The DOI matches its Crossref record; 38 of the 38 references it cites were found in a registry or an index.
Quantifying excess deaths related to heatwaves under climate change scenarios: A multicountry time series modelling study
Open accessAbstract
BACKGROUND: Heatwaves are a critical public health problem. There will be an increase in the frequency and severity of heatwaves under changing climate. However, evidence about the impacts of climate change on heatwave-related mortality at a global scale is limited. METHODS AND FINDINGS: We collected historical daily time series of mean temperature and mortality for all causes or nonexternal causes, in periods ranging from January 1, 1984, to December 31, 2015, in 412 communities within 20 countries/regions. We estimated heatwave-mortality associations through a two-stage time series design. Current and future daily mean temperature series were projected under four scenarios of greenhouse gas emissions from 1971-2099, with five general circulation models. We projected excess mortality in relation to heatwaves in the future under each scenario of greenhouse gas emissions, with two assumptions for adaptation (no adaptation and hypothetical adaptation) and three scenarios of population change (high variant, median variant, and low variant). Results show that, if there is no adaptation, heatwave-related excess mortality is expected to increase the most in tropical and subtropical countries/regions (close to the equator), while European countries and the United States will have smaller percent increases in heatwave-related excess mortality. The higher the population variant and the greenhouse gas emissions, the higher the increase of heatwave-related excess mortality in the future. The changes in 2031-2080 compared with 1971-2020 range from approximately 2,000% in Colombia to 150% in Moldova under the highest emission scenario and high-variant population scenario, without any adaptation. If we considered hypothetical adaptation to future climate, under high-variant population scenario and all scenarios of greenhouse gas emissions, the heatwave-related excess mortality is expected to still increase across all the countries/regions except Moldova and Japan. However, the increase would be much smaller than the no adaptation scenario. The simple assumptions with respect to adaptation as follows: no adaptation and hypothetical adaptation results in some uncertainties of projections. CONCLUSIONS: This study provides a comprehensive characterisation of future heatwave-related excess mortality across various regions and under alternative scenarios of greenhouse gas emissions, different assumptions of adaptation, and different scenarios of population change. The projections can help decision makers in planning adaptation and mitigation strategies for climate change.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
(2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781107415379 · Cited by 11,249
The representative concentration pathways: an overview
van Vuuren, D. P., Edmonds, J., Kainuma, M., Riahi, K., Thomson, A., Hibbard, K., Hurtt, G. C., Kram, T., Krey, V., Lamarque, J.-F., et al. (2011) · Climatic Change · doi:10.1007/s10584-011-0148-z · Cited by 7,741
More Intense, More Frequent, and Longer Lasting Heat Waves in the 21st Century
Meehl, G. A., & Tebaldi, C. (2004) · Science · doi:10.1126/science.1098704 · Cited by 4,322
(2014) · Cambridge University Press eBooks · doi:10.1017/cbo9781107415386 · Cited by 4,056
Impact of regional climate change on human health
Patz, J. A., Campbell-Lendrum, D., Holloway, T., & Foley, J. A. (2005) · Nature · doi:10.1038/nature04188 · Cited by 3,103
Managing the health effects of climate change
Costello, A., Abbas, M., Allen, A., Ball, S., Bell, S., Bellamy, R., Friel, S., Groce, N., Johnson, A., Kett, M., et al. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60935-1 · Cited by 3,102
Mortality risk attributable to high and low ambient temperature: a multicountry observational study
Gasparrini, A., Guo, Y., Hashizume, M., Lavigne, E., Zanobetti, A., Schwartz, J., Tobias, A., Tong, S., Rocklöv, J., Forsberg, B., et al. (2015) · The Lancet · doi:10.1016/s0140-6736(14)62114-0 · Cited by 2,965
Self-citationDeath toll exceeded 70,000 in Europe during the summer of 2003
Robine, J.-M., Cheung, S. L. K., Le Roy, S., Van Oyen, H., Griffiths, C., Michel, J.-P., & Herrmann, F. R. (2007) · Comptes Rendus. Biologies · doi:10.1016/j.crvi.2007.12.001 · Cited by 2,127 · cited 1×
“example, the European heatwaves in the summer of 2003 were responsible for the deaths of tens of thousands of people [10].”
