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Cited by 1,347Climate Change and Health ImpactsThermoregulation and physiological responsesAir Quality and Health Impacts

The burden of heat-related mortality attributable to recent human-induced climate change

Open access
Vicedo-Cabrera, A. M., Scovronick, N., Sera, F., Royé, D., Schneider, R., Tobias, A., Astrom, C., Guo, Y. +62 more·2021·Nature Climate Change
DOI 10.1038/s41558-021-01058-xPMC PMC7611104
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Abstract

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. Current and future climate change is expected to impact human health, both indirectly and directly, through increasing temperatures. Climate change has already had an impact and is responsible for 37% of warm-season heat-related deaths between 1991 and 2018, with increases in mortality observed globally.

Integrity signals

Registry

Crossref · 10.1038/s41558-021-01058-x

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

10 of 15 cited sources checked · 8 supported · 0 flagged · accuracy not yet measured

  • Premisecitation

    Detection and attribution studies seldom estimate the associated human health impacts.

    “These studies are often conducted in the climate science disciplines and rarely take the additional step of estimating associated human health impacts9–11.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [9] Ebi, K. L., Ogden, N. H., Semenza, J. C. & Woodward, A. Detecting and attributing health burdens to climate change. Environ. Health Perspect. 125, 085004 (2017). source
    • cites [10] Mitchell, D. et al. Attributing human mortality during extreme heat waves to anthropogenic climate change. Environ. Res. Lett. 11, 074006 (2016). source
    • cites [11] Christidis, N., Mitchell, D. & Stott, P. A. Anthropogenic climate change and heat effects on health. Int. J. Climatol. 39, 4751–4768 (2019). source
  • Findingown data

    In the counterfactual scenario, heat-related mortality averaged 0.98% (95% CI 0.26-1.80) of all warm-season deaths across all locations.

    “there was less heat-related mortality in all countries under the counterfactual scenario, with an average estimate of 0.98% (95% CI, 0.26–1.80) across all locations.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.
  • Findingown data

    Attributable mortality was evident on every inhabited continent represented in the study.

    “increased mortality is evident on every continent”
    • Also stated in: § Heat-mortality impacts attributed to climate change · plain
      “Impacts were evident in all of our study countries, which included locations on every inhabited continent”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.
  • Findingown data

    Country-specific average temperature increases ranged from about 0.5°C in Argentina to more than 1°C in Iran, Kuwait, parts of South and Central America, and northern Europe.

    “the country-specific average temperature increase ranged from ~0.5 °C in Argentina to >1 °C in Iran, Kuwait, some countries in South and Central America and North of Europe”
    Quote in the paperNot a substantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.
  • Findingown data

    The population-level burden of heat-related deaths attributable to human-induced climate change was relatively heavy in southern and eastern Europe, where several countries had rates above 6 per 100,000 over 1991-2018 versus a study average of 2.2 per 100,000.

    “indicating a relatively heavy population-level burden in southern and eastern Europe, where rates in several countries are >6 per 100,000 population over the 1991–2018 period compared to the study average of 2.2 per 100,000.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.
  • Classified as probably not a substantial claim. 6
  • The quote only partly states this claim. 2
  • May combine two claims. 12

  • Classified as probably not a substantial claim. The quote only partly states this claim.

    Study design and conductcitation

    Temperature series were bias-corrected using local weather station data following a published method.

    “Location-specific temperature series were extracted from the gridded products on the basis of the corresponding centroid and bias-corrected following a method described elsewhere19.”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [19] Hempel, S., Frieler, K., Warszawski, L., Schewe, J. & Piontek, F. A trend-preserving bias correction—the ISI-MIP approach. Earth Syst. Dynam. 4, 219–236 (2013). source

      Section 3 describes a method for bias-correcting simulated temperature series against observations. The Observations section identifies the reference as WATCH Forcing Data, a gridded observational dataset, not local weather-station data. The citing sentence itself attributes the correction method—not the use of station data—to this source. (LLM, conf=0.88)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    DAMIP is designed to assess individual contributions of external factors to past and future changes in global and regional climate.

