Understanding vaccine effects on post-infection outcomes is critical for evaluating the full value proposition of a vaccine. However, defining appropriate causal effects on such outcomes can be challenging. We propose causal estimands for post-infection outcomes in the Naturally Infected subpopulation consisting of individuals who would be infected in absence of vaccine. We discuss partial identification using bounds and point identification and estimation using semi-parametric efficient one-step estimators with robustness properties under inconsistent nuisance parameter estimation. We further show under what conditions the same identification functional can be interpreted as targeting an effect among individuals exposed to a sufficiently infectious dose of the pathogen, thereby avoiding direct reliance on cross-world parameters and fundamentally untestable causal assumptions. We illustrate the method using an analysis of a rotavirus vaccine trial and simulation studies aimed to guide the design of Shigella vaccine trials.