Modeling the Effect of Asymptomatic Cases, Social Distancing, and Lockdowns in the First and Second waves of the COVID-19 Pandemic: A Case Study of Italy

  1. Muhamad Khairulbahri

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

The SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns, and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is too high, so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding of the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow. Doi: 10.28991/SciMedJ-2021-0303-8 Full Text: PDF

Article activity feed

  1. Version published to 10.28991/scimedj-2021-0303-8
  2. Version published to 10.1101/2021.01.08.21249273v3 on medRxiv
  3. Version published to 10.1101/2021.01.08.21249273v2 on medRxiv
  4. ScreenIT

    SciScore for 10.1101/2021.01.08.21249273: (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

    No key resources detected.

    Results from OddPub: Thank you for sharing your data.

    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.

    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.

  5. Version published to 10.1101/2021.01.08.21249273v1 on medRxiv