COVID-19 epidemic in Malaysia: Impact of lockdown on infection dynamics

  1. Naomie Salim
  2. Weng Howe Chan
  3. Shuhaimi Mansor
  4. Nor Erne Nazira Bazin
  5. Safiya Amaran
  6. Ahmad Athif Mohd Faudzi
  7. Anazida Zainal
  8. Sharin Hazlin Huspi
  9. Eric Khoo Jiun Hooi
  10. Shaekh Mohammad Shithil

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Abstract

COVID-19 epidemic in Malaysia started as a small wave of 22 cases in January 2020 through imported cases. It was followed by a bigger wave mainly from local transmissions resulting in 651 cases. The following wave saw unexpectedly three digit number of daily cases following a mass gathering urged the government to choose a more stringent measure. A limited lock-down approach called Movement Control Order (MCO) was immediately initiated to the whole country as a way to suppress the epidemic trajectory. The lock-down causes a major socio-economic disruption thus the ability to forecast the infection dynamic is urgently required to assist the government on timely decisions. Limited testing capacity and limited epidemiological data complicate the understanding of the future infection dynamic of the COVID-19 epidemic. Three different epidemic forecasting models was used to generate forecasts of COVID-19 cases in Malaysia using daily reported cumulative case data up until 1st April 2020 from the Malaysia Ministry of Health. The forecasts were generated using a Curve Fitting Model with Probability Density Function and Skewness Effect, the SIR Model, and a System Dynamic Model. Method one based on curve fitting with probability density function estimated that the peak will be on 19th April 2020 with an estimation of 5,637 infected persons. Method two based on SIR Model estimated that the peak will be on 20th - 31st May 2020 if Movement Contro (MCO) is in place with an estimation of 630,000 to 800,000 infected persons. Method three based on System Dynamic Model estimated that the peak will be on 17th May 2020 with an estimation of 22,421 infected persons. Forecasts from each of model suggested the epidemic may peak between middle of April to end of May 2020.

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    SciScore for 10.1101/2020.04.08.20057463: (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
    For Malaysia, daily data has been published by the STAR [25], Malaysiakini [26] and also by the Ministry of Health Malaysia [8-10].
    STAR
    suggested: (STAR, RRID:SCR_015899)

    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.

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  2. Version published to 10.1101/2020.04.08.20057463v1 on medRxiv