INTERVENTION DECISION-MODEL TO PREVENT SPIKING MORTALITY OF TURKEYS

Based on the daily records on turkeys' mortalities for the series of f locks placed on different farms in a relatively compact geographical a rea for the period of approximately 2 yr and other relevant explanator y variables, the goal of the research was to design a decision model t o determine whether or not to use the fluorquinolone antibiotic, saraf loxacin, to prevent spiking mortality of turkeys. The core of the desi gned decision model is the forecasting model that attempts to ex-ante predict the cumulative nock mortality for the period between 8 and 28 d of age. Forecasts were generated with the parameters of the Linear r egression model where continuous values of daily mortalities served as a dependent variable. The decision variable is a binary (yes/no) choi ce variable, where ''yes'' means ''go ahead with treatment'' and ''no' ' means ''do nothing''. If the predicted cumulative mortality for the period between 8 and 28 d of age exceeds 9% of the total initial place ment, the model generates a ''yes'' signal. If the predicted cumulativ e mortality for the same period is below 9% of the total initial place ment, the model generates a ''no'' signal. The results indicate a reas onable accuracy of the prediction model where the number of correct pr ediction increases and the number or incorrect predictions falls very fast as the forecasting window shortens. The intervention decision mod el could help veterinarians in making decisions on whether or not to t reat the suspect flocks.