Prioritizing emerging zoonoses in the Netherlands

PLoS One. 2010 Nov 15;5(11):e13965. doi: 10.1371/journal.pone.0013965.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Animals
  • Communicable Diseases, Emerging / epidemiology
  • Communicable Diseases, Emerging / transmission*
  • Disease Reservoirs / microbiology
  • Disease Reservoirs / parasitology
  • Disease Reservoirs / virology
  • Humans
  • Models, Biological*
  • Netherlands / epidemiology
  • Zoonoses / epidemiology
  • Zoonoses / transmission*