A SEIAR mathematical model to analyse the effect of COVID-19 pandemic over the crowded and dense populated regions. Issue 7 (3rd October 2022)

• Record Type: Journal Article
• Authors: Negi, Sunil Singh; Sharma, Nitin; Rana, Pankaj Singh
• Is Part Of: Journal of interdisciplinary mathematics. Volume 25:Issue 7(2022)
• Page Start: 2063
• Page End: 2071
• Publication Date: 2022-10-03
• Subjects: 92B05 -- 62P10 -- 92D30; Coronavirus -- Epidemiology -- Asymptomatic infected -- Density -- Intervention policy; Mathematics -- Periodicals; Mathematics; Periodicals; 510.5
• DOI: 10.1080/09720502.2022.2133233
• Languages: English
• ISSNs: 0972-0502

Abstract

Abstract: In this study, an attempt has been made to formulate a SEIR-type mathematical model for the dynamics of SARS-CoV-2 (COVID-19) pandemic by incorporating an additional asymptomatic compartment. The formulated model contains a system of ordinary differential equations. The basic reproduction number R 0 is obtained by applying the next-generation matrix method. For India, daily death cases and cumulative COVID-19 death cases were used to fit the model from March 20, 2020 to May 10, 2020. A tool MATLAB is used for numerical simulation and validation of analytical results. It is found that the coronavirus infection rate depends on the compactness of the population i.e., the infection rate in a particular region either increases or decreases depending on the population density of the region. The infection dynamics of coronavirus are also reduced when masks are worn and social distance is maintained.