Interventions and their efficacy in controlling the spread of an epidemic: A numerical study.

The effect of interventions on the progression of an epidemic is studied by numerically modeling attributes, such as lockdowns and vaccinations within a stochastic, highly connected, mobile community using an agent-based model. Based on real life assumptions, we are able to gauge the effectiveness of various strategies to contain the spread of a disease through a population. The fine-tuning of control parameters makes the model coherent with real life scenarios and robust from a policy-maker's perspective.

Predictive modeling of disease propagation in a mobile, connected community using cellular automata.

We present numerical results obtained from the modeling of a stochastic, highly connected, and mobile community. The spread of attributes like health and disease among the community members is simulated using cellular automata on a planar two-dimensional surface. With remarkably few assumptions, we are able to predict the future course of propagation of such a disease as a function of time and the fine-tuning of parameters related to interactions among the automata.