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

  • Federal University of Technology, Owerri
  • Government College University Lahore
  • China Medical University Taichung
  • Lebanese American University
  • Institute for Space Sciences

Research output: Contribution to journalArticlepeer-review

16 Citations (Scopus)

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: R0S = 3.0651. 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.

Original languageEnglish
Pages (from-to)2973-3012
Number of pages40
JournalCMES - Computer Modeling in Engineering and Sciences
Volume138
Issue number3
DOIs
Publication statusPublished - 2024
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • COVID-19
  • ergodicity
  • extinction
  • real data
  • stochastic model
  • Viral hepatitis B

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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