Correlation of the global spread of coronavirus disease-19 with atmospheric air temperature

  1. Yihienew M. Bezabih
  2. Alemitu Mequanint
  3. Endalkachew Alamneh
  4. Alemayehu Bezabih
  5. Wilber Sabiiti
  6. Anna Roujeinikova
  7. Woldesellassie M. Bezabhe

Reviewed by

Read the full article

Discuss this preprint

Start a discussion What are Sciety discussions?

Listed in

Log in to save this article

Abstract

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an enveloped virus that may be sensitive to heat. We assessed whether the spread of coronavirus disease 2019 (COVID-19) correlates with air temperature. We also studied whether additional climate, geographical, and population variables were correlated. The total number of confirmed COVID-19 cases and mortality rates reported in each country between 1 st Jan and 31 st Mar 2020 were compared with the country’s three-month average atmospheric air temperature, precipitation and latitude. Spearman’s correlation coefficient (ρ) was used to identify significant correlations. Our analysis included a total of 748,555 confirmed COVID-19 cases worldwide. The total number of patients with COVID-19 decreased with increasing atmospheric air temperature (ρ = –0.54, 95%CI: [-0.64, –0.42]; P <0.001) and increased with an increasing latitude (ρ = 0.60, 95%CI: [0.48, 0.70]; P <0.001). Our findings justify further studies to examine the effect of air temperature on infectivity of SAR-CoV-2.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.05.27.20115048: (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

    Software and Algorithms
    SentencesResources
    The population density of countries was obtained from https://data.worldbank.org/, and data on the national BCG policy and World Bank income group classification of individual countries were obtained from the BCG world atlas http://www.bcgatlas.org/) [27].
    https://data.worldbank.org/
    suggested: (Data World Bank, RRID:SCR_012767)
    Further correlations were performed for countries with ongoing and ceased BCG vaccination programs. 2.4. Statistical Analysis: Spearman correlation coefficient (ρ) was obtained from bivariate correlation analysis using GraphPad Prism version 8.0.2 for Windows (GraphPad Software, San Diego, Cal., USA).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Partial correlation analysis and the Kaiser-Meyer-Olkin measure of sampling adequacy (KMO) and Bartlett’s test of sphericity was performed using SPSS Statistics for Windows, version 23.0 (SPSS Inc., Chicago, Ill., USA).
    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 has several limitations. First, since most of the variables were already interrelated, the multivariate model (partial correlation analysis) did not give statistically significant associations. The second major limitation is that COVID-19 epidemic is still unfolding in most of the tropical countries particularly Africa. Nevertheless, considering case rate increase, case incidence rate was lower in some African countries relative to European countries using the same testing strategy. There could also be many other unidentified factors behind the case incidence rate reported in each country.

    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 10.1101/2020.05.27.20115048 on medRxiv