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

被引：3
|
作者：
Karthick, K. [1 ]
Aruna, S. K. [2 ]
Manikandan, R. [3 ]
机构：
[1] GMR Inst Technol, Dept Elect & Elect Engn, Rajam 532127, Andhra Pradesh, India
[2] CHRIST Deemed Be Univ, Sch Engn & Technol, Dept Comp Sci & Engn, Bangalore 560029, Karnataka, India
[3] Panimalar Engn Coll, Dept Elect & Instrumentat Engn, Chennai 600123, Tamil Nadu, India
来源：
JOURNAL OF INTERDISCIPLINARY MATHEMATICS | 2022年 / 25卷 / 03期
关键词：
Bootstrap resampling method; COVID-19; Early prediction of epidemic; Maximum-likelihood approach; R0; value; Reproduction number;
D O I：
10.1080/09720502.2021.2012890
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
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 (R-0) using maximum likelihood approach and 'projections' package is applied for getting trajectories of epidemic curve. The minimum, median, mean and maximum projected value of R-0 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.
引用
收藏
页码：615 / 627
页数：13
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