A common source of bias in evaluating vaccine efficacy following a disease outbreak is the presence of persons who had the disease prior to the outbreak. This paper examines the effects of including and excluding pre-outbreak disease cases from the calculation of vaccine efficacy based on the cumulative incidence at the end of an outbreak. Using a five-stage model, the effects of the following factors on the bias of vaccine efficacy estimates are examined: the true protective efficacy of the vaccine, the prevaccination infection rate, differences in vaccine uptake among the previously diseased and nondiseased, differences in pre-outbreak exposure to infection between vaccinees and nonvaccinees, and differences in exposure during the outbreak between vaccinees and nonvaccinees. Numerical calculations of the bias are performed for a hypothetical outbreak of measles in a developing country. Exclusion of pre-outbreak disease cases requires accurate data on disease rates prior to the outbreak, and such data are often unreliable or nonexistent. Inclusion of pre-outbreak cases contributes to the bias of the estimated vaccine efficacy, especially when there is a high prevaccination infection rate and vaccine uptake among the previously diseased is considerably lower than that among the nondiseased. In most practical cases, however, this bias is not very large.