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      A comparison study of Zika virus outbreaks in French Polynesia, Colombia and the State of Bahia in Brazil

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          Abstract

          Zika virus (ZIKV) disease outbreaks occurred in French Polynesia in 2013–2014 and in Brazil and Colombia in 2015–2016, respectively. Using our recently developed ZIKV disease model, we simulated the reported ZIKV infection cases from French Polynesia, Colombia and the State of Bahia of Brazil. Moreover, we estimated that the infection attack rates were 78.0% (95% confidence interval (CI): 63.5–86.3%) in French Polynesia which closely matches a previous serological study; 20.8% (95% CI: 1.1–50.0%) in Colombia which suggests that the attack rate was most likely less than 50%; and 32.4% (95% CI: 2.5–94.2%) in the State of Bahia in Brazil which suggests that the attack rate is unidentifiable with monthly data in Bahia. Furthermore, we found that the association of precipitation and ZIKV outbreak was more evident in Colombia than the other two places. These results are helpful for us to understand the possible evolution, to control the on-going outbreaks, to prevent the potential geographic spread, and to study the ecological and epidemiological characteristics of ZIKV.

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          Zika Virus Transmission from French Polynesia to Brazil

          To the Editor: Campos et al. ( 1 ) reported a Zika virus (ZIKV) outbreak in Brazil in 2015. This response adds complementary data related to the propagation of this mosquitoborne disease. To date, the largest ZIKV outbreak occurred in French Polynesia during 2013–2014. The outbreak spread to other Pacific Islands: New Caledonia, Cook Islands, Easter Island, Vanuatu, and Solomon Islands ( 2 ). The origin of introduction of ZIKV to French Polynesia remains unknown; introduction of ZIKV in New Caledonia was after imported cases from French Polynesia ( 3 ); introduction to Easter Island was suspected to have occurred among attendees of the annual Tapati festival, including those from French Polynesia ( 4 ). The virus was likely transmitted to New Caledonia, Cook Islands, and Easter Island when infected travelers from French Polynesia were bitten by vectors while on the islands. Frequent travel between New Caledonia and Vanuatu is likely related to the introduction of ZIKV in the latter country. Phylogenetic studies showed that the closest strain to the one that emerged in Brazil was isolated from samples from case-patients in French Polynesia and spread among the Pacific Islands ( 1 ); both strains belong to the Asian lineage. It has been assumed that ZIKV was introduced to Brazil during a World Cup soccer competition in 2014 ( 5 ), although no ZIKV-endemic Pacific countries competed. However, in August 2014, the Va’a World Sprint Championship canoe race was held in Rio de Janeiro, Brazil. Four Pacific countries (French Polynesia, New Caledonia, Cook Islands, and Easter Island) in which ZIKV circulated during 2014 had teams engaged in this contest in several categories. These data combined with phylogenetic studies by Zanluca et al. ( 5 ) suggest that ZIKV introduction in Brazil may have been a consequence of this event. In areas where potential vectors are present, vigilance should be enhanced to detect imported cases of ZIKV, and laboratory capacity to confirm suspected ZIKV infections should be strengthened.
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            Plug-and-play inference for disease dynamics: measles in large and small populations as a case study

            Statistical inference for mechanistic models of partially observed dynamic systems is an active area of research. Most existing inference methods place substantial restrictions upon the form of models that can be fitted and hence upon the nature of the scientific hypotheses that can be entertained and the data that can be used to evaluate them. In contrast, the so-called plug-and-play methods require only simulations from a model and are thus free of such restrictions. We show the utility of the plug-and-play approach in the context of an investigation of measles transmission dynamics. Our novel methodology enables us to ask and answer questions that previous analyses have been unable to address. Specifically, we demonstrate that plug-and-play methods permit the development of a modelling and inference framework applicable to data from both large and small populations. We thereby obtain novel insights into the nature of heterogeneity in mixing and comment on the importance of including extra-demographic stochasticity as a means of dealing with environmental stochasticity and model misspecification. Our approach is readily applicable to many other epidemiological and ecological systems.
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              From Mosquitos to Humans: Genetic Evolution of Zika Virus.

              Initially isolated in 1947, Zika virus (ZIKV) has recently emerged as a significant public health concern. Sequence analysis of all 41 known ZIKV RNA open reading frames to date indicates that ZIKV has undergone significant changes in both protein and nucleotide sequences during the past half century.
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                Author and article information

                Contributors
                ruan@math.miami.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                21 March 2017
                21 March 2017
                2017
                : 7
                : 273
                Affiliations
                [1 ]ISNI 0000 0004 1764 6123, GRID grid.16890.36, Department of Applied Mathematics, , The Hong Kong Polytechnic University, Hung Hom, ; Kowloon, Hong Kong (SAR) China
                [2 ]ISNI 0000 0001 0701 1077, GRID grid.412531.0, Mathematics and Science College, , Shanghai Normal University, ; Shanghai, 200234 China
                [3 ]ISNI 0000 0004 1936 8606, GRID grid.26790.3a, Department of Mathematics, , University of Miami, ; Coral Gables, FL 33146 USA
                Article
                253
                10.1038/s41598-017-00253-1
                5428201
                28325935
                32d99d4d-06fb-4fdc-a0c4-faae21f47b0e
                © The Author(s) 2017

                This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 1 December 2016
                : 15 February 2017
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