Abstract
In Norfolk, VA there are significant health disparities among residents. Several explanations exist for these disparities, however, none of these explanations have been formalized into an unambiguous model. In this paper we grow an explanation as to how repeated exposure to harmful environmental elements can create health disparities within Norfolk, VA despite all residents following the same daily schedule. The agents in our model accurately reflect the demographic characteristics of residents within each census tract of Norfolk, VA. Each agent has a home which reflects a residence in the area, and a place of work and place of leisure that represents an actual physical address in the city. All agents travel from home to work and to places of leisure. During their travel, agents are exposed to various levels of harmful environmental elements including bad air quality (also referred to as smog), and excessive noise. The extent to which an agent is exposed depends on the prevalence of the harmful environmental element where the agent is located at that timestep. Our results show for every demographic of agent represented in the model and across the census tracts in Norfolk, VA that one group is exposed to a statistically significant amount more harmful environmental elements than another group. Correlating the exposures of these groups with the variance in health outcomes in the area provides a path to explaining and remedying the health inequities in the area.
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This work is funded by the Hampton Roads Biomedical Research Consortium (300675–010 IRAD).
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Zamponi, V., O’Brien, K., Gore, R., Lynch, C.J. (2023). Growing an Explanation of Health Inequities in Norfolk, VA with an Agent-Based Model. In: Mazal, J., et al. Modelling and Simulation for Autonomous Systems. MESAS 2022. Lecture Notes in Computer Science, vol 13866. Springer, Cham. https://doi.org/10.1007/978-3-031-31268-7_20
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