Network interventions for managing the COVID-19 pandemic and sustaining economy
Citation:
Nishi, A. and Dewey, G. and Endo, A. and Neman, S. and Iwamoto, S.K. and Ni, M.Y. and Tsugawa, Y. and Iosifidis, G. and Smith, J.D. and Young, S.D., Network interventions for managing the COVID-19 pandemic and sustaining economy, Proceedings of the National Academy of Sciences of the United States of America, 2020, 117, 48, 30285-30294Download Item:
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).
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Grant Number
Science Foundation Ireland (SFI)
16/IA/4610
Author's Homepage:
http://people.tcd.ie/iosifidg
Author: Iosifidis, Georgios
Sponsor:
Science Foundation Ireland (SFI)Type of material:
Journal ArticleCollections
Series/Report no:
Proceedings of the National Academy of Sciences of the United States of America;117;
48;
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Full text availableDOI:
http://dx.doi.org/10.1073/pnas.2014297117Metadata
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