From an Attican Hollow: Vulnerabilities and Vaccination Rates in Ohio Counties

Ani Ruhil

The interesting questions, though, would be to ask how vaccination rates square against existing selected underlying medical conditions associated with increased risk for severe COVID-19 illness? We have data from an important study(Razzaghi 2020) so let us get to it!

The scatterplot maps vaccination rates (on the vertical axis) against vulnerability to severe illness from contracting COVID-19 (on the horizontal axis), with the size of the blue circle reflecting the size of the 18+ population. The county labeled is the blue dot in the center of black circle. Southeast Ohio is at elevated risk, with Jackson, Morgan, and Vinton counties leading the State.

What is of topical concern though is current vaccination rates plotted against elevated risk. Some 48.7% of Van Wert’s 18+ population has elevated risk but current vaccination rates for this age-group stand at 23.3%, the second-lowest in the state. Holmes’ vaccination rate is low as well but the Amish presence there always introduces expected noise in the estimates. Why the seemingly negative relationship between risk of severe illness and vaccination rates?

What about vaccine hesitancy? We know that the Household Pulse Survey the Census Bureau has been running for a while now has tried to gauge resistance to the COVID-19 vaccine. It would be interesting to see where hesitancy is high. County-level data are available for analysis, along with social vulnerability.

Where are these data coming from? To support state and local communication and outreach efforts, the Office of the Assistant Secretary of Planning and Evaluation (ASPE) has developed state, county, and sub-state level predictions of hesitancy rates (https://aspe.hhs.gov/pdf-report/vaccine-hesitancy) using the most recently available federal survey data. Specifically, ASPE uses the U.S. Census Bureau’s Household Pulse Survey (HPS) (https://www.census.gov/programs-surveys/household-pulse-survey.html) data to predict hesitancy rates at the Public Use Microdata Areas (PUMA) level using the Census Bureau’s 2019 American Community Survey (ACS) 1-year Public Use Microdata Sample (PUMS)(https://www.census.gov/programs-surveys/acs/microdata.html). County-level estimates are generated from a PUMA-to-county crosswalk available from the Missouri Census Data Center(https://mcdc.missouri.edu/applications/geocorr2014.html). PUMAs spanning multiple counties had their estimates apportioned across those counties based on overall 2010 Census populations.¹

Razzaghi, Hilda. 2020. “Estimated County-Level Prevalence of Selected Underlying Medical Conditions Associated with Increased Risk for Severe COVID-19 Illness — United States, 2018.” MMWR Morb Mortal Wkly Rep 69. https://doi.org/10.15585/mmwr.mm6929a1.

PUMA COVID-19 Hesitancy Data are here: https://data.cdc.gov/Vaccinations/Vaccine-Hesitancy-for-COVID-19-Public-Use-Microdat/djj9-kh3p ↩︎

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Ruhil (2021, June 19). From an Attican Hollow: Vulnerabilities and Vaccination Rates in Ohio Counties. Retrieved from https://aniruhil.org/posts/2021-03-27-county-vaccination-rates/

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@misc{ruhil2021vulnerabilities,
  author = {Ruhil, Ani},
  title = {From an Attican Hollow: Vulnerabilities and Vaccination Rates in Ohio Counties},
  url = {https://aniruhil.org/posts/2021-03-27-county-vaccination-rates/},
  year = {2021}
}

Vulnerabilities and Vaccination Rates in Ohio Counties

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