Comparison of epidemiological characteristics of COVID-19 patients in Vietnam

  1. Toan Ha
  2. Gualberto Ruaño
  3. Lewis Judy

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Abstract

Background

There are limited data on COVID-19 patients in Vietnam. The paper examined and compared epidemiological characteristics of COVID-19 patients in Vietnam

Method

The data was obtained using publicly available information from the official website of Vietnam Ministry of Health covering a period of 01/23/2020 to 05/27/2020. T-test, Chi-square test and Fisher’s Exact test were utilized to compare characteristics of COVID-19 patients between under-treatment and discharge groups and between overseas and non-overseas travel groups.

Results

Vietnam had a total of 327 cases of COVID-19 as of May 27, 2020. The median age of patients was 30 years (ranging from 3 months to 88 years). About 68% of patients (n=223) had acquired the disease from overseas while 32% were infected from local transmission. Among those infected from local transmission, 66% were women. Men were more likely than women to be infected with COVID-19 from overseas (p<0.001). Younger patients were significantly associated with international travel (p=.001). While patients in the South reported highest levels of overseas travel history (77.9%), those (100%) in the Central reported the highest level of being discharged (p<0.001). Women (54.7%) had a higher rate of discharge compared to men (45.3%) [p <0.001]. Nearly 86% have recovered and discharged from hospitals. There has been no reported fatality.

Conclusions

A majority of COVID-19 cases in Vietnam were acquired overseas. A significantly higher number of women than men were infected inside the country calling for further research about gender disparities in the fight against COVID-19 in Vietnam.

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  1. ScreenIT

    SciScore for 10.1101/2020.06.03.20121467: (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 variableFifty percent (n=164) were female (Table 1).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Data sources: The data from this paper was obtained using publicly available information from the official website of the Vietnam Ministry of Health [5] during the period of 01/23/2020 to 05/27/2020 and was entered and organized using SPSS 22.0 (IBM Corp., Armonk, NY).
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 should be interpreted in light of certain limitations. While there is no case fatality yet, 49 patients remain in the hospital and outcomes yet to be known. A time of this writing, Vietnam has not reported any locally transmitted COVID-19 cases for 41-days. All new cases registered since April 16, 2020 are Vietnamese workers and students returning from overseas. However, the pandemic is still going on worldwide, the data therefore should be read as time-dependent and temporary. At this time, no serological data is available on antibody responses in the population.

    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 10.1101/2020.06.03.20121467v2 on medRxiv
  3. Version published to 10.1101/2020.06.03.20121467v1 on medRxiv