Evidence map›Paper›PMID 30829832›Full record

ArticleEpidemiology (Cambridge, Mass.)2019

Hands-on Tutorial on a Modeling Framework for Projections of Climate Change Impacts on Health.

Ana M Vicedo-Cabrera, Francesco Sera, Antonio Gasparrini

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

74 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Waterborne diseases and climate change.Nature reviews. Microbiology · 2026
    Review
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  14. Skillful heat-related mortality forecasting during recent deadly European summers.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
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  16. Article
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14 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ana M Vicedo-CabreraFrom the Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Francesco SeraFrom the Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom.
Antonio GasparriniFrom the Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, London, United Kingdom.

Funding

Medical Research Council MR/M022625/1Medical Research Council MR/R013349/1
6 · The paper itself

Abstract

Reliable estimates of future health impacts due to climate change are needed to inform and contribute to the design of efficient adaptation and mitigation strategies. However, projecting health burdens associated to specific environmental stressors is a challenging task because of the complex risk patterns and inherent uncertainty of future climate scenarios. These assessments involve multidisciplinary knowledge, requiring expertise in epidemiology, statistics, and climate science, among other subjects. Here, we present a methodologic framework to estimate future health impacts under climate change scenarios based on a defined set of assumptions and advanced statistical techniques developed in time-series analysis in environmental epidemiology. The proposed methodology is illustrated through a step-by-step hands-on tutorial structured in well-defined sections that cover the main methodological steps and essential elements. Each section provides a thorough description of each step, along with a discussion on available analytical options and the rationale on the choices made in the proposed framework. The illustration is complemented with a practical example of study using real-world data and a series of R scripts included as Supplementary Digital Content; http://links.lww.com/EDE/B504, which facilitates its replication and extension on other environmental stressors, outcomes, study settings, and projection scenarios. Users should critically assess the potential modeling alternatives and modify the framework and R code to adapt them to their research on health impact projections.

Indexed as

Climate ChangeEnvironmental HealthModels, TheoreticalForecastingHumansRisk AssessmentUser-Computer Interface

Identifiers

PMID30829832
PMCPMC6533172

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.