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Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries
BACKGROUND: Zika virus (ZIKV) infection is emerging globally, currently causing outbreaks in the Caribbean, and Central and South America, and putting travellers to affected countries at risk. Model-based estimates for the basic reproduction number (R (0)) of ZIKV in affected Caribbean and Central a...
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/PMC5264286/ https://www.ncbi.nlm.nih.gov/pubmed/28122631 http://dx.doi.org/10.1186/s13071-017-1977-z |
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author | Ogden, Nicholas H. Fazil, Aamir Safronetz, David Drebot, Michael A. Wallace, Justine Rees, Erin E. Decock, Kristina Ng, Victoria |
author_facet | Ogden, Nicholas H. Fazil, Aamir Safronetz, David Drebot, Michael A. Wallace, Justine Rees, Erin E. Decock, Kristina Ng, Victoria |
author_sort | Ogden, Nicholas H. |
collection | PubMed |
description | BACKGROUND: Zika virus (ZIKV) infection is emerging globally, currently causing outbreaks in the Caribbean, and Central and South America, and putting travellers to affected countries at risk. Model-based estimates for the basic reproduction number (R (0)) of ZIKV in affected Caribbean and Central and South American countries, obtained from 2015 to 2016 human case surveillance data, were compared by logistic regression and Receiver-Operating Characteristic (ROC), with the prevalence of ZIKV-positive test results in Canadians who travelled to them. RESULTS: Estimates of R (0) for each country were a good predictor of the ZIKV test result (ROC area under the curve = 0.83) and the odds of testing positive was 11-fold greater for travellers visiting countries with estimated R (0) ≥ 2.76, compared to those visiting countries with R (0) < 2.76. CONCLUSIONS: Risk to travellers varies widely amongst countries affected by ZIKV outbreaks. Estimates of R (0) from surveillance data can assist in assessing levels of risk for travellers and may help improve travel advice. They may also allow better prediction of spread of ZIKV from affected countries by travellers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-017-1977-z) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5264286 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52642862017-01-30 Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries Ogden, Nicholas H. Fazil, Aamir Safronetz, David Drebot, Michael A. Wallace, Justine Rees, Erin E. Decock, Kristina Ng, Victoria Parasit Vectors Research BACKGROUND: Zika virus (ZIKV) infection is emerging globally, currently causing outbreaks in the Caribbean, and Central and South America, and putting travellers to affected countries at risk. Model-based estimates for the basic reproduction number (R (0)) of ZIKV in affected Caribbean and Central and South American countries, obtained from 2015 to 2016 human case surveillance data, were compared by logistic regression and Receiver-Operating Characteristic (ROC), with the prevalence of ZIKV-positive test results in Canadians who travelled to them. RESULTS: Estimates of R (0) for each country were a good predictor of the ZIKV test result (ROC area under the curve = 0.83) and the odds of testing positive was 11-fold greater for travellers visiting countries with estimated R (0) ≥ 2.76, compared to those visiting countries with R (0) < 2.76. CONCLUSIONS: Risk to travellers varies widely amongst countries affected by ZIKV outbreaks. Estimates of R (0) from surveillance data can assist in assessing levels of risk for travellers and may help improve travel advice. They may also allow better prediction of spread of ZIKV from affected countries by travellers. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-017-1977-z) contains supplementary material, which is available to authorized users. BioMed Central 2017-01-25 /pmc/articles/PMC5264286/ /pubmed/28122631 http://dx.doi.org/10.1186/s13071-017-1977-z 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 Ogden, Nicholas H. Fazil, Aamir Safronetz, David Drebot, Michael A. Wallace, Justine Rees, Erin E. Decock, Kristina Ng, Victoria Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title | Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title_full | Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title_fullStr | Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title_full_unstemmed | Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title_short | Risk of travel-related cases of Zika virus infection is predicted by transmission intensity in outbreak-affected countries |
title_sort | risk of travel-related cases of zika virus infection is predicted by transmission intensity in outbreak-affected countries |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5264286/ https://www.ncbi.nlm.nih.gov/pubmed/28122631 http://dx.doi.org/10.1186/s13071-017-1977-z |
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