature rise, but it is unclear how much climate change will increase the frequency and severity of extreme summer seasons with high impact on human health. In this probabilistic analysis, we combined empirical heat-mortality relationships for 748 locations from 47 countries with climate model large ensemble data to identify probable past and future highly impactful summer seasons. Across most locations, heat mortality counts of a 1-in-100 year season in the climate of 2000 would be expected once every ten to twenty years in the climate of 2020. These return periods are projected to further shorten under warming levels of 1.5°C and 2°C, where heat-mortality extremes of the past climate will eventually become commonplace if no adaptation occurs. Our findings highlight the urgent need for strong mitigation and adaptation to reduce impacts on human lives.

While previous research on historical changes in heat-related mortality observed decreasing trends over the recent decades, future projections suggest increasing impact of heat on mortality in most regions of the world. This study aimed to analyse temporal changes in temperature-mortality relationships in Prague, Czech Republic in the warm season (May–September), using a daily mortality time series from 1982 to 2019. To investigate possible effect of adaptation to increasing temperature, we divided the study period into four decades (1980s–2010s). We used conditional Poisson regression models to identify decade-specific relative risk of heat-related mortality and to calculate the annual number of heat-attributable deaths and the heat-attributable fraction of total warm season deaths. We estimated their trends over the whole study period by a generalized additive model with non-parametric smoothing spline. Our results showed that the unprecedentedly hot 2010s was associated with approximately twice as large relative risk of heat-related mortality than in previous decades. This resulted in the reversal of the trend in heat-attributable mortality in the 1990s and its increase during the last two decades. Our findings highlight the importance of further improvement of adaptation measures such as heat-and-health warning systems to protect the heat-susceptible population.

Because of climate change, summer temperatures are predicted to rise and heat waves to be more recurrent, including in Central Europe. It is important to understand heat-related risks on human mortality and to identify inequalities in vulnerability among the population, such as sex and gender inequalities. In this study, the associations between daily temperature and mortality during the five warmest months of the year (from May to September) have been analysed in the Czech Republic for the period 1995–2019. The primary focus of the analysis was on the differences in the associations by sex, i.e., between men and women. These two categories were further divided by age, marital status, residence’s location and cause of death. Mortality time series have been modelled by a quasi-Poisson regression model with a distributed lag non-linear model (DLNM) to account for the delayed and non-linear effects of temperature on mortality. The heat-related mortality risks obtained in each population group were expressed in terms of risk at the 99th percentile of summer temperature relative to the minimum mortality temperature.The results showed that women were more at risk to die because of heat than men. With regard to age, the highest risk for men was observed between 75 to 84 years old, while risk for women was higher for women above 85 years old. Risks among married people were lower than risks among single, divorced and widowed people, and risks in divorced women were significantly higher than in divorced men. Thus, this study showed that social and demographic criteria impacted the heat vulnerability and in particular, results highlighted the important role of sex and gender inequalities in heat-related mortality. Deeper studies on these social drivers would be relevant to design efficient and fair mitigation and adaptation strategies.

Episodes of extremely high temperatures (heatwaves) are associated with an increased risk of human mortality. People living in cities are at the most significant risk of heat-related mortality due to the urban heat island effect. Although most studies investigate the impact of heat stress on mortality in a city as a whole, the magnitude of the heat stress in a particular part of the city depends on its physical characteristics.Our study aims to investigate spatio-temporal links between the spatial distribution of the surface urban heat island intensity (SUHII) and heatwave-related mortality in Prague, the Czech Republic. We will analyse daily all-cause mortality in ten Prague districts between 2001 and 2010. A mortality baseline in each district will be determined using generalized additive models adjusted for long-term trends and seasonal and weekly cycles. Relative deviations from the baseline mortality will be calculated to quantify excess mortality during heat waves, defined as periods of at least three consecutive days with a mean daily temperature higher than the 95th percentile of the annual distribution. Six major heatwaves will be selected to investigate the links between the spatial distribution of SUHII and heat wave-related mortality. Daily MODIS land surface temperature images will be used to analyse the spatio-temporal changes in SUHII during the major heatwaves. Spatial statistics tools in ArcGIS will be used to investigate the spatio-temporal patterns.Our study hypothesizes that the spatial distribution of heat-related mortality is associated with the distribution of SUHII during the major heatwaves. Due to climate change, the frequency and intensity of heatwaves are expected to increase, and the urban heat island intensity is likely to increase in response to heatwaves. The results of our study will help to identify areas in Prague with the most significant impact of urban design on heat-related mortality. This information is vital for identifying hot spots of heat-related mortality and developing strategies to mitigate heat stress in the city.

