COVID-19 Forecasting: A Statistical Approach
Keywords:SARS-coronavirus-2; COVID-19, Statistical Analysis; Forecast; Fbprophet; Moving Average; Autoregressive Integrated Moving Average.
Background: SARS-coronavirus-2 is a new virus infecting people and causing COVID-19 disease. The disease is causing a worldwide pandemic. Although some people never develop any signs or symptoms of disease when they are infected, other people are at very high risk for severe disease and death.
Objective: If we’re able to intervene to prevent even some transmission, we can dramatically reduce the number of cases. And this is the public health goal for controlling COVID-19.
Methods: This article initializes an approach for comparatively accurate values prediction of new cases and deaths for a particular day in order to be considered for preventive measures. The three statistical analysis methods considered for forecasting are Fbprophet, Moving average and the Autoregressive Integrated Moving Average algorithm.
Results: The results obtained are in-line with the past and present trend of COVID-19 data collected from WHO website.
Conclusion: The output is satisfactory for further consideration.
Bangladesh Journal of Medical Science Vol.20(5) 2021 p.85-96
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Copyright (c) 2021 Arti Saxena, Falak Bhardwaj, Vijay Kumar
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