Conference Papers
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Item An Appraisal on the Application of Reproduction Number for the Stability Analysis of Disease - Free Equilibrium State for S-I-R Type Models(Proceedings of International Conference on Mathematical Modelling Optimization and Analysis of Disease Dynamics (ICMMOADD) 2024, 2024-02-28) Abdurrahman, Nurat Olamide; Somma S. A.; Akinwande, N. I.; Ashezua, T. T.; Gweryina, R.One of the key ideas in mathematical biology is the basic reproduction number, which can be utilized to comprehend how a disease epidemic profile might evolve in the future. The basic reproduction number, represented by R0 , is the anticipated number of secondary cases that a typical infectious individual would cause in a population that is fully susceptible. This threshold parameter is highly valuable in characterizing mathematical problems related to infectious diseases. If R0 < 1, this suggests that, on average, during the infectious period, an infected individual produces less than one new infected individual, suggesting that the infection may eventually be eradicated from the population. On the other hand, if R0 < 1, every infected person develops an average of multiple new infections, it suggests that the disease may continue to spread throughout the population. We discuss the Reproduction number in this work and provide some examples, both for straightforward and complicated situations.Item Population dynamics of a mathematical model for Campylobacteriosis(Proceedings of International Conference on Mathematical Modelling Optimization and Analysis of Disease Dynamics (ICMMOADD), 2024-02-22) Ashezua, T. T.; Salemkaan, M. T.; Somma, Samuel AbuThe bacterium campylobacter is the cause of campylobacteriosis, a major cause of foodborne illness that goes by the most common name for diarrheal illnesses. This paper develops and analyzes a new mathematical model for campylobacteriosis. It is demonstrated that in cases where the corresponding reproduction number is smaller than unity, the model's disease-free equilibrium is both locally and globally stable. The numerical simulation results indicate that increasing the treatment rate for both symptomatic and asymptomatic disease-infected individuals resulted in a decrease in the number of asymptomatic and symptomatic individuals, respectively, and a rise in the population's number of recovered individuals.