Evidence map›Paper›PMID 40966207›Full record

ArticlePLoS neglected tropical diseases2025

Climate change, urbanisation and transmission potential: Aedes aegypti mosquito projections forecast future arboviral disease hotspots in Brazil.

Katherine Heath, Lincoln Muniz Alves, Michael B Bonsall

Abstract read
In one paragraph

Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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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

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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

1 citing paper in PubMed.

  1. Review
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.

Katherine HeathBurnet Institute, Melbourne, Victoria, Australia.ORCID 0000-0002-4752-9732
Lincoln Muniz AlvesCentro de Ciência do Sistema Terrestre CCST, Instituto Nacional de Pesquisas Espaciais INPE, São José dos Campos, Brazil.
Michael B BonsallMathematical Ecology Research Group, Department of Biology, University of Oxford, Oxford, United Kingdom.

Funding

Biotechnology and Biological Sciences Research Council BB/M011224/1
6 · The paper itself

Abstract

backgroundClimate change and urban expansion pose significant challenges to controlling Aedes aegypti mosquito populations, a primary vector of arboviruses such as dengue, Zika, and chikungunya. This study aims assess how climate and anthropogenic factors will jointly shape Ae. aegypti densities in Brazil, which is crucial to forecasting transmission risks and informing public health strategies.

methodsThis study combined a biologically informed, stage-structured delay-differential equation model with climate and anthropogenic data. Climate projections from the Coupled Model Intercomparison Project Phase 6 under different Shared Socioeconomic Pathways (SSPs) were used to forecast future climate scenarios from 2024 to 2080. Boosted Regression Trees integrated anthropogenic factors like urbanisation, population growth, and urban accessibility. Model outputs were validated with entomological surveillance data, and the basic reproductive number for dengue fever was used to assess changes in disease transmission potential.

findingsOur findings predicted that Ae. aegypti mosquito density will increase nationally, but unevenly, exceeding thermal limits in North Brazil while rising substantially in the South and Southeast. Increases in density were particularly pronounced under high greenhouse gas emission scenario SSP5-8.5 (up to 92% in the Southeast). These trends were projected to elevate the transmission potential for dengue fever, with Southeast Brazil facing the biggest increases due to mosquito population growth outpacing human population expansion. Validation against historical data confirmed model robustness.

interpretationBy directly linking mosquito abundance to SSP-specific emissions trajectories, our results show that climate mitigation can markedly reduce disease risk. Shifting from SSP5-8.5 to SSP1-2.6 could cut projected mosquito density increases from 31% to 11% nationally by 2080. The model's spatial granularity and integration of local administrative boundaries support its utility for national and sub-national health planning. Addressing compounded risks in vulnerable peri-urban and rural populations will require coordinated interventions that span climate policy, vector control, and health equity.

Indexed as

AedesArbovirus InfectionsClimate ChangeMosquito VectorsUrbanizationAnimalsArbovirusesBrazilDengueForecastingHumansPopulation Density

Identifiers

PMID40966207
PMCPMC12445552

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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.