Evidence map›Paper›PMID 20435552›Full record

ArticleEnvironmental health perspectives2010

Modeling the effects of weather and climate change on malaria transmission.

Paul Edward Parham, Edwin Michael

Open access · diamondAbstract read
In one paragraph

Article in Environmental health perspectives, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 167 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
167citing papers in PubMed, 3 pooled it
9.5field-weighted citation impact, top 2% of its field
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

167 citing papers in PubMed, 3 syntheses or guidelines pooled it, 406 citations in OpenAlex.

  1. Association between temperature and malaria (1959-2019): a systematic review and meta-analysis.Archives of public health = Archives belges de sante publique · 2025
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  18. Climate Change Integration in Nursing Academic Curricula and Continuing Education: A Scoping Review.The Canadian journal of nursing research = Revue canadienne de recherche en sciences infirmieres · 2025
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107 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

2 authors at 2 institutions in 1 country.

Paul Edward ParhamDepartment of Infectious Disease Epidemiology, Grantham Institute for Climate Change, Imperial College London, London, United Kingdom. paul.parham@imperial.ac.uk
Edwin Michael
Committee on Climate Change · GBImperial College London · GB

Funding

Modeling lymphatic filariasis transmission and eradication in Papua New GuineaR01AI069387 · NIAID · UNIVERSITY OF NOTRE DAME · PI MICHAEL, EDWIN · 2007 to 2011
$773k
NIAID NIH HHS R01 AI069387NIAID NIH HHS R01 AI069387-01A1
6 · The paper itself

Abstract

backgroundIn recent years, the impact of climate change on human health has attracted considerable attention; the effects on malaria have been of particular interest because of its disease burden and its transmission sensitivity to environmental conditions.

objectivesWe investigated and illustrated the role that dynamic process-based mathematical models can play in providing strategic insights into the effects of climate change on malaria transmission.

methodsWe evaluated a relatively simple model that permitted valuable and novel insights into the simultaneous effects of rainfall and temperature on mosquito population dynamics, malaria invasion, persistence and local seasonal extinction, and the impact of seasonality on transmission. We illustrated how large-scale climate simulations and infectious disease systems may be modeled and analyzed and how these methods may be applied to predicting changes in the basic reproduction number of malaria across Tanzania.

resultsWe found extinction to be more strongly dependent on rainfall than on temperature and identified a temperature window of around 32-33 degrees C where endemic transmission and the rate of spread in disease-free regions is optimized. This window was the same for Plasmodium falciparum and P. vivax, but mosquito density played a stronger role in driving the rate of malaria spread than did the Plasmodium species. The results improved our understanding of how temperature shifts affect the global distribution of at-risk regions, as well as how rapidly malaria outbreaks take off within vulnerable populations.

conclusionsDisease emergence, extinction, and transmission all depend strongly on climate. Mathematical models offer powerful tools for understanding geographic shifts in incidence as climate changes. Nonlinear dependences of transmission on climate necessitates consideration of both changing climate trends and variability across time scales of interest.

Indexed as

Climate ChangeModels, BiologicalWeatherAnimalsAnophelesEnvironmental HealthHumansInsect VectorsMalariaMalaria, FalciparumMalaria, VivaxPopulation DynamicsSeasonsTanzania

Identifiers

PMID20435552
PMCPMC2866676
OpenAlexW1973313221

What OpenQuestion holds

Textmetadata
LicenceCC0
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.