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 and Sean D. Young
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Akihiro Nishi: Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095; California Center for Population Research, University of California, Los Angeles, CA 90095; Bedari Kindness Institute, University of California, Los Angeles, CA 90095;
George Dewey: Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, CA 90095;
Akira Endo: Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine, WC1E 7HT London, United Kingdom; The Alan Turing Institute, NW1 2DB London, United Kingdom
Sophia Neman: School of Medicine, Medical College of Wisconsin, Wauwatosa, WI 53213
Sage K. Iwamoto: College of Letters & Science, University of California, Berkeley, CA 94720
Michael Y. Ni: School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China; The State Key Laboratory of Brain and Cognitive Sciences, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China; Healthy High Density Cities Lab, HKUrbanLab, The University of Hong Kong, 999077, Hong Kong Special Administrative Region, China
Yusuke Tsugawa: Division of General Internal Medicine and Health Services Research, David Geffen School of Medicine, University of California, Los Angeles, CA 90024; Department of Health Policy and Management, Fielding School of Public Health, University of California, Los Angeles, CA 90095
Georgios Iosifidis: School of Computer Science and Statistics, Trinity College Dublin, Dublin 2, Ireland
Justin D. Smith: Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City, UT 84108; Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611; Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611; Department of Pediatrics, Feinberg School of Medicine, Northwestern University, Chicago, IL 60611
Sean D. Young: University of California Institute for Prediction Technology, Department of Informatics, University of California, Irvine, CA 92617; Department of Emergency Medicine, University of California, Irvine, CA 92868

Proceedings of the National Academy of Sciences, 2020, vol. 117, issue 48, 30285-30294

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).

Keywords: COVID-19; pandemic preparedness; agent-based simulation; network interventions (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:nas:journl:v:117:y:2020:p:30285-30294

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