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Risk Maps for the Spread of Highly Pathogenic Avian Influenza in Poultry

Overview of attention for article published in PLoS Computational Biology, April 2007
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Title
Risk Maps for the Spread of Highly Pathogenic Avian Influenza in Poultry
Published in
PLoS Computational Biology, April 2007
DOI 10.1371/journal.pcbi.0030071
Pubmed ID
Authors

Gert Jan Boender, Thomas J Hagenaars, Annemarie Bouma, Gonnie Nodelijk, Armin R. W Elbers, Mart C. M de Jong, Michiel van Boven

Abstract

Devastating epidemics of highly contagious animal diseases such as avian influenza, classical swine fever, and foot-and-mouth disease underline the need for improved understanding of the factors promoting the spread of these pathogens. Here the authors present a spatial analysis of the between-farm transmission of a highly pathogenic H7N7 avian influenza virus that caused a large epidemic in The Netherlands in 2003. The authors developed a method to estimate key parameters determining the spread of highly transmissible animal diseases between farms based on outbreak data. The method allows for the identification of high-risk areas for propagating spread in an epidemiologically underpinned manner. A central concept is the transmission kernel, which determines the probability of pathogen transmission from infected to uninfected farms as a function of interfarm distance. The authors show how an estimate of the transmission kernel naturally provides estimates of the critical farm density and local reproduction numbers, which allows one to evaluate the effectiveness of control strategies. For avian influenza, the analyses show that there are two poultry-dense areas in The Netherlands where epidemic spread is possible, and in which local control measures are unlikely to be able to halt an unfolding epidemic. In these regions an epidemic can only be brought to an end by the depletion of susceptible farms by infection or massive culling. The analyses provide an estimate of the spatial range over which highly pathogenic avian influenza viruses spread between farms, and emphasize that control measures aimed at controlling such outbreaks need to take into account the local density of farms.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 232 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 8 3%
United States 6 3%
Vietnam 2 <1%
Germany 1 <1%
Chile 1 <1%
Italy 1 <1%
Réunion 1 <1%
Kenya 1 <1%
Australia 1 <1%
Other 9 4%
Unknown 201 87%

Demographic breakdown

Readers by professional status Count As %
Researcher 60 26%
Student > Ph. D. Student 43 19%
Student > Master 29 13%
Other 14 6%
Professor 14 6%
Other 43 19%
Unknown 29 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 85 37%
Medicine and Dentistry 28 12%
Veterinary Science and Veterinary Medicine 26 11%
Mathematics 16 7%
Computer Science 6 3%
Other 30 13%
Unknown 41 18%