Mathematical estimation of COVID-19 prevalence in Latin America

  1. Marcos Matabuena
  2. Pablo Rodríguez-Mier
  3. Carlos Meijide-García
  4. Víctor Leborán
  5. Francisco Gude

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

After the rapid spread with severe consequences in Europe and China, the SARS-CoV-2 virus is now manifesting itself in more vulnerable countries, including those in Latin America. In order to guide political decision-making via epidemiological criteria, it is crucial to assess the real impact of the epidemic. However, the use of large-scale population testing is unrealistic or not feasible in some countries. Based on a newly developed mathematical model, we estimated the seroprevalence of SARS-CoV-2 in Latin American countries. The results show that the virus spreads unevenly across countries. For example, Ecuador and Brazil are the most affected countries, with approximately 3% of the infected population. Currently, the number of new infections is increasing in all countries examined, with the exception of some Caribbean countries as Cuba. Moreover, in these countries, the peak of newly infected patients has not yet been reached.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.06.09.20126326: (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 variablenot detected.

    Table 2: Resources

    No key resources detected.

    Results from OddPub: Thank you for sharing your code.

    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 10.1101/2020.06.09.20126326v1 on medRxiv