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A bivariate autoregressive model for estimation of prevalence of fasciolosis in cattle

Published online by Cambridge University Press:  02 September 2010

E. A. Goodall
Affiliation:
Biometrics Division, Department of Agriculture for Northern Ireland, Newforge Lane, Belfast BT9 5PX
F. D. Menzies
Affiliation:
Veterinary Sciences Division, Stormont, Stoney Road, Belfast BT4 3SD
S. M. Taylor
Affiliation:
Veterinary Sciences Division, Stormont, Stoney Road, Belfast BT4 3SD
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Abstract

Fasciolosis is a serious economic disease of cattle and sheep with a worldwide distribution. In the annual control of the disease, it is vital that the issue of specific veterinary advice on the strategic use of control measures should be based on precise estimates of the levels of risk of the occurrence of the disease. This paper describes the construction of a mathematical model to forecast the level of risk of the disease in cattle in any year. The model has been developed in Northern Ireland using a computerized information database retrieval system for abattoir condemnation data. The information recorded by the system details the specific cause and location of all condemnations in cattle, sheep and pigs for all abattoirs in Northern Ireland. Analysis of a subset of these data (1976 to 1991) for cattle resulted in a univariate time series model for the recorded prevalence of condemnations due to fasciolosis in cattle livers. The overall mathematical forecasting model was constructed by regressing the residual terms of the univariate time series model with the corresponding time series of all the key meteorological variables. The best model (R2 =0·8) was obtained using the mean air temperature for the period fune to August inclusive. The model could be adopted for use in any region of the world where relevant abattoir condemnation and meteorological data are available.

Type
Research Article
Copyright
Copyright © British Society of Animal Science 1993

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