Abstract:
Since the COVID-19 epidemic disease outbreak in China in December 2019, the worldwide spread of the disease has enormously impacted the socio-economic and political affairs of all countries and call scientific works across the globe. The SIR stochastic epidemic model is an important tool to determine the probability distribution of epidemic disease transmission. This study aims to describe the analysis of the Stochastic Model of pandemic disease Coronavirus (Covid-19) transmission with a discrete-time Markov chain in Gondar city administration. To achieve this aim, the researcher uses a descriptive research design and mixed research approach has been employed. Secondary data has been collected from the University of Gondar referral hospital. Based on the data collected from the University of Gondar referral hospital the researcher find out that the stochastic model is random; the deterministic model and the column sum of the stochastic matrix are equal to one and show the stochastic and deterministic model graphically. The researcher determines the parameter; transmission rate, recovery rate, and the basic reproduction number at each period, and simulates the result by using python and Matlab programs. The recovery rate ( ) is greater than that of the transmission rate ( ) this infers the infected individuals are recovered gradually in the City. The basic reproduction number (R0) is less than one and it confirms the disease-free equilibrium that means the disease is not reached as an epidemic level in the city because the transmission is small. The probability distribution of the epidemic outbreak is zero. The researcher also determines the forward Kolmogorov equation (Fokker plank equation) to estimate the probability of an outbreak and got relevance to reach at the generalization of the probability of the disease outbreak is small.
Key Words: basic reproduction number, COVID-19, forward Kolmogorov equation, recovery rate, SIR model, stochastic and deterministic model, transmission rate
