We propose a dynamic framework to study the value of medical innovation in the context of infectious disease. We apply our framework to evaluate an HIV treatment breakthrough known as HAART. The model captures how, in lowering both the expected cost and likelihood of HIV infection, HAART reduced the implicit price of risky sex. Forward-looking agents responded by optimally shifting their behaviour. The model also imposes equilibrium constraints, explicitly capturing how optimal shifts in behaviour affect equilibrium choices by changing both infection probabilities and the ease of finding partners willing to engage in risky sex. Using the estimated model, we conduct counterfactual simulations to compute the value of HAART from the perspective of uninfected agents. This includes the option value of the innovation along with value accruing from changes in sex behaviour in response to HAART introduction. We also calculate the added value of a fully functional vaccine from the perspective of both infected and uninfected agents, where infected agents benefit from a vaccine due to resulting shifts in market equilibrium.

Many randomized experiments are plagued by attrition, even among subjects receiving more effective treatments. We estimate the subject’s utility associated with the receipt of treatment, as revealed by dropout behavior, to evaluate treatment effects. Utility is a function of both “publicly observed” outcomes and side effects privately observed by the subject. We analyze an influential AIDS clinical trial, ACTG 175, and show that for many subjects, AZT yields the highest level of utility despite having the smallest impact on the publicly observed outcome because of mild side effects. Moreover, although subjects enter the experiment uncertain of treatment effectiveness (and often the treatment received), the learning process implies that early dropout in ACTG 175 is primarily driven by side effects, whereas later attrition reflects declining treatment effectiveness.