ArticleOxford open immunology2024
Climate change impacts on dengue transmission areas in Espírito Santo state, Brazil.
Article in Oxford open immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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.
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.
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Who cites it
2 citing papers in PubMed.
- Emergence of Oropouche Virus in Espírito Santo State, Brazil, 2024.Emerging infectious diseases · 2025Article
- A State-of-the-Science Review of Long-Term Predictions of Climate Change Impacts on Dengue Transmission Risk.Environmental health perspectives · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Espírito Santo state, in Brazil, is a dengue-endemic region predicted to suffer from an increase in temperature and drought due to climate change, which could affect the areas with active dengue virus transmission. The study objective was modeling climatic factors and climate change effects in zones suitable for dengue virus transmission in Espírito Santo state, Brazil. Data on dengue reports from 2022 were used to determine climatic variables related to spatial distribution. The climate change projections were generated for the 2030s, 2050s, 2070s, and 2090s for three distinct Shared Socioeconomic Pathways: SSP1-2.6, SSP2-4.5 and SSP5-8.5. A maximum entropy algorithm was used to construct the three models and projections, and the results were used to calculate the ensemble mean. Isothermality, the maximum temperature of the warmest month, precipitation of the wettest month, precipitation of the warmest quarter, and annual precipitation impacted the model. Projections indicated a change in areas suitable for dengue virus transmission, varying from -30.44% in the 2070s (SSP1-2.6) to +13.07% in the 2070s (SSP5-8.5) compared to 2022. The coastal regions were consistently suitable in all scenarios. Urbanized and highly populated areas were predicted to persist with active dengue transmission in Espírito Santo state, posing challenges for public health response.
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