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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2510.22080 |
| Etiquetas: |
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- 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.