ABSTRACT
We consider the problem of sparse signal recovery in a non-adaptive pool-test setting using quantitative measurements from a non-linear model. The quantitative measurements are obtained using the reverse transcription (quantitative) polymerase chain reaction (RT-qPCR) test, which is the standard test used to detect Covid-19. Each quantitative measurement refers to the cycle threshold, a proxy for the viral load in the test sample. We propose two novel, robust recovery algorithms based on alternating direction method of multipliers and block coordinate descent to recover the individual sample cycle thresholds and hence determine the sick individuals, given the pooled sample cycle thresholds and the pooling matrix. We numerically evaluate the normalized mean squared error, false positive rate, false negative rate, and the maximum sparsity levels up to which error-free recovery is possible. We also demonstrate the advantage of using quantitative measurements (as opposed to binary outcomes) in non-adaptive pool testing methods in terms of the testing rate using publicly available data on Covid-19 testing. The simulation results show the effectiveness of the proposed algorithms. IEEE
ABSTRACT
Introduction: Brazil is the second largest country with COVID-19 positive cases worldwide. Due to the potent spread of the virus and the scarcity of kits and supplies, the Brazilian Ministry of Health has granted authorization for the use of kits available during this emergency, without an accurate evaluation of their performance. This study compared the performance and cost-effectiveness of seven molecular assays/kits available in São Paulo, Brazil, for SARS-CoV-2 diagnosis. Materials and methods: A total of 205 nasopharyngeal/oropharyngeal samples from suspected cases of COVID-19, were tested using the following assays: (i) GeneFinder COVID-19 plus RealAmp kit; (ii) 2019-nCoV RNA PCR-Fluorescence Probing, Da An Gene Co.; (iii) in-house RT-qPCR SARS-CoV-2 IAL; (iv) 2019-nCoV kit, IDT; (v) molecular SARS-CoV-2 (E) kit, Bio-Manguinhos; (vi) Allplex 2019-nCoV modified Assay, Seegene Inc, and (vii) Biomol one-step COVID-19 kit, IBMP. The criteria for determining a SARS-CoV-2 true positive result included the cycle threshold cut-off values, the characteristics of exponential/linear curves, the gene target diversity, and a positive result in at least two assays. Results: The overall sensitivity of the assays listed were GeneFinder 83.6%, Da An Gene 100.0%, IAL 90.4%, IDT 94.6%, Bio-Manguinhos 87.7%, Allplex 97.3%, and IBMP 87.7%. The minor sensitive gene target was RdRP. Although all assays had a Cohen's Kappa index ≥0.893, the best tests used multiplex assays identifying N-gene and/or E-gene targets. Conclusion: All assays tested accurate for diagnosis, but considering cost-effectiveness (cost, time consumption, number of samples tested, and performance), the in-house IAL assay was ideal for COVID-19 diagnosis in São Paulo, Brazil.
ABSTRACT
The World Health Organization (WHO) has declared the coronavirus disease 2019 (COVID-19) as an international health emergency. Current diagnostic tests are based on the reverse transcription-quantitative polymerase chain reaction (RT-qPCR) method, which is the gold standard test that involves the amplification of viral RNA. However, the RT-qPCR assay has limitations in terms of sensitivity and quantification. In this study, we tested both qPCR and droplet digital PCR (ddPCR) to detect low amounts of viral RNA. The cycle threshold (CT) of the viral RNA by RT-PCR significantly varied according to the sequences of the primer and probe sets with in vitro transcript (IVT) RNA or viral RNA as templates, whereas the copy number of the viral RNA by ddPCR was effectively quantified with IVT RNA, cultured viral RNA, and RNA from clinical samples. Furthermore, the clinical samples were assayed via both methods, and the sensitivity of the ddPCR was determined to be equal to or more than that of the RT-qPCR. However, the ddPCR assay is more suitable for determining the copy number of reference materials. These findings suggest that the qPCR assay with the ddPCR defined reference materials could be used as a highly sensitive and compatible diagnostic method for viral RNA detection.