A novel method to select time-varying multivariate time series models for the surveillance of infectious diseases.

ABSTRACT:

Background

Describing the transmission dynamics of infectious diseases across different regions is crucial for effective disease surveillance. The multivariate time series (MTS) model has been widely adopted for constructing cross-regional infectious disease transmission networks due to its strengths in interpretability and predictive performance. Nevertheless, the assumption of constant parameters frequently disregards the dynamic shifts in disease transmission rates, thereby compromising the accuracy of early warnings. This study investigated the applicability of time-varying MTS models in multi-regional infectious disease monitoring and explored strategies for model selection.

Methods

This study focused on two prominent time-varying MTS models: the time-varying parameter-

SUBMITTER: Yu J 

PROVIDER: S-EPMC11328433 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature