DESIGN AND VALIDATION OF A DYNAMIC DISCRETE-EVENT STOCHASTIC SIMULATION-MODEL OF MASTITIS CONTROL IN DAIRY HERDS

A dynamic stochastic simulation model for discrete events, SIMMAST, wa s developed to simulate the effect of mastitis on the composition of t he bulk tank milk of dairy herds. Intramammary infections caused by St reptococcus agalactiae, Streptococcus spp, other than Strep. agalactia e, Staphylococcus aureus, and coagulase-negative staphylococci were mo deled as were the milk, fat, and protein test day solutions for indivi dual cows, which accounted for the fixed effects of days in milk, age at calving, season of calving, somatic cell count (SCC), and random ef fects of test day, cow yield differences from herdmates, and autocorre lated errors. Probabilities for the transitions among various states o f udder health (uninfected or subclinically or clinically infected) we re calculated to account for exposure, heifer infection, spontaneous r ecovery, lactation cure, infection or cure during the dry period, mont h of lactation, parity, within-herd yields, and the number of quarters with clinical intramammary infection in the previous and current lact ations. The stochastic simulation model was constructed using estimate s from the literature and also using data from 164 herds enrolled with Quality Milk Promotion Services that each had bulk tank SCC between 5 00,000 and 750,000/ml. Model parameters and outputs were validated aga inst a separate data file of 69 herds from the Northeast Dairy Herd Im provement Association, each with a bulk tank SCC that was greater than or equal to 500,000/ml. Sensitivity analysis was performed on all inp ut parameters for control herds. Using the validated stochastic simula tion model, the control herds had a stable time average bulk tank SCC between 500,000 and 750,000/ml.