Susceptibility and Sustainability of India against CoVid19: a multivariate approach

  1. Soumi Ray
  2. Mitu Roy

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Abstract

Purpose

We are currently in the middle of a global crisis. Covid19 pandemic has suddenly threatened the existence of human life. Till date, as no medicine or vaccine is discovered, the best way to fight against this pandemic is prevention. The impact of different environmental, social, economic and health parameters is unknown and under research. It is important to identify the factors which can weaken the virus, and the nations which are more vulnerable to this virus.

Materials and Methods

Data of weather, vaccination trends, life expectancy, lung disease, number of infected people in the pre-lockdown and post-lockdown period of highly infected nations are collected. These are extracted from authentic online resources and published reports. Analysis is done to find the possible impact of each parameter on CoVid19.

Results

CoVid19 has no linear correlation with any of the selected parameters, though few parameters have depicted non-linear relationship in the graphs. Further investigations have shown better result for some parameters. A combination of the parameters results in a better correlation with infection rate.

Conclusions

Though depending on the study outcome, the impact of CoVid19 in India can be predicted, the required lockdown period cannot be calculated due to data limitation.

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  1. ScreenIT

    SciScore for 10.1101/2020.04.16.20066159: (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: 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 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.

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  2. Version published to 10.1101/2020.04.16.20066159 on medRxiv