Prioritizing Emerging Zoonoses in The Netherlands
Citation: Havelaar AH, van Rosse F, Bucura C, Toetenel MA, Haagsma JA, et al. (
Prioritizing Emerging Zoonoses in The Netherlands
Arie H. Havelaar 0 1
Floor van Rosse 0 1
Catalin Bucura 0 1
Milou A. Toetenel 0 1
Juanita A. Haagsma 0 1
Dorota Kurowicka 0 1
J. (Hans) A. P. Heesterbeek 0 1
Niko Speybroeck 0 1
Merel F. M. Langelaar 0 1
Johanna W. B. van der Giessen 0 1
Roger M. Cooke 0 1
Marieta A. H. Braks 0 1
Adam J. Ratner, Columbia University, United States of America
0 1 National Institute for Public Health and the Environment, Bilthoven, The Netherlands, 2 Utrecht University , Utrecht , The Netherlands , 3 Delft University of Technology , Delft , The Netherlands , 4 Wageningen University and Research Centre , Wageningen , The Netherlands , 5 Erasmus Medical Centre , Rotterdam , The Netherlands , 6 Institute of Tropical Medicine, Antwerp, Belgium, 7 Institute of Health and Society, Universite Catholique de Louvain , Brussels , Belgium
1 The EmZoo project is a collaboration between:
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.
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Funding: The EmZoo project is funded by the Dutch Ministry of Agriculture, Nature and Food Quality (www.minlnv.nl). The funders had no role in study design,
data collection and analysis, decision to publish, or preparation of the manuscript, other than guidance and feedback by the EmZoo Supervisory Committee on
the relevance of criteria for policy decisions.
Competing Interests: The authors have declared that no competing interests exist.
Human health is threatened by a wide variety of pathogens
transmitted from animals to humans. In the Netherlands, a
systematic approach for early warning and surveillance of
emerging zoonoses and a blueprint for an efficient network of
collaborators from the medical and veterinary professions to
prevent and control emerging zoonoses are being developed by a
consortium of national institutes for human and animal health (the
EmZoo consortium). To support this task, a prioritized list of
emerging zoonotic pathogens of relevance for the Netherlands was
needed. The HAIRS Group in the UK [1] has developed
qualitative decision trees to assess the zoonotic potential of
emerging diseases [2] and to classify the risk to public health,
based on probability and impact of infection [3].
Priority setting is a multi-dimensional problem, in which
technical information is often intertwined with value judgments.
Traditionally, a priority setting procedure entails asking a limited
number of experts to reach consensus. An example of this
approach in the domain of emerging zoonoses has been published
in France [4]. This method is relatively straightforward, but not
very transparent and the repeatability is low. Currently,
semiquantitative methods are frequently used in which criteria are
divided into a limited number of classes (e.g. low, medium and
high). Criteria may also be scored on arbitrary scales (e.g. 0, 1, ,
5), while scores for all criteria are aggregated to produce an overall
score. An example of this approach was published in Belgium [5],
and a similar approach was taken for animal diseases by
McKenzie et al. [6] in New Zealand. Here, the transparency and
the repeatability are improved, but the classes are chosen rather
arbitrarily. Linear relations between the different classes of a
criterion or between criteria are often assumed but are not
supported by data. For the current project, the aim was to develop
a quantitative method to rank emerging zoonoses using clearly
interpretable criteria, expressed on natural numerical scales.
Furthermore, weights were incorporated for these criteria, elicited
by a systematic procedure from a panel of judges, independent
from the authors or scientific experts in the project. The method
was designed to simultaneously be the basis of a web-based
knowledge management system.
The quantita (...truncated)