The measles epidemic model assessment under real statistics: an application of stochastic optimal control theory. Issue 2 (25th January 2023)

• Record Type: Journal Article
• Authors: Liu, Peijiang; Ikram, Rukhsar; Khan, Amir; Din, Anwarud
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 26:Issue 2(2023)
• Page Start: 138
• Page End: 159
• Publication Date: 2023-01-25
• Subjects: Stochastic epidemic model -- threshold value -- real data -- stationary distribution -- extinction -- stochastic optimal control; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: 10.1080/10255842.2022.2050222
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract: A stochastic epidemic model with random noise transmission is taken into account, describing the dynamics of the measles viral infection. The basic reproductive number is calculated corresponding to the stochastic model. It is determined that, given initial positive data, the model has bounded, unique, and positive solution. Additionally, utilizing stochastic Lyapunov functional theory, we study the extinction of the disease. Stationary distribution and extinction of the infection are examined by providing sufficient conditions. We employed optimal control principles and examined stochastic control systems to regulate the transmission of the virus using environmental factors. Graphical representations have been offered for simplicity of comprehending in order to further verify the acquired analytical findings.