A spatiotemporal transmission simulator for respiratory infectious diseases and its application to COVID-19.

ABSTRACT: The present study introduces a transmission dynamic simulator for respiratory infectious diseases by incorporating human movement data into a spatiotemporal transmission model. The model spatially divides areas into multiple patches according to administrative regions. The transmission of respiratory pathogens within each patch is depicted using an improved Susceptible-Exposed-Infectious-Removed (SEIR) compartmental framework, which incorporates quarantine and isolation measures. The risk of transmission between patches is determined by a gravity-constrained model that considers passenger volume and the spatial distance between patches. We simulate changes in intervention policies and detection methods by adjusting quarantine and detection rates at different stages of the epidemic, thereby

SUBMITTER: Shi T 

PROVIDER: S-EPMC12302290 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature