Estimating Epidemic Rate Parameters: Adaptivity, Bias, and Convolution

Jeremy Goldwasser

Estimating Epidemic Rate Parameters: Adaptivity, Bias, and Convolution

Applications 2026-08-10 v1

Authors: Jeremy Goldwasser

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.

Keywords

epidemic rate parameters case-fatality rate reproduction number real-time estimation epidemiology

Cite

@article{arxiv.2608.10138,
  title  = {Estimating Epidemic Rate Parameters: Adaptivity, Bias, and Convolution},
  author = {Jeremy Goldwasser},
  journal= {arXiv preprint arXiv:2608.10138},
  year   = {2026}
}