Risk Assesment of nCOVID-19 Pandemic In India: A Mathematical Model And Simulation

  1. Swarnava Biswas
  2. Moumita Mukherjee

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Abstract

The entire world is now eventually locked down due to the outbreak of nCOVID-19 corona virus outbreak. The fast and relentless spread nCOVID-19 has basically segmented the populace only into merely into three classes, such as susceptible, infected and recovered compartments. Adapting the classical SEIR-type epidemic modelling framework, the direct person-to-person contact transmission is taken as the direct route of transmission of nCOVID-19 pandemic. In this research, the authors have developed a model of the nation-wide trends of the outburst of the nCOVID-19 infection using an SEIR Model. The SEIR dynamics are expressed using ordinary differential equations. The creators initially determined the parameters of the model from the accessible day by day information for Indian States dependent on around 35 days history of diseases, recuperations and deaths. The determined parameters have been amassed to extend future patterns for the Indian subcontinent, which is right now at a beginning time in the contamination cycle. The novelty of the study lies in the prediction of both the pessimistic and optimistic mathematical model based comprehensive analysis of nCOVID-19 infection spreading, for two different conditions: (a) if lockdown gets withdrawn and (b) if lockdown continues as a whole. If the complete lockdown in India is withdrawn on 14th April 2020, as a whole, then from the simulation, the authors have predicted that the infected population will flare-up to a large extent, suddenly, however, gradual or zone specific withdrawal would be more effective solution. This study also suggested some possible way-out to get rid of this situation by providing a trade-off between ‘ flattening of the curve” as well as “less economic turbulence. The projections are intended to provide a base/ action plan for the socio-economic counter measures to alleviate nCOVID-19.

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    SciScore for 10.1101/2020.04.10.20060830: (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 variablenot detected.

    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 10.1101/2020.04.10.20060830v1 on medRxiv