Within cities there can be stark differences in health across neighborhoods. Often, surveys of city residents are conducted to provide information related to health and then reported to the public at the city level.
However, understanding health characteristics for smaller areas with a city, such as by census tract, zip code, or neighborhood, allow public health practitioners to identify areas of high need and allocate resources. Small area estimation techniques are a way to overcome problems from smaller sample sizes to provide more reliable estimates.
The Drexel Urban Health Collaborative (UHC) utilizes a method of small area estimation called Bayesian hierarchical models that employs both spatial and temporal smoothing to borrow strength from nearby neighborhoods and from the same neighborhood across time. This method was developed by Dr. Harrison Quick, assistant professor of epidemiology and biostatistics at the Drexel Univesity Dornsife School of Public Health. UHC developed a companion methods brief to provide examples of the small area estimates method and their utility.
The UHC publishes methods briefs to provide leadership to the broader community of scholars looking to create a rigorous urban health evidence base. These briefs highlight best practices and emerging directions for collecting, analyzing, and presenting urban health data.Friday Letter Submission, Publish on January 10