Background and aim The associations between COVID-19 transmission and meteorological factors are scientifically debated. Several studies have been conducted worldwide, with inconsistent findings. However, often these studies had methodological issues, e.g., did not exclude important confounding factors, or had limited geographic or temporal resolution. Our aim was to quantify associations between temporal variations in COVID-19 incidence and meteorological variables globally. Methods We analysed data from 455 cities across 20 countries from 3 February to 31 October 2020. We used a time-series analysis that assumes a quasi-Poisson distribution of the cases and incorporates distributed lag non-linear modelling for the exposure associations at the city-level while considering effects of autocorrelation, long-term trends, and day of the week. The confounding by governmental measures was accounted for by incorporating the Oxford Governmental Stringency Index. The effects of daily mean air temperature, relative and absolute humidity, and UV radiation were estimated by applying a meta-regression of local estimates with multi-level random effects for location, country, and climatic zone. Results We found that air temperature and absolute humidity influenced the spread of COVID-19 over a lag period of 15 days. Pooling the estimates globally showed that overall low temperatures (7.5 °C compared to 17.0 °C) and low absolute humidity (6.0 g/m3 compared to 11.0 g/m3) were associated with higher COVID-19 incidence (RR temp =1.33 with 95%CI: 1.08; 1.64 and RR AH =1.33 with 95%CI: 1.12; 1.57). RH revealed no significant trend and for UV some evidence of a positive association was found. These results were robust to sensitivity analysis. However, the study results also emphasise the heterogeneity of these associations in different countries. Conclusion Globally, our results suggest that comparatively low temperatures and low absolute humidity were associated with increased risks of COVID-19 incidence. However, this study underlines regional heterogeneity of weather-related effects on COVID-19 transmission., This paper used Copernicus Climate Change Service (C3S) and Copernicus Atmosphere Monitoring Service (CAMS) information. Hence, the authors would like to thank the European Centre for Medium-Range Weather Forecasts (ECMWF) for its data generation on behalf of the European Union.

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.

Studies projecting the impacts of future climate change on temperature-mortality relationships suggest increasing heat-related mortality in most regions of the world. On the contrary, a reduced risk of heat-related mortality has been observed in many countries over the last decades, suggesting a positive effect of technological development and improved health care systems. However, most of the studies show that the decline in vulnerability of populations to heat has abated in the early 2000s and further decreasing trend is unlikely.In this study, we analysed temperature-mortality relationships in Prague, Czech Republic during 1982–2019. The study was restricted to five warmest months (May–September). To investigate possible changes in the temperature–mortality relationship, the study period was divided in four decades (1980s to 2010s). Conditional Poisson Regression coupled with the Distributed Lag Non-Linear Model (DLNM) was run separately in each decade, to derive decade-specific temperature–mortality associations. A stratum indicator variable composed of year, month, and day of the week was used to control for long-term, seasonal trends and weekly effects. The DLNM approach was applied in order to analyse delayed effects of temperature on mortality. The attributable number of deaths (AD) and the attributable fraction (AF %) of total May–September deaths on hot days was calculated from the model’s outputs, separately for each decade. Hot days were defined as days with daily mean temperature larger than the 95th percentile of the decade-specific May–September distribution.We observed a quadratic trend shape in the number of deaths attributable to heat; maximum in the 2010s and minimum in the 1990s. The total number of heat-attributable deaths increased from ≈500 to almost 900 per decade between the 1980s and the 2010s, which corresponds to the fraction of 0.90 and 1.75 %, respectively, of the total number of deaths in a warm season.

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.

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.

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.

