Networks and Epidemics: Designing network-based intervention strategies from edge-based infection probability

Epidemics underscore the critical role of human contact networks in shaping the spread of infectious diseases. The transmission varies depending on a range of factors, including the virus characteristics, the type and duration of contact, and whether it occurs indoor or outdoor. However, not only does the probability of transmission differ, but the impact of each transmission event depends on the ability of a single transmission event to transmit the virus to new, previously unaffected, socially segmented groups in society. Effective policy-making should be guided by a nuanced understanding of how infections spread , ensuring that interventions are proportional to the risk they aim to address. In this study, we performed a number of theoretical experiments on generated networks that are structurally similar to real social contact networks. We simulated a fictitious epidemic on different sample graphs and with different contact restrictions, and then compared the trajectories. Based on the observed differences, we identified the contact types whose restriction can have effect in curbing the epidemic. We find that it is particularly worth focusing on the relationships that form a bridge between clusters or communities. By doing so, public health efforts can more successfully balance the dual goals of minimizing transmission and maintaining social and economic stability.