COVID-19 Outcomes in Saudi Arabia and the UK: A Tale of Two Kingdoms

  1. Saleh Komies
  2. Abdulelah M. Aldhahir
  3. Mater Almehmadi
  4. Saeed M. Alghamdi
  5. Ali Alqarni
  6. Tope Oyelade
  7. Jaber S. Alqahtani

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

While the number of COVID-19 cases and deaths around the world is starting to peak, it is essential to point out how different countries manage the outbreak and how different measures and experience resulted in different outcomes. This study aimed to compare the effect of the measures taken by Saudi Arabia and the United Kingdom (UK) governments on the outcome of the COVID-19 pandemic as predicted by a mathematical model.

Method

Data on the numbers of cases, deaths and government measures were collected from Saudi’s Ministry of Health and Public Health England. A prediction of the trend of cases, deaths and days to peak was then modelled using the mathematical technique, Exponential Logistic Growth and Susceptible Infectious Recovered (SIR) model. The measures taken by the governments and the predicted outcomes were compared to assess effectiveness.

Result

We found over three months that 22 fast and extreme measures had been taken in Saudi Arabia compared to eight slow and late measures in the UK. This resulted in a decline in numbers of current infected cases per day and mortality in Saudi Arabia compared to the UK. Based on the SIR model, the predicted number of COVID-19 cases in Saudi as of 31st of March was 2,064, while the predicted number of cases was 63012 in the UK. In addition, the pandemic is predicted to peak earlier on the 27th of March in Saudi Arabia compared to the 2nd of May 2020 in the UK. The end of transition phases for Saudi and UK according to the model, were predicted to be on 18th of April and 24th of May, respectively. These numbers relate to early and decisive measures adopted by the Saudi government.

Conclusion

We show that early extreme measures, informed by science and guided by experience, helped reduce the spread and related deaths from COVID-19 in Saudi. Actions were taken by Saudi under the national slogan “We are all responsible” resulted in the observed reduced number of current and predicted cases and deaths compared to the UK approach “keep calm and carry on”.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.25.20079640: (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 algorithm is available online on the MathWorks website and runs on MATLAB program software (29).
    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.

    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 10.1101/2020.04.25.20079640v1 on medRxiv