Evaluating seasonal variations in human contact patterns and their impact on the transmission of respiratory infectious diseases

Considerable uncertainty surrounds the seasonality of respiratory infectious diseases. To which extent the observed seasonality is associated with biological reasons (e.g., virus survival rates, host immune dynamics) or human behavior remains unclear. Here, we investigate the association between temperature and human contact patterns using data collected through a contact diary-based survey between December 24, 2017, and May 30, 2018, in Shanghai, China. We identified a significant inverse relationship between the number of contacts and both the seasonal temperature trend (p=0.003) and daily temperature variation (p=0.009). The average number of contacts increased from 18.9 (95% CI: 14.5-21.6) in December to 20.9 (95% CI: 15.4-26.5) in January before decreasing to 11.6 (95% CI: 8.7-14.8) in May. This seasonal trend in the number of contacts translates into a seasonal trend in the reproduction number – the mean number of secondary cases generated by a typical infector. We developed a compartment model of influenza transmission informed by the derived seasonal trends in the number of contact patterns and validated against A(H1N1)pdm09 influenza data for the focus location and study period. We found that the model shows an excellent agreement with the estimated influenza dynamics providing support to the hypothesis that the seasonality in contact patterns shapes influenza transmission dynamics. Our findings contribute to a deeper understanding of the epidemiology of respiratory infectious diseases and could potentially inform improved preparedness planning.