In this work a deterministic and stochastic model is developed to investigate the dynamics of Ebola epidemic. The model includes susceptible, exposed, infected, quarantined and removed or recovered individuals. The model used in this work is based on a deterministic model. The Chowel et. al (2015) work on early detection of Ebola is modified by introducing an assumption that the quarantined class is totally successful and cannot infect the susceptible class. The resulting model is transformed into a stochastic model and solved using the Euler Maruyama method. Data generated with the values assigned to the parameters are used for the simulation. We have been able to develop and analyse a model with an effective isolation of infected individuals and its effect to the basic reproductive number is analysed. In our simulation, the population of infectious individuals is shown over a period of time. It is seen that the disease will produce an epidemic and after some time, the infected class maintain a uniform increment.
Udeze, C., E.N, E , R.A, U & C.A, N (2021). Dynamics of Ebola Virus. Afribary. Retrieved from https://track.afribary.com/works/dynamics-of-ebola-virus
Udeze, Chigozie, et. al. "Dynamics of Ebola Virus" Afribary. Afribary, 01 Dec. 2021, https://track.afribary.com/works/dynamics-of-ebola-virus. Accessed 27 Nov. 2024.
Udeze, Chigozie, Erumaka E.N , Umana R.A and Nse C.A . "Dynamics of Ebola Virus". Afribary, Afribary, 01 Dec. 2021. Web. 27 Nov. 2024. < https://track.afribary.com/works/dynamics-of-ebola-virus >.
Udeze, Chigozie, Erumaka E.N , Umana R.A and Nse C.A . "Dynamics of Ebola Virus" Afribary (2021). Accessed November 27, 2024. https://track.afribary.com/works/dynamics-of-ebola-virus