The role of mathematical modelling in understanding the epidemiology and control of sheep transmissible spongiform encephalopathies: a review
Institute for Animal Health, Pirbright Laboratory, Ash Road, Pirbright, Surrey GU24 0NF, United Kingdom
2 INRA, UR341 Mathématiques et Informatique Appliquées, F-78350 Jouy-en-Josas, France
3 Quantitative Veterinary Epidemiology and Risk Analysis, Department of Virology, Central Veterinary Institute of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
* Corresponding author: firstname.lastname@example.org
Accepted: 19 February 2010
To deal with the incompleteness of observations and disentangle the complexities of transmission much use has been made of mathematical modelling when investigating the epidemiology of sheep transmissible spongiform encephalopathies (TSE) and, in particular, scrapie. Importantly, these modelling approaches allow the incidence of clinical disease to be related to the underlying prevalence of infection, thereby overcoming one of the major difficulties when studying these diseases. Models have been used to investigate the epidemiology of scrapie within individual flocks and at a regional level; to assess the efficacy of different control strategies, especially selective breeding programmes based on prion protein (PrP) genotype; to interpret the results of scrapie surveillance; and to inform the design of surveillance programmes. Furthermore, mathematical modelling has played an important role when assessing the risk to human health posed by the possible presence of bovine spongiform encephalopathy in sheep. Here, we review the various approaches that have been taken when developing and analysing mathematical models for the epidemiology and control of sheep TSE and assess their impact on our understanding of these diseases. We also identify areas that require further work, discuss future challenges and identify data gaps.
Key words: epidemiology / transmissible spongiform encephalopathy / scrapie / mathematical modelling / sheep
© INRA, EDP Sciences, 2010
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