ArticleEpidemics2020
Optimally pooled viral testing.
Article in Epidemics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Dorfman pooling enhances SARS-CoV-2 large-scale community testing efficiency.PLOS global public health · 2023Article
- Strategies for Scaling up SARS-CoV-2 Molecular Testing Capacity.Clinics in laboratory medicine · 2022Review
- Cost analysis of coronavirus disease 2019 test strategies using pooled reverse transcriptase-polymerase chain reaction technique.Journal of clinical laboratory analysis · 2022Article
- SARS-CoV-2 RT-qPCR testing of pooled saliva samples: A case study of 824 asymptomatic individuals and a questionnaire survey in Japan.PloS one · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It has long been known that pooling samples may be used to reduce the total number of tests required in order to identify each infected individual in a population. Pooling is most advantageous in populations with low infection (positivity) rates, but is expected to remain better than non-pooled testing in populations with infection rates up to 30%. For populations with infection rates lower than 10%, additional testing efficiency may be realized by performing a second round of pooling to test all the samples in the positive first-round pools. The present predictions are validated by recent COVID-19 (SARS-CoV-2) pooled testing and detection sensitivity measurements performed using non-optimal pool sizes, and quantify the additional improvement in testing efficiency that could have been obtained using optimal pooling. Although large pools are most advantageous for testing populations with very low infection rates, they are predicted to become highly non-optimal with increasing infection rate, while pool sizes smaller than 10 remain near-optimal over a broader range of infection rates.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.