scholarly journals Pooling of coronavirus tests under unknown prevalence

2020 ◽  
Vol 148 ◽  
Author(s):  
A. Pikovski ◽  
K. Bentele
Keyword(s):  
Diagnostic Testing ◽  
False Positives ◽  
Pool Size ◽  
The Novel ◽  
Average Model ◽  
Pooled Testing ◽  
Testing Protocol ◽  
Test Errors ◽  
Novel Coronavirus ◽  
Dilution Effects

Abstract Diagnostic testing for the novel coronavirus is an important tool to fight the coronavirus disease (Covid-19) pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are ‘pooled’ (i.e. grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. The results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.

scholarly journals Remarks on pooling Coronavirus tests

2020 ◽  
Author(s):  
Alexander Pikovski ◽  
Kajetan Bentele
Keyword(s):  
Diagnostic Testing ◽  
False Positives ◽  
Pool Size ◽  
The Novel ◽  
Average Model ◽  
Pooled Testing ◽  
Testing Protocol ◽  
Test Errors ◽  
Novel Coronavirus ◽  
Dilution Effects

AbstractDiagnostic testing for the novel Coronavirus is an important tool to fight the Covid-19 pandemic. However, testing capacities are limited. A modified testing protocol, whereby a number of probes are “pooled” (that is, grouped), is known to increase the capacity for testing. Here, we model pooled testing with a double-average model, which we think to be close to reality for Covid-19 testing. The optimal pool size and the effect of test errors are considered. Results show that the best pool size is three to five, under reasonable assumptions. Pool testing even reduces the number of false positives in the absence of dilution effects.

scholarly journals 458. Molecular SARS-CoV-2 Testing During the COVID-19 Outbreak: Experiences of a Hospital in Southeast Michigan, USA

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S296-S297
Author(s):  
Trini A Mathew ◽  
Jonathan Hopkins ◽  
Diane Kamerer ◽  
Shagufta N Ali ◽  
Daniel Ortiz ◽  
...  
Keyword(s):  
Clinical Features ◽  
Diagnostic Testing ◽  
Beaumont Hospital ◽  
High Capacity ◽  
Turnaround Time ◽  
Molecular Diagnostic ◽  
The Novel ◽  
Repeat Testing ◽  
Asymptomatic Patients ◽  
Novel Coronavirus

Abstract Background The novel Coronavirus SARS CoV-2 (COVID-19) outbreak was complicated by the lack of diagnostic testing kits. In early March 2020, leadership at Beaumont Hospital, Royal Oak Michigan (Beaumont) identified the need to develop high capacity testing modalities with appropriate sensitivity and specificity and rapid turnaround time. We describe the molecular diagnostic testing experience since initial rollout on March 16, 2020 at Beaumont, and results of repeat testing during the peak of the COVID-19 pandemic in MI. Methods Beaumont is an 1100 bed hospital in Southeast MI. In March, testing was initially performed with the EUA Luminex NxTAG CoV Extended Panel until March 28, 2020 when testing was converted to the EUA Cepheid Xpert Xpress SARS-CoV-2 for quicker turnaround times. Each assay was validated with a combination of patient samples and contrived specimens. Results During the initial week of testing there was > 20 % specimen positivity. As the prevalence grew the positivity rate reached 68% by the end of March (Figure 1). Many state and hospital initiatives were implemented during the outbreak, including social distancing and screening of asymptomatic patients to increase case-finding and prevent transmission. We also adopted a process for clinical review of symptomatic patients who initially tested negative for SARS-CoV-2 by a group of infectious disease physicians (Figure 2). This process was expanded to include other trained clinicians who were redeployed from other departments in the hospital. Repeat testing was performed to allow consideration of discontinuation of isolation precautions. During the surge of community cases from March 16 to April 30, 2020, we identified patients with negative PCR tests who subsequently had repeat testing based on clinical evaluation, with 7.1% (39/551) returning positive for SARS- CoV2. Of the patients who expired due to COVID-19 during this period, 4.3% (9/206) initially tested negative before ultimately testing positive. Figure 1 BH RO testing Epicurve Figure 2: Screening tool for repeat COVID19 testing and precautions Conclusion Many state and hospital initiatives helped us flatten the curve for COVID-19. Our hospital testing experience indicate that repeat testing may be warranted for those patients with clinical features suggestive of COVID-19. We will further analyze these cases and clinical features that prompted repeat testing. Disclosures All Authors: No reported disclosures

scholarly journals Has the Pandemic Triggered a ‘Paperdemic’? Towards an Assessment of Diagnostic Indicators for COVID-19

