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Transmission risk of Oropouche fever across the Americas

BACKGROUND: Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile...

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Autores principales: Romero-Alvarez, Daniel, Escobar, Luis E., Auguste, Albert J., Del Valle, Sara Y., Manore, Carrie A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163756/
https://www.ncbi.nlm.nih.gov/pubmed/37149619
http://dx.doi.org/10.1186/s40249-023-01091-2
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author Romero-Alvarez, Daniel
Escobar, Luis E.
Auguste, Albert J.
Del Valle, Sara Y.
Manore, Carrie A.
author_facet Romero-Alvarez, Daniel
Escobar, Luis E.
Auguste, Albert J.
Del Valle, Sara Y.
Manore, Carrie A.
author_sort Romero-Alvarez, Daniel
collection PubMed
description BACKGROUND: Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. METHODS: To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. RESULTS: Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. CONCLUSIONS: Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01091-2.
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spelling pubmed-101637562023-05-07 Transmission risk of Oropouche fever across the Americas Romero-Alvarez, Daniel Escobar, Luis E. Auguste, Albert J. Del Valle, Sara Y. Manore, Carrie A. Infect Dis Poverty Research Article BACKGROUND: Vector-borne diseases (VBDs) are important contributors to the global burden of infectious diseases due to their epidemic potential, which can result in significant population and economic impacts. Oropouche fever, caused by Oropouche virus (OROV), is an understudied zoonotic VBD febrile illness reported in Central and South America. The epidemic potential and areas of likely OROV spread remain unexplored, limiting capacities to improve epidemiological surveillance. METHODS: To better understand the capacity for spread of OROV, we developed spatial epidemiology models using human outbreaks as OROV transmission-locality data, coupled with high-resolution satellite-derived vegetation phenology. Data were integrated using hypervolume modeling to infer likely areas of OROV transmission and emergence across the Americas. RESULTS: Models based on one-support vector machine hypervolumes consistently predicted risk areas for OROV transmission across the tropics of Latin America despite the inclusion of different parameters such as different study areas and environmental predictors. Models estimate that up to 5 million people are at risk of exposure to OROV. Nevertheless, the limited epidemiological data available generates uncertainty in projections. For example, some outbreaks have occurred under climatic conditions outside those where most transmission events occur. The distribution models also revealed that landscape variation, expressed as vegetation loss, is linked to OROV outbreaks. CONCLUSIONS: Hotspots of OROV transmission risk were detected along the tropics of South America. Vegetation loss might be a driver of Oropouche fever emergence. Modeling based on hypervolumes in spatial epidemiology might be considered an exploratory tool for analyzing data-limited emerging infectious diseases for which little understanding exists on their sylvatic cycles. OROV transmission risk maps can be used to improve surveillance, investigate OROV ecology and epidemiology, and inform early detection. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s40249-023-01091-2. BioMed Central 2023-05-06 /pmc/articles/PMC10163756/ /pubmed/37149619 http://dx.doi.org/10.1186/s40249-023-01091-2 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Romero-Alvarez, Daniel
Escobar, Luis E.
Auguste, Albert J.
Del Valle, Sara Y.
Manore, Carrie A.
Transmission risk of Oropouche fever across the Americas
title Transmission risk of Oropouche fever across the Americas
title_full Transmission risk of Oropouche fever across the Americas
title_fullStr Transmission risk of Oropouche fever across the Americas
title_full_unstemmed Transmission risk of Oropouche fever across the Americas
title_short Transmission risk of Oropouche fever across the Americas
title_sort transmission risk of oropouche fever across the americas
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10163756/
https://www.ncbi.nlm.nih.gov/pubmed/37149619
http://dx.doi.org/10.1186/s40249-023-01091-2
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