tetano
Editor, Senior Moderator
Nonlinear Dyn
. 2020 Sep 21;1-17.
doi: 10.1007/s11071-020-05958-z. Online ahead of print.
COVID-19 pandemic in India: a mathematical model study
Sudhanshu Kumar Biswas[SUP] 1 [/SUP], Jayanta Kumar Ghosh[SUP] 2 [/SUP], Susmita Sarkar[SUP] 2 [/SUP], Uttam Ghosh[SUP] 2 [/SUP]
Affiliations
Abstract
The present novel coronavirus (SARS-CoV-2) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. But there is no vaccine, anti-viral medicine for such infection. So at this moment, a major worldwide problem is that how we can control this pandemic. On the other hand, India is high population density country, where the coronavirus infection disease (COVID-19) has started from 1 March 2020. Due to high population density, human to human social contact rate is very high in India. So controlling pandemic COVID-19 in early stage is very urgent and challenging problem of India. Mathematical models are employed to study the disease dynamics, identify the influential parameters and access the proper prevention strategies for reduction outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the influential model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impact have also been studied. Prediction are given on the future trends of the virus transmission under some control measures. Finally, the positive measures to control the disease have been summarized in the conclusion section.
Keywords: Asymptomatic class; Basic reproduction number; COVID-19; Prevention measure; Quarantine; Sensitivity analysis.
. 2020 Sep 21;1-17.
doi: 10.1007/s11071-020-05958-z. Online ahead of print.
COVID-19 pandemic in India: a mathematical model study
Sudhanshu Kumar Biswas[SUP] 1 [/SUP], Jayanta Kumar Ghosh[SUP] 2 [/SUP], Susmita Sarkar[SUP] 2 [/SUP], Uttam Ghosh[SUP] 2 [/SUP]
Affiliations
- PMID: 32982061
- PMCID: PMC7505224
- DOI: 10.1007/s11071-020-05958-z
Abstract
The present novel coronavirus (SARS-CoV-2) infection has created a global emergency situation by spreading all over the world in a large scale within very short time period. But there is no vaccine, anti-viral medicine for such infection. So at this moment, a major worldwide problem is that how we can control this pandemic. On the other hand, India is high population density country, where the coronavirus infection disease (COVID-19) has started from 1 March 2020. Due to high population density, human to human social contact rate is very high in India. So controlling pandemic COVID-19 in early stage is very urgent and challenging problem of India. Mathematical models are employed to study the disease dynamics, identify the influential parameters and access the proper prevention strategies for reduction outbreak size. In this work, we have formulated a deterministic compartmental model to study the spreading of COVID-19 and estimated the model parameters by fitting the model with reported data of ongoing pandemic in India. Sensitivity analysis has been done to identify the influential model parameters. The basic reproduction number has been estimated from actual data and the effective basic reproduction number has been studied on the basis of reported cases. Some effective preventive measures and their impact have also been studied. Prediction are given on the future trends of the virus transmission under some control measures. Finally, the positive measures to control the disease have been summarized in the conclusion section.
Keywords: Asymptomatic class; Basic reproduction number; COVID-19; Prevention measure; Quarantine; Sensitivity analysis.