SARS-CoV-2 Pandemic Preventive Methods Efficacy - A Simulation Case Study

  1. Malak Saad
  2. Emad M. Boctor

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Abstract

The world has been facing the SARS-CoV-2, a.k.a. COVID-19, pandemic with different preventive methods including social distancing, face masking, screening tests (a.k.a. active surveillance), and vaccination. There are many publications and studies on the efficacy of each of these preventive methods for the last couple of years. Not all methods are readily available in each country and not all methods are accepted by all people in each society.

In this study, we explore the interaction of the three preventive methods: face masking, vaccinations, and screening tests. We study a confined space to represent schools, businesses, or healthcare facilities and we model the spread of the COVID-19 virus for a 60-day period among a sample population while varying the percentage of people adopting one or more of the three preventive methods.

To interpret the simulation results, we define a (Health Goal) target, for example achieving <5% infection rate, i.e., protecting 95% or more of the sample population. We then construct a (Decision Tree) that depicts all valid combinations that achieve this goal. Multiple scenarios are derived from the decision tree to guide decision makers in drawing effective policies to contain the virus spread. We demonstrate a ramping vaccination rate scenario, a removal of the face-masking mandate scenario, and a cost-minimizing goal scenario.

The study highlights the efficacy of combining the three prevention methods to constrain the virus spread among the sample population. For example, results show that a combination of 0% vaccination rate, 6% daily screening test rate, and 80% face masking rate will achieve the target ≥95 protection rate, which can represent a scenario in which vaccination is not yet readily available. As the vaccination rate ramps up to 80% among the sample population, the screening test rate can be 0%, while the face masking rate can be as low as 5% to still achieve the health target. Many other scenarios are derived from this study to meet the defined health target, which represents the flexibility afforded to policy and decision makers when trying to adopt a combination of these preventive methods to contain virus spread.

The study also reveals the higher efficiency of either the vaccination or screening test over face masking under the assumed virus transmissibility rates in the study.

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  1. ScreenIT

    SciScore for 10.1101/2021.10.17.21265111: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    The simulation study is based on the Coronavirus Simulation Matlab program written by Joshua Gafford27, which is a recreation of the Washington Post COVID-19 simulation study.
    Matlab
    suggested: (MATLAB, RRID:SCR_001622)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    Results from scite Reference Check: We found no unreliable references.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. Version published to 10.1101/2021.10.17.21265111v1 on medRxiv