PROJECT ABSTRACT Public health scientists lack reliable data on the burden of many infectious diseases, which is a barrier to effective control measures. Seroepidemiology provides an efficient means to generate unbiased estimates of disease burden such as seroincidence, the rate at which new infections occur in a population. This project supports the development of an open-source R software package, called serocalculator, to generate seroincidence estimates from cross-sectional population surveys of serologic antibody response data. Our package will implement an innovative statistical approach for estimating seroincidence that leverages information about antibody waning from confirmed cases and overcomes many methodological challenges that have stymied other approaches. Our specific aims are: Aim 1) Build an open-source, free-to-use R software package for estimating incidence from cross-sectional serosurveys that is efficient, reliable, and user-friendly and Aim 2) Enable widespread adoption and sustainable use of our serocalculator R package through open-source access, a graphical user interface for non-R- users, and a training curriculum. Our software will fill a gap between theory and practice by equipping a new community of users with a tool to efficiently estimate incidence from cross- sectional serosurveys. We expect this tool will be used to generate incidence estimates for a range of infectious diseases, providing critical information needed to inform disease control interventions and ultimately reduce the burden of disease.