Network interventions for managing the COVID-19 pandemic and sustaining economy

Akihiro Nishi*, George Dewey, Akira Endo, Sophia Neman, Sage K. Iwamoto, Michael Y. Ni, Yusuke Tsugawa, Georgios Iosifidis, Justin D. Smith, Sean D. Young

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

15 Scopus citations

Abstract

Sustaining economic activities while curbing the number of new coronavirus disease 2019 (COVID-19) cases until effective vaccines or treatments become available is a major public health and policy challenge. In this paper, we use agent-based simulations of a network-based susceptible−exposed−infectious−recovered (SEIR) model to investigate two network intervention strategies for mitigating the spread of transmission while maintaining economic activities. In the simulations, we assume that people engage in group activities in multiple sectors (e.g., going to work, going to a local grocery store), where they interact with others in the same group and potentially become infected. In the first strategy, each group is divided into two subgroups (e.g., a group of customers can only go to the grocery store in the morning, while another separate group of customers can only go in the afternoon). In the second strategy, we balance the number of group members across different groups within the same sector (e.g., every grocery store has the same number of customers). The simulation results show that the dividing groups strategy substantially reduces transmission, and the joint implementation of the two strategies could effectively bring the spread of transmission under control (i.e., effective reproduction number ≈ 1.0).

Original languageEnglish (US)
Pages (from-to)30285-30294
Number of pages10
JournalProceedings of the National Academy of Sciences of the United States of America
Volume117
Issue number48
DOIs
StatePublished - Dec 1 2020

Keywords

  • COVID-19 | pandemic preparedness | agent-based simulation | network interventions

ASJC Scopus subject areas

  • General

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