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Related Experiment Video

Updated: Aug 14, 2025

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Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations.

Jacob A Searcy1, Camille C Cioffi2, Hannah F Tavalire2

  • 1Presidential Initiative in Data Science, University of Oregon, 203 Pacific Hall, Eugene, OR, 97403, USA. jsearcy@uoregon.edu.

Prevention Science : the Official Journal of the Society for Prevention Research
|January 9, 2023
PubMed
Summary

Optimizing testing site locations by minimizing drive times significantly increased COVID-19 testing turnout among Latinx communities in Oregon. This approach improved access and addressed health disparities during the pandemic.

Keywords:
COVID-19 testingCommunity-informed researchFacilities location problemLatino/a/x population

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Area of Science:

  • Public Health
  • Health Services Research
  • Epidemiology

Background:

  • COVID-19 disproportionately impacted minority communities, including Latinx populations.
  • Oregon Saludable: Juntos Podemos (OSJP) aimed to reduce disparities through increased SARS-CoV-2 testing and intervention studies.
  • Effective site selection is crucial for community-based health promotion.

Purpose of the Study:

  • To develop and evaluate an algorithmic approach for selecting SARS-CoV-2 testing sites.
  • To maximize accessibility for Latinx community members in Oregon.
  • To assess the impact of drive time optimization on testing turnout.

Main Methods:

  • Implemented a facility location algorithm minimizing driving time from Latinx population centers to testing sites.
  • Utilized community partners to refine proposed testing locations.
  • Analyzed the correlation between drive time optimization and testing service utilization.

Main Results:

  • Minimizing drive time was strongly correlated with increased testing turnout among Latinx individuals.
  • Algorithmic site proposals facilitated discussions with community partners.
  • Variations in site accessibility influenced the effectiveness of optimization.

Conclusions:

  • Algorithmic optimization of drive times is an effective strategy for increasing COVID-19 testing uptake in underserved communities.
  • Community-based participatory research requires adapting algorithmic recommendations to local contexts.
  • This approach offers valuable insights for health promotion research and intervention delivery.