    “DAMIP is part of the CMIP6 and was specifically designed to allow for the assessment of the individual contributions of various external factors to past and future changes in global and regional climate17,18.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [17] Gillett, N. P. et al. The detection and attribution model intercomparison project (DAMIP v1.0) contribution to CMIP6. Geosci. Model Dev. 9, 3685–3697 (2016). source
    • cites [18] Gillett, N. P. et al. Constraining human contributions to observed warming since preindustrial. Nat. Clim. Change 11, 207–212 (2021). source

      The ‘Attribution of global mean temperature changes’ section identifies DAMIP as part of CMIP6 and describes experiments separating historical natural, aerosol, and greenhouse-gas forcings. It supports assessing individual contributions to past global temperature change, but does not establish the claimed design purpose for future changes or regional climate. Page numbers are unavailable in our copy. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    Model choices for the cross-basis and control terms were based on related studies from the MCC Collaborative Research Network.

    “These choices that specify the cross-basis and model terms used to control for long-term and seasonal trends were based on related studies from the MCC Collaborative Research Network20,24.”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [20] Gasparrini, A. et al. Changes in susceptibility to heat during the summer: a multicountry analysis. Am. J. Epidemiol. 183, 1027–1036 (2016). source
    • cites [24] Gasparrini, A. et al. Temporal variation in heat-mortality associations: a multicountry study. Environ. Health Perspect. 123, 1200–1207 (2015). source

  • May combine two claims.

    Premisecitation

    Heat-related mortality risks tend to appear soon after exposure and vanish within 10 days.

    “Prior research has demonstrated that heat risks tend to occur quickly after exposure and then disappear within 10 d (ref. 20).”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [20] Gasparrini, A. et al. Changes in susceptibility to heat during the summer: a multicountry analysis. Am. J. Epidemiol. 183, 1027–1036 (2016). source

  • May combine two claims.

    Premisecitation

    Exposure to high outdoor temperatures is linked to illness and a higher risk of premature death.

    “An immediate and direct impact of climate change is through human exposure to high outdoor temperatures, which is associated with morbidity and an increased risk of premature death (mortality)2–4.”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [2] Gasparrini, A. et al. Mortality risk attributable to high and low ambient temperature: a multicountry observational study. Lancet 386, 369–375 (2015). source
    • cites [3] Hsiang, S. et al. Estimating economic damage from climate change in the United States. Science 356, 1362–1369 (2017). source
    • cites [4] Ye, X. et al. Ambient temperature and morbidity: a review of epidemiological evidence. Environ. Health Perspect. 120, 19–28 (2012). source

  • May combine two claims.

    Findingown data

    Country-specific heat-related mortality fractions in the factual scenario ranged from below 1% (e.g., USA, Colombia, Sweden, Norway, UK, Japan, South Korea) to above 5% in Southern Europe.

    “The country-specific estimates ranged from <1% (for example, the USA, Colombia, Sweden, Norway, UK, Japan and South Korea) to >5% in countries of Southern Europe”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.

  • May combine two claims.

    Findingown data

    The average temperature difference between factual and counterfactual scenarios over 1991-2018 was about 0.8°C, with strong regional variation.

    “Warming is also reflected in the overall temperature difference between scenarios over the study period (1991–2018), with ~0.8 °C increase on average and strong differences across regions of the world”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.

  • May combine two claims.

    Findingown data

    Across the 732 locations, average warm-season temperature in the factual scenario rose from about 21.5°C at the end of the twentieth century to nearly 23°C in the 2010s, while the counterfactual scenario stayed near 21.5°C.

    “Across the 732 locations, the annual average temperature in the warm season in the factual scenario increased from nearly 21.5 °C at the end of the twentieth century to almost 23 °C in the 2010s, whereas in the counterfactual scenario, annual temperatures remained relatively stable at around 21.5 °C”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.

  • May combine two claims.

    Findingown data

    The overall attributable fraction of 0.58% (95% CI 0.24-1.14) of all warm-season deaths corresponds to an average of 9,702 (95% CI 4,005-19,135) deaths across the 732 locations.

    “The overall estimate that 0.58% (95% CI: 0.24–1.14) of all warm-season deaths are attributable to climate change translates to an average of 9,702 (95% CI, 4,005–19,135) deaths across the 732 locations”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.

