ArticleRoyal Society open science2025
Large-scale epidemiological modelling: scanning for mosquito-borne diseases spatio-temporal patterns in Brazil.
Article in Royal Society open science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Leveraging probabilistic forecasts for dengue preparedness and control: The 2024 Dengue Forecasting Sprint in Brazil.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Climate change and the global food chain: a catalyst for emerging infectious diseases?International journal of emergency medicine · 2025Review
- Large-scale epidemiological modelling: scanning for mosquito-borne diseases spatio-temporal patterns in Brazil.Royal Society open science · 2025Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
The influence of climate on mosquito-borne diseases like dengue and chikungunya is well established, but comprehensively tracking long-term spatial and temporal trends across large areas has been hindered by fragmented data and limited analysis tools. This study presents an unprecedented analysis, in terms of breadth, estimating the susceptible-infectious-recovered transmission parameters from incidence data in all 5570 municipalities in Brazil over 14 years (2010-2023) for both dengue and chikungunya. We describe the Episcanner computational pipeline, developed to estimate these parameters, producing a reusable dataset characterizing all dengue and chikungunya epidemics that have taken place in this period in Brazil. The analysis reveals new insights into the climate-epidemic nexus: we identify distinct geographical and temporal patterns of arbovirus disease incidence across Brazil, highlighting how climatic factors like temperature and precipitation influence the timing and intensity of dengue and chikungunya epidemics. The innovative Episcanner tool empowers researchers and public health officials to explore these patterns in detail, facilitating targeted interventions and risk assessments. This research offers the possibility of exploring the main characteristics of dengue and chikungunya epidemics and their geographical specificities linked to the effects of global temperature fluctuations such as those captured by the El Niño-Southern Oscillation index.
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Registered trials
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