Temporal Shifts in Climate-Influenza Dynamics: A Multi-Subtype Analysis in Southern China Spanning the COVID-19 Era.

ABSTRACT: Background: The COVID-19 pandemic disrupted global influenza transmission. We aimed to elucidate how meteorological and air pollution drivers influenced seasonal influenza A subtypes and B lineage in Southern China pre-, during-, and postpandemic. Methods: We analyzed weekly influenza surveillance data from Southern China (2011-2024) and corresponding meteorological data. Using an interpretable machine learning framework combining XG-Boost and SHapley Additive exPlanation (SHAP), we quantified the dynamic contributions of environmental factors to influenza subtype positivity rates. GAM models were employed to identify climate thresholds for influenza transmission. Findings: The pandemic reshaped influenza transmission and environmental dependencies in Southern China. P

SUBMITTER: Zhang L 

PROVIDER: S-EPMC12360877 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature