Lifestyle Acquired Immunity, Decentralized Intelligent Infrastructures, and Revised Healthcare Expenditures May Limit Pandemic Catastrophe: A Lesson From COVID-19

  1. Asif Ahmed
  2. Tasnima Haque
  3. Mohammad Mahmudur Rahman

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Abstract

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  1. Version published to 10.3389/fpubh.2020.566114
  2. ScreenIT

    SciScore for 10.1101/2020.05.23.20111104: (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 variableSocioeconomic and demographic data including total population, population density, median age, urban population percentages, male and female ratio and financial information together with gross domestic product (GDP) in USD, gross national income (GNI) per capita (purchasing power parity, PPP) in USD, health expenditure (% of GDP) in USD were attained from the databank of World Bank (36).

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    2.5 Statistical analysis: One to one regression analysis of ungrouped data was performed in SPSS version 26.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)
    GraphPad Prism version 6 was used to generate graphs.
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    All the final graphs generated in GraphPad Prism were combined using Inkscape version 0.92 graphics software.
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)
    Inkscape
    suggested: (Inkscape, RRID:SCR_014479)

    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:
    4.3 Limitation and future direction: COVID-19 pandemic is ongoing and not yet closed; data used in our study reflects a snapshot of a time point. This limits our study to capture full view of the dynamic nature of this disease. In addition, self-reported government data often pose reliability issues. As COVID-19 is multifactor mediated, not all factors could be included in this particular study specially integrating molecular mechanism of disease was beyond the scope. In addition, as molecular mechanism of pathogenesis will gradually unfold, and more clinical data will be available, the factors discussed in this study will be easier to interpret. Finally, the interpretation presented in our study can be useful to design future plans to contain such contagious pandemic outbreak within very short time.

    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.

  3. Version published to 10.1101/2020.05.23.20111104v1 on medRxiv