ArticleInfectious Disease Modelling2026
Absolute humidity drives seasonal influenza A transmission in Hong Kong through social contact modulation: Evidence from compartmental modeling.
Article in Infectious Disease Modelling, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Prior studies propose a U-shaped humidity-influenza relationship, yet the interplay between humidity-driven contact behaviors and transmission dynamics remains unclear. Objective: The study investigates how absolute humidity (AH) modulates social contact (SC) to drive influenza A transmission, quantifies the relative contributions of AH-mediated contact behavior versus viral survivability, and identifies optimal contact-reduction strategies for outbreak control. Methods: WHO FluNet data (2016-2024), Hong Kong contact surveys, and meteorological records into a genetic algorithm-optimized SEIR model were integrated. The framework dynamically simulates dual AH-dependent transmission mechanisms (behavioral and environmental), evaluates optimal contact-reduction strategies via incidence minimization, and employs LHS/PRCC sensitivity analysis to identify key drivers. Results: Seasonal changes in AH induce cyclical fluctuations in social contact, thereby modulating the influenza A transmission dynamics. The potential effect of AH-driven SC patterns on influenza A has gradually diminished. The GA-optimized SEIR dynamic reveals seasonally heterogeneous requirements for control strategies. The highest risk for outbreak initiation is posed in winter. Contact intervention can reach its peak in winter (intervention intensity reaches 62 %) and summer (intervention intensity is between 16 % and 23 %). Sensitivity analysis highlighted Absolute humidity-modulated infection effect and recovery rate as dominant drivers. Conclusions: The association between absolute humidity and influenza transmission can be attributed to humidity-driven shifts in social contact. This necessitates seasonally tailored interventions: winter strategies should prioritize stringent contact restrictions, while warmer seasons permit relaxed measures. Future models should integrate multi-climate zone validation and dynamic behavioral sensing to improve outbreak predictions.
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