THE EFFECT OF BACILLE CALMETTE GUERIN IMMUNIZATION AND MOSQUIRIX VACCINE ON THE SPREAD OF CORONA VIRUS MARKOV CHAIN MONTE CARLO SIMULATION

Abstract

**Please note that the full text is embargoed** ABSTRACT: This is on the development of a mathematical model to study the spread of COVID-19. A SEIR model with a modified MCMC-MH model was used to characterize the susceptibility of Bacille Calmette Guerin (BCG) immunized individuals, RTS, S/A S01 (Mosquirix) vaccine immunized and non-immunized individuals. From the basic SEIR model it was observed that the distribution of recovered individuals showed to increase with increase in number of days. While the more individuals recovered, the number of infectious individuals decreased. During the initial days of corona virus, a jump in exposed individuals was observed for the first 15 days. After this, it starts to decrease as the recovered population continues to increase. The susceptible population decreases for the first 10 days and remains constant for the remaining time. From the SEIR model, it was observed that BCG immunized individuals are less susceptible than all other groups. This population susceptibility was followed by Mosquirix immunized individuals and finally the non-immunized showing the highest susceptibility to corona virus. Further studies using the MCMC-MH model were shown. The immunization Gaussian distributed proposal distribution coupled with the mean and variance extracted from the SEIR model were used to illustrate Markov chains generated by and adaptive algorithm for populations of Bacille Calmette Guerin (BCG) immunized individuals, RTS, S/A S01 (Mosquirix) vaccine immunized and non-immunized individuals.