Air temperature has been the most commonly used exposure metric in assessing relationships between thermal stress and mortality. Lack of the high-quality meteorological station data necessary to adequately characterize the thermal environment has been one of the main limitations for the use of more complex thermal indices. Global climate reanalyses may provide an ideal platform to overcome this limitation and define complex heat and cold stress conditions anywhere in the world. In this study, we explored the potential of the Universal Thermal Climate Index (UTCI) based on ERA5 – the latest global climate reanalysis from the European Centre for Medium-Range Weather Forecasts (ECMWF) – as a health-related tool. Employing a novel ERA5-based thermal comfort dataset ERA5-HEAT, we investigated the relationships between the UTCI and daily mortality data in 21 cities across 9 European countries. We used distributed lag nonlinear models to assess exposure-response relationships between mortality and thermal conditions in individual cities. We then employed meta-regression models to pool the results for each city into four groups according to climate zone. To evaluate the performance of ERA5-based UTCI, we compared its effects on mortality with those for the station-based UTCI data. In order to assess the additional effect of the UTCI, the performance of ERA5-and station-based air temperature (T) was evaluated. Whilst generally similar heat- and cold-effects were observed for the ERA5-and station-based data in most locations, the important role of wind in the UTCI appeared in the results. The largest difference between any two datasets was found in the Southern European group of cities, where the relative risk of mortality at the 1st percentile of daily mean temperature distribution (1.29 and 1.30 according to the ERA5 vs station data, respectively) considerably exceeded the one for the daily mean UTCI (1.19 vs 1.22). These differences were mainly due to the effect of wind in the cold tail of the UTCI distribution. The comparison of exposure-response relationships between ERA5-and station-based data shows that ERA5-based UTCI may be a useful tool for definition of life-threatening thermal conditions in locations where high-quality station data are not available., We would like to thank all the national data providers for supplying meteorological as well as health data (see more details in the Supplementary Material). The study was primarily supported by the Czech Science Foundation, project no. 18-22125S (AU and JK), the European Commission's HORIZON2020 ANYWHERE project (Enhancing Emergency Management and Response to Extreme Weather and Climate Events, Project ID 700099, CDN, HLC), and FATHUM (Forecasts for AnTicipatory HUManitarian action) part of the UKRI NERC/DFID SHEAR programme, grant number NE/P000525/1 (HLC). The following individual grants also supported this work: Medical Research Council-UK (Grant ID: MR/M022625/1), Natural Environment Research Council UK (Grant ID: NE/R009384/1), European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655), Spanish Ministry of Economy, Industry and Competitiveness (Grant ID: PCIN-2017-046).

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.

Seniors constitute the population group generally most at risk of mortality due to heat stress. As life expectancy increases and health conditions of elderly people improve over time, vulnerability of the population to heat changes as well. We employed the years-of-life-lost (YLL) approach, considering life expectancy at the time of each death, to investigate how population ageing affects temporal changes in heat-related mortality in the Czech Republic. Using an updated gridded meteorological database, we identified heat waves during 1994–2017, and analysed temporal changes in their impacts on YLL and mortality. The mean impact of a heat-wave day on relative excess mortality and YLL had declined by approximately 2–3% per decade. That decline abated in the current decade, however, and the decreasing trend in mean excess mortality as well as YLL vanished when the short-term mortality displacement effect was considered. Moreover, the cumulative number of excess deaths and YLL during heat waves rose due to increasing frequency and intensity of heat waves during the examined period. The results show that in studies of temporal changes it is important to differentiate between mean effects of heat waves on mortality and the overall death burden associated with heat waves. Analysis of the average ratio of excess YLL/death per heat-wave day indicated that the major heat-vulnerable population group shifted towards older age (70+ years among males and 75+ years among females). Our findings highlight the importance of focusing heat-protection measures especially upon the elderly population, which is most heat-vulnerable and whose numbers are rising.

There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature.We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset.In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. City-specific associations were summarized using meta-analytic techniques.Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1-3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly.The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430.

