SIR Monte Carlo Simulation Model - Multimethod Simulation Software Tool AnyLogic
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Spread of Disease
SIR Monte Carlo Simulation Model
The built-in OptQuest optimizer is used to calibrate an agent based model of contagious disease diffusion. In the model each person has 3 possible states: Susceptible, Infectious and Recovered (SIR). Initially all but few people are susceptible, and few – infectious. A person can contact another person, and in case one is susceptible and another – infectious, the first may get infected with a certain probability. The agents are put on a grid and contacts occur only between the immediate neighbors. The objective is to find the parameters of the agents (contact frequencies and infection probabilities) so that the output of the simulation model fits best with the historical data – the dynamics of infectious population (disease prevalence). As the model is stochastic, the calibration is done under uncertainty, and simulation replications are used. A separate 1st order Monte Carlo experiment is included to demonstrate the variation of output of the agent based model.
Features used: agents, environment with discrete space, message passing, function, statechart, internal transition, rate transition, message transition, dataset, 2D histogram, plot, time plot, 2D histogram chart, button, working with clipboard, Monte-Carlo experiment, calibration experiment, visualization of optimization progress.