Abstract
Spatial data analytics can detect patterns of clustering of events in small geographies across an urban region. This study presents and demonstrates a robust research design to study the longitudinal stability of spatial clustering with small case numbers per census tract and assess the clustering changes over time across the urban environment to better inform public health policy making at the community level. We argue this analysis enables the greater efficiency of public health departments, while leveraging existing data and preserving citizen personal privacy. Analysis at the census tract level is conducted in Mecklenburg County, North Carolina, on hypertension during pregnancy compiled from 2011–2014 birth certificates. Data were derived from per year and per multi-year moving counts by aggregating spatially to census tracts and then assessed for clustering using global Moran’s I. With evidence of clustering, local indicators of spatial association are calculated to pinpoint hot spots, while time series data identified hot spot changes. Knowledge regarding the geographical distribution of diseases is essential in public health to define strategies that improve the health of populations and quality of life. Our findings support that spatial aggregation at the census tract level contributes to identifying the location of at-risk “hot spot” communities to refine health programs, while temporal windowing reduces random noise effects on spatial clustering patterns. With tight state budgets limiting health departments’ funds, using geographic analytics provides for a targeted and efficient approach to health resource planning.
Highlights
In 2014, the U.S Public Health Leadership Forum proposed that local and state health departments act as the Community Chief Health Strategist [1]
Given the geography of census tracts and the series of prenatal hypertension rates, we find the distribution of prenatal hypertension exhibits a significantly positive Moran’s I statistic for each of the eight data series tested (Table 2), indicating a level of positive spatial autocorrelation in hypertension across the county
When we look at neighborhoods within the Mecklenburg County region, we find that hot spots tend to be loosely found in a crescent to the north of the county center throughout the study years
Summary
In 2014, the U.S Public Health Leadership Forum proposed that local and state health departments act as the Community Chief Health Strategist [1]. The overarching objective of this undertaking is to identify trends in health outcomes in a population, and the associated socio-economic determinants that may be conducive to developing adequate and efficient interventions to enhance public health. This is deemed of particular relevance for the resilience of urban regions, where inter-generational and cross-cultural population dynamics challenges standards and practices in healthy cities. As local health departments seek to act as Community Chief Health Strategists, public health administrators will want geospatially informed analysis
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