Modeling the influence of restriction policies and perceived risk due to COVID-19 on daily activity scheduling
Cloe Cortes Balcells,
Fabian Torres,
Rico Krueger and
Michel Bierlaire
Transportation Research Part A: Policy and Practice, 2025, vol. 200, issue C
Abstract:
This study develops an Activity-Based Model (ABM) framework to provide a deeper understanding of how activity restriction policies and perceived risks influence human mobility and, consequently, disease transmission. We propose three main contributions: (i) the Activity-Based Restriction Model (ABRM) systematically implements various activity restriction policies, such as closures, curfews, and distance-based limitations, (ii) we introduce a dynamic programming algorithm to address computational intractability in large-scale scenarios, significantly reducing computation time, (iii) we build a Risk Perception Latent Variable Model to simulate how perceived risks influence individual scheduling behavior. By embedding this model into the ABRM, we create the Activity-Based Risk Perception Restriction Model (ABR2M), which captures the dynamic interplay between risk perception and activity scheduling given activity-restriction policies. This integrated approach provides a detailed evaluation of individual schedules, offering valuable insights for the development of informed transportation policies.
Keywords: Interdisciplinary discipline; Discrete choice model; Activity-based modeling; Non-pharmaceutical interventions; Public health policy; Behavioral adaptations (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:transa:v:200:y:2025:i:c:s0965856425002320
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DOI: 10.1016/j.tra.2025.104604
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