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

Adithya Narayanan, Sarah Muldoon, Matthew Jehrio and Rachael Hageman Blair

PLOS Complex Systems, 2025, vol. 2, issue 6, 1-16

Abstract: 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 SARS-CoV-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.Author summary: Contact tracing to effect quarantines is a common method to stem disease dispersion, of which primary tracing (tracing the immediate contacts of an identified case) and secondary tracing (tracing the immediate contacts and the contacts of contacts of an identified case) are the most employed strategies. Due to the rigorous nature of quarantining 2-hop neighborhoods, the latter is extremely effective in outbreak control, but yields a high number of individuals placed in quarantines simultaneously. This strategy is also rigorous to deploy, owing to the vast number of individuals to be traced for every infection. Adopting a network-based approach to modeling social associations, we identify the most influential nodes in a network - the super spreaders in a community - and harness this information to develop novel tracing strategies that are more effective than primary tracing (reduced cumulative and concurrent infections, isolations, and quarantines). Compared to secondary tracing, these strategies offer a significant reduction in the maximum number of people quarantined concurrently with a minor increase in concurrent infections and isolations- however, with the additional benefit of tracing fewer individuals for every identified case and cumulatively, in most scenarios.

Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pcsy00:0000041

DOI: 10.1371/journal.pcsy.0000041

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