Informing pandemic intervention strategies through coupled contact tracing and network node prioritization

SARS-CoV-2 has highlighted the challenges of social intervention measures for disease control, which are difficult to implement and highly disruptive to modern society. Simulation models have demonstrated the efficacy of primary and secondary tracing at SARSCoV-2 disease control but at the cost of quarantining large proportions of the population. This paper develops novel tracing strategies that harness node (individual) influence in a social association network for contact-tracing approaches to disease control. The overarching assumption is that an individual’s potential to spread disease can be modeled by their ability to propagate influence through a network. Models of idea and influence propagation have been widely studied in the context of social networks but have limited application to disease models. The PRIoritization and Complex Elucidation (PRINCE) algorithm is leveraged to estimate an individual node’s influence score that reflects their ability to propagate disease based on network connectivity. In this study, we propose novel augmented tracing strategies that leverage a node’s influence to assist with targeted tracing in its 1-hop and 2-hop neighborhoods: i) pseudo-secondary tracing (tracing and quarantining the immediate contacts and the influential contacts of contacts of an infectious symptomatic individual) and ii) selective secondary tracing (tracing and quarantining the influential immediate contacts, and influential contacts of contacts of an infectious symptomatic individual). Contagion dynamics on simulated and real-world networks, benchmarked with existing strategies, demonstrate that our novel strategies mitigate societal disruption by lowering the maximum number of people quarantined concurrently while also assisting the ease of on-ground deployment by reducing the number of individuals to be traced for every infectious individual detected when compared with the most effective existing tracing strategy. Novel approaches of this type that embed network influence into pandemic control provide an opportunity for disease control that ultimately lessens the disruption to society.