A spatio-temporal causal network for multi-scale analysis of infectious respiratory diseases transmission.

ABSTRACT: Understanding the spatio-temporal transmission characteristics of infectious respiratory diseases is crucial for effective control. However, most existing studies rely on correlation analysis, which obscures the true causal pathways and directionality of infectious respiratory disease transmission, preventing accurate identification of epidemic sources and sinks. To address these challenges, we proposed a novel spatio-temporal causal analysis framework. First, a spatio-temporal causal network is constructed using the Convergent Cross Mapping (CCM) model. This method effectively overcomes the limitations of traditional correlation analysis in identifying spurious correlations and determining causal direction. Subsequently, the weighted k-shell decomposition and Louvain algorithm are applied

SUBMITTER: Zheng X 

PROVIDER: S-EPMC12857356 | biostudies-literature | 2026 Jun

REPOSITORIES: biostudies-literature