Modeling Complex Systems: A Case Study of Compartmental Models in Epidemiology

Figure 5

Heterogeneous connectivity, susceptibility, and infectiousness can substantially change the trajectory of the epidemic. Since the groups are well separated, each group exhibits a unique growth rate. If a homogeneous compartmental model was used to forecast the trajectory at , we would be led to believe that the epidemic was about to end. Parameters: , , number of groups = 5, and contact parameters are approximately exponentially distributed with mean 1. The seed infection is in the group with (see Appendix C).