UrbanPop: A spatial microsimulation framework for exploring demographic influences on human dynamics. (February 2023)

• Record Type: Journal Article
• Authors: Tuccillo, Joseph; Stewart, Robert; Rose, Amy; Trombley, Nathan; Moehl, Jessica; Nagle, Nicholas; Bhaduri, Budhendra
• Is Part Of: Applied geography. Volume 151(2023)
• Publication Date: 2023-02
• Subjects: Spatial microsimulation -- Synthetic population -- Human dynamics -- Planning -- Resilience -- COVID-19 pandemic; Geography -- Periodicals; Human geography -- Periodicals; Human ecology -- Periodicals; 910
• DOI: 10.1016/j.apgeog.2022.102844
• Languages: English
• ISSNs: 0143-6228

Abstract

Abstract: Ensuring the social equity of planning measures in social systems requires an understanding of human dynamics, particularly how individual relationships, activities, and interactions intersect with individual needs. Spatial microsimulation models (SMSMs) support planning for human security goals by representing human dynamics through realistic, georeferenced synthetic populations, that a) provide a complete representation of social systems while b) also protecting individual privacy. In this paper, we present UrbanPop, an open and reproducible SMSM framework for analysis of human dynamics with high spatial, temporal, and demographic resolution. UrbanPop creates synthetic populations of demographically detailed worker and student agents, positioning them first at probable nighttime locations (home), then moving them to probable daytime locations (work/school). Summary aggregations of these populations match the granular detail available at the census block group level in the American Community Survey Summary File (SF), providing realistic approximations of the actual population. UrbanPop users can select particular demographic traits important in their application, resulting in a highly tailored agent population. We first lay out UrbanPop's baseline methodology, including population synthesis, activity modeling, and diagnostics, then demonstrate these capabilities by developing case studies of shifting population distributions and high-risk populations in Knox County, TN during the global COVID-19 pandemic. Highlights: Individual demographics, location, and activities influence population responses to transformational events. Increased telework rates, school closures altered daytime population distributions early in the COVID-19 pandemic. Spatial heterogeneity of high-risk individuals during COVID-19 pandemic during both nighttime and daytime.