COVID-19 Forecasting: A Statistical Approach

Abstract

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

Implementation of Holt-Winter Exponential Smoothing Method to Forecast The Spread of Covid-19

“…This can be confirmed by several research results of researchers with other statistical methods. However, we cannot specifically compare research with different research data objects [1]- [3].…”

“…President Joko Widodo declared the Covid-19 pandemic over after two years causing a worldwide pandemic. Saxena [1] uses the Fbprophet forecasting method, Moving average and Autoregressive Integrated Moving Average Algorithm to predict the spread of Covid-19. The results obtained indicate that the trend in the COVID-19 data needs further consideration.…”

​Key findings regarding COVID 19 in Bangladesh and wider and their implications

“…This is important as there have been concerns with forecasting the potential rise in cases and their subsequent impact on morbidity and mortality. Improving forecasting has appreciable implications for health planners, with Saxena et al in their paper discussing possible statistical approaches to improve this in the current and future pandemics 35 . Improved planning includes dedicated COVID-19 wards as well as re-organising emergency trauma intensive care units (ICUs) to deal with an increasing number of patients with severe COVID-19.…”