Halting SARS-CoV-2 by targeting high-contact individuals

Abstract

Two decades ago network scientists proposed that infectious diseases may be effectively halted by targeting interventions at a minority of highly connected individuals. Can this strategy be effective in combating a disease transmitted through physical proximity such as the contemporary SARS-CoV-2? The strategy's effectiveness critically depends on high between-person variability in close-range contacts. We analyze population survey data showing that indeed the frequency of close-range contacts across individuals is characterized by a small fraction of people reporting very high frequencies of close-range contacts. We simulate a population with empirical contact distributions coming out of lockdown. Simulations show that targeting a small fraction of high-degree individuals dramatically improves containment. Our results further suggest two concrete procedures for identifying high-contact individuals: acquaintance sampling and employment-based target.