Ecologic correlation between underlying population level morbidities and COVID-19 case fatality rate among countries infected with SARS-CoV-2

  1. Evaezi Okpokoro
  2. Victoria Igbinomwanhia
  3. Elima Jedy-Agba
  4. Gbenga Kayode
  5. Ezenwa James Onyemata
  6. Alash’le Abimiku

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Background

The ongoing Coronavirus disease 2019 (COVID-19) pandemic is unprecedented in scope. High income countries (HIC) seemingly account for the majority of the mortalities considering that these countries have screened more persons. Low middle income countries (LMIC) countries may experience far worse mortalities considering the existence of a weaker health care system and the several underlying population level morbidities. As a result, it becomes imperative to understand the ecological correlation between critical underlying population level morbidities and COVID-19 case fatality rates (CFR).

Method

This is an ecological study using data on COVID-19 cases, prevalence of COPD, prevalence of tobacco use, adult HIV prevalence, quality of air and life expectancy. We plotted a histogram, performed the Shapiro-Wilk normality test and used spearman correlation to assess the degree of correlation between COVID-19 case fatality rate (CFR) and other covariates mentioned above.

Result

As at the 31 st of March 2020, there were a total of 846,281 cases of COVID-19 from 204 countries and a global case fatality rate of 5% (range 0% to 29%). Angola and Sudan both had the highest CFR of 29%, while Italy had the highest number of deaths (i.e. 12,428) as at 31 st of March 2020. Adult HIV prevalence has a significant but weak negative correlation with CFR (correlation coefficient = - 0.24, p value =0.01) while all the other variables have positive correlation with CFR due to COVID-19 though not statistically significant. Of the 204 countries analyzed, only 11 countries (i.e. 5%) had complete datasets across all 5 population level morbidities (i.e. prevalence of COPD, prevalence of tobacco use, life expectancy, quality of air, and adult HIV prevalence variables). Correlations of CFR from these 11 countries were similar to that from the 204 countries except for the correlation with quality of air and prevalence of tobacco use. Conclusion: While we interpret our data with caution given the fact that this is an ecological study, our findings suggest that population level factors such as prevalence of COPD, prevalence of tobacco use, life expectancy and quality of air are positively correlated with CFR from COVID-19 but, adult HIV prevalence has a weak and negative correlation with COVID-19 CFR and would require extensive research.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.04.28.20082370: (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: 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:
    An important limitation of this study is the ecological nature of the study, hence, findings must be interpreted with caution and should not be directly extrapolated to individual levels. Secondly, COVID-19 is a rapidly evolving disease and total numbers of confirmed cases and mortality figures are constantly changing. Thirdly, the datasets used for our analysis were publicly available on the internet and may not be accurate as officially published estimates by the respective countries included in our study. However, our study presents data from 204 countries worldwide on 846, 281 confirmed cases of COVID-19. Additionally, this study also provides useful information on population level factors that may contribute to the noticeable differences in mortality rates worldwide, which is an issue of significant interest to epidemiologists, clinicians, and public health policy makers worldwide.

    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 10.1101/2020.04.28.20082370v1 on medRxiv