About: 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.   Goto Sponge  NotDistinct  Permalink

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  • 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.
Subject
  • Virology
  • Flaviviruses
  • Zika virus
  • Continents
  • Insect-borne diseases
  • International relations
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