Ranking disease control strategies with stochastic outcomes.

This paper explains how the methodologies of first and second order stochastic dominance, and expected utility using specific risk preferences, can be applied to epidemiology when choosing among control strategies that have stochastic outcomes. We provide a step-by-step guide on how epidemiologists can rank a number of control strategies based on their distribution of estimated benefits. We also explain how the expected utility model and decision maker’s risk preferences can be used to select between outcomes when none stochastically dominates. To illustrate these techniques, we show the ranking of various control strategies for a dairy herd endemically infected with Mycobacterium avium subs. paratuberculosis (MAP) and mastitis, and explain how decision maker’s risk preferences affect the ranking.