Modelling to Predict Disease and Severity Using Age Specific Seroprevalence Data

Gavin Ramsay

No 164584, Animal Health Economics from University of Queensland, School of Economics

Abstract: This paper outlines the use of modelling in animal health with an emphasis on Markov chain models. Models that have been used to predict the incidence of disease caused by B. bovis are then examined. The development of a model that enables the use of age specific seroprevalence data to estimate the incidence of clinical disease is then described. This involves the use of a method to transform the seroprevalence data to incidence risk which is incorporated into a Markov chain disease prediction model. This in turn is linked to a herd model. The model predicts the proportion of animals in each age and sex class that would be affected by different severities of disease. Using the herd model, estimates of the number of animals affected are made. The model is then used to predict disease incidence and severity for B. bovis infection as an initial step in the determination of the effects of control of B. bovis by vaccination which is examined in subsequent discussion papers.

Keywords: Health Economics and Policy; Livestock Production/Industries (search for similar items in EconPapers)
Pages: 33
Date: 1997-03
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Citations: View citations in EconPapers (25)

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Persistent link: https://EconPapers.repec.org/RePEc:ags:uqseah:164584

DOI: 10.22004/ag.econ.164584

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