Print Email Facebook Twitter Using Agent-Based Simulation to Investigate Behavioral Interventions in a Pandemic Simulating Behavioral Interventions in a Pandemic Title Using Agent-Based Simulation to Investigate Behavioral Interventions in a Pandemic Simulating Behavioral Interventions in a Pandemic Author de Mooij, Jan (Universiteit Utrecht) Dell'Anna, D. (TU Delft Control & Simulation) Bhattacharya, Parantapa (University of Virginia) Dastani, Mehdi (Universiteit Utrecht) Logan, Brian (Universiteit Utrecht; University of Aberdeen) Swarup, Samarth (University of Virginia) Date 2022 Abstract Simulation is a useful tool for evaluating behavioral interventions when the adoption rate among a population is uncertain. Individual agent models are often prohibitively expensive, but, unlike stochastic models, allow studying compliance heterogeneity. In this paper we demonstrate the feasibility of evaluating behavioral intervention policies using large-scale data-driven agent-based simulations. We explain how the simulation is calibrated with respect to real-world data, and demonstrate the utility of our approach by studying the effectiveness of interventions used in Virginia in early 2020 through counterfactual simulations. Subject Agent-based Computational EpidemiologyAgent-based ModelingBelief-Desire-IntentionComplex Social SimulationMulti-agent SimulationNormative ReasoningPolicy EvaluationSynthetic Population To reference this document use: http://resolver.tudelft.nl/uuid:cf2da6a7-e8da-4ece-a643-a34b8f412a81 ISSN 1613-0073 Source CEUR Workshop Proceedings, 3182 Event 1st Workshop on Agent-Based Modeling and Policy-Making, AMPM 2021, 2021-12-08 → , Virtual, Vulnius, Lithuania Part of collection Institutional Repository Document type journal article Rights © 2022 Jan de Mooij, D. Dell'Anna, Parantapa Bhattacharya, Mehdi Dastani, Brian Logan, Samarth Swarup Files PDF paper7.pdf 766.01 KB Close viewer /islandora/object/uuid:cf2da6a7-e8da-4ece-a643-a34b8f412a81/datastream/OBJ/view