  Non-pharmaceutical measures such as preventive quarantines, remote working,
school and workplace closures, lockdowns, etc. have shown effectivenness from
an epidemic control perspective; however they have also significant negative
consequences on social life and relationships, work routines, and community
engagement. In particular, complex ideas, work and school collaborations,
innovative discoveries, and resilient norms formation and maintenance, which
often require face-to-face interactions of two or more parties to be developed
and synergically coordinated, are particularly affected. In this study, we
propose an alternative hybrid solution that balances the slowdown of epidemic
diffusion with the preservation of face-to-face interactions. Our approach
involves a two-step partitioning of the population. First, we tune the level of
node clustering, creating "social bubbles" with increased contacts within each
bubble and fewer outside, while maintaining the average number of contacts in
each network. Second, we tune the level of temporal clustering by pairing, for
a certain time interval, nodes from specific social bubbles. Our results
demonstrate that a hybrid approach can achieve better trade-offs between
epidemic control and complex knowledge diffusion. The versatility of our model
enables tuning and refining clustering levels to optimally achieve the desired
trade-off, based on the potentially changing characteristics of a disease or
knowledge diffusion process.
