Propagation Analysis of COVID-19: An SIR Model-Based Investigation of the Pandemic

被引:10
作者
Saxena, Rahul [1 ,2 ]
Jadeja, Mahipal [1 ]
Bhateja, Vikrant [3 ]
机构
[1] Malaviya Natl Inst Technol, Jaipur, Rajasthan, India
[2] Manipal Univ Jaipur, Jaipur, Rajasthan, India
[3] Dr APJ Abdul Kalam Tech Univ, Shri Ramswaroop Mem Grp Profess Coll, Lucknow, Uttar Pradesh, India
关键词
Covid-19; Epidemic modeling; SIR model; Trend analysis; Predictive model;
D O I
10.1007/s13369-021-05904-0
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The paper investigates the spread pattern and dynamics of Covid-19 propagation based on SIR model. Using the model dynamics, an analytical estimation has been obtained for virus span, its longevity, growing pattern, etc. Experimental simulations are carried out on the data of four regions of India over a period of two months of country-wide lockdown. The analysis illustrates the effect of lockdown on the contact rate and its implication. Simulation results illustrate that there is a cut-down in effective contact rate by a considerable factor ranging from 2 to 4 for the selected regions. Further, the estimates for the vaccines to be developed, maximum range and span of the disease can be also estimated. Results portray that the SIR model is a significant tool to cast the dynamics and predictions of Covid-19 outbreak in comparison to other epidemic models. The study demonstrates the progression of real time data in accordance with the SIR model with high accuracy.
引用
收藏
页码:11103 / 11115
页数:13
相关论文
共 45 条
[31]   A new SEAIRD pandemic prediction model with clinical and epidemiological data analysis on COVID-19 outbreak [J].
Liu, Xian-Xian ;
Fong, Simon James ;
Dey, Nilanjan ;
Crespo, Ruben Gonzalez ;
Herrera-Viedma, Enrique .
APPLIED INTELLIGENCE, 2021, 51 (07) :4162-4198
[32]  
Mkhatshwa T, 2010, ARXIV10070908
[33]  
Mpeshe Saul C., 2017, INT J ADV APPL MATH, V4, P14
[34]  
Nesteruk I., 2020, RESEARCHGATE
[35]   AN OPTIMAL CONTROL MODEL FOR EBOLA VIRUS DISEASE [J].
Njankou, Sylvie Diane Djiomba ;
Nyabadza, Farai .
JOURNAL OF BIOLOGICAL SYSTEMS, 2016, 24 (01) :29-49
[36]  
Rachah A., 2017, ARXIV170501079
[37]   A comparative analysis of Chikungunya and Zika transmission [J].
Riou, Julien ;
Poletto, Chiara ;
Boelle, Pierre-Yves .
EPIDEMICS, 2017, 19 :43-52
[38]  
Russo L., 2020, Tracing DAY-ZERO and Forecasting the Fade out of the COVID-19 Outbreak in Lombardy. Italy: a compartmental modelling and numerical optimization approach
[39]  
Sanche S, 2020, NOVEL CORONAVIRUS 20, DOI 10.1101/2020.02.07.20021154
[40]   Forecasting Models for Coronavirus Disease (COVID-19): A Survey of the State-of-the-Art [J].
Shinde G.R. ;
Kalamkar A.B. ;
Mahalle P.N. ;
Dey N. ;
Chaki J. ;
Hassanien A.E. .
SN Computer Science, 2020, 1 (4)