BackgroundBouchama, A., & Knochel, J. P. (2002) · New England Journal of Medicine · doi:10.1056/nejmra011089 · Cited by 1,898
The Effects of Climate Change on Cardiac Health
De Blois, J., Kjellstrom, T., Agewall, S., Ezekowitz, J. A., Armstrong, P. W., & Atar, D. (2015) · Cardiology · doi:10.1159/000398787 · Cited by 1,697
Cited by
Hot weather and heat extremes: health risks
Ebi, K. L., Capon, A., Berry, P., Broderick, C., de Dear, R., Havenith, G., Honda, Y., Kovats, R. S., Ma, W., Malik, A., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)01208-3 · Cited by 2,172
Self-citationZhao, Q., Guo, Y., Ye, T., Gasparrini, A., Tong, S., Overcenco, A., Urban, A., Schneider, A., Entezari, A., Vicedo-Cabrera, A. M., et al. (2021) · The Lancet Planetary Health · doi:10.1016/s2542-5196(21)00081-4 · Cited by 984
Self-citationCheng, J., Xu, Z., Bambrick, H., Prescott, V., Wang, N., Zhang, Y., Su, H., Tong, S., & Hu, W. (2019) · Environmental Research · doi:10.1016/j.envres.2019.108610 · Cited by 334
Self-citationVanos, J., Guzman-Echavarria, G., Baldwin, J. W., Bongers, C., Ebi, K. L., & Jay, O. (2023) · Nature Communications · doi:10.1038/s41467-023-43121-5 · Cited by 206
Self-citationLow-count whole-body PET with deep learning in a multicenter and externally validated study
Chaudhari, A. S., Mittra, E., Davidzon, G. A., Gulaka, P., Gandhi, H., Brown, A., Zhang, T., Srinivas, S., Gong, E., Zaharchuk, G., et al. (2021) · npj Digital Medicine · doi:10.1038/s41746-021-00497-2 · Cited by 83
Metadata
- Authors
- Guo, Y., Gasparrini, A., Li, S., Sera, F., Vicedo-Cabrera, A. M., de Sousa Zanotti Stagliorio Coelho, M., Saldiva, P. H. N., Lavigne, E., Tawatsupa, B., Punnasiri, K., Overcenco, A., Correa, P. M., Ortega, N. V., Kan, H., Osorio, S., Jaakkola, J. J. K., Ryti, N. R. I., Goodman, P. G., Zeka, A., Michelozzi, P., Scortichini, M., Hashizume, M., Honda, Y., Seposo, X., Kim, H., Tobias, A., Íñiguez, C., Forsberg, B., Åström, D. O., Guo, Y. L., Chen, B.-Y., Zanobetti, A., Schwartz, J., Dang, T. N., Van, D. D., Bell, M. L., Armstrong, B., Ebi, K. L., & Tong, S.
- Venue
- PLOS Medicine
- Publisher
- Public Library of Science (PLoS)
- Published
- 2018-07-31
- Volume
- 15
- Issue
- 7
- Pages
- e1002629
- ISSN
- 1549-1277 (ISSN-L)
- 1549-1676
- OpenAlex
- W2885527392
- Cited by
- 434
- References
- 38
- FWCI
- 17.02
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Quantifying excess deaths related to heatwaves under climate change scenarios: A multicountry time series modelling study. https://app.cochat.ai/papers/10.1371/journal.pmed.1002629
- The paper
- Guo, Y., Gasparrini, A., Li, S., Sera, F., Vicedo-Cabrera, A. M., de Sousa Zanotti Stagliorio Coelho, M., Saldiva, P. H. N., Lavigne, E., Tawatsupa, B., Punnasiri, K., Overcenco, A., Correa, P. M., Ortega, N. V., Kan, H., Osorio, S., Jaakkola, J. J. K., Ryti, N. R. I., Goodman, P. G., Zeka, A., . . . Tong, S. (2018). Quantifying excess deaths related to heatwaves under climate change scenarios: A multicountry time series modelling study. PLOS Medicine. https://doi.org/10.1371/journal.pmed.1002629
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.