Social interactions make communicable disease a core concern of public health policy. A prevalent problem is scarcity of empirical evidence informative about how interventions affect illness. Randomized trials, which have been important to evaluation of treatments for noninfectious diseases, are less informative about treatment of communicable diseases because they do not fully reveal the indirect preventive (herd immunity) effect of vaccination on persons who are not vaccinated or are unsuccessfully vaccinated. This paper studies the decision problem faced by a health planner who observes the illness rate that occurs when persons make decentralized vaccination choices and who contemplates whether to mandate vaccination. The planner's objective is to minimize the social cost of illness and vaccination. Uncertainty about the magnitude of the indirect effect of vaccination implies uncertainty about the illness rate that a mandate would yield. I first study a simple representative‐agent setting and derive conditions under which the planner can determine whether mandating vaccination is optimal. When optimal policy is indeterminate, I juxtapose several criteria for decision making—expected utility, minimax, and minimax‐regret—and compare the policies they generate. I then extend the analysis to a more general setting in which members of the population may have heterogenous attributes. I have benefitted from the opportunity to present this work in seminars at the Booth School of Business, University of Chicago, the Department of Economics, University of California at Santa Barbara, and the Schaeffer Center for Health Policy and Economics, University of Southern California. I have also benefitted from the comments of an anonymous reviewer and associate editor.