The first thousands of cases of coronavirus disease 2019 (COVID-19) in Algeria: some risk factors

  1. Salima Taleb
  2. Marwa Boussakta

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Abstract

Objectives

Providing valuable information on the prevalence of Covid-19 is a crucial step to improve and accentuate the disease surveillance and prevention system as this can limit the spread of the virus.

Methods

COVID-19 is caused by the SARS-CoV-2 virus. It is essential to understand the epidemiological characteristics of the first cases in each country. The purpose of this study is to describe the geographic distribution and some risk factors in the first thousands of cases in Algeria. This descriptive study was carried out to examine recent data published by public health institutions in Algeria, websites and the world health organization.

Results

The 8306 cases of COVID-19 have been confirmed in Algeria. By sex, men with 55.76% predominate, the most affected age group was 25 to 49 years old (41.1%), 600 cases of death were reported, subjects aged over 60 years are the most likely to die from COVID-19. Most of the confirmed subjects came from the cities of Blida and Algiers. All cases are human-to-human transmissions.

Conclusion

The COVID-19 pandemic has highlighted the lack of dical equipment in Algeria and in all countries of the world. This requires better management of the health sector on an international scale.

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  1. ScreenIT

    SciScore for 10.1101/2020.08.17.20176396: (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 variableWe conducted a retrospective study on the epidemiological characteristics of 8306 COVID-19 patients of all ages (3675 female sexes and 4631 male sexes).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Statistical: Data were entered and processed by Excel 2007 software.
    Excel
    suggested: None

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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 10.1101/2020.08.17.20176396 on medRxiv