Story time with public Data, Summit County, Ohio, Part 1

Plot made in RStudio, Sima Sharghi, PhD

Plot made in RStudio, Sima Sharghi, PhD

I recently spent some time exploring what can be learned from public neighborhood-level data alone — without using any patient-level information.

Using American Community Survey (ACS) estimates, ZIP/ZCTA geographic data, and the Child Opportunity Index (COI), I created an exploratory view of Summit County looking at: • neighborhood opportunity • median household income • pediatric population density • and geographic clustering patterns

What stood out most was how clearly opportunity appeared geographically patterned across ZIP areas. Lower-opportunity neighborhoods appeared more concentrated around central Akron, while higher-opportunity areas were more visible in surrounding suburban ZIPs.

The bubble plot added another layer of context by showing how pediatric population density and income varied simultaneously across neighborhoods.

This was a great reminder that thoughtfully linked public datasets can reveal meaningful structural patterns and support population health thinking — even before patient-level analyses begin.

Built in R using: • ACS 2023 5-year estimates • Census ZCTA geography • Child Opportunity Index (COI) data

RStats #PublicHealth #DataScience #HealthEquity #PopulationHealth #GeospatialAnalytics #CensusData