Using Agent-Based Simulation to Investigate Behavioral Interventions in a Pandemic Simulating Behavioral Interventions in a Pandemic

Journal Article (2022)
Author(s)

Jan de Mooij (Universiteit Utrecht)

D. Dell'Anna (TU Delft - Control & Simulation)

Parantapa Bhattacharya (University of Virginia)

Mehdi Dastani (Universiteit Utrecht)

Brian Logan (Universiteit Utrecht, University of Aberdeen)

Samarth Swarup (University of Virginia)

Research Group
Control & Simulation
Copyright
© 2022 Jan de Mooij, D. Dell'Anna, Parantapa Bhattacharya, Mehdi Dastani, Brian Logan, Samarth Swarup
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Jan de Mooij, D. Dell'Anna, Parantapa Bhattacharya, Mehdi Dastani, Brian Logan, Samarth Swarup
Research Group
Control & Simulation
Volume number
3182
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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.