Evaluation of A Spatial Microsimulation Framework for Small-Area Estimation of Population Health Outcomes Using the Behavioral Risk Factor Surveillance System

Emma Von Hoene, Aanya Gupta, Hamdi Kavak, Amira Roess, Taylor Anderson
10/24/2025
stat.APcs.MA

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Abstract

This study introduces the Spatial Health and Population Estimator (SHAPE), a spatial microsimulation framework that applies hierarchical iterative proportional fitting (IPF) to estimate two health risk behaviors and eleven health outcomes across multiple spatial scales. SHAPE was evaluated using county-level direct estimates from the Behavioral Risk Factor Surveillance System (BRFSS) and both county and census tract level data from CDC PLACES for New York (2021) and Florida (2019). Results show that SHAPE's SAEs are moderately consistent with BRFSS (average Pearson's correlation coefficient r of about 0.5), similar to CDC PLACES (average r of about 0.6), and are strongly aligned with CDC PLACES model-based estimates at both county (average r of about 0.8) and census tract (average r of about 0.7) levels. SHAPE is an open, reproducible, and transparent framework programmed in R that meets a need for accessible SAE methods in public health.

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Cite this paper

@article{hoene2025evaluation,
  title  = {Evaluation of A Spatial Microsimulation Framework for Small-Area Estimation of Population Health Outcomes Using the Behavioral Risk Factor Surveillance System},
  author = {Emma Von Hoene and Aanya Gupta and Hamdi Kavak and Amira Roess and Taylor Anderson},
  year   = {2025},
  eprint = {2510.22080},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2510.22080v1}
}

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