A BIVARIATE AUTOREGRESSIVE MODEL FOR ESTIMATION OF PREVALENCE OF FASCIOLIASIS IN CATTLE

Fasciolosis is a serious economic disease of cattle and sheep with a w orldwide distribution. In the annual control of the disease, it is vit al that the issue of specific veterinary advice on the strategic use o f control measures should be based on precise estimates of the levels of risk of the occurrence of the disease. This paper describes the con struction of a mathematical model to forecast the level of risk of the - disease in cattle in any year. The model has been developed in North ern Ireland using a computerized information database retrieval system for abattoir condemnation data. The information recorded by the syste m details the specific cause and location of all condemnations in catt le, sheep and pigs for all abattoirs in Northern Ireland. Analysis of a subset of these data (1976 to 1991) for cattle resulted in a univari ate 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 univari ate time series model with the corresponding time series of all the ke y meteorological variables. The best model (R2 = 0.8) was obtained usi ng the mean air temperature for the period June to August inclusive. T he model could be adopted for use in any region of the world where rel evant abattoir condemnation and meteorological data are available.