We estimate a utility-theoretic choice model to quantify demand for publicly provided medical treatment policies. We find diminishing marginal utility for increased recoveries and avoided premature deaths. Willingness to pay for different types of treatment policies varies with who would benefit, with each respondent's own characteristics, community ethnic fractionalization and immigrant composition, as well as the respondent's expected private benefits from the policy, attitude toward government interventions and overall health care funding priorities.
Information about preferences for treatment and prevention policies can help policy makers more effectively allocate public health resources. We estimate a random utility model of preferences for treatment and prevention policies and explore sources of systematic heterogeneity in preferences. Marginal utility associated with avoided deaths is about twice as high for prevention policies as for treatment policies, and there is significant heterogeneity with respect to disease type, the group targeted by the policy, and respondent characteristics.
One instance of the online survey involving choice experiments concerning public health risk reductions. This "treatment" survey employed choice tasks concerning public policies that would (1) treat children, adults and seniors (in different proportions) who have a specific type of illness. Policies also varied in terms of (2) how many people would get sick over a specified number of future years, (3) how many would recover fully without and with the policy, (4) how many deaths would occur with and without the policy, and (5) the cost per month to the respondent.