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Could the Recent Zika Epidemic Have Been Predicted?

Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in t...

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Autores principales: Muñoz, Ángel G., Thomson, Madeleine C., Stewart-Ibarra, Anna M., Vecchi, Gabriel A., Chourio, Xandre, Nájera, Patricia, Moran, Zelda, Yang, Xiaosong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5506221/
https://www.ncbi.nlm.nih.gov/pubmed/28747901
http://dx.doi.org/10.3389/fmicb.2017.01291
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author Muñoz, Ángel G.
Thomson, Madeleine C.
Stewart-Ibarra, Anna M.
Vecchi, Gabriel A.
Chourio, Xandre
Nájera, Patricia
Moran, Zelda
Yang, Xiaosong
author_facet Muñoz, Ángel G.
Thomson, Madeleine C.
Stewart-Ibarra, Anna M.
Vecchi, Gabriel A.
Chourio, Xandre
Nájera, Patricia
Moran, Zelda
Yang, Xiaosong
author_sort Muñoz, Ángel G.
collection PubMed
description Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics.
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spelling pubmed-55062212017-07-26 Could the Recent Zika Epidemic Have Been Predicted? Muñoz, Ángel G. Thomson, Madeleine C. Stewart-Ibarra, Anna M. Vecchi, Gabriel A. Chourio, Xandre Nájera, Patricia Moran, Zelda Yang, Xiaosong Front Microbiol Microbiology Given knowledge at the time, the recent 2015–2016 zika virus (ZIKV) epidemic probably could not have been predicted. Without the prior knowledge of ZIKV being already present in South America, and given the lack of understanding of key epidemiologic processes and long-term records of ZIKV cases in the continent, the best related prediction could be carried out for the potential risk of a generic Aedes-borne disease epidemic. Here we use a recently published two-vector basic reproduction number model to assess the predictability of the conditions conducive to epidemics of diseases like zika, chikungunya, or dengue, transmitted by the independent or concurrent presence of Aedes aegypti and Aedes albopictus. We compare the potential risk of transmission forcing the model with the observed climate and with state-of-the-art operational forecasts from the North American Multi Model Ensemble (NMME), finding that the predictive skill of this new seasonal forecast system is highest for multiple countries in Latin America and the Caribbean during the December-February and March-May seasons, and slightly lower—but still of potential use to decision-makers—for the rest of the year. In particular, we find that above-normal suitable conditions for the occurrence of the zika epidemic at the beginning of 2015 could have been successfully predicted at least 1 month in advance for several zika hotspots, and in particular for Northeast Brazil: the heart of the epidemic. Nonetheless, the initiation and spread of an epidemic depends on the effect of multiple factors beyond climate conditions, and thus this type of approach must be considered as a guide and not as a formal predictive tool of vector-borne epidemics. Frontiers Media S.A. 2017-07-12 /pmc/articles/PMC5506221/ /pubmed/28747901 http://dx.doi.org/10.3389/fmicb.2017.01291 Text en Copyright © 2017 Muñoz, Thomson, Stewart-Ibarra, Vecchi, Chourio, Nájera, Moran and Yang. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Microbiology
Muñoz, Ángel G.
Thomson, Madeleine C.
Stewart-Ibarra, Anna M.
Vecchi, Gabriel A.
Chourio, Xandre
Nájera, Patricia
Moran, Zelda
Yang, Xiaosong
Could the Recent Zika Epidemic Have Been Predicted?
title Could the Recent Zika Epidemic Have Been Predicted?
title_full Could the Recent Zika Epidemic Have Been Predicted?
title_fullStr Could the Recent Zika Epidemic Have Been Predicted?
title_full_unstemmed Could the Recent Zika Epidemic Have Been Predicted?
title_short Could the Recent Zika Epidemic Have Been Predicted?
title_sort could the recent zika epidemic have been predicted?
topic Microbiology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5506221/
https://www.ncbi.nlm.nih.gov/pubmed/28747901
http://dx.doi.org/10.3389/fmicb.2017.01291
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