ArticlePhilosophical transactions of the Royal Society of London. Series B, Biological sciences2019
Mosquito and primate ecology predict human risk of yellow fever virus spillover in Brazil.
Article in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 2 of them syntheses that pooled it.
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Who cites it
32 citing papers in PubMed, 2 syntheses or guidelines pooled it, 59 citations in OpenAlex.
- A systematic review of the data, methods and environmental covariates used to map Aedes-borne arbovirus transmission risk.BMC infectious diseases · 2023Pooled it
- Are we overestimating risk of enteric pathogen spillover from wild birds to humans?Biological reviews of the Cambridge Philosophical Society · 2020Pooled it
- Drought dynamics explain once in a century yellow fever virus outbreak in Brazil with implications for climate change.Science advances · 2026Article
- Bioinformatics-driven genome-wide identification of viral miRNAs in high spillover bat coronaviruses and their target genes in human.Archives of microbiology · 2026Article
- RNA virome comparison between sylvatic and urban-interface mosquitoes from Southeastern Brazil.Frontiers in cellular and infection microbiology · 2026Article
- Challenges for the effectiveness of infectious disease interventions during global change.Communications health · 2026Article
- Ecological suitability of Japanese encephalitis virus in Australia: A modelling analysis of vector-host transmission dynamics to potential spillover in humans.PLoS neglected tropical diseases · 2025Article
- Predictability of infectious disease outbreak severity: Chikungunya as a case study.Science advances · 2025Article
- Why the growth of arboviral diseases necessitates a new generation of global risk maps and future projections.PLoS computational biology · 2025Article
- Advancements and Challenges in Addressing Zoonotic Viral Infections with Epidemic and Pandemic Threats.Viruses · 2025Review
- Article
- Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil.PLOS global public health · 2024Article
- Weekly Forecasting of Yellow Fever Occurrence and Incidence via Eco-Meteorological Dynamics.GeoHealth · 2023Article
- Ecological drivers of sustained enzootic yellow fever virus transmission in Brazil, 2017-2021.PLoS neglected tropical diseases · 2023Article
- Occurrence of yellow fever outbreaks in a partially vaccinated population: An analysis of the effective reproduction number.PLoS neglected tropical diseases · 2022Article
- Zoonotic malaria transmission and land use change in Southeast Asia: what is known about the vectors.Malaria journal · 2022Review
- Environmental determinants predicting population vulnerability to high yellow fever incidence.Royal Society open science · 2022Article
- Reemergence of yellow fever virus in southeastern Brazil, 2017-2018: What sparked the spread?PLoS neglected tropical diseases · 2022Article
- Ecological and environmental factors affecting transmission of sylvatic yellow fever in the 2017-2019 outbreak in the Atlantic Forest, Brazil.Parasites & vectors · 2022Article
- Mapping environmental suitability of Haemagogus and Sabethes spp. mosquitoes to understand sylvatic transmission risk of yellow fever virus in Brazil.PLoS neglected tropical diseases · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Many (re)emerging infectious diseases in humans arise from pathogen spillover from wildlife or livestock, and accurately predicting pathogen spillover is an important public health goal. In the Americas, yellow fever in humans primarily occurs following spillover from non-human primates via mosquitoes. Predicting yellow fever spillover can improve public health responses through vector control and mass vaccination. Here, we develop and test a mechanistic model of pathogen spillover to predict human risk for yellow fever in Brazil. This environmental risk model, based on the ecology of mosquito vectors and non-human primate hosts, distinguished municipality-months with yellow fever spillover from 2001 to 2016 with high accuracy (AUC = 0.72). Incorporating hypothesized cyclical dynamics of infected primates improved accuracy (AUC = 0.79). Using boosted regression trees to identify gaps in the mechanistic model, we found that important predictors include current and one-month lagged environmental risk, vaccine coverage, population density, temperature and precipitation. More broadly, we show that for a widespread human viral pathogen, the ecological interactions between environment, vectors, reservoir hosts and humans can predict spillover with surprising accuracy, suggesting the potential to improve preventive action to reduce yellow fever spillover and avert onward epidemics in humans. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
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