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SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs
The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9839449/ https://www.ncbi.nlm.nih.gov/pubmed/36624344 http://dx.doi.org/10.1038/s41588-022-01267-w |
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author | Han, Alvin X. Toporowski, Amy Sacks, Jilian A. Perkins, Mark D. Briand, Sylvie van Kerkhove, Maria Hannay, Emma Carmona, Sergio Rodriguez, Bill Parker, Edyth Nichols, Brooke E. Russell, Colin A. |
author_facet | Han, Alvin X. Toporowski, Amy Sacks, Jilian A. Perkins, Mark D. Briand, Sylvie van Kerkhove, Maria Hannay, Emma Carmona, Sergio Rodriguez, Bill Parker, Edyth Nichols, Brooke E. Russell, Colin A. |
author_sort | Han, Alvin X. |
collection | PubMed |
description | The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated COVID-19 epidemics in a prototypical low- and middle-income country to investigate how testing rates, sampling strategies and sequencing proportions jointly impact surveillance outcomes, and showed that low testing rates and spatiotemporal biases delay time to detection of new variants by weeks to months and can lead to unreliable estimates of variant prevalence, even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of approximately 100 tests per 100,000 people per day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing. |
format | Online Article Text |
id | pubmed-9839449 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-98394492023-01-15 SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs Han, Alvin X. Toporowski, Amy Sacks, Jilian A. Perkins, Mark D. Briand, Sylvie van Kerkhove, Maria Hannay, Emma Carmona, Sergio Rodriguez, Bill Parker, Edyth Nichols, Brooke E. Russell, Colin A. Nat Genet Article The first step in SARS-CoV-2 genomic surveillance is testing to identify people who are infected. However, global testing rates are falling as we emerge from the acute health emergency and remain low in many low- and middle-income countries (mean = 27 tests per 100,000 people per day). We simulated COVID-19 epidemics in a prototypical low- and middle-income country to investigate how testing rates, sampling strategies and sequencing proportions jointly impact surveillance outcomes, and showed that low testing rates and spatiotemporal biases delay time to detection of new variants by weeks to months and can lead to unreliable estimates of variant prevalence, even when the proportion of samples sequenced is increased. Accordingly, investments in wider access to diagnostics to support testing rates of approximately 100 tests per 100,000 people per day could enable more timely detection of new variants and reliable estimates of variant prevalence. The performance of global SARS-CoV-2 genomic surveillance programs is fundamentally limited by access to diagnostic testing. Nature Publishing Group US 2023-01-09 2023 /pmc/articles/PMC9839449/ /pubmed/36624344 http://dx.doi.org/10.1038/s41588-022-01267-w Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Han, Alvin X. Toporowski, Amy Sacks, Jilian A. Perkins, Mark D. Briand, Sylvie van Kerkhove, Maria Hannay, Emma Carmona, Sergio Rodriguez, Bill Parker, Edyth Nichols, Brooke E. Russell, Colin A. SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title | SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title_full | SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title_fullStr | SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title_full_unstemmed | SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title_short | SARS-CoV-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
title_sort | sars-cov-2 diagnostic testing rates determine the sensitivity of genomic surveillance programs |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9839449/ https://www.ncbi.nlm.nih.gov/pubmed/36624344 http://dx.doi.org/10.1038/s41588-022-01267-w |
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