ADIOS - Case Study "Optimizing Interventions for Agent-Based Infectious Disease Simulations"

The Agent-based Disease Intervention Optimization System (ADIOS) is a heuristic (and prototypical) approach to find optimal interventions for agent-based infectious disease simulations. It uses a domain-specific language for (non-pharmaceutical) interventions and a grammar-guided genetic programming approach to generate and optimize interventions. This artifact contains all the necessary artifacts to reproduce the case study from our paper, "Optimizing Interventions for Agent-Based Infectious Disease Simulations," which will be published in the proceedings of the ACM SIGSIM International Conference on Principles of Advanced Discrete Simulation 2026. In this case study, we apply ADIOS to a simple GEMS simulation model of its default pathogen that is loosely based on COVID-19 (using GEMS version v.0.7.0 (https://github.com/IMMIDD/GEMS/tree/v0.7.0)). Please note that these experiments are of a purely hypothetical nature and designed to test ADIOS. All results are thus only to be interpreted in the context of testing ADIOS and cannot be generalized.