Epidemiological characteristics of SARS-COV-2 in Myanmar

  1. Aung Minn Thway
  2. Htun Teza
  3. Tun Tun Win
  4. Ye Min Htun
  5. Moe Myint Aung
  6. Yan Naung Win
  7. Kyaw Myo Tun

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Abstract

Coronavirus disease (COVID-19) is an infectious disease caused by a newly discovered severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In Myanmar, first COVID-19 reported cases were identified on 23 rd March 2020. There were 336 reported confirmed cases, 261 recovered and 6 deaths through 13 th July 2020. The study was a retrospective case series and all COVID-19 confirmed cases from 23 rd March to 13 th July 2020 were included. The data series of COVID-19 cases were extracted from the daily official reports of the Ministry of Health and Sports (MOHS), Myanmar and Centers for Disease Control and Prevention (CDC), Myanmar. Among 336 confirmed cases, there were 169 cases with reported transmission events. The median serial interval was 4 days (IQR 3, 2-5) with the range of 0 - 26 days. The mean of the reproduction number was 1.44 with (95% CI = 1.30-1.60) by exponential growth method and 1.32 with (95% CI = 0.98-1.73) confident interval by maximum likelihood method. This study outlined the epidemiological characteristics and epidemic parameters of COVID-19 in Myanmar. The estimation parameters in this study can be comparable with other studies and variability of these parameters can be considered when implementing disease control strategy in Myanmar.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.02.20166504: (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 distributions of age and sex, epidemic curve and distribution of estimated serial interval were shown by GraphPad Prism version 7(GraphPad Software).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    The data were analyzed using Excel version 2016, R0 package (version 1.2-6 released in May 2015) and Epicontacts package (version 1.1.1 released in May 2017) of R environment (version 3.6.2 released in December 2019).
    Excel
    suggested: None

    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:
    This study is an epidemiological characteristic of COVID-19 cases in Myanmar, and we recognize the following limitations. First, the actual cases in the country within the study period could be underestimated due to low testing capabilities. Second, the recall bias of cases might have affected data accuracy because of self-reported contact history and symptom onset. Third, with slight inaccuracies of epidemiological information on confirmed cases reported by MOHS, more detailed information regarding date of symptom onset and clinical features were unavailable at the time of analysis. Therefore, dates of test positive of confirmed cases were inferred as the dates of symptom onset to explore the serial interval of transmission event. The closed contacts were identified within a few days after confirmation of their contact history, and were kept at quarantined centers till the result came out. It could be expected that the variation of this duration would be minimal. Fourth, for some patients, the official reports link the person with multiple confirmed cases as contacts. This is not a problem unique to our study but in the other similar studies as well, especially in clusters. This is addressed by considering the earliest confirmed case of the contacts as the source.

    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 10.1101/2020.08.02.20166504v1 on medRxiv