MARKOVIAN RANDOM WALK MODELING AND VISUALIZATION OF THE EPIDEMIC SPREAD OF COVID-19

Haluk Akay; George Barbastathis

First, a theoretical environment is considered to measure the effect that changes in susceptible population density and testing rates have on the spread of CoVID-19 in a closed system. While holding the population density index D constant at 1.0, the testing rate T was altered, and the changes in population of susceptible, infected and quarantined, and removed agents over time were simulated, shown in figure 1. Frames from the visualization of simulation taken at timesteps of 5, 25, 45, and 65, for the system with no testing policy and the system with a testing rate T of 0.2 are displayed in figure 3 . The theoretical environment was also used to demonstrate the effect changes in population density had on the changes in makeup of population with respect to state of all agents in the system. The results of these simulations are shown in figure 2 . In both figures 1 and 2, the vertical axes denotes the percentage of total agent population in each closed system.