Alternatively to using differential equations, a SIR model can also be implemented as a network. In this case, each node in the network represents a person. The edges between nodes represent social connections over which a disease can be transmitted. In every iteration step neighbors of an infected node are infected with a certain probability (Probability infection), while already infected persons recover with a certain probability (Probability recovery). Other than in the equation-based version, the structure of a network influences the propagation of the disease. This can be observed in the population plot to the right of the network.
You can start the epidemic simulation by using the Start-button, or alternatively click on a node to infect a member of the population directly.
The Pause-button halts the simulation for analysis. The Reset-button stops the simulation run. Speed refers to the time between two iteration steps and is the only parameter that can influence the running simulation. The other parameters refer to the above mentioned probabilities and the generation of networks.