Related Experiment Video
Updated: Jun 12, 2025
Swabbing the Urban Environment - A Pipeline for Sampling and Detection of SARS-CoV-2 From Environmental Reservoirs
Published on: April 9, 2021
The Test and Protect Program: A Data-Driven, Community-Engaged Approach to COVID-19 Testing Site Localization
Andrew F Beck1, Tiffany Mattingly, Cole Brokamp
1Cincinnati Children's; University of Cincinnati College of Medicine (Drs Beck, Brokamp, Sahay, Margolis, Kahn, Hartley, Ms, Manning, and Mr, Taylor, Kuhnell ); The Health Collaborative (Mattingly and Dr Kegley) University of Cincinnati College of Medicine (Drs Beck, Brokamp, Margolis, Kahn, and Hartley); and bi3 (Ms Trabue).
Community-based COVID-19 testing programs can be optimized for accessibility and equity. A successful program in Hamilton County, Ohio, utilized geospatial analytics and community engagement to provide over 65,000 tests.
Area of Science:
- Public Health
- Epidemiology
- Health Services Research
Background:
- The COVID-19 pandemic necessitated community-based testing to alleviate hospital burdens.
- Accessible, equitable testing strategies were crucial for managing the pandemic's spread.
Purpose of the Study:
- To develop and optimize an accessible, equitable, county-wide COVID-19 testing program.
- To implement a testing strategy that reached underserved communities without overwhelming healthcare facilities.
Main Methods:
- Utilized geospatial analytics to strategically select testing locations for optimal community access.
- Engaged communities to ensure testing sites were established in trusted and accessible locations.
- Tracked data over time to enable continuous program improvement and adaptation.
Main Results:
- The "Test and Protect" program successfully administered over 65,000 COVID-19 tests to nearly 46,000 individuals between August 2020 and December 2021.
- The program demonstrated the feasibility of implementing equitable and accessible community-based testing in diverse urban, suburban, and rural settings.
- Geospatial analytics and community engagement were key factors in the program's success.
Conclusions:
- Community-based testing programs can be effectively designed and implemented using data-driven approaches and community partnerships.
- The developed model offers a replicable strategy for public health initiatives beyond the COVID-19 pandemic.
- Equitable access to testing is achievable through strategic planning and community collaboration.
