MétaCan
Menu
Back to cohort
Record W2769759576 · doi:10.1016/s2542-5196(17)30156-0

Projections of temperature-related excess mortality under climate change scenarios

2017· article· en· W2769759576 on OpenAlexaff
Antonio Gasparrini, Yuming Guo, Francesco Sera, Ana M. Vicedo‐Cabrera, Veronika Huber, Shilu Tong, Micheline de Sousa Zanotti Stagliorio Coêlho, Paulo Hilário Nascimento Saldiva, Éric Lavigne, Patricia Matus Correa, Nicolás Valdés Ortega, Haidong Kan, Samuel Osorio, Jan Kyselý, Aleš Urban, Jouni J. K. Jaakkola, Niilo Ryti, Mathilde Pascal, Ariana Zeka, Paola Michelozzi, Matteo Scortichini, Masahiro Hashizume, Yasushi Honda, Magali Hurtado‐Díaz, César De la Cruz Valencia, Xerxes Seposo, Ho Kim, Aurelio Tobı́as, Carmen Íñiguez, Bertil Forsberg, Daniel Oudin Åström, Martina S. Ragettli, Yue Leon Guo, Chang‐Fu Wu, Antonella Zanobetti, Joel Schwartz, Michelle L. Bell, Trần Ngọc Đăng, Clare Heaviside, Sotiris Vardoulakis, Shakoor Hajat, Andy Haines, Ben Armstrong

Bibliographic record

VenueThe Lancet Planetary Health · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsUniversity of Ottawa
FundersNational Health and Medical Research CouncilMedical Research CouncilBundesministerium für Bildung und ForschungGrantová Agentura České RepublikyPaul Mellon Centre for Studies in British Art, Yale UniversityNational Health Research InstitutesNational Research FoundationMinistry of the Environment, Government of JapanYale UniversityNational Research Foundation of KoreaU.S. Environmental Protection Agency
KeywordsClimate changeRepresentative Concentration PathwaysTemperate climateEnvironmental scienceClimatologyGreenhouse gasGeographyMean radiant temperatureClimate modelPopulationExcess mortalityAtmospheric sciencesDemographyEcologyBiology

Abstract

fetched live from OpenAlex

BACKGROUND: Climate change can directly affect human health by varying exposure to non-optimal outdoor temperature. However, evidence on this direct impact at a global scale is limited, mainly due to issues in modelling and projecting complex and highly heterogeneous epidemiological relationships across different populations and climates. METHODS: We collected observed daily time series of mean temperature and mortality counts for all causes or non-external causes only, in periods ranging from Jan 1, 1984, to Dec 31, 2015, from various locations across the globe through the Multi-Country Multi-City Collaborative Research Network. We estimated temperature-mortality relationships through a two-stage time series design. We generated current and future daily mean temperature series under four scenarios of climate change, determined by varying trajectories of greenhouse gas emissions, using five general circulation models. We projected excess mortality for cold and heat and their net change in 1990-2099 under each scenario of climate change, assuming no adaptation or population changes. FINDINGS: Our dataset comprised 451 locations in 23 countries across nine regions of the world, including 85 879 895 deaths. Results indicate, on average, a net increase in temperature-related excess mortality under high-emission scenarios, although with important geographical differences. In temperate areas such as northern Europe, east Asia, and Australia, the less intense warming and large decrease in cold-related excess would induce a null or marginally negative net effect, with the net change in 2090-99 compared with 2010-19 ranging from -1·2% (empirical 95% CI -3·6 to 1·4) in Australia to -0·1% (-2·1 to 1·6) in east Asia under the highest emission scenario, although the decreasing trends would reverse during the course of the century. Conversely, warmer regions, such as the central and southern parts of America or Europe, and especially southeast Asia, would experience a sharp surge in heat-related impacts and extremely large net increases, with the net change at the end of the century ranging from 3·0% (-3·0 to 9·3) in Central America to 12·7% (-4·7 to 28·1) in southeast Asia under the highest emission scenario. Most of the health effects directly due to temperature increase could be avoided under scenarios involving mitigation strategies to limit emissions and further warming of the planet. INTERPRETATION: This study shows the negative health impacts of climate change that, under high-emission scenarios, would disproportionately affect warmer and poorer regions of the world. Comparison with lower emission scenarios emphasises the importance of mitigation policies for limiting global warming and reducing the associated health risks. FUNDING: UK Medical Research Council.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.029
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.177
GPT teacher head0.378
Teacher spread0.202 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations900
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueThe Lancet Planetary HealthSame topicClimate Change and Health ImpactsFrench-language works237,207