Predicting the Peak and COVID-19 trend in six high incidence countries: A study based on Modified SEIRD model

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Abstract

The novel Coronavirus (COVID-19) has claimed the lives of almost a million people across the globe and this trend continues to rise rapidly day by day. The fear of getting infected by Corona virus is affecting the people emotionally, psychologically and mentally. They are not able to work to their full capacity and are also worried about the well beings of their near and dear ones. The National governments have taken up several measures like lockdowns, closing of educational institutions, and work from home for employees of companies wherever feasible. Governments are also advising people to take precautions like not to go out if not necessary, use of mask and keep a distance of appx. 6 ft. if you need to go out as the virus spreads from human to human in close proximity. These measures have helped to limit the spread of this virus in the past few months. However, due to rapid increase in the daily confirmed cases, it is becoming tougher for the governments to provide facilities like testing kits, hospitalization facilities, oxygen cylinders etc. to the infected persons. Thus, there is an urgent need to accurately estimate the number of cases in coming future that can help governments in acquiring the required resources. Further, to handle the economic distress caused by this virus, long-term planning is equally important. Focusing on these two aspects, this paper proposes to use the Modified SEIRD (Susceptible-Exposed-Infected-Recovered-Deceased) model to predict the peak and spread trend of COVID-19 in six countries namely USA, India, Brazil, Russia, Peru and Colombia having the highest number of confirmed cases. As in COVID-19, even infected asymptomatic persons can spread the infection, the chosen model is well suited as exposed compartment of SEIRD model includes asymptomatic exposed individuals which are infectious. Epidemiological data till 9 th September 2020 has been utilised to perform short-term predictions till 31 st December 2020. Long-term predictions have been computed till 31 st December 2023, to estimate the end of the virus in the above-mentioned six nations. Small values of MAPE (Mean Absolute Percentage Error) have been obtained for the models fitted to reported data for all the countries. Student t-test has been used for accepting the predictions of the Modified SEIRD model based on the reported data.

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  1. SciScore for 10.1101/2020.12.14.20248117: (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.

    About SciScore

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