title: Robust surveillance of animal diseases: an application to the detection of bluetongue disease.
abstract: Control of endemic, exotic, and emerging animal diseases critically depends on their early detection and timely management. This paper proposes a novel approach to evaluate alternative surveillance programs based on info-gap theory. A general modeling framework is developed explicitly accounting for severe uncertainty about the incursion, detection, spread, and control of exotic and emergent diseases. The model is illustrated by an evaluation of bluetongue disease surveillance strategies. Key results indicate that, when available, vaccination of the entire population is the most robust strategy. If vaccines are not available then active reporting of suspect clinical signs by farmers is a very robust surveillance policy.
authors.affiliation: University of Kent, Kent Business School, Room 7, Canterbury, Kent, CT2 7PE, UK. D.M.Souza-Monteiro@kent.ac.uk
authors.forename: Diogo M
authors.initials: DM
authors.lastname: Souza Monteiro
authors.forename: L Roman
authors.initials: LR
authors.lastname: Carrasco
authors.forename: L Joe
authors.initials: LJ
authors.lastname: Moffitt
authors.forename: Alasdair J C
authors.initials: AJ
authors.lastname: Cook
mesh_terms: D000818:Animals; D001819:Bluetongue / Q000175:diagnosis / Q000453:epidemiology* / Q000517:prevention & control; D003140:Communicable Disease Control / Q000379:methods; D021821:Communicable Diseases, Emerging / Q000175:diagnosis / Q000453:epidemiology / Q000517:prevention & control / Q000662:veterinary*; D003661:Decision Support Techniques; D004739:England / Q000453:epidemiology; D008954:Models, Biological; D011159:Population Surveillance / Q000379:methods; D012756:Sheep; D035501:Uncertainty; D014852:Wales / Q000453:epidemiology