BACKGROUND: There is strong experimental evidence that physiologic stress from high temperatures is greater if humidity is higher. However, heat indices developed to allow for this have not consistently predicted mortality better than dry-bulb temperature. OBJECTIVES: We aimed to clarify the potential contribution of humidity an addition to temperature in predicting daily mortality in summer by using a large multicountry dataset. METHODS: In 445 cities in 24 countries, we fit a time-series regression model for summer mortality with a distributed lag nonlinear model (DLNM) for temperature (up to lag 3) and supplemented this with a range of terms for relative humidity (RH) and its interaction with temperature. Cityspecific associations were summarized using meta-analytic techniques. RESULTS: Adding a linear term for RH to the temperature term improved fit slightly, with an increase of 23% in RH (the 99th percentile anomaly) associated with a 1.1% [95% confidence interval (CI): 0.8, 1.3] decrease in mortality. Allowing curvature in the RH term or adding terms for interaction of RH with temperature did not improve the model fit. The humidity-related decreased risk was made up of a positive coefficient at lag 0 outweighed by negative coefficients at lags of 1–3 d. Key results were broadly robust to small model changes and replacing RH with absolute measures of humidity. Replacing temperature with apparent temperature, a metric combining humidity and temperature, reduced goodness of fit slightly. DISCUSSION: The absence of a positive association of humidity with mortality in summer in this large multinational study is counter to expectations from physiologic studies, though consistent with previous epidemiologic studies finding little evidence for improved prediction by heat indices. The result that there was a small negative average association of humidity with mortality should be interpreted cautiously; the lag structure has unclear interpretation and suggests the need for future work to clarify. https://doi.org/10.1289/EHP5430. © 2019, Public Health Services, US Dept of Health and Human Services. All rights reserved., B.A. was supported by the UK National Institute for Health Research (NIHR) Health Protection Research Unit in Environmental Change and Health; A.G., F.S., and A.V.C. were supported by grants from the UK Medical Research Council (grant IDs: MR/M022625/1, MR/R013349/1) and from the UK Natural Environment Research Council (grant ID: NE/R009384/1); and M.L.B. was supported by Assistance Agreement No. 83587101 awarded by the U.S. Environmental Protection Agency and R01 MD012769 awarded by the U.S. National Institutes of Health. Y.G. was supported by the Career Development Fellowship of Australian National Health and Medical Research Council (APP1107107). A.T. was supported by the Japanese Society for the Promotion of Science (JSPS) Invitational Fellowships for Research in Japan (S18149). Y.L.G. was supported by NHRI-105-EMSP09 from National Health Research Institutes, Taiwan. H.O. and E.I. were supported by Ministry of Education and Research (Estonia) grant IUT34-17. J.K. and A.U. were supported by the Czech Science Foundation, grant 18-22125S. H.K., M.H., and Y.H. were supported by the Global Research Lab (#K21004000001-10A0500-00710) through the National Research Foundation of Korea. M.H. and Y.H. were supported by the Environment Research and Technology Development Fund (S-14) of the Environmental Restoration and Conservation Agency.

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

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

Although impacts of extremely cold temperatures on human health have been widely studied, adverse effects of other extreme weather phenomena have so far received much less attention. We employed a high-quality long-term mortality time series (1982-2017) to evaluate impacts of extreme winter weather in the Czech Republic. We aimed to clarify whether compound events of extreme weather cause larger impacts on mortality than do each type of extreme if evaluated individually. Using daily data from the E-OBS and ERA5 datasets, we analyzed 9 types of extreme events: extreme wind gust, precipitation, snowfall, and sudden temperature and pressure changes. Relative mortality deviations from the adjusted baseline were used to estimate the immediate effect of the selected extreme events on excess mortality. The impact was adjusted for the effect of extreme cold. Extreme events associated with sudden rise of minimum temperature and pressure drops had generally significant impact on excess mortality (3.7% and 1.4% increase). The impacts were even more pronounced if these events occurred simultaneously or were compounded with other types of extremes, such as heavy precipitation, snowfall, maximum temperature rise, and their combinations (increase as great as 14.4%). Effects of some compound events were significant even for combinations of extremes having no significant impact on mortality when evaluated separately. On the other hand, a "protective" effect of pressure increases reduced the risk for its compound events. Meteorological patterns during extreme events linked to excess mortality indicate passage of a low-pressure system northerly from the study domain. We identified extreme winter weather events other than cold temperatures with significant impact on excess mortality. Our results suggest that occurrence of compound extreme events strengthen the impacts on mortality and therefore analysis of multiple meteorological parameters is a useful approach in defining adverse weather conditions.

We compared selected thermal indices in their ability to predict heat-related mortality in Prague, Czech Republic, during the extraordinary summer 2015. Relatively, novel thermal indices—Universal Thermal Climate Index and Excess Heat Factor (EHF)—were compared with more traditional ones (apparent temperature, simplified wet-bulb globe temperature (WBGT), and physiologically equivalent temperature). The relationships between thermal indices and all-cause relative mortality deviations from the baseline (excess mortality) were estimated by generalized additive models for the extended summer season (May–September) during 1994–2014. The resulting models were applied to predict excess mortality in 2015 based on observed meteorology, and the mortality estimates by different indices were compared. Although all predictors showed a clear association between thermal conditions and excess mortality, we found important variability in their performance. The EHF formula performed best in estimating the intensity of heat waves and magnitude of heat-impacts on excess mortality on the most extreme days. Afternoon WBGT, on the other hand, was most precise in the selection of heat-alert days during the extended summer season, mainly due to a relatively small number of “false alerts” compared to other predictors. Since the main purpose of heat warning systems is identification of days with an increased risk of heat-related death rather than prediction of exact magnitude of the excess mortality, WBGT seemed to be a slightly favorable predictor for such a system.

