Wavelet analysis is employed in epidemiology to identify and interpret patterns within health data, such as seasonal trends, periodic outbreaks, and long-term changes in disease incidence. By transforming time-series data, epidemiologists can isolate different frequencies and magnitudes of fluctuations, allowing for a more nuanced understanding of disease dynamics. For example, it can be used to study the seasonality of infectious diseases like influenza or dengue fever.
