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2022 | OriginalPaper | Chapter

Quantifying the Effects of Norms on COVID-19 Cases Using an Agent-Based Simulation

Authors : Jan de Mooij, Davide Dell’Anna, Parantapa Bhattacharya, Mehdi Dastani, Brian Logan, Samarth Swarup

Published in: Multi-Agent-Based Simulation XXII

Publisher: Springer International Publishing

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Abstract

Modelling social phenomena in large-scale agent-based simulations has long been a challenge due to the computational cost of incorporating agents whose behaviors are determined by reasoning about their internal attitudes and external factors. However, COVID-19 has brought the urgency of doing this to the fore, as, in the absence of viable pharmaceutical interventions, the progression of the pandemic has primarily been driven by behaviors and behavioral interventions. In this paper, we address this problem by developing a large-scale data-driven agent-based simulation model where individual agents reason about their beliefs, objectives, trust in government, and the norms imposed by the government. These internal and external attitudes are based on actual data concerning daily activities of individuals, their political orientation, and norms being enforced in the US state of Virginia. Our model is calibrated using mobility and COVID-19 case data. We show the utility of our model by quantifying the benefits of the various behavioral interventions through counterfactual runs of our calibrated simulation.

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Footnotes
1
Our choice of the factors influencing the agents’ decisions, as well as of the norms mentioned above, should be considered as a ‘proof of concept’ to illustrate our framework. In more realistic simulations, elicitation of the most relevant factors in a well-designed study would be paramount. This is left for future work.
 
2
Due to space limitations, we refer to the code repository for the specific details of the factors: https://​bitbucket.​org/​goldenagents/​sim2apl-episimpledemics.
 
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Metadata
Title
Quantifying the Effects of Norms on COVID-19 Cases Using an Agent-Based Simulation
Authors
Jan de Mooij
Davide Dell’Anna
Parantapa Bhattacharya
Mehdi Dastani
Brian Logan
Samarth Swarup
Copyright Year
2022
DOI
https://doi.org/10.1007/978-3-030-94548-0_8

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