Empirical Simulation of Tuberculosis Transmission using Susceptible-Infected Model in Closed Space

Abstract

The mathematical model is one of the best approaches to simulate the spreading behaviour of communicable diseases. However, current work primarily focuses on implementing simulation models in open public spaces with large populations, such as for a whole country. Not all communicable diseases are active in an open space; some illnesses like Tuberculosis (TB) spread actively in a condensed and closed area. Hence, in this paper, we develop a simulation using the Susceptible-Infected (SI) model on TB with the combination of the social force model to portray the heterogeneity of human behaviour. This model is applied to a small community with 30 to 120 population numbers within a closed space. We use the computational model to evaluate the effect of total populations on the reproduction number of TB transmission and the infection time. The reproduction number of TB spread in a closed area is influenced directly by the infection time and the number of total populations. The result indicates that knowing the reproduction number of a communicable disease can predict the spread of illness, and preventative action can be performed to limit the disease. Based on the simulation, we found out that the simulation model generates R_0>1 and the infection time falls between six hours and two years, mimicking the duration of the real-life incubation period for TB. The research may benefit public health in forecasting TB transmission and controlling the outbreak.