Time-series modeling of epidemics in complex populations: Detecting changes in incidence volatility over time.

ABSTRACT: Trends in infectious disease incidence provide important information about epidemic dynamics and prospects for control. Higher-frequency variation around incidence trends can shed light on the processes driving epidemics in complex populations, as transmission heterogeneity, shifting landscapes of susceptibility, and fluctuations in reporting can impact the volatility of observed case counts. However, measures of temporal volatility in incidence, and how volatility changes over time, are often overlooked in population-level analyses of incidence data, which typically focus on moving averages. Here we present a statistical framework to quantify temporal changes in incidence dispersion and to detect rapid shifts in the dispersion parameter, which may signal new epidemic phases. We apply the

SUBMITTER: Aber R 

PROVIDER: S-EPMC12266409 | biostudies-literature | 2025 Jul

REPOSITORIES: biostudies-literature