On the COVID-19 Pandemic in Indian State of Maharashtra: Forecasting & Effect of different parameters

  1. Arvind S. Avhad
  2. Prasad P. Sutar
  3. Onkar T. Mohite
  4. Vaibhav S. Pawar

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Abstract

This work details the outbreak and factors affecting the spread of novel coronavirus (COVID-19) in the Indian state of Maharashtra, which is considered as one of the most massive and deadly pandemic outbreaks. Observational data collected between 14 March 2020 and 4 May 2020 is statistically analyzed to determine the nonlinear behavior of the epidemic. It is followed by validating predicted results with real-time data. Proposed model is further used to obtain statistical summaries in which Grubbs tests for outlier detection have justified high values of evaluation metrics. Outliers are found to be pilot elements in an outbreak under considered region. Statistically, a significant correlation has been observed between dependent and explanatory variables. Transmission pattern of this virus is very much different from the SARS-CoV-1 virus. Key findings of this work will be predominant in maintaining environment conditions at healthcare facilities to reduce transmission rates at these most vulnerable places.

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    SciScore for 10.1101/2020.05.23.20111179: (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
    XLSTAT statistical analysis tool is used to build, evaluate, and prepare the predictions of the model.
    XLSTAT
    suggested: (XLSTAT, RRID:SCR_016299)

    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 10.1101/2020.05.23.20111179v2 on medRxiv
  3. Version published to 10.1101/2020.05.23.20111179v1 on medRxiv