  • May combine two claims.

    Findingown data

    Heat-related mortality risks at the 99th percentile temperature versus the optimum ranged from 0.97 to 2.47 across the 732 locations, with only 28 locations below 1.

    “Heat-related mortality risks ranged from 0.97 to 2.47 but with only 28 of the 732 locations <1.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Country-specific attributable deaths show a north-south pattern within regions, with less than 1% of total deaths in northern subregions of America, Europe and Asia and larger contributions in southern Europe, southern and western Asia, and some countries in southeast Asia and South America.

    “Country-specific estimates (Fig. 4b) show a clear north-south pattern within regions; human-induced climate change attributable deaths are <1% of total deaths for countries in northern subregions of America, Europe and Asia, while larger contributions were observed in southern Europe, southern and western Asia and some countries in southeast Asia and South America.”
    Quote in the paperNot a substantial claim
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.

  • May combine two claims.

    Findingown data

    Larger heat-related mortality risks occurred in Europe, especially Western and Central Europe, while most locations in Asia and the Americas had estimates below 1.5.

    “Larger risks are observed in the European region, in particular the Western and Central area of the continent, while smaller estimates <1.5 were found in most locations in Asia and the Americas.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. The quote only partly states this claim.

    Study design and conductown data

    Uncertainty was quantified by Monte Carlo simulation of 1,000 BLUP coefficient samples, with empirical confidence intervals accounting for exposure-response imprecision and model variability.

    “We obtained empirical confidence intervals corresponding to the 2.5th and 97.5th percentiles of the empirical distribution of the heat-related mortality impacts across coefficients and models.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Anthropogenic climate change is already producing non-trivial health burdens that are geographically widespread.

    “We have demonstrated that health burdens from anthropogenic climate change are occurring, are geographically widespread and are non-trivial”
    Quote in the paperSubstantial claim
    • The authors state this as an assumption: The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.
    • Rests on an assumption: The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.
    • The authors state this as an assumption: The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.

  • May combine two claims.

    Interpretationown data

    The dataset's broad and heterogeneous geographic coverage enabled assessment of spatial patterns and identification of disproportionately affected areas.

    “the wide and heterogeneous geographical scope of our dataset allowed us to assess spatial patterns in the estimated impacts and to identify areas that have already been disproportionately affected.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Several high-population regions have warmed by more than 2°C, while others have warmed relatively little.

    “several high-population regions have warmed by >2 °C, while others have experienced relatively little change1.”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [1] IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (WMO, 2018).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Global mean surface temperature is about 1°C above the pre-industrial level.

    “The world is now an average of ~1°C above the pre-industrial era”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [1] IPCC Special Report on Global Warming of 1.5 °C (eds Masson-Delmotte, V. et al.) (WMO, 2018).

      Couldn’t be matched to a paper in Crossref, so it can’t be checked.

17 of 17

  • The paper relies on this without support.

    No large-scale, systematic studies had already quantified the heat-related health impacts of climate change.

    “there have been no large-scale, systematic efforts to quantify the heat-related human health impacts that have already occurred due to climate change.”

  • The authors state this as an assumption.

    The counterfactual climate simulations, driven only by natural forcings, approximate a world without human-induced climate change.

    “a counterfactual scenario where climate simulations are driven by natural forcings only, thus approximating the climate that would have occurred in a world without human-induced or anthropogenic climate change16.”

  • The paper relies on this without support.

    The exposure-response functions estimated from observed data apply to the modelled temperature series under both scenarios.

    “we used the estimated exposure-response functions to compute the heat-related mortality burden between 1991 and 2018 for each location under two scenarios”

  • The authors state this as an assumption.

    The difference in heat-related mortality between factual and counterfactual scenarios represents the proportion of warm-season deaths attributable to human-induced climate change.

    “The difference between the factual and counterfactual scenarios is interpretable as the proportion of total deaths during the warm season attributable to human-induced climate change.”

  • The paper relies on this without support.

    The study is the largest attribution study so far on climate change health impacts.

    “To our knowledge, this is the largest attribution study to date on the health impacts of climate change.”

