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Eight challenges in modelling infectious livestock diseases.


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Authors

Brooks-Pollock, E 
de Jong, MCM 
Keeling, MJ 
Klinkenberg, D 
Wood, JLN 

Abstract

The transmission of infectious diseases of livestock does not differ in principle from disease transmission in any other animals, apart from that the aim of control is ultimately economic, with the influence of social, political and welfare constraints often poorly defined. Modelling of livestock diseases suffers simultaneously from a wealth and a lack of data. On the one hand, the ability to conduct transmission experiments, detailed within-host studies and track individual animals between geocoded locations make livestock diseases a particularly rich potential source of realistic data for illuminating biological mechanisms of transmission and conducting explicit analyses of contact networks. On the other hand, scarcity of funding, as compared to human diseases, often results in incomplete and partial data for many livestock diseases and regions of the world. In this overview of challenges in livestock disease modelling, we highlight eight areas unique to livestock that, if addressed, would mark major progress in the area.

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Keywords

Challenges, Data-driven modelling, Livestock diseases, Mathematical modelling, Modelling for policy, Animal Husbandry, Animals, Communicable Disease Control, Communicable Diseases, Livestock, Models, Statistical, Selective Breeding

Journal Title

Epidemics

Conference Name

Journal ISSN

1755-4365
1878-0067

Volume Title

10

Publisher

Elsevier BV
Sponsorship
Biotechnology and Biological Sciences Research Council (BB/I012192/1)
Engineering and Physical Sciences Research Council (EP/H027270/1)
European Commission (278976)
EBP is funded by EPSRC fellowship EP/H027270/1. MJK was supported by the ERA-NET anihwa call funded by Defra. JLNW is supported by the Alborada Trust, the RAPIDD program of the Science & Technology Directorate, U.S. Department of Homeland Security, the Fogarty International Center, U.S. National Institutes of Health, the European Union FP7 project ANTIGONE (contract number 278976) and by BBSRC grant BB/I012192/1.