The influence of infection control policies: A systematic study of the dynamics of an individual-based epidemic model with isolation

We present and discuss how the so called equation-free approach for multi-scale computations can be used to systematically study certain aspects of the dynamics of detailed individual-based epidemic simulators. In particular we address the development of a computational protocol that enables detailed epidemic simulators to converge to their coarse-grained critical points which mark the onset of instabilities including the emergence of time-dependent solutions. As our illustrative example, we choose a simple individual-based stochastic epidemic model deploying in a fixed random regular network. We show how control policies based on the isolation of the infected population can dramatically influence the dynamics of the disease resulting to big-amplitude oscillations. We also construct the approximate coarse-grained bifurcation diagrams illustrating the dependence of the solutions on the disease characteristics.