1. Epidemiology and Global Health
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Structure in the variability of the basic reproductive number (R0) for Zika epidemics in the Pacific islands

  1. Clara Champagne  Is a corresponding author
  2. David Georges Salthouse
  3. Richard Paul
  4. Van-Mai Cao-Lormeau
  5. Benjamin Roche
  6. Bernard Cazelles  Is a corresponding author
  1. IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, France
  2. Institut Pasteur, France
  3. Institut Louis Malardé, French Polynesia
  4. International Center for Mathematical and Computational Modeling of Complex Systems, UMI 209 UPMC/IRD, France
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Cite this article as: eLife 2016;5:e19874 doi: 10.7554/eLife.19874

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 recent 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.

Article and author information

Author details

  1. Clara Champagne

    IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, Paris, France
    For correspondence
    champagn@biologie.ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-0369-6758
  2. David Georges Salthouse

    IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  3. Richard Paul

    Unité de Génétique Fonctionnelle des Maladies Infectieuses, Department of Genomes and Genetics, Institut Pasteur, Paris, France
    Competing interests
    The authors declare that no competing interests exist.
  4. Van-Mai Cao-Lormeau

    Unit of Emerging Infectious Diseases, Institut Louis Malardé, Papeete, Tahiti, French Polynesia
    Competing interests
    The authors declare that no competing interests exist.
  5. Benjamin Roche

    International Center for Mathematical and Computational Modeling of Complex Systems, UMI 209 UPMC/IRD, Montpellier, France
    Competing interests
    The authors declare that no competing interests exist.
  6. Bernard Cazelles

    IBENS, UMR 8197 CNRS-ENS Ecole Normale Supérieure, Paris, France
    For correspondence
    cazelles@biologie.ens.fr
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-7972-361X

Funding

Centre National de la Recherche Scientifique (Pepiniere interdisciplinaire Eco-Evo-Devo)

  • Clara Champagne
  • David Georges Salthouse
  • Bernard Cazelles

European Commission (Seventh Framework Program [FP7 2007-2013] for the DENFREE project under Grant Agreement 282 348)

  • Clara Champagne
  • David Georges Salthouse
  • Richard Paul
  • Van-Mai Cao-Lormeau
  • Bernard Cazelles

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Mark Jit, London School of Hygiene & Tropical Medicine, and Public Health England, United Kingdom

Publication history

  1. Received: July 21, 2016
  2. Accepted: November 22, 2016
  3. Accepted Manuscript published: November 29, 2016 (version 1)
  4. Version of Record published: January 24, 2017 (version 2)

Copyright

© 2016, Champagne et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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Further reading

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    Background:

    The virus SARS-CoV-2 can exploit biological vulnerabilities (e.g. host proteins) in susceptible hosts that predispose to the development of severe COVID-19.

    Methods:

    To identify host proteins that may contribute to the risk of severe COVID-19, we undertook proteome-wide genetic colocalisation tests, and polygenic (pan) and cis-Mendelian randomisation analyses leveraging publicly available protein and COVID-19 datasets.

    Results:

    Our analytic approach identified several known targets (e.g. ABO, OAS1), but also nominated new proteins such as soluble Fas (colocalisation probability >0.9, p=1 × 10-4), implicating Fas-mediated apoptosis as a potential target for COVID-19 risk. The polygenic (pan) and cis-Mendelian randomisation analyses showed consistent associations of genetically predicted ABO protein with several COVID-19 phenotypes. The ABO signal is highly pleiotropic, and a look-up of proteins associated with the ABO signal revealed that the strongest association was with soluble CD209. We demonstrated experimentally that CD209 directly interacts with the spike protein of SARS-CoV-2, suggesting a mechanism that could explain the ABO association with COVID-19.

    Conclusions:

    Our work provides a prioritised list of host targets potentially exploited by SARS-CoV-2 and is a precursor for further research on CD209 and FAS as therapeutically tractable targets for COVID-19.

    Funding:

    MAK, JSc, JH, AB, DO, MC, EMM, MG, ID were funded by Open Targets. J.Z. and T.R.G were funded by the UK Medical Research Council Integrative Epidemiology Unit (MC_UU_00011/4). JSh and GJW were funded by the Wellcome Trust Grant 206194. This research was funded in part by the Wellcome Trust [Grant 206194]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission.

    1. Epidemiology and Global Health
    Lawrence Lubyayi et al.
    Research Article

    Background:

    Lack of early infection-exposure has been associated with increased allergy-related disease (ARD) susceptibility. In tropical Africa, little is known about which infections contribute to development of ARDs, and at which time.

    Methods:

    We used latent class analysis to characterise the early infection-exposure of participants in a Ugandan birth cohort and assessed ARDs in later childhood.

    Results:

    Of 2345 live births, 2115 children (90%) had data on infections within the first year of life while 1179 (50%) had outcome data at 9 years. We identified two latent classes of children based on first-year infection-exposure. Class 1 (32% membership), characterised by higher probabilities for malaria (80%), diarrhoea (76%), and lower respiratory tract infections (LRTI) (22%), was associated with lower prevalence of wheeze, eczema, rhinitis, and Dermatophagoides skin prick test (SPT) positivity at 9 years. Based on 5-year cumulative infection experience, class 1 (31% membership), characterised by higher probabilities for helminths (92%), malaria (79%), and LRTI (45%), was associated with lower probabilities of SPT positivity at 9 years.

    Conclusions:

    In this Ugandan birth cohort, early childhood infection-exposure, notably to malaria, helminths, LRTI, and diarrhoea, is associated with lower prevalence of atopy and ARDs in later childhood.

    Funding:

    This work was supported by several funding sources. The Entebbe Mother and Baby Study (EMaBS) was supported by the Wellcome Trust, UK, senior fellowships for AME (grant numbers 064693, 079110, 95778) with additional support from the UK Medical Research Council. LL is supported by a PhD fellowship through the DELTAS Africa Initiative SSACAB (grant number 107754). ELW received funding from MRC Grant Reference MR/K012126/1. SAL was supported by the PANDORA-ID-NET Consortium (EDCTP Reg/Grant RIA2016E-1609). HM was supported by the Wellcome’s Institutional Strategic Support Fund (grant number 204928/Z/16/Z).