ArticleBMJ global health2025
Global, regional and national burden of chikungunya: force of infection mapping and spatial modelling study.
Article in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed.
- New article types atBMJ global health · 2026Article
- Article
- Recent advances in machine learning and Bayesian modeling for tropical disease prediction, diagnosis, and risk analysis: a scoping review.BMC infectious diseases · 2026Article
- Expert Recommendations to Strengthen Chikungunya Outbreak Surveillance and Reporting for Traveler Health Protection.The American journal of tropical medicine and hygiene · 2026Article
- Methods for estimating the burden of acute tropical infectious diseases: A scoping review.PLoS neglected tropical diseases · 2026Article
- Overview of Chikungunya Virus Pathogenesis, Genome Variation, Epidemiology, and Control.Virus research · 2026Review
- Predicting the global risk of chikungunya virus under climate change using ensemble species distribution models.Frontiers in cellular and infection microbiology · 2026Article
- Age-specific chikungunya outbreak response immunisation strategies in Brazil: a modelling study.EClinicalMedicine · 2025Article
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17 authors.
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Abstract
introductionChikungunya virus, an arbovirus transmitted by
methodsWe used a random forest model to predict force of infection and estimate chikungunya burden at high spatial resolution (5×5 km) using covariates from climatic, socioeconomic and ecological domains. We used a focal scenario to estimate the observed burden (lower bound) and an at-risk scenario to estimate the potential burden (upper bound) of chikungunya transmission.
resultsWe predicted global long-term average annual force of infection at 0.012 (95% UI: 0.007 to 0.019) for focal scenario and 0.013 (95% UI: 0.005 to 0.03) for at-risk scenario in 103 countries. We estimated global chikungunya burden annually of 14.4 million (95% UI: 11.0 to 17.8 million) infections and 0.96 million (95% UI: 0.56 to 1.6 million) disability-adjusted life years (DALYs) in the focal scenario, and 34.9 million infections (95% UI: 26.7 to 43.1 million) and 2.3 million DALYs (95% UI: 1.4 to 3.8 million) in the at-risk scenario for 2020. The chronic phase accounts for 54% of chikungunya burden, with relatively higher burden among 40-60-year-old population, with mortality disproportionately affecting children under 10 and adults over 80.
conclusionWhile chikungunya transmission has high geographical uncertainty, high force of infection is not limited to tropical regions and is distributed across all continents. Our estimates of chikungunya burden are useful for prioritisation of regions and target age groups for chikungunya vaccine introduction.
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