Estimating Epidemic Rate Parameters: Adaptivity, Bias, and Convolution

Abstract

Metrics like the case-fatality rate and reproduction number are key descriptors of epidemics from the COVID-19 pandemic to the seasonal flu. In retrospect, these quantities enrich our understanding of infectious disease outbreaks; in real-time, they are absolutely critical to informing public health response. Thus, an important question in epidemiology is how best to estimate such metrics, especially in real-time. This question is complicated by practical considerations like data availability, as well as the fact that the metrics themselves may change as the epidemic unfolds.