Jiarong Xie, Xiangrong Wang, Ling Feng, Jin-Hua Zhao, Wenyuan Liu, Yamir Moreno, and Yanqing Hu

PNAS Vol. 119 | No. 9

Increasing empirical evidence in diverse social and ecological systems has shown that indirect interactions play a pivotal role in shaping systems’ dynamical behavior. Our empirical study on collaboration networks of scientists further reveals that an indirect effect can dominate over direct influence in behavioral spreading. However, almost all models in existence focus on direct interactions, and the general impact of indirect interactions has not been studied. We propose a new percolation process, termed induced percolation, to characterize indirect interactions and find that indirect interactions raise a plethora of new phenomena, including the wide range of possible phase transitions. Such an indirect mechanism leads to very different spreading outcomes from that of direct influences.

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Allisandra G. Kummer, Juanjuan Zhang, Maria Litvinova, Alessandro Vespignani, Hongjie Yu, Marco Ajelli

Considerable uncertainties surround 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 found a significant inverse relationship between number of contacts and temperature seasonal trend (p=0.003) and temperature daily variation (p=0.009), with contacts increasing from 19.6 (95%CI: 14.9-22.2) in December to 24.4 (95%CI: 19.0-28.0) in January and declining to 10.9 (95%CI: 10.1-11.9) in May. This seasonal trend in number of contacts translates into a seasonal trend in the basic reproduction number – mean number of secondary cases generated by a typical infector in a fully susceptible population. By setting the basic reproduction number at 1.4 on December 24, weekly mean estimates showed a clear increasing trend during the fall, beginning at 1.14 (95%CI: 0.78-1.39) in October and reaching 2.02 (95%CI: 1.60-1.35) in February and then remaining below 1 in the summer. Epidemic dynamics comparable with those of seasonal influenza are obtained through model simulations when the infection is seeded during the fall; however, their dynamics become more complex when seeded after February (e.g., double peaks or no epidemic until after the summer). Our findings indicate a distinct seasonal trend among human contact patterns and highlight a behavioral mechanism contributing to the seasonality of respiratory infectious diseases.

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Gabriela Lobinska, Ady Pauzner, Arne Traulsen, Yitzhak Pilpel & Martin A. Nowak 
Nature Human Behaviour volume 6, pages193–206 (2022)

The greatest hope for a return to normalcy following the COVID-19 pandemic is worldwide vaccination. Yet, a relaxation of social distancing that allows increased transmissibility, coupled with selection pressure due to vaccination, will probably lead to the emergence of vaccine resistance. We analyse the evolutionary dynamics of COVID-19 in the presence of dynamic contact reduction and in response to vaccination. We use infection and vaccination data from six different countries. We show that under slow vaccination, resistance is very likely to appear even if social distancing is maintained. Under fast vaccination, the emergence of mutants can be prevented if social distancing is maintained during vaccination. We analyse multiple human factors that affect the evolutionary potential of the virus, including the extent of dynamic social distancing, vaccination campaigns, vaccine design, boosters and vaccine hesitancy. We provide guidelines for policies that aim to minimize the probability of emergence of vaccine-resistant variants.

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