Analysis of COVID-19 cases and associated ventilator requirement in Indian States

  1. V Dhanya
  2. R Anitha
  3. Ashwini Kumar Kishan
  4. S R Sumathi
  5. Amrit Roy

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Abstract

Analysis of COVID-19 cases and prediction of quantity of associated ventilator requirement is very relevant during this pandemic. This paper presents a method for predictive estimation of ventilator requirement for COVID-19 patients in Indian states. It uses ARIMA (Autoregressive Integrated Moving Average) model for predicting the future cumulative cases and daily fatality. Taking cue from this, ventilator requirement is estimated for each state. State wise estimation of ventilator is important because public healthcare system in India is managed at state level. Dataset on Novel Corona Disease 2019 in India from Kaggle website is used in this work.

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    SciScore for 10.1101/2020.07.13.20153056: (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
    This model is implemented in Python.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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 10.1101/2020.07.13.20153056v1 on medRxiv