CHPC - Research Computing and Data Support for the University

An Agent-Based Model for Estimating Human Activity Patterns on the Wasatch Front

By Albert M. Lund^1,2, Nicole B. Burnett^2,3, Ramkiran Gouripeddi^1,2, and Julio C. Facelli^1,2

¹Department of Biomedical Informatics, ²Center for Clinical and Translational Science, ³Department of Chemistry, University of Utah

It is difficult to measure the impact of air quality on human health because populations are mobile. Additionally, air quality data is reported at low geographic resolutions (> 1 km²), which makes it difficult to characterize acute local variations in air quality. There are few examples of combining human movement and activity data with high resolution air quality data to capture trajectory based exposure profiles in a comprehensive way. An agent-based model helps simulate human activities and locations throughout an arbitrary day. Simulation is used to overcome the limitations of existing datasets; simulated households based on aggregate data for the state of Utah are modeled and activity profiles generated from the American Time Use Survey of the U.S. Bureau of Labor Statistics. The activity profiles are combined with the simulated households to build individual trajectories of activity and location over the desired region of study.

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