Understanding transmission risk and predicting environmental suitability for Mayaro Virus in Central and South America.


Journal

PLoS neglected tropical diseases
ISSN: 1935-2735
Titre abrégé: PLoS Negl Trop Dis
Pays: United States
ID NLM: 101291488

Informations de publication

Date de publication:
Jan 2024
Historique:
received: 10 06 2023
accepted: 12 12 2023
medline: 9 1 2024
pubmed: 9 1 2024
entrez: 9 1 2024
Statut: epublish

Résumé

Mayaro virus (MAYV) is a mosquito-borne Alphavirus that is widespread in South America. MAYV infection often presents with non-specific febrile symptoms but may progress to debilitating chronic arthritis or arthralgia. Despite the pandemic threat of MAYV, its true distribution remains unknown. The objective of this study was to clarify the geographic distribution of MAYV using an established risk mapping framework. This consisted of generating evidence consensus scores for MAYV presence, modeling the potential distribution of MAYV in select countries across Central and South America, and estimating the population residing in areas suitable for MAYV transmission. We compiled a georeferenced compendium of MAYV occurrence in humans, animals, and arthropods. Based on an established evidence consensus framework, we integrated multiple information sources to assess the total evidence supporting ongoing transmission of MAYV within each country in our study region. We then developed high resolution maps of the disease's estimated distribution using a boosted regression tree approach. Models were developed using nine climatic and environmental covariates that are related to the MAYV transmission cycle. Using the output of our boosted regression tree models, we estimated the total population living in regions suitable for MAYV transmission. The evidence consensus scores revealed high or very high evidence of MAYV transmission in several countries including Brazil (especially the states of Mato Grosso and Goiás), Venezuela, Peru, Trinidad and Tobago, and French Guiana. According to the boosted regression tree models, a substantial region of South America is suitable for MAYV transmission, including north and central Brazil, French Guiana, and Suriname. Some regions (e.g., Guyana) with only moderate evidence of known transmission were identified as highly suitable for MAYV. We estimate that approximately 58.9 million people (95% CI: 21.4-100.4) in Central and South America live in areas that may be suitable for MAYV transmission, including 46.2 million people (95% CI: 17.6-68.9) in Brazil. Our results may assist in prioritizing high-risk areas for vector control, human disease surveillance and ecological studies.

Identifiants

pubmed: 38194417
doi: 10.1371/journal.pntd.0011859
pii: PNTD-D-23-00724
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0011859

Informations de copyright

Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Déclaration de conflit d'intérêts

The authors have declared that no competing interests exist.

Auteurs

Michael Celone (M)

Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, F. Edward Hébert School of Medicine, Bethesda, Maryland, United States of America.

Sean Beeman (S)

Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, F. Edward Hébert School of Medicine, Bethesda, Maryland, United States of America.

Barbara A Han (BA)

Cary Institute of Ecosystem Studies, Millbrook, New York, United States of America.

Alexander M Potter (AM)

One Health Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.
Walter Reed Biosystematics Unit, Smithsonian Museum Support Center, Suitland, Maryland, United States of America.
Department of Entomology, Smithsonian Institution-National Museum of Natural History (NMNH), Washington, DC, United States of America.

David B Pecor (DB)

One Health Branch, Walter Reed Army Institute of Research, Silver Spring, Maryland, United States of America.
Walter Reed Biosystematics Unit, Smithsonian Museum Support Center, Suitland, Maryland, United States of America.
Department of Entomology, Smithsonian Institution-National Museum of Natural History (NMNH), Washington, DC, United States of America.

Bernard Okech (B)

Department of Preventive Medicine & Biostatistics, Uniformed Services University of the Health Sciences, F. Edward Hébert School of Medicine, Bethesda, Maryland, United States of America.

Simon Pollett (S)

Infectious Disease Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.
Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, Maryland, United States of America.

Classifications MeSH