Agent-based modeling of urban exposome interventions: prospects, model architectures, and methodological challenges

Abstract

With ever more people living in cities worldwide, it becomes increasingly important to understand and improve the impact of the urban habitat on livability, 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 can capture complex behavior-environment interactions, exposure dynamics, and social outcomes in a spatial context. This paper discusses model architectures and methodological challenges for successfully modeling urban exposome interventions using spatial agent-based modeling. 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. Major challenges for a successful application of agent-based modeling 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. Although challenges exist, strategies are proposed to improve the implementation of ABM in exposome research.

The urban physical exposome and leisure-time physical activity in early midlife: a FinnTwin12 study

“…Measurement errors could skew our identification of key determinants, as exposures with larger errors might show weaker associations and be classified as less influential, even if they are actually more important than those identified as most influential. More granular and accurate estimations of exposure and behavior could facilitate the exploration in the dynamic interaction between the environment and human behavior 12 . Fourth, some exposures were available in 2023 but merged with the address in 2020, posing a temporality issue.…”

“…Urban regeneration projects are a good example, usually designed to improve public health by implementing structural and risk-minimizing solutions. They often yield collateral effects on other aspects, such as bringing economic, social, and cultural benefits, within the city's complex system [12][13][14] . For example, an urban riverside park regeneration project in Barcelona, Spain was estimated to attract over five thousand adult users daily to perform different types of physical activity 15 .…”

Ontology of active and passive environmental exposure

“…Finally, the environment can be modified by behaviour (e.g., when we decide to take a car instead of walking). Thus in environmental exposure, the environment can occur both as cause and effect in various causal chains [59].…”

“…It asks whether the health exposure studied is largely under the subjects' control or not. The former we call active exposure and applies, for instance, to the exposure to unhealthy food, whereas the latter is called passive, for example, when being exposed to air pollution [59]. In the former case, buying or eating food is an activity that causes an exposure that can potentially be controlled by the involved person, while in the latter case, such control is not possible (furthermore, there are different types of passive exposure, which will be further explained in Section 4.…”

“…This distinction 2 is relevant because it determines which model components are required. For passive exposure, tracking of people's (mobility) behaviour and environmental stressor concentrations need to be modelled in detail, while for active exposure, behavioural choices of humans move into focus [59]. The distinction also has ethical and intervention/policy implications, because it determines to what extent a health impact due to exposure can be attributed to a person's responsibility.…”