Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Uncertainty Quantification (1.0.0)

This archive contains the SAFE-ABM computational model developed to evaluate targeted intervention strategies for protecting essential workers during epidemic conditions, accompanying the published article “Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Uncertainty Quantification” in the Journal of Artificial Societies and Social Simulation, 29(4), Article 7 (2026). https://doi.org/10.18564/jasss.6276. SAFE-ABM is an agent-based model that simulates disease transmission through structured interactions across households, workplaces, and schools, while incorporating stochastic disease progression and uncertainty in transmission, recovery, and mortality parameters.

The model evaluates five intervention scenarios: Scenario 1, no restrictions; Scenario 2, school-from-home; Scenario 3, essential-workers-only movement; Scenario 4, rotational shifts among essential workers with quarantine of symptomatic active workers; and Scenario 5, rotational shifts among essential workers without quarantine. The archive includes scenario-specific simulation scripts, comparison-analysis scripts, saved derived outputs, README documentation, software requirements, and reproducibility notes.

The included comparison scripts reproduce the main numerical summaries and manuscript outputs, including median epidemic trajectories, predictive-uncertainty plots, cumulative recovery and death summaries, inflection-point summaries, Welch-test comparisons, and mutual-information sensitivity rankings. Saved derived outputs are included so that the main figures and tables can be reproduced without rerunning all large-scale simulations.

Full reruns of the complete manuscript simulation workflow require generating 100 distinct synthetic populations of 10,000 agents per scenario and simulating each population over 120 days. This archive accompanies the published SAFE-ABM article and provides the computational code, documentation, and derived outputs to support reproducibility and further research.

Release Notes

Initial public release (v1.0.0) of the SAFE-ABM computational model accompanying the published article “Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Uncertainty Quantification” in the Journal of Artificial Societies and Social Simulation (2026). This release includes source code, scenario-specific simulation scripts, comparison-analysis scripts, saved derived outputs, README documentation, software requirements, and reproducibility notes.

Article DOI: https://doi.org/10.18564/jasss.6276

Associated Publications

Essential Workers at Risk: An Agent-Based Model (SAFE-ABM) with Uncertainty Quantification. Journal of Artificial Societies and Social Simulation (JASSS), 29(4), Article 7 (2026). https://doi.org/10.18564/jasss.6276