Smart Pooled Sample Testing for COVID-19: A Possible Solution For Sparcity of Test Kits (Preprint)
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Abstract
Corona virus disease (COVID-19) has severely affected a large number of people from all over the world. At present, there is no medicine available for its treatment. Adopting preventive measures to limit the spread of infection among the people is the best solution to this global health issue. The identification of infected cases and their isolation from healthy people is one of the essential preventive measures. In this regard, screening of the samples from a large number of people is needed, which requires many reagent kits for the detection of SARS-CoV-2. Data of COVID-19 testing for the screening purposes from various countries revealed that most of the tests were negative. Based on this data, the smart pooling of samples will reduce the kit consumption without affecting the outcome.
OBJECTIVE
The main objective is to find out an effective method for the conduction of maximum testing for SARS-CoV-2 diagnosis with less utilization of reagent kits.
METHODS
The available data of COVID-19 testing from different countries were evaluated by applying the simulators for the calculation of smart pooled sample testing size.
RESULTS
The simulation results show that the Test to Positive Ratio (TPR) is directly linked with the number of tests needed to test a population of 10,000. It TPR is low, the required number of tests will be low, and if TPR is high, then the required tests will be high. If the TPR is below 30, a significant optimization can be achieved, resulting in performing fewer tests for every 10,000 population. The results also show that if the TPR is below or close to 10, a higher group size is more beneficial. Whereas a group size of 2 might be a better choice if TPR is 15 or above.
CONCLUSIONS
The smart pooled sample testing may be a useful strategy in the current prevailing scenario of the COVID-19 pandemic. The application of algorithms to determine the appropriate number of specimens to be pooled for a single test would be a cost-effective solution for the screening of the community.
CLINICALTRIAL
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SciScore for 10.1101/2020.04.21.20044594: (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 To answer that question, we develop a hypothesis that if we made a group with the number of people that is some power of 2, and apply divide and conquer strategy, a significant optimization can be achieved. 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: An explicit section about the limitations of the techniques employed in this study was not found. We …SciScore for 10.1101/2020.04.21.20044594: (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 To answer that question, we develop a hypothesis that if we made a group with the number of people that is some power of 2, and apply divide and conquer strategy, a significant optimization can be achieved. 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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.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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SciScore for 10.1101/2020.04.21.20044594: (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 To answer that question, we develop a hypothesis that if we made a group with the number of people that is some power of 2, and apply divide and conquer strategy, a significant optimization can be achieved. Sex as a biological variable not detected. Table 2: Resources
Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting …
SciScore for 10.1101/2020.04.21.20044594: (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 To answer that question, we develop a hypothesis that if we made a group with the number of people that is some power of 2, and apply divide and conquer strategy, a significant optimization can be achieved. Sex as a biological variable not detected. Table 2: Resources
Results from OddPub: We did not find a statement about open data. We also did not find a statement about open code. Researchers are encouraged to share open data when possible (see Nature blog).
About SciScore
SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, please follow this link.
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