Open Access

ARTICLE

A Stochastic Model to Assess the Epidemiological Impact of Vaccine Booster Doses on COVID-19 and Viral Hepatitis B Co-Dynamics with Real Data

Andrew Omame^1,2,*, Mujahid Abbas^3,6, Dumitru Baleanu^4,5,6

1 Department of Mathematics, Federal University of Technology, Owerri, 460114, Nigeria
2 Abdus Salam School of Mathematical Sciences, Government College University, Lahore, 54000, Pakistan
3 Department of Mathematics, Government College University, Lahore, 54000, Pakistan
4 Department of Computer Science and Mathematics, Labanese American University, Beirut, Lebanon
5 Institute of Space Sciences, Magurele-Bucharest, Romania
6 Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, 40402, Taiwan

* Corresponding Author: Andrew Omame. Email:

(This article belongs to the Special Issue: Mathematical Aspects of Computational Biology and Bioinformatics-II)

Computer Modeling in Engineering & Sciences 2024, 138(3), 2973-3012. https://doi.org/10.32604/cmes.2023.029681

Received 02 March 2023; Accepted 04 August 2023; Issue published 15 December 2023

Abstract

A patient co-infected with COVID-19 and viral hepatitis B can be at more risk of severe complications than the one infected with a single infection. This study develops a comprehensive stochastic model to assess the epidemiological impact of vaccine booster doses on the co-dynamics of viral hepatitis B and COVID-19. The model is fitted to real COVID-19 data from Pakistan. The proposed model incorporates logistic growth and saturated incidence functions. Rigorous analyses using the tools of stochastic calculus, are performed to study appropriate conditions for the existence of unique global solutions, stationary distribution in the sense of ergodicity and disease extinction. The stochastic threshold estimated from the data fitting is given by: . Numerical assessments are implemented to illustrate the impact of double-dose vaccination and saturated incidence functions on the dynamics of both diseases. The effects of stochastic white noise intensities are also highlighted.

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Keywords

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