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Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations
The COVID-19 pandemic has disproportionately affected communities of color, including Latinx communities. Oregon Saludable: Juntos Podemos (OSJP) is a randomized clinical trial aimed at reducing this disparity by both increasing access to testing for SARS-CoV-2, the virus that causes COVID-19, for O...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827438/ https://www.ncbi.nlm.nih.gov/pubmed/36622480 http://dx.doi.org/10.1007/s11121-022-01478-x |
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author | Searcy, Jacob A. Cioffi, Camille C. Tavalire, Hannah F. Budd, Elizabeth L. Cresko, William A. DeGarmo, David S. Leve, Leslie D. |
author_facet | Searcy, Jacob A. Cioffi, Camille C. Tavalire, Hannah F. Budd, Elizabeth L. Cresko, William A. DeGarmo, David S. Leve, Leslie D. |
author_sort | Searcy, Jacob A. |
collection | PubMed |
description | The COVID-19 pandemic has disproportionately affected communities of color, including Latinx communities. Oregon Saludable: Juntos Podemos (OSJP) is a randomized clinical trial aimed at reducing this disparity by both increasing access to testing for SARS-CoV-2, the virus that causes COVID-19, for Oregon Latinx community members and studying the effectiveness of health and behavioral health interventions on turnout and health outcomes. OSJP established SARS-CoV-2 testing events at sites across Oregon. A critical early question was how to locate these sites to best serve Latinx community members. To propose sites in each participating county, we implemented an algorithmic approach solving a facilities location problem. This algorithm was based on minimizing driving time from Latinx population centers to SARS-CoV-2 testing locations. OSJP staff presented these proposed testing locations to community partners as a starting place for identifying final testing sites. Due to differences in geography, population distributions, and potential site accessibility, the study sites exhibited variation in how well the algorithmic optimization objectives could be satisfied. From this variation, we inferred the effects of the drive time optimization metric on the likelihood of Latinx community members utilizing SARS-CoV-2 testing services. After controlling for potential confounders, we found that minimizing the drive time optimization metric was strongly correlated with increased turnout among Latinx community members. This paper presents the algorithm and data sources used for site proposals and discusses challenges and opportunities for community-based health promotion research when translating algorithm proposals into action across a range of health outcomes. |
format | Online Article Text |
id | pubmed-9827438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-98274382023-01-09 Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations Searcy, Jacob A. Cioffi, Camille C. Tavalire, Hannah F. Budd, Elizabeth L. Cresko, William A. DeGarmo, David S. Leve, Leslie D. Prev Sci Article The COVID-19 pandemic has disproportionately affected communities of color, including Latinx communities. Oregon Saludable: Juntos Podemos (OSJP) is a randomized clinical trial aimed at reducing this disparity by both increasing access to testing for SARS-CoV-2, the virus that causes COVID-19, for Oregon Latinx community members and studying the effectiveness of health and behavioral health interventions on turnout and health outcomes. OSJP established SARS-CoV-2 testing events at sites across Oregon. A critical early question was how to locate these sites to best serve Latinx community members. To propose sites in each participating county, we implemented an algorithmic approach solving a facilities location problem. This algorithm was based on minimizing driving time from Latinx population centers to SARS-CoV-2 testing locations. OSJP staff presented these proposed testing locations to community partners as a starting place for identifying final testing sites. Due to differences in geography, population distributions, and potential site accessibility, the study sites exhibited variation in how well the algorithmic optimization objectives could be satisfied. From this variation, we inferred the effects of the drive time optimization metric on the likelihood of Latinx community members utilizing SARS-CoV-2 testing services. After controlling for potential confounders, we found that minimizing the drive time optimization metric was strongly correlated with increased turnout among Latinx community members. This paper presents the algorithm and data sources used for site proposals and discusses challenges and opportunities for community-based health promotion research when translating algorithm proposals into action across a range of health outcomes. Springer US 2023-01-09 2023 /pmc/articles/PMC9827438/ /pubmed/36622480 http://dx.doi.org/10.1007/s11121-022-01478-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Searcy, Jacob A. Cioffi, Camille C. Tavalire, Hannah F. Budd, Elizabeth L. Cresko, William A. DeGarmo, David S. Leve, Leslie D. Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title | Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title_full | Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title_fullStr | Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title_full_unstemmed | Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title_short | Reaching Latinx Communities with Algorithmic Optimization for SARS-CoV-2 Testing Locations |
title_sort | reaching latinx communities with algorithmic optimization for sars-cov-2 testing locations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9827438/ https://www.ncbi.nlm.nih.gov/pubmed/36622480 http://dx.doi.org/10.1007/s11121-022-01478-x |
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