Development and evaluation of the bootstrap resampling technique based statistical prediction model for Covid-19 real time data : A data driven approach

Abstract

The objective of the article is to develop ‘earlyR’ package based novel coronavirus disease (COVID-19) forecasting model. The reported COVID-19 serial interval data is applied for obtaining maximum likelihood value of the reproduction number (R₀) using maximum likelihood approach and ‘projections’ package is applied for getting trajectories of epidemic curve. The minimum, median, mean and maximum projected value of R₀ with 95% confidence interval (CI) is obtained by using bootstrap resampling strategy and the predicted cumulative probable count of new cases is also presented with different quantile. To validate the results with real scenario, the past COVID-19 data is considered. The % error rate ranges from -7.91% to 21.27% for the developed model for the five Indian States.

Subject Classification:

• Primary 62-XX
• Secondary 62P30

Keywords:

• Bootstrap resampling method
• COVID-19
• Early prediction of epidemic
• Maximum-likelihood approach
• R0 value
• Reproduction number