Prioritizing emerging zoonoses in The Netherlands

AH Havelaar, F van Rosse, C Bucura, MA Toetenel, JA Haagsma, D Kurowicka, JH Heesterbeek, N Speybroeck, MF Langelaar, JW van der Giessen, RM Cooke, MA Braks

    Research output: Contribution to journalA1: Web of Science-article

    Abstract

    BACKGROUND: To support the development of early warning and surveillance systems of emerging zoonoses, we present a general method to prioritize pathogens using a quantitative, stochastic multi-criteria model, parameterized for the Netherlands. METHODOLOGY/PRINCIPAL FINDINGS: A risk score was based on seven criteria, reflecting assessments of the epidemiology and impact of these pathogens on society. Criteria were weighed, based on the preferences of a panel of judges with a background in infectious disease control. CONCLUSIONS/SIGNIFICANCE: Pathogens with the highest risk for the Netherlands included pathogens in the livestock reservoir with a high actual human disease burden (e.g. Campylobacter spp., Toxoplasma gondii, Coxiella burnetii) or a low current but higher historic burden (e.g. Mycobacterium bovis), rare zoonotic pathogens in domestic animals with severe disease manifestations in humans (e.g. BSE prion, Capnocytophaga canimorsus) as well as arthropod-borne and wildlife associated pathogens which may pose a severe risk in future (e.g. Japanese encephalitis virus and West-Nile virus). These agents are key targets for development of early warning and surveillance
    Original languageEnglish
    JournalPLoS ONE
    Volume5
    Issue number11
    Pages (from-to)e13965
    Number of pages9
    ISSN1932-6203
    DOIs
    Publication statusPublished - 2010

    Keywords

    • B780-tropical-medicine
    • Zoonoses
    • Reservoirs
    • Livestock
    • Domestic animals
    • Humans
    • Disease burden
    • Early warning
    • Surveillance system
    • Priority setting
    • Criteria
    • Probability
    • Disease transmission
    • Economic impact
    • Pathogens
    • Morbidity
    • Mortality
    • Mathematical modeling
    • Risk assessment
    • Epidemiology
    • Impact
    • Sensitivity
    • Cluster analysis
    • Netherlands
    • Europe-West

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