Agent-based Modeling of Urban Exposome Interventions: Prospects, Methodological Considerations and Challenges
Year: 2022
Type: conference-abstract
Abstract: BACKGROUND AND AIM: With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on health behaviors and health outcomes. However, implementing interventions that tackle the exposome in complex urban systems can be costly and have long-term, sometimes unforeseen, impacts. Hence, it is crucial to assess the health impact, cost-effectiveness, and social distributional impacts of possible urban exposome interventions before implementing them. Spatial agent-based modeling (ABM) can capture complex behavior-environment interactions, exposure dynamics, and social outcomes in a spatial context. This paper discusses methodological architectures and challenges for successfully modeling urban exposome interventions using spatial ABM. METHODS: We review the potential and limitations of the method; model components required to capture active and passive exposure and intervention effects; human-environment interactions and their integration into the macro-level health impact assessment and social costs benefit analysis; strategies for model calibration. RESULTS: Major challenges for a successful application of ABM to urban exposome intervention assessment are (1) the design of realistic behavioral models that can capture different types of exposure and that respond to urban interventions, (2) the mismatch between the possible granularity of exposure estimates and the evidence for corresponding exposure-response functions, (3) the scalability issues that emerge when aiming to estimate long-term effects such as health and social impacts based on high-resolution models of human-environment interactions, (4) as well as the data- and computational complexity of calibrating the resulting agent-based model. CONCLUSION: This paper suggests possible strategies for addressing these challenges and provides a roadmap for further implementing spatial ABM for urban exposome intervention assessment. Future work should analyse the level of detail that is needed and the short-cuts that can be made. KEYWORDS: Urban Exposome, Agent-based Modeling, Scenario Modeling, Urban Health Interventions, Complex Systems
Source: ISEE Conference Abstracts
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4316924581