Modeling the Epidemic Dynamics of COVID-19 Outbreak in Iran

  1. Majid Einian
  2. Hamid Reza Tabarraei

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Abstract

The COVID-19 impact on global health and economic system has been profound and unseen since the Spanish flu of 1918-19. Iran is one of the countries that has been severely affected partly because of slow responses to the crisis, ill-preparedness of the health system, and fragile health infrastructure and shortage of protective equipment due to economic sanctions. Due to shortcomings in the reported data, this note tries to estimate a model-based number of infected cases and examines the effectiveness of different policy responses to contain this crisis. Our results show that in an optimistic estimation, the number of unidentified cases can be 3 to 6 times more than the reported numbers. Social distancing alone cannot be an effective policy at this stage of pandemic unless at least 80 percent of the population confine themselves for an extended period of time. An alternative policy is to increase testing extensively and isolate identified cases actively combined with effective social distancing. Otherwise, many lives will be lost and the health system will collapse, adding to the ongoing economic crisis as a result of sanctions for many years to come.

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  1. ScreenIT

    SciScore for 10.1101/2020.03.27.20045849: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    No key resources detected.

    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.

    About SciScore

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  2. Version published to 10.1101/2020.03.27.20045849v2 on medRxiv
  3. Version published to 10.1101/2020.03.27.20045849v1 on medRxiv