Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct Groups Article Swipe
Lindsey M. Filiatreau
,
Paul N. Zivich
,
Jessie K. Edwards
,
Grace E. Mulholland
,
Ryan Max
,
Daniel Westreich
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1093/aje/kwac178
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1093/aje/kwac178
Pooled testing has been successfully used to expand SARS-CoV-2 testing, especially in settings requiring high volumes of screening of lower-risk individuals, but efficiency of pooling declines as prevalence rises. We propose a differentiated pooling strategy that independently optimizes pool sizes for distinct groups with different probabilities of infection to further improve the efficiency of pooled testing. We compared the efficiency (results obtained per test kit used) of the differentiated strategy with a traditional pooling strategy in which all samples are processed using uniform pool sizes under a range of scenarios. For most scenarios, differentiated pooling is more efficient than traditional pooling. In scenarios examined here, an improvement in efficiency of up to 3.94 results per test kit could be obtained through differentiated versus traditional pooling, with more likely scenarios resulting in 0.12 to 0.61 additional results per kit. Under circumstances similar to those observed in a university setting, implementation of our strategy could result in an improvement in efficiency between 0.03 to 3.21 results per test kit. Our results can help identify settings, such as universities and workplaces, where differentiated pooling can conserve critical testing resources.
Related Topics
Concepts
Pooling
Group testing
Computer science
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
Statistics
Test (biology)
Coronavirus disease 2019 (COVID-19)
Operations management
Medicine
Mathematics
Biology
Internal medicine
Artificial intelligence
Engineering
Disease
Infectious disease (medical specialty)
Combinatorics
Paleontology
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/aje/kwac178
- https://academic.oup.com/aje/article-pdf/192/2/246/49088234/kwac178.pdf
- OA Status
- bronze
- Cited By
- 3
- References
- 51
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4304758093
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4304758093Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1093/aje/kwac178Digital Object Identifier
- Title
-
Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct GroupsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-10Full publication date if available
- Authors
-
Lindsey M. Filiatreau, Paul N. Zivich, Jessie K. Edwards, Grace E. Mulholland, Ryan Max, Daniel WestreichList of authors in order
- Landing page
-
https://doi.org/10.1093/aje/kwac178Publisher landing page
- PDF URL
-
https://academic.oup.com/aje/article-pdf/192/2/246/49088234/kwac178.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://academic.oup.com/aje/article-pdf/192/2/246/49088234/kwac178.pdfDirect OA link when available
- Concepts
-
Pooling, Group testing, Computer science, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Statistics, Test (biology), Coronavirus disease 2019 (COVID-19), Operations management, Medicine, Mathematics, Biology, Internal medicine, Artificial intelligence, Engineering, Disease, Infectious disease (medical specialty), Combinatorics, PaleontologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
3Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 1, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
51Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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