  • The paper relies on this without support.

    The MCC database is the largest consortium of weather and health data assembled so far.

    “The observed temperature and mortality data were collected through the Multi-Country Multi-City (MCC) Collaborative Research Network, the largest weather and health data consortium to date (https://mccstudy.lshtm.ac.uk).”
6 of 6

Cites

Flagged first, then by citations

2 of the 31 references couldn’t be matched to a known paper.

Research works printed but not linked: 1

  1. Cramer, W. et al. in IPCC Climate Change 2014: Impacts, Adaptation, and Vulnerability (eds Field, C. B. et al.) 979–1037 (Cambridge Univ. Press, 2014).

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Authors
Vicedo-Cabrera, A. M., Scovronick, N., Sera, F., Royé, D., Schneider, R., Tobias, A., Astrom, C., Guo, Y., Honda, Y., Hondula, D. M., Abrutzky, R., Tong, S., Coelho, M. D. S. Z. S., Saldiva, P. H. N., Lavigne, E., Correa, P. M., Ortega, N. V., Kan, H., Osorio, S., Kyselý, J., Urban, A., Orru, H., Indermitte, E., Jaakkola, J. J. K., Ryti, N., Pascal, M., Schneider, A., Katsouyanni, K., Samoli, E., Mayvaneh, F., Entezari, A., Goodman, P., Zeka, A., Michelozzi, P., de’Donato, F., Hashizume, M., Alahmad, B., Diaz, M. H., Valencia, C. D. L. C., Overcenco, A., Houthuijs, D., Ameling, C., Rao, S., Di Ruscio, F., Carrasco-Escobar, G., Seposo, X., Silva, S., Madureira, J., Holobaca, I. H., Fratianni, S., Acquaotta, F., Kim, H., Lee, W., Iniguez, C., Forsberg, B., Ragettli, M. S., Guo, Y. L. L., Chen, B. Y., Li, S., Armstrong, B., Aleman, A., Zanobetti, A., Schwartz, J., Dang, T. N., Dung, D. V., Gillett, N., Haines, A., Mengel, M., Huber, V., & Gasparrini, A.
Affiliations
  • University of Bern (CH)
  • Emory University (US)
  • London School of Hygiene & Tropical Medicine (GB)
  • Universidade de Santiago de Compostela (ES)
  • European Centre for Medium-Range Weather Forecasts (GB)
  • University of Tsukuba (JP)
  • Arizona State University (US)
  • Universidad de Buenos Aires (AR)
  • Queensland University of Technology (AU)
  • Universidade de São Paulo (BR)
  • Universidad de Los Andes, Chile (CL)
  • Fudan University (CN)
  • Czech University of Life Sciences Prague (CZ)
  • University of Tartu (EE)
  • Finnish Meteorological Institute (FI)
  • University of Oulu (FI)
  • Santé Publique France (FR)
  • National and Kapodistrian University of Athens (GR)
  • Hakim Sabzevari University (IR)
  • Technological University Dublin (IE)
  • Brunel University of London (GB)
  • Regione Lazio (IT)
  • The University of Tokyo (JP)
  • Harvard University (US)
  • Instituto Nacional de Salud Pública (MX)
  • National Institute for Public Health and the Environment (NL)
  • Norwegian Institute of Public Health (NO)
  • Kyoto University (JP)
  • National Institute of Health Dr. Ricardo Jorge (PT)
  • Universidade do Porto (PT)
  • University of Turin (IT)
  • Seoul National University (KR)
  • Umeå University (SE)
  • Swiss Tropical and Public Health Institute (CH)
  • National Health Research Institutes (TW)
  • Universidad de la República de Uruguay (UY)
  • University of Medicine and Pharmacy at Ho Chi Minh City (VN)
  • Environment and Climate Change Canada (CA)
  • European Space Agency (FR)
  • Potsdam Institute for Climate Impact Research (DE)
Corresponding author
  • Vicedo-Cabrera, A. M.
  • Gasparrini, A.
ORCID
Venue
Nature Climate Change
Publisher
Springer Science and Business Media LLC
Published
2021-05-31
Volume
11
Issue
6
Pages
492-500
ISSN
  • 1758-678X (ISSN-L)
  • 1758-6798
DOI
10.1038/s41558-021-01058-x
PMC
PMC7611104
OpenAlex
W3171801815
Semantic Scholar
54d26db7b47f4929e373af434772c36da4d5260a
Cited by
1,347
References
31
Citations by year
2026: 228 · 2025: 273 · 2024: 266 · 2023: 369 · 2022: 158 · 2021: 50 · 2019: 1 · 2018: 1
FWCI
83.55
Type
journal article
Language
en
Open access
