Differential privacy is a mathematical framework designed to provide privacy guarantees when analyzing and sharing data. It ensures that the inclusion or exclusion of a single individual's data does not significantly affect the outcome of the analysis. This is particularly crucial in epidemiological studies where sensitive health data is often involved.
