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SARS-CoV-2 Testing Disparities in Massachusetts
OBJECTIVE: Early deficiencies in testing capacity contributed to poor control of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the context of marked improvement in SARS-CoV-2 testing infrastructure, we sought to examine the alignment of testing with epidemic intens...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654915/ https://www.ncbi.nlm.nih.gov/pubmed/33173919 http://dx.doi.org/10.1101/2020.11.02.20224469 |
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author | Dryden-Peterson, Scott Velásquez, Gustavo E. Stopka, Thomas J. Davey, Sonya Lockman, Shahin Ojikutu, Bisola |
author_facet | Dryden-Peterson, Scott Velásquez, Gustavo E. Stopka, Thomas J. Davey, Sonya Lockman, Shahin Ojikutu, Bisola |
author_sort | Dryden-Peterson, Scott |
collection | PubMed |
description | OBJECTIVE: Early deficiencies in testing capacity contributed to poor control of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the context of marked improvement in SARS-CoV-2 testing infrastructure, we sought to examine the alignment of testing with epidemic intensity to mitigate subsequent waves of COVID-19 in Massachusetts. METHODS: We compiled publicly available weekly SARS-CoV-2 molecular testing data for period (May 27 to October 14, 2020) following the initial COVID-19 wave. We defined testing intensity as weekly SARS-CoV-2 tests performed per 100,000 population and used weekly test positivity (percent of tests positive) as a measure of epidemic intensity. We considered optimal alignment of testing resources to be matching community ranks of testing and positivity. In communities with a lower rank of testing than positivity in a given week, the testing gap was calculated as the additional tests required to achieve matching ranks. Multivariable Poisson modeling was utilized to assess for trends and association with community characteristics. RESULTS: During the observation period, 4,262,000 tests were reported in Massachusetts and the misalignment of testing with epidemic intensity increased. The weekly testing gap increased 9.0% per week (adjusted rate ratio [aRR]: 1.090, 95% confidence interval [CI]: 1.08–1.10). Increasing levels of community socioeconomic vulnerability (aRR: 1.35 per quartile increase, 95% CI: 1.23–1.50) and the highest quartile of minority and language vulnerability (aRR: 1.46, 95% CI 0.96–1.49) were associated with increased testing gaps, but the latter association was not statistically significant. Presence of large university student population (>10% of population) was associated with a marked decrease in testing gap (aRR 0.21, 95% CI: 0.12–0.38). CONCLUSION: These analyses indicate that despite objectives to promote equity and enhance epidemic control in vulnerable communities, testing resources across Massachusetts have been disproportionally allocated to more affluent communities. Worsening structural inequities in access to SARS-CoV-2 testing increase the risk for another intense wave of COVID-19 in Massachusetts, particularly among vulnerable communities. |
format | Online Article Text |
id | pubmed-7654915 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-76549152020-11-11 SARS-CoV-2 Testing Disparities in Massachusetts Dryden-Peterson, Scott Velásquez, Gustavo E. Stopka, Thomas J. Davey, Sonya Lockman, Shahin Ojikutu, Bisola medRxiv Article OBJECTIVE: Early deficiencies in testing capacity contributed to poor control of transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In the context of marked improvement in SARS-CoV-2 testing infrastructure, we sought to examine the alignment of testing with epidemic intensity to mitigate subsequent waves of COVID-19 in Massachusetts. METHODS: We compiled publicly available weekly SARS-CoV-2 molecular testing data for period (May 27 to October 14, 2020) following the initial COVID-19 wave. We defined testing intensity as weekly SARS-CoV-2 tests performed per 100,000 population and used weekly test positivity (percent of tests positive) as a measure of epidemic intensity. We considered optimal alignment of testing resources to be matching community ranks of testing and positivity. In communities with a lower rank of testing than positivity in a given week, the testing gap was calculated as the additional tests required to achieve matching ranks. Multivariable Poisson modeling was utilized to assess for trends and association with community characteristics. RESULTS: During the observation period, 4,262,000 tests were reported in Massachusetts and the misalignment of testing with epidemic intensity increased. The weekly testing gap increased 9.0% per week (adjusted rate ratio [aRR]: 1.090, 95% confidence interval [CI]: 1.08–1.10). Increasing levels of community socioeconomic vulnerability (aRR: 1.35 per quartile increase, 95% CI: 1.23–1.50) and the highest quartile of minority and language vulnerability (aRR: 1.46, 95% CI 0.96–1.49) were associated with increased testing gaps, but the latter association was not statistically significant. Presence of large university student population (>10% of population) was associated with a marked decrease in testing gap (aRR 0.21, 95% CI: 0.12–0.38). CONCLUSION: These analyses indicate that despite objectives to promote equity and enhance epidemic control in vulnerable communities, testing resources across Massachusetts have been disproportionally allocated to more affluent communities. Worsening structural inequities in access to SARS-CoV-2 testing increase the risk for another intense wave of COVID-19 in Massachusetts, particularly among vulnerable communities. Cold Spring Harbor Laboratory 2020-11-04 /pmc/articles/PMC7654915/ /pubmed/33173919 http://dx.doi.org/10.1101/2020.11.02.20224469 Text en http://creativecommons.org/licenses/by-nd/4.0/It is made available under a CC-BY-ND 4.0 International license (http://creativecommons.org/licenses/by-nd/4.0/) . |
spellingShingle | Article Dryden-Peterson, Scott Velásquez, Gustavo E. Stopka, Thomas J. Davey, Sonya Lockman, Shahin Ojikutu, Bisola SARS-CoV-2 Testing Disparities in Massachusetts |
title | SARS-CoV-2 Testing Disparities in Massachusetts |
title_full | SARS-CoV-2 Testing Disparities in Massachusetts |
title_fullStr | SARS-CoV-2 Testing Disparities in Massachusetts |
title_full_unstemmed | SARS-CoV-2 Testing Disparities in Massachusetts |
title_short | SARS-CoV-2 Testing Disparities in Massachusetts |
title_sort | sars-cov-2 testing disparities in massachusetts |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7654915/ https://www.ncbi.nlm.nih.gov/pubmed/33173919 http://dx.doi.org/10.1101/2020.11.02.20224469 |
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