Abstract
In this paper, three approaches (Markov processes, discrete-event simulation, and differential equations) to modeling intramammary infections (IMI; focusing on the dynamic changes between uninfected, subclinical, and clinical udder-health states) are described. The objectives were to describe the various approaches to modeling intramammary infections, determine if simulations of the examples of the three approaches yield stable prevalences, and discuss the approaches' limitations. The literature review showed that there is no agreement on the proportion of animals that change health states. The approach of discrete-event simulation modeling included the most cow-level risk factors and udder-health states (hence, was judged to replicated best the dynamics of the infection process) and yielded stable prevalences for all udder-health states. However, there remain parts of the dynamics that need further research. These include the pathogen-specific probabilities and times of occurrence for: regression of clinical IMI to subclinical IMI, flare-up of subclinical IMI to clinical IMI, and incidence of subclinical IMI. Also, the assumption in all current approaches of homogenous mixing is violated because the primary contact structure for contagious pathogens during milking is either between cows through residual infectious milk in the milking machine or within a cow by vacuum fluctuations or teat-cup liner slips. Better contact structures should be incorporated so that the effects of control strategies can be better-estimated. Moreover, the three modeling approaches discussed assumed that all non-infected quarters are susceptible to infection—which might be denied by work in genetic resistance.
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