Estimating COVID-19-Related Infections, Deaths, and Hospitalizations in Iran Under Different Physical Distancing and Isolation Scenarios

  1. Hamid Sharifi
  2. Yunes Jahani
  3. Ali Mirzazadeh
  4. Milad Ahmadi Gohari
  5. Mehran Nakhaeizadeh
  6. Mostafa Shokoohi
  7. Sana Eybpoosh
  8. Hamid Reza Tohidinik
  9. Ehsan Mostafavi
  10. Davood Khalili
  11. Seyed Saeed Hashemi Nazari
  12. Mohammad Karamouzian
  13. Ali Akbar Haghdoost

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Abstract

Background: Iran is one of the first few countries that was hit hard with the coronavirus disease 2019 (COVID-19) pandemic. We aimed to estimate the total number of COVID-19 related infections, deaths, and hospitalizations in Iran under different physical distancing and isolation scenarios. Methods: We developed a susceptible-exposed-infected/infectious-recovered/removed (SEIR) model, parameterized to the COVID-19 pandemic in Iran. We used the model to quantify the magnitude of the outbreak in Iran and assess the effectiveness of isolation and physical distancing under five different scenarios (A: 0% isolation, through E: 40% isolation of all infected cases). We used Monte-Carlo simulation to calculate the 95% uncertainty intervals (UIs). Results: Under scenario A, we estimated 5 196 000 (UI 1 753 000-10 220 000) infections to happen till mid-June with 966 000 (UI 467 800-1 702 000) hospitalizations and 111 000 (UI 53 400-200 000) deaths. Successful implantation of scenario E would reduce the number of infections by 90% (ie, 550 000) and change the epidemic peak from 66 000 on June 9, to 9400 on March 1, 2020. Scenario E also reduces the hospitalizations by 92% (ie, 74 500), and deaths by 93% (ie, 7800). Conclusion: With no approved vaccination or therapy available, we found physical distancing and isolation that include public awareness and case-finding and isolation of 40% of infected people could reduce the burden of COVID-19 in Iran by 90% by mid-June.

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  1. Version published to 10.34172/ijhpm.2020.134
  2. ScreenIT

    SciScore for 10.1101/2020.04.22.20075440: (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: 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: We detected the following sentences addressing limitations in the study:
    Our study had three major limitations. First, some of the key parameters (e.g. hospitalization rate, incubation period, transmission probability) that were used in the model were from other countries or expert opinion, but not from empirical data from Iran. To address this limitation, we reported a range of uncertainty intervals. Second, the uncertainty intervals are fairly wide for most of our results which resulted from the uncertainty in model parameters. Third, our projection for the course of the epidemic in the coming months in Iran is based on the assumption we made about implementing and sustaining the physical distancing as planned, and any changes in policy and public interventions may change the course of the epidemic. Despite these limitations, our results under different scenarios provide a foundation to measure the effect of interventions that are ongoing in the country. With no approved vaccination, prophylaxis or therapy, we found physical distancing and isolation that includes public awareness and case-finding/isolation of 40% of the infected cases could reduce the burden of COVID-19 in Iran by 90% by mid-June.

    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.

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  3. Version published to 10.1101/2020.04.22.20075440v1 on medRxiv