SEIR-VQ model for the NB.1.8.1 COVID-19 variant: Mathematical analysis and numerical simulations

Faiza Arif; Sana Ullah Saqib; Yin-Tzer Shih; Aneela Kausar; Faiza Arif; Sana Ullah Saqib; Yin-Tzer Shih; Aneela Kausar

doi:10.3934/math.2025803

AIMS Mathematics

2025, Volume 10, Issue 8: 18024-18054. doi: 10.3934/math.2025803

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SEIR-VQ model for the NB.1.8.1 COVID-19 variant: Mathematical analysis and numerical simulations

1.
Abdus Salam School of Mathematical Sciences, Government College University, Lahore 54600, Pakistan
2.
Department of Applied Mathematics, National Chung Hsing University, Taichung 40227, Taiwan
3.
Department of Computer Science and Information Engineering, National Yunlin University of Science and Technology, Yunlin 64002, Taiwan
^‡These authors contributed equally to this work

Received: 21 June 2025 Revised: 27 July 2025 Accepted: 30 July 2025 Published: 08 August 2025
MSC : 26A33, 34A08, 34A34, 65L20, 92B20, 92D30

This the study proposes a novel susceptible, exposed, infectious, recovered, vaccinated, and quarantined (SEIR-VQ)-type compartmental model specifically designed to capture the transmission dynamics of the NB.1.8.1 variant of COVID-19, a recently emerged virus known for its higher transmissibility and reduced vaccine effectiveness. The model divides the population into six distinct compartments: Susceptible, exposed, infectious, quarantined, recovered, and vaccinated. The proposed formulation reflects key contemporary epidemiological factors, such as waning immunity, partial vaccine effectiveness due to viral mutations, and infectivity during quarantine. Additionally, the study conducts both dimensional and non-dimensional analyses of the system, establishes the positivity and boundedness of solutions, and derives the basic reproduction number, $ \mathcal{R}_0 $. It also examines the local and global stability of the disease-free equilibrium with respect to $ \mathcal{R}_0 $. Numerical solutions utilizing the Runge-Kutta (RK4) method and MATLAB's ode45 solver are used to simulate infection dynamics. Finally, a sensitivity analysis evaluates the influence of the key parameters that most significantly impact disease spread. The findings indicate that increasing vaccine efficacy, reducing transmission through non-pharmaceutical interventions, and enhancing the isolation of infectious individuals are effective strategies for controlling the spread of the NB.1.8.1 variant. These results support public health policies by highlighting effective control strategies.
- NB.1.8.1 COVID-19,
- mathematical modeling,
- stability analysis,
- sensitivity analysis,
- virus-free equilibrium,
- basic reproductive number,
- public health policy
Citation: Faiza Arif, Sana Ullah Saqib, Yin-Tzer Shih, Aneela Kausar. SEIR-VQ model for the NB.1.8.1 COVID-19 variant: Mathematical analysis and numerical simulations[J]. AIMS Mathematics, 2025, 10(8): 18024-18054. doi: 10.3934/math.2025803

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Abstract

This the study proposes a novel susceptible, exposed, infectious, recovered, vaccinated, and quarantined (SEIR-VQ)-type compartmental model specifically designed to capture the transmission dynamics of the NB.1.8.1 variant of COVID-19, a recently emerged virus known for its higher transmissibility and reduced vaccine effectiveness. The model divides the population into six distinct compartments: Susceptible, exposed, infectious, quarantined, recovered, and vaccinated. The proposed formulation reflects key contemporary epidemiological factors, such as waning immunity, partial vaccine effectiveness due to viral mutations, and infectivity during quarantine. Additionally, the study conducts both dimensional and non-dimensional analyses of the system, establishes the positivity and boundedness of solutions, and derives the basic reproduction number, $ \mathcal{R}_0 $. It also examines the local and global stability of the disease-free equilibrium with respect to $ \mathcal{R}_0 $. Numerical solutions utilizing the Runge-Kutta (RK4) method and MATLAB's ode45 solver are used to simulate infection dynamics. Finally, a sensitivity analysis evaluates the influence of the key parameters that most significantly impact disease spread. The findings indicate that increasing vaccine efficacy, reducing transmission through non-pharmaceutical interventions, and enhancing the isolation of infectious individuals are effective strategies for controlling the spread of the NB.1.8.1 variant. These results support public health policies by highlighting effective control strategies.

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