Determinants of the incidence and mortality rates of COVID-19 during the first six months of the pandemic; a cross-country study

  1. Noha Asem
  2. Ahmed Ramadan
  3. Mohamed Hassany
  4. Ramy Mohamed Ghazy
  5. Mohamed Abdallah
  6. Eman M. Gamal
  7. Shaimaa Hassan
  8. Nehal Kamal
  9. Hala Zaid

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Abstract

COVID-19 pandemic raises an extraordinary challenge to the healthcare systems globally. The governments are taking key measures to constrain the corresponding health, social, and economic impacts, however, these measures vary depending on the nature of the crisis and country-specific circumstances.

Objectives

Considering different incidence and mortality rates across different countries, we aimed at explaining variance of these variables by performing accurate and precise multivariate analysis with aid of suitable predictors, accordingly, the model would proactively guide the governmental responses to the crisis.

Methods

Using linear and exponential time series analysis, this research aimed at studying the incidence and mortality rates of COVID-19 in 18 countries during the first six months of the pandemic, and further utilize multivariate techniques to explain the variance in monthly exponential growth rates of cases and deaths with aid of a set of different predictors: the recorded Google mobility trends towards six categories of places, daily average temperature, daily humidity, and key socioeconomic attributes of each country.

Results

The analysis showed that changes in mobility trends were the most significant predictors of the incidence and mortality rates, temperature and humidity were also significant but to a much lesser extent, on the other hand, the socioeconomic attributes did not contribute significantly to explaining different incidence and mortality rates across countries.

Conclusion

Changes in mobility trends across countries dramatically affected the incidence and mortality rates across different countries, thus, it might be used as a proxy measure of contact frequency.

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  1. ScreenIT

    SciScore for 10.1101/2021.01.21.21250226: (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

    Software and Algorithms
    SentencesResources
    For each of the selected countries (except for China and Iran), Google daily documentation on mobility trends across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential was retrieved.
    Google
    suggested: (Google, RRID:SCR_017097)
    Statistical Analysis: Data analysis was conducted using SPSS software (version 25, IBM, 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:
    Limitation and strength: To the best of our knowledge, this research is the first to address the pattern of the spread either linear or exponential, it modelled the effect of social mobility environmental temperature, and humidity simultaneously, we did not include other important determinant of health like income, health care facilities, access to health systems, comorbidities and extra. An important point of limitation was that case definition was variable across different countries. Furthermore, case definition of suspected case or confirmed case may vary across time in the same country. Absolutely this may affect the number of reported cases and the same problem can be encountered for number of deaths. These facts may affect the external validity of our models.

    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 10.1101/2021.01.21.21250226v1 on medRxiv