Halting SARS-CoV-2 by Targeting High-Contact Individuals
Gianluca Manzo () and
Arnout van de Rijt ()
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Gianluca Manzo: https://www.gemass.fr/manzo/
Arnout van de Rijt: https://www.eui.eu/DepartmentsAndCentres/PoliticalAndSocialSciences/People/Professors/Van-de-Rijt
Journal of Artificial Societies and Social Simulation, 2020, vol. 23, issue 4, 10
Network scientists have proposed that infectious diseases involving person-to-person transmission could be effectively halted by interventions targeting a minority of highly connected individuals. Could this strategy be effective in combating a virus partly transmitted in close-range contact, as many believe SARS-CoV-2 to be? Effectiveness critically depends on high between-person variability in the number of close-range contacts. We analyzed population survey data showing that the distribution of close-range contacts across individuals is indeed characterized by a small proportion of individuals reporting very high frequency contacts. Strikingly, we found that the average duration of contact is mostly invariant in the number of contacts, reinforcing the criticality of hubs. We simulated a population embedded in a network with empirically observed contact frequencies. Simulations showed that targeting hubs robustly improves containment.
Keywords: Agent-Based Computational Models; Complex Social Networks; Virus Diffusion; Immunization Strategies; Epidemiological Models (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:jas:jasssj:2020-83-3
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