TY - GEN
T1 - Analysis of a Modified SEIRS Compartmental Model for COVID-19
AU - Lavanya Shri, S. A.
AU - Patel, Bhavikumar
AU - Banavar, Mahesh K.
AU - Tepedelenlioglu, Cihan
AU - Spanias, Andreas
AU - Schuckers, Stephanie
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Mathematical representations of infectious diseases include compartment-based SEIR and SEIRS models. These models are represented using coupled differential equations that capture the flow of populations from one compartment to another. While these models have been used for several infectious diseases such as HIV/AIDS, tuberculosis, dengue fever, and COVID-19, the models do not generally incorporate compartments for vaccinated populations, asymptomatic infections, or the possibility of reinfection. This paper presents a modified Susceptible - Exposed - Infected - Recovered - Susceptible (SEIRS) compartment model for COVID-19 disease. We incorporate the compartments for exposed vaccinated and non-vaccinated populations, and those with symptomatic and asymptomatic infections. We represent this model with a set of coupled differential equations to show that this system has fixed points validated through attractor plots. Our results show that we have a fixed point that represents endemic equilibrium and that this fixed point is globally stable.
AB - Mathematical representations of infectious diseases include compartment-based SEIR and SEIRS models. These models are represented using coupled differential equations that capture the flow of populations from one compartment to another. While these models have been used for several infectious diseases such as HIV/AIDS, tuberculosis, dengue fever, and COVID-19, the models do not generally incorporate compartments for vaccinated populations, asymptomatic infections, or the possibility of reinfection. This paper presents a modified Susceptible - Exposed - Infected - Recovered - Susceptible (SEIRS) compartment model for COVID-19 disease. We incorporate the compartments for exposed vaccinated and non-vaccinated populations, and those with symptomatic and asymptomatic infections. We represent this model with a set of coupled differential equations to show that this system has fixed points validated through attractor plots. Our results show that we have a fixed point that represents endemic equilibrium and that this fixed point is globally stable.
UR - http://www.scopus.com/inward/record.url?scp=85190391768&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85190391768&partnerID=8YFLogxK
U2 - 10.1109/IEEECONF59524.2023.10477067
DO - 10.1109/IEEECONF59524.2023.10477067
M3 - Conference contribution
AN - SCOPUS:85190391768
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 965
EP - 969
BT - Conference Record of the 57th Asilomar Conference on Signals, Systems and Computers, ACSSC 2023
A2 - Matthews, Michael B.
PB - IEEE Computer Society
T2 - 57th Asilomar Conference on Signals, Systems and Computers, ACSSC 2023
Y2 - 29 October 2023 through 1 November 2023
ER -