COVID-19 DEATH TOLL: THE ROLE OF THE NATION’S ECONOMIC DEVELOPMENT

  1. Gabriel Chodick
  2. Clara Weil

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

Background

Several months into the novel coronavirus disease (COVID-19) pandemic, there is a limited understanding of the underlying country-specific factors associated with COVID-19 spread and mortality. This study aims to investigate the role of nations’ economic development in the death toll associated with COVID-19 in Europe and Israel.

Methods

Number of COVID-19 cases, deaths per million, and case fatality rate (CFR) in Israel and 39 countries in Europe were described across quintiles of gross domestic product (GDP) per capita. The association between GDP per capita and COVID-19 incidence, mortality, and CFR was investigated using generalized linear modeling adjusting for the proportion of elderly and density of the population.

Results

In countries belonging to the three lower GDP quintiles, COVID-19 incidence rates per million (range 708-1134) were substantially lower compared to countries in the fourth (3939) and fifth (3476) quintiles. Major differences were also calculated in COVID-19 mortality rates per million (25-31 vs. 222-268). There was no significant (p=0.19) differences in CFR between GDP quintiles (range: 2.79-7.62%).

Conclusions

COVID-19 had a greater toll in more developed nations. Though comparisons are limited by differences in testing, reporting and lockdown policies, this association likely reflects increased spread from trade and tourism in wealthier countries, whereas limited health system capacity and lack of treatment and vaccination options contributed to higher than expected CFR in wealthier countries. This unique situation will probably encourage the stronger economies to invest the required financial capacity to respond to and recover from the current crisis.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.07.18.20156778: (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: 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.

    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 10.1101/2020.07.18.20156778v1 on medRxiv