File Name: Simulation – Infectious Diseases
Location: Modeling Toolkit | Risk Simulator | Infectious Diseases
Brief Description: Illustrates how to build an epidemic diseases model and use Risk Simulator for running a Monte Carlo simulation on the epidemic model to determine survival probabilities
Requirements: Modeling Toolkit, Risk Simulator
Remember the science fiction movies where some terrorist cell sets off a chemical or biological weapon in a major cosmopolitan area and the heroes in the movie will be in a high-tech situation room with the president and high-ranking military officials looking at a large screen indicating the possible scenarios with the number of people perishing within a day, within two days, and so forth?
Well, the model in this chapter briefly illustrates how an epidemic can spread within a population and how the input assumptions that are uncertain (as in any rampant disease) can be simulated (Figures 141.1 and 141.2). By simulating these assumptions, we can obtain the number of people who might perish if this disease becomes an epidemic. The input parameters include the total population size in the infected area, the probability of contact with an infected person, the initial number of infected individuals, and the potential healing rate. The total numbers of people who might be susceptible, the infected individuals, and those removed from the infected list (cured) are shown over several time periods. The output forecast of interest is the total number of people who perished in this epidemic.
Figure 141.1: Simulating an infectious diseases epidemic model
Figure 141.2: Epidemic interactive model
