Modeling COVID-19 epidemic trends and health system needs leading to projections for developing countries: a case study of Thailand

  1. Nawaphan Metchanun
  2. Christian Borgemeister
  3. Caitlin Bever
  4. David Galick

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Thailand was the first country outside China to report a COVID-19 case but had a mild impact from the outbreak especially at the beginning of the pandemic. This study systematically investigates the evolution of the COVID-19 epidemic in Thailand from January 2020 to March 2021 to uncover the COVID-19 situation in the country. By modeling all health districts throughout the country, the study found that COVID-19 contributed to an increase in excess deaths and that COVID-19 deaths might be underreported. There was a lag time in ramping up testing although testing is key to control the disease. The estimated total number of beds required by COVID-19 seems low, but it may not ensure the capacity to take care of critical cases that required ICU beds, specific medical equipment, and trained medical staff.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2021.11.05.21265992: (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: Thank you for sharing your code and data.

    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.

    Results from scite Reference Check: We found no unreliable references.

    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 10.1101/2021.11.05.21265992v1 on medRxiv