Modeling the Effects of Intervention Strategies on COVID-19 Transmission Dynamics

29 Pages Posted: 13 May 2020

See all articles by Deanna Kennedy

Deanna Kennedy

Texas A&M University

Gustavo Zambrano

Arena235 Research Lab

Yiyu Wang

Texas A&M University

Osmar Pinto Neto

Universidade Anhembi Morumbi

Date Written: May 8, 2020

Abstract

Objectives: To model the effects of continuous, intermittent, and stepping-down social distancing (SD) strategies and personal protection measures on COVID-19 transmission dynamics.

Methods: Constant, intermittent, and stepping-down SD strategies were modeled at 4 mean magnitudes (5%, 10%, 15% and 20%), 2 time windows (40-days, 80-days), and 2 levels of personal caution (30% and 50%).

Results: The stepping-down strategy was the best long-term SD strategy to minimize the peak number of active COVID-19 cases and associated deaths. The stepping-down strategy also resulted in a reduction in total time required to SD over a two-year period by 6.5% compared to an intermittent or constant SD strategy. An 80-day SD time-window was statistically more effective in maintaining control over the COVID-19 pandemic than a 40-day window. However, the results were dependent upon 50% of people being cautious (engaging in personal protection measures).

Conclusion: If people exercise caution while in public by protecting themselves (e.g., wearing a facemask, proper hand hygiene and avoid agglomeration) the magnitude and duration of SD necessary to maintain control over the pandemic can be reduced. Our models suggest that the most effective way to reduce SD over a two-year period is a stepping-down approach every 80 days. According to our model, this method would prevent a second peak and the number of intensive care units needed per day would be within the threshold of those currently available.

Note: Funding: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors

Conflict of Interest: The authors declare no conflict of interest

Ethical Statement: Patients did not participate in this study.

Keywords: COVID-19, mathematical modeling, compartmental model, intervention strategies, pandemic

Suggested Citation

Kennedy, Deanna and Zambrano, Gustavo and Wang, Yiyu and Neto, Osmar Pinto, Modeling the Effects of Intervention Strategies on COVID-19 Transmission Dynamics (May 8, 2020). Available at SSRN: https://ssrn.com/abstract=3595898 or http://dx.doi.org/10.2139/ssrn.3595898

Deanna Kennedy

Texas A&M University ( email )

Langford Building A
798 Ross St.
College Station, TX 77843-3137
United States

Gustavo Zambrano

Arena235 Research Lab ( email )

São José dos Campos
Brazil

Yiyu Wang

Texas A&M University ( email )

Langford Building A
798 Ross St.
College Station, TX 77843-3137
United States

Osmar Pinto Neto (Contact Author)

Universidade Anhembi Morumbi ( email )

Rua Casa do Ator 90
Sao Paulo, SP 04546000
Brazil

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