Overdispersion in COVID-19 increases the effectiveness of limiting nonrepetitive contacts for transmission control

Kim Sneppen, Bjarke Frost Nielsen, Robert J Taylor, Lone Simonsen

Research output: Contribution to journalJournal articlepeer-review

Abstract

Increasing evidence indicates that superspreading plays a dominant role in COVID-19 transmission. Recent estimates suggest that the dispersion parameter k for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is on the order of 0.1, which corresponds to about 10% of cases being the source of 80% of infections. To investigate how overdispersion might affect the outcome of various mitigation strategies, we developed an agent-based model with a social network that allows transmission through contact in three sectors: “close” (a small, unchanging group of mutual contacts as might be found in a household), “regular” (a larger, unchanging group as might be found in a workplace or school), and “random” (drawn from the entire model population and not repeated regularly). We assigned individual infectivity from a gamma distribution with dispersion parameter k. We found that when k was low (i.e., greater heterogeneity, more superspreading events), reducing random sector contacts had a far greater impact on the epidemic trajectory than did reducing regular contacts; when k was high (i.e., less heterogeneity, no superspreading events), that difference disappeared. These results suggest that overdispersion of COVID-19 transmission gives the virus an Achilles’ heel: Reducing contacts between people who do not regularly meet would substantially reduce the pandemic, while reducing repeated contacts in defined social groups would be less effective.
Original languageEnglish
Article numbere2016623118
JournalProceedings of the National Academy of Sciences of the United States of America
Volume118
Issue number14
ISSN0027-8424
DOIs
Publication statusPublished - 6 Apr 2021

Keywords

  • Mitigation strategies
  • Overdispersion
  • Pandemic
  • Social networks
  • Superspreading

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