The Paris Agreement binds all nations to undertake ambitious efforts to combat climate change, with the commitment to hold warming well below 2 degrees C in global mean temperature (GMT), relative to pre-industrial levels, and to pursue efforts to limit warming to 1.5 degrees C. The 1.5 degrees C limit constitutes an ambitious goal for which greater evidence on its benefits for health would help guide policy and potentially increase the motivation for action. Here we contribute to this gap with an assessment on the potential health benefits, in terms of reductions in temperature-related mortality, derived from the compliance to the agreed temperature targets, compared to more extreme warming scenarios. We performed a multi-region analysis in 451 locations in 23 countries with different climate zones, and evaluated changes in heat and cold-related mortality under scenarios consistent with the Paris Agreement targets (1.5 and 2 degrees C) and more extreme GMT increases (3 and 4 degrees C), and under the assumption of no changes in demographic distribution and vulnerability. Our results suggest that limiting warming below 2 degrees C could prevent large increases in temperature-related mortality in most regions worldwide. The comparison between 1.5 and 2 degrees C is more complex and characterized by higher uncertainty, with geographical differences that indicate potential benefits limited to areas located in warmer climates, where direct climate change impacts will be more discernible.

This study aimed to assess the impacts of heat waves during the summer of 2015 on mortality in the Czech Republic and to compare them with those of heat waves back to the previous record-breaking summer of 1994. We analyzed daily natural-cause mortality across the country's entire population. A mortality baseline was determined using generalized additive models adjusted for long-term trends, seasonal and weekly cycles, and identified heat waves. Mortality deviations from the baseline were calculated to quantify excess mortality during heat waves, defined as periods of at least three consecutive days with mean daily temperature higher than the 95th percentile of annual distribution. The summer of 2015 was record-breaking in the total duration of heat waves as well as their total heat load. Consequently, the impact of the major heat wave in 2015 on the increase in excess mortality relative to the baseline was greater than during the previous record-breaking heat wave in 1994 (265% vs. 240%). Excess mortality was comparable among the younger age group (0-64 years) and the elderly (65+ years) in the 1994 major heat wave while it was significantly larger among the elderly in 2015. The results suggest that the total heat load of a heat wave needs to be considered when assessing its impact on mortality, as the cumulative excess heat factor explains the magnitude of excess mortality during a heat wave better than other characteristics such as duration or average daily mean temperature during the heat wave. Comparison of the mortality impacts of the 2015 and 1994 major heat waves suggests that the recently reported decline in overall heat-related mortality in Central Europe has abated and simple extrapolation of the trend would lead to biased conclusions even for the near future. Further research is needed toward understanding the additional mitigation measures required to prevent heat-related mortality in the Czech Republic and elsewhere.

Spatial synoptic classification (SSC) is here first employed in assessing heat-related mortality and morbidity in Central Europe. It is applied for examining links between weather patterns and cardiovascular (CVD) mortality and morbidity in an extended summer season (16 May-15 September) during 1994-2009. As in previous studies, two SSC air masses (AMs)-dry tropical (DT) and moist tropical (MT)-are associated with significant excess CVD mortality in Prague, while effects on CVD hospital admissions are small and insignificant. Excess mortality for ischaemic heart diseases is more strongly associated with DT, while MT has adverse effect especially on cerebrovascular mortality. Links between the oppressive AMs and excess mortality relate also to conditions on previous days, as DT and MT occur in typical sequences. The highest CVD mortality deviations are found 1 day after a hot spell's onset, when temperature as well as frequency of the oppressive AMs are highest. Following this peak is typically DT- to MT-like weather transition, characterized by decrease in temperature and increase in humidity. The transition between upward (DT) and downward (MT) phases is associated with the largest excess CVD mortality, and the change contributes to the increased and more lagged effects on cerebrovascular mortality. The study highlights the importance of critically evaluating SSC's applicability and benefits within warning systems relative to other synoptic and epidemiological approaches. Only a subset of days with the oppressive AMs is associated with excess mortality, and regression models accounting for possible meteorological and other factors explain little of the mortality variance.