Evaluation of Group Testing for SARS-CoV-2 RNA
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Abstract
During the current COVID-19 pandemic, testing kit and RNA extraction kit availability has become a major limiting factor in the ability to determine patient disease status and accurately quantify prevalence. Current testing strategies rely on individual tests of cases matching restrictive diagnostic criteria to detect SARS-CoV-2 RNA, limiting testing of asymptomatic and mild cases. Testing these individuals is one effective way to understand and reduce the spread of COVID-19.
Here, we develop a pooled testing strategy to identify these low-risk individuals. Drawing on the well-studied group testing literature, modeling suggests practical changes to testing protocols which can reduce test costs and stretch a limited test kit supply. When most tests are negative, pooling reduces the total number of tests up to four-fold at 2% prevalence and eight-fold at 0.5% prevalence. At current SARS-CoV-2 prevalence, randomized group testing optimized per country could double the number of tested individuals from 1.85M to 3.7M using only 671k more tests.
This strategy is well-suited to supplement testing for asymptomatic and mild cases who would otherwise go untested, and enable them to adopt behavioral changes to slow the spread of COVID-19.
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SciScore for 10.1101/2020.03.27.20043968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Further extensions of this approach might be justifiable given the current extreme limitations on testing resources. For instance, testing efficiency can be increased at the expense of specificity by pooling people in close …
SciScore for 10.1101/2020.03.27.20043968: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Further extensions of this approach might be justifiable given the current extreme limitations on testing resources. For instance, testing efficiency can be increased at the expense of specificity by pooling people in close contact (ex. family groups, work units) into a single sample prior to group allocation or RNA extraction. This reduces test volume by a constant factor under the assumption that individuals in close contact have positively correlated infection status and that cluster identification is more vital to suppression than determining a particular individual’s infection status. In addition, pooling samples from the same individual (sputum, nasopharyngeal swab, etc) will obtain similar benefits with essentially no loss of information. Overall, we present a straightforward and directly applicable approach to extend testing for SARS-CoV-2 to lower-risk individuals using pooling. While there are numerous technical hurdles left to overcome, we anticipate that strategies such as those proposed here will be valuable in obtaining more accurate estimates of population prevalence and disease spread in the coming months. Minimizing pipetting errors: Pipetting errors are clearly a large concern in the implementation of this approach, as single missteps are both difficult to detect and result in both false positives and false negatives. We consider multiple possible mitigation strategies: Independent of the modest efficiency gains of clinical-risk-driven ordering (as in Figure...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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