This dissertation examines cholera vaccination policy in a developing country context based on a combination of epidemiological and microeconomic data representing private demand for purchasing vaccinations, cost of illness, cost of vaccination, and herd protection impacts of vaccination. The dissertation incorporates data from Matlab, Bangladesh. Matlab’s population is subdivided into four distinct population groups based on variation in disease burden and age. Mathematical optimization is used to solve for the socially optimal prices across population groups that maximize either (1) societal net benefits; or (2) the number of DALYs saved across subject to a budget constraint. This analysis demonstrates that is optimal to charge the lowest prices to children in high incidence villages and the highest prices to adults in average incidence villages. Sensitivity analysis reveals that the use of cross-subsidies has only a small impact on program outcomes including both net societal benefits and total DALYs saved (e.g., adults who purchase vaccines in average incidence villages would pay more per vaccine to subsidize children in high incidence villages). This analysis shows that cross-subsidies may be less useful for scenarios in which the herd protection impacts of vaccination are similar across population groups.