ArticleEcoHealth2019
Predicting Yellow Fever Through Species Distribution Modeling of Virus, Vector, and Monkeys.
Article in EcoHealth, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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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
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 62 citations in OpenAlex.
- Trends in mosquito species distribution modeling: insights for vector surveillance and disease control.Parasites & vectors · 2023Pooled it
- Behavioral Flexibility and the Conservation Value of Howler Monkey Populations in Small Habitat Patches.American journal of primatology · 2026Article
- Entomo-virological investigation during the epizootic outbreak of sylvatic yellow fever in Rio Grande do Sul, Brazil, between 2021 and 2022Memorias do Instituto Oswaldo Cruz · 2026Article
- Spatial and social determinants of the 1857 yellow fever epidemic in Lisbon.PLoS neglected tropical diseases · 2026Article
- Population densities of black-and-gold howler monkeys (Alouatta caraya) in northeastern Argentina and the possible influence of a yellow fever outbreak.Primates; journal of primatology · 2026Article
- Ecology and environment predict spatially stratified risk of H5 highly pathogenic avian influenza clade 2.3.4.4b in wild birds across Europe.Scientific reports · 2025Article
- Fatal yellow fever among captive non-human primates in southern Colombia, 2025.Frontiers in veterinary science · 2025Article
- Potential effects of brown howler monkey extinction on dispersal services in fragmented forests void of large dispersers.Primates; journal of primatology · 2024Article
- Review
- Exploring environmental and climate features associated with yellow fever across space and time in the Brazilian Atlantic Forest biome.PloS one · 2024Article
- Weekly Forecasting of Yellow Fever Occurrence and Incidence via Eco-Meteorological Dynamics.GeoHealth · 2023Article
- Ecological, Genetic, and Phylogenetic Aspects of YFV 2017-2019 Spread in Rio de Janeiro State.Viruses · 2023Article
- Article
- An ecological niche model to predict the geographic distribution of Haemagogus janthinomys, Dyar, 1921 a yellow fever and Mayaro virus vector, in South America.PLoS neglected tropical diseases · 2022Article
- Environmental determinants predicting population vulnerability to high yellow fever incidence.Royal Society open science · 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
- Burden is in the eye of the beholder: Sensitivity of yellow fever disease burden estimates to modeling assumptions.Science advances · 2021Article
- Seasonal and inter-annual drivers of yellow fever transmission in South America.PLoS neglected tropical diseases · 2021Article
- Reemergence of Yellow Fever in Brazil: The Role of Distinct Landscape Fragmentation Thresholds.Journal of environmental and public health · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mapping yellow fever (YF) risk is often based on place of infection of human cases, whereas the circulation between nonhuman primates (NHP) and vectors is neglected. In 2008/2009, YF devastated NHP at the southern limit of the disease in the Americas. In view of the recent expansion of YF in Brazil, we modeled the environmental suitability for YF with data from 2008/2009 epizootic, the distribution of NHP (Alouatta spp.), and the mosquito (Haemagogus leucocelaenus) using the maximum entropy algorithm (Maxent) to define risk areas for YF and their main environmental predictors. We evaluated points of occurrence of YF based on dates of confirmed deaths of NHP in three periods, from October 2008 to: December 2008, March 2009, and June 2009. Variables with greatest influence on suitability for YF were seasonality in water vapor pressure (36%), distribution of NHP (32%), maximum wind speed (11%), annual mean rainfall (7%), and maximum temperature in the warmest month (5%). Models of early periods of the epizootic identified suitability for YF in localities that recorded NHP deaths only months later, demonstrating usefulness of the approach for predicting the disease spread. Our data supported influence of rainfall, air humidity, and ambient temperature on the distribution of epizootics. Wind was highlighted as a predicting variable, probably due to its influence on the dispersal of vectors infected with YF in fragmented landscapes. Further studies on the role of wind are necessary to improve our understanding of the occurrence of YF and other arboviruses and their dispersal in the landscape.
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Registered trials
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.