ABSTRACT In 2007, the Department of Housing and Urban Development initiated a point-in-time count of the homeless across the United States. The counts are administered by the Continuum of Care Program, which provides spatial and temporal data for the homeless population over the last decade. Unfortunately, this administrative spatial unit does not align with the more common areal units defined by the United States Census Bureau, which limits usability of these data. To unify these two areal units, spatial disaggregation, matching, and imputation allow for aligning Continuum of Care data with county data. The resulting county-level homeless counts for the years 2005 to 2017 are provided as an R package. The county-level data display more spatial precision and more temporal variation than the Continuum of Care-level data. Nonparametric regression analyses reveal that the spatiotemporal variation in the data can be well approximated by additive spatial and temporal effects at both the county and Continuum of Care level.

中文翻译：

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将 Continuum of Care 无家可归者计数与美国人口普查地区单位联系起来

摘要 2007 年，住房和城市发展部启动了美国各地无家可归者的时间点统计。计数由 Continuum of Care Program 管理，该计划提供过去十年无家可归人口的空间和时间数据。不幸的是，这个行政空间单位与美国人口普查局定义的更常见的区域单位不一致，这限制了这些数据的可用性。为了统一这两个区域单位，空间分解、匹配和插补允许将 Continuum of Care 数据与县数据对齐。由此产生的 2005 年至 2017 年县级无家可归者人数以 R 包的形式提供。县级数据比 Continuum of Care 级数据显示出更高的空间精度和更多的时间变化。