Proposing A stochastic model for spread of corona virus dynamics in Nigeria

Subject Areas : International Journal of Mathematical Modelling & Computations

Aliyu  Kinafa ¹ (Department of Mathematics, Gombe State University)

Received: 2020-03-01 Accepted : 2020-06-16 Published : 2020-06-20

Keywords: Vaccination, Corona virus, Birth-Death process, Stochastic Simulation, Differential-Difference equations,

Abstract :

The emergence of corona virus (COVID-19) has create a great public concern as the outbreak is still ongoing and government are taking actions such as holiday extension, travel restriction, temporary closure of public work place, borders, schools, quarantine/isolation, social distancing and so on. To mitigate the spread, we proposed and analyzed a stochastic model for the continue spread of corona virus (COVID-19) dynamics considering the impact of vaccination among susceptible, exposed and quarantine cases. The difference and differential-difference equations for the dynamics of (COVID-19) were derived and simulated with available parameters using stochastic simulation (Gillespie Algorithm). The study adopts Continues–Time Birth and Death stochastic process and the probability distribution describing the dynamics of coronavirus was derived and simulated which shows an exponential decay over time. As the time increase, the probability of coronavirus incidents decline to zero. We therefore conclude that vaccination has an impact of 20% among susceptible, exposed and quarantine cases.