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Assessing real-time Zika risk in the United States
BACKGROUND: Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV’s low reporting rates and the geographic variability in suita...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415743/ https://www.ncbi.nlm.nih.gov/pubmed/28468671 http://dx.doi.org/10.1186/s12879-017-2394-9 |
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author | Castro, Lauren A. Fox, Spencer J. Chen, Xi Liu, Kai Bellan, Steven E. Dimitrov, Nedialko B. Galvani, Alison P. Meyers, Lauren Ancel |
author_facet | Castro, Lauren A. Fox, Spencer J. Chen, Xi Liu, Kai Bellan, Steven E. Dimitrov, Nedialko B. Galvani, Alison P. Meyers, Lauren Ancel |
author_sort | Castro, Lauren A. |
collection | PubMed |
description | BACKGROUND: Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV’s low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic. METHODS: We present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics. RESULTS: We assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk. CONCLUSIONS: This framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-017-2394-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5415743 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-54157432017-05-04 Assessing real-time Zika risk in the United States Castro, Lauren A. Fox, Spencer J. Chen, Xi Liu, Kai Bellan, Steven E. Dimitrov, Nedialko B. Galvani, Alison P. Meyers, Lauren Ancel BMC Infect Dis Research Article BACKGROUND: Confirmed local transmission of Zika Virus (ZIKV) in Texas and Florida have heightened the need for early and accurate indicators of self-sustaining transmission in high risk areas across the southern United States. Given ZIKV’s low reporting rates and the geographic variability in suitable conditions, a cluster of reported cases may reflect diverse scenarios, ranging from independent introductions to a self-sustaining local epidemic. METHODS: We present a quantitative framework for real-time ZIKV risk assessment that captures uncertainty in case reporting, importations, and vector-human transmission dynamics. RESULTS: We assessed county-level risk throughout Texas, as of summer 2016, and found that importation risk was concentrated in large metropolitan regions, while sustained ZIKV transmission risk is concentrated in the southeastern counties including the Houston metropolitan region and the Texas-Mexico border (where the sole autochthonous cases have occurred in 2016). We found that counties most likely to detect cases are not necessarily the most likely to experience epidemics, and used our framework to identify triggers to signal the start of an epidemic based on a policymakers propensity for risk. CONCLUSIONS: This framework can inform the strategic timing and spatial allocation of public health resources to combat ZIKV throughout the US, and highlights the need to develop methods to obtain reliable estimates of key epidemiological parameters. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12879-017-2394-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-05-04 /pmc/articles/PMC5415743/ /pubmed/28468671 http://dx.doi.org/10.1186/s12879-017-2394-9 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Castro, Lauren A. Fox, Spencer J. Chen, Xi Liu, Kai Bellan, Steven E. Dimitrov, Nedialko B. Galvani, Alison P. Meyers, Lauren Ancel Assessing real-time Zika risk in the United States |
title | Assessing real-time Zika risk in the United States |
title_full | Assessing real-time Zika risk in the United States |
title_fullStr | Assessing real-time Zika risk in the United States |
title_full_unstemmed | Assessing real-time Zika risk in the United States |
title_short | Assessing real-time Zika risk in the United States |
title_sort | assessing real-time zika risk in the united states |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5415743/ https://www.ncbi.nlm.nih.gov/pubmed/28468671 http://dx.doi.org/10.1186/s12879-017-2394-9 |
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