title: Developing stochastic epidemiological models to quantify the dynamics of infectious diseases in domestic livestock.
abstract: A stochastic model describing disease transmission dynamics for a microparasitic infection in a structured domestic animal population is developed and applied to hypothetical epidemics on a pig farm. Rational decision making regarding appropriate control strategies for infectious diseases in domestic livestock requires an understanding of the disease dynamics and risk profiles for different groups of animals. This is best achieved by means of stochastic epidemic models. Methodologies are presented for 1) estimating the probability of an epidemic, given the presence of an infected animal, whether this epidemic is major (requires intervention) or minor (dies out without intervention), and how the location of the infected animal on the farm influences the epidemic probabilities; 2) estimating the basic reproductive ratio, R0 (i.e., the expected number of secondary cases on the introduction of a single infected animal) and the variability of the estimate of this parameter; and 3) estimating the total proportion of animals infected during an epidemic and the total proportion infected at any point in time. The model can be used for assessing impact of altering farm structure on disease dynamics, as well as disease control strategies, including altering farm structure, vaccination, culling, and genetic selection.
authors.affiliation: Roslin Institute (Edinburgh), Roslin, Midlothian, United Kingdom. Katrin.MacKenzie@bbsrc.ac.uk
authors.forename: K
authors.initials: K
authors.lastname: MacKenzie
authors.forename: S C
authors.initials: SC
authors.lastname: Bishop
mesh_terms: D000818:Animals; D004196:Disease Outbreaks / Q000662:veterinary*; D008962:Models, Theoretical; D010273:Parasitic Diseases, Animal / Q000453:epidemiology* / Q000635:transmission; D011897:Random Allocation; D013552:Swine; D013553:Swine Diseases / Q000453:epidemiology* / Q000635:transmission