Modelling the COVID-19 Pandemic: Asymptomatic Patients, Lockdown and Herd Immunity

Ansumali, Santosh and Kaushal, Shaurya and Kumar, Aloke and Prakash, Meher K. and Vidyasagar, Mathukumalli (2020) Modelling the COVID-19 Pandemic: Asymptomatic Patients, Lockdown and Herd Immunity. In: 3rd IFAC Workshop on Cyber-Physical and Human Systems, CPHS 2020, 3 December 2020through 5 December 2020, Beijing.

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Abstract

The SARS-Cov-2 is a type of coronavirus that has caused the COVID-19 pandemic. In traditional epidemiological models such as SEIR (Susceptible, Exposed, Infected, Removed), the exposed group E does not infect the susceptible group S. A distinguishing feature of COVID-19 is that, unlike with previous viruses, there is a distinct "asymptomatic"group A, who do not show any symptoms, but can nevertheless infect others, at the same rate as infected patients. This situation is captured in a model known as SAIR (Susceptible, Asymptomatic, Infected, Removed), introduced in Robinson and Stilianakis (2013). The dynamical behavior of the SAIR model is quite different from that of the SEIR model. In this paper, we use Lyapunov theory to establish the global asymptotic stabiilty of the SAIR model. Next, we present methods for estimating the parameters in the SAIR model. We apply these estimation methods to data from several countries including India, and show that the predicted trajectories of the disease closely match actual data. ©2020 The Authors.This is an open access article under the CC BY-NC-ND license.

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IITH Creators:

IITH Creators	ORCiD
Vidyasagar, Mathukumalli	UNSPECIFIED

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

Asymptomatic patients; Coronaviruses; Dynamical behaviors; Epidemiological models; Estimation methods; Herd immunities; Infected patients; Lyapunov theories

Subjects:

Electrical Engineering

Divisions:

Department of Electrical Engineering

Depositing User:

. LibTrainee 2021

Date Deposited:

15 Nov 2022 05:59

Last Modified:

15 Nov 2022 05:59

URI:

http://raiithold.iith.ac.in/id/eprint/11254