Mobility-informed metapopulation models predict the spatio-temporal spread of respiratory epidemics across scales.

ABSTRACT: Understanding the spatiotemporal dynamics of infectious disease spread is critical for anticipating epidemic trajectories and guiding public health responses. Accurate forecasts of where and when outbreaks are likely to emerge can support efficient resource allocation, particularly during the early stages of epidemics when surveillance data are limited. In this study, we used empirical human mobility data derived from county-level commuting and air traffic flows, and a theoretical mobility model (the radiation model) to study the relative order of epidemic onset across spatial scales. These mobility models were incorporated into a metapopulation framework to predict the spread of three major respiratory pathogens: COVID-19, seasonal influenza, and respiratory syncytial virus (RSV). We appl

SUBMITTER: Pandey A 

PROVIDER: S-EPMC12262780 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature