A model based study on the dynamics of COVID-19: Prediction and control

Abstract

As there is no vaccination and proper medicine for treatment, the recent pandemic caused by COVID-19 has drawn attention to the strategies of quarantine and other governmental measures, like lockdown, media coverage on social isolation, and improvement of public hygiene, etc to control the disease. The mathematical model can help when these intervention measures are the best strategies for disease control as well as how they might affect the disease dynamics. Motivated by this, in this article, we have formulated a mathematical model introducing a quarantine class and governmental intervention measures to mitigate disease transmission. We study a thorough dynamical behavior of the model in terms of the basic reproduction number. Further, we perform the sensitivity analysis of the essential reproduction number and found that reducing the contact of exposed and susceptible humans is the most critical factor in achieving disease control. To lessen the infected individuals as well as to minimize the cost of implementing government control measures, we formulate an optimal control problem, and optimal control is determined. Finally, we forecast a short-term trend of COVID-19 for the three highly affected states, Maharashtra, Delhi, and Tamil Nadu, in India, and it suggests that the first two states need further monitoring of control measures to reduce the contact of exposed and susceptible humans.

Analysis of second outbreak of COVID-19 after relaxation of control measures in India

“…Many researchers also gave analysis and prediction of the development trend of the pandemic based on the SEIR (Susceptible, Exposed, Infectious, Recovered) model and SEIR-like models [11][12][13][14][15][16][17]. Fang et al used the parameterized SEIR model to simulate the spread dynamics of the COVID-19 outbreak and the impact of different control measures.…”

Stochastic approach to study control strategies of Covid-19 pandemic in India

“…Likewise, there have been many studies on the Covid-19 pandemic in India using various mathematical models. However, most of these studies adopt deterministic methods [10][11][12][13][14][15][16][17][18][19][20][21]. On the other hand, to capture the qualitative as well as quantitative real dynamic situations to intervene in disease outbreaks, a stochastic approach needs to be employed.…”

Temporal Analysis of COVID - 19 Pandemic in India and R0 prediction

“…The key advantage of SEIR models is that it can accommodate additional compartments (such as Asymptomatic Class, Mildly Symptomatic, Hospitalized, Quarantined, etc.) as well as various factors that influence the transmission of the disease (Kumar et al;Das 2020;Dhanwant and Ramanathan 2020;Kumar 2020;Mandal et al 2020;Pandey et al 2020;Sardar et al 2020;Sarkar and Khajanchi 2020;Ranjan 2020). Researchers have exploited this modelling strategy extensively for study of the spread the COVID -19 pandemic where such factors such as lockdown implementations, migration, transport networks, influx of migrant workers have been considered for a near-accurate estimate of the when and how the pandemic can be controlled.…”