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Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

Clara Champagne, David Georges Salthouse, Richard Paul, Van-Mai Cao-Lormeau, Benjamin Roche, Bernard Cazelles
doi: https://doi.org/10.1101/064949
Clara Champagne
1IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, 46 rue d’Ulm, 75230 Paris, France
2Centre de Recherche en Economie et Statistiques (CREST), 15 boulevard Gabriel Péri, 92245 Malakoff cedex, France
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David Georges Salthouse
1IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, 46 rue d’Ulm, 75230 Paris, France
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Richard Paul
3Institut Pasteur, Unité de Génétique Fonctionnelle des Maladies Infectieuses, Department of Genomes and Genetics, F-75724 Paris cedex 15, France
4Centre National de la Recherche Scientifique, Unité de Recherche associée 3012, Paris, France
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Van-Mai Cao-Lormeau
5Unit of Emerging Infectious Diseases, Institut Louis Malardé, 98713 Papeete, Tahiti, French Polynesia
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Benjamin Roche
6International Center for Mathematical and Computational Modeling of Complex Systems (UMMISCO), UMI 209 UPMC/IRD, Bondy cedex, France
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Bernard Cazelles
1IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, 46 rue d’Ulm, 75230 Paris, France
6International Center for Mathematical and Computational Modeling of Complex Systems (UMMISCO), UMI 209 UPMC/IRD, Bondy cedex, France
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Abstract

Before the outbreak that reached the Americas in 2015, Zika virus (ZIKV) circulated in Asia and the Pacific: these past epidemics can be highly informative on the key parameters driving virus transmission, such as the basic reproduction number (R0). We compare two compartmental models with different mosquito representations, using surveillance and seroprevalence data for several ZIKV outbreaks in Pacific islands (Yap, Micronesia 2007, Tahiti and Moorea, French Polynesia 2013-2014, New Caledonia 2014). Models are estimated in a stochastic framework with state-of-the-art Bayesian techniques. R0 for the Pacific ZIKV epidemics is estimated between 1.5 and 4.1, the smallest islands displaying higher and more variable values. This relatively low range of R0 suggests that intervention strategies developed for other flaviviruses should enable as, if not more effective control of ZIKV. Our study also highlights the importance of seroprevalence data for precise quantitative analysis of pathogen propagation, to design prevention and control strategies.

Footnotes

  • ↵* champagn{at}biologie.ens.fr

  • ↵† cazelles{at}biologie.ens.fr

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 20, 2016.
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Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands
Clara Champagne, David Georges Salthouse, Richard Paul, Van-Mai Cao-Lormeau, Benjamin Roche, Bernard Cazelles
bioRxiv 064949; doi: https://doi.org/10.1101/064949
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Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands
Clara Champagne, David Georges Salthouse, Richard Paul, Van-Mai Cao-Lormeau, Benjamin Roche, Bernard Cazelles
bioRxiv 064949; doi: https://doi.org/10.1101/064949

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