Licence
Locations
  • Nature Climate Change (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
  • Bern Open Repository and Information System (University of Bern) (acceptedVersion, other-oa)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
  • Institutional Research Information System University of Turin (University of Turin) (submittedVersion, other-oa)
  • RePEc: Research Papers in Economics (submittedVersion)
  • BORIS (University Library Bern) (submittedVersion)
  • Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion, cc-by-nc-nd)
  • DIGITAL.CSIC (Spanish National Research Council (CSIC)) (submittedVersion)
  • edoc (University of Basel) (submittedVersion)
  • QUT ePrints (Queensland University of Technology) (submittedVersion)
  • Florence Research (University of Florence) (submittedVersion, cc-by-nc-nd)
  • Site cant be reached (submittedVersion, other-oa)
  • Publication Database PIK (Potsdam Institute for Climate Impact Research (PIK)) (submittedVersion)
  • PuSH - Publication Server of Helmholtz Zentrum München (submittedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion)
  • Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) (submittedVersion, cc-by)
  • Seoul National University Open Repository (Seoul National University) (submittedVersion)
  • Rivm (National Institute for Public Health and the Environment) (submittedVersion, other-oa)
Funders
  • Emory University
  • Harvard University
  • Arizona State University
  • Universität Basel
  • University of Ottawa
  • University of Bern
  • Environmental Restoration and Conservation Agency
  • Instituto de Investigaciones Gino Germani
  • European Space Agency
  • European Commission (820655, 310372, HORIZON2020)
  • Public Health Agency
  • Monash University
  • Queensland University of Technology
  • Grantová Agentura České Republiky (GA20-28560S)
  • Bundesministerium für Bildung und Forschung (01LS1201A2)
  • Seoul National University
  • Anhui Medical University
  • Fudan University
  • Universitat de València
  • Akademie Věd České Republiky
  • Università degli Studi di Firenze
  • University of Tokyo
  • Umeå Universitet
  • Shanghai Jiao Tong University
  • National and Kapodistrian University of Athens
  • Universidad de Buenos Aires
  • Universidade de São Paulo
  • Hakim Sabzevari University
  • Oulun Yliopisto
  • University of Tsukuba
  • Universidade do Porto
  • Nanjing Medical University
  • Tartu Ülikool
  • Technological University Dublin
  • Ministerio de Asuntos Económicos y Transformación Digital, Gobierno de España (PCIN-2017–046)
  • Universidade de Santiago de Compostela
  • MRC-PHE Centre for Environment and Health
  • Health Canada
  • Medical Research Council (MR/M022625/1, MR/S019669/1, MR/R013349/1)
  • Natural Environment Research Council (NE/R009384/1)
  • National Health and Medical Research Council (1163693, 1109193)
  • Fundação para a Ciência e a Tecnologia (SFRH/BPD/115112/2016)
  • Japan Science and Technology Agency (JPMJSC20E4)
  • Rijksinstituut voor Volksgezondheid en Milieu
  • School of Medicine, Shanghai Jiao Tong University
  • Helmholtz Zentrum München
  • School of Public Health, Imperial College London
  • Norwegian Institute of Public Health
  • National Institute of Environmental Health Sciences (P30ES019776)
  • Strategic International Collaborative Research Program (JPMJSC20E4)
Topics
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Climate Change and Health Impacts
  • Health Sciences › Medicine › Physiology › Thermoregulation and physiological responses
  • Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
Keywords
heat-related mortality, anthropogenic climate change, attributable mortality, anthropogenic warming, health impacts of climate change, climate change mitigation, climate change adaptation, global health burden

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