2021 ◽  
Author(s):  
AISDL
Keyword(s):  
Predictive Value ◽  
Diagnostic Testing ◽  
Supporting Evidence ◽  
The Novel ◽  
Scientific Publications ◽  
Widespread Belief ◽  
Novel Method ◽  
Consistency Problem ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

This paper is a preliminary step towards the assessment of an alarming widespread belief that victims of the novel coronavirus SARS-CoV-2 include the quality and accuracy of scientific publications about it. Our initial results suggest that this belief cannot be readily ignored, denied, dismissed or refuted, since some genuine supporting evidence can be forwarded for it. This evidence includes an obvious increase in retractions of papers published about the COVID-19 pandemic plus an extra-ordinary phenomenon of inconsistency that we report herein. In fact, we provide a novel method for validating any purported set of the four most prominent indicators of diagnostic testing (Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value), by observing that these indicators constitute three rather than four independent quantities. This observation has virtually been unheard of in the open medical literature, and hence researchers have not taken it into consideration. We define two functions, which serve as consistency criteria, since each of them checks consistency for any set of four numerical values (naturally belonging to the interval [0.0,1.0]) claimed to be the four basic diagnostic indicators. Most of the data we came across in various international journals met our criteria for consistency, but in a few cases, there were obvious unexplained blunders. We explored the same consistency problem for some diagnostic data published in 2020 concerning the ongoing COVID-19 pandemic and observed that the afore-mentioned unexplained blunders tended to be on the rise. A systematic extensive statistical assessment of this resumed tendency is warranted.

scholarly journals A blueprint for academic laboratories to produce SARS-CoV-2 quantitative RT-PCR test kits

2020 ◽  
Vol 295 (46) ◽  
pp. 15438-15453 ◽  
Author(s):  
Samantha J. Mascuch ◽  
Sara Fakhretaha-Aval ◽  
Jessica C. Bowman ◽  
Minh Thu H. Ma ◽  
Gwendell Thomas ◽  
...  
Keyword(s):  
Support Group ◽  
Diagnostic Testing ◽  
The Novel ◽  
Rt Pcr ◽  
Research Teams ◽  
Environmental Testing ◽  
Resource Limited ◽  
Test Kit ◽  
Institute Of Technology ◽  
Novel Coronavirus

Widespread testing for the presence of the novel coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in individuals remains vital for controlling the COVID-19 pandemic prior to the advent of an effective treatment. Challenges in testing can be traced to an initial shortage of supplies, expertise, and/or instrumentation necessary to detect the virus by quantitative RT-PCR (RT-qPCR), the most robust, sensitive, and specific assay currently available. Here we show that academic biochemistry and molecular biology laboratories equipped with appropriate expertise and infrastructure can replicate commercially available SARS-CoV-2 RT-qPCR test kits and backfill pipeline shortages. The Georgia Tech COVID-19 Test Kit Support Group, composed of faculty, staff, and trainees across the biotechnology quad at Georgia Institute of Technology, synthesized multiplexed primers and probes and formulated a master mix composed of enzymes and proteins produced in-house. Our in-house kit compares favorably with a commercial product used for diagnostic testing. We also developed an environmental testing protocol to readily monitor surfaces for the presence of SARS-CoV-2. Our blueprint should be readily reproducible by research teams at other institutions, and our protocols may be modified and adapted to enable SARS-CoV-2 detection in more resource-limited settings.

scholarly journals Multiobjective Genetic Algorithm and Convolutional Neural Network Based COVID-19 Identification in Chest X-Ray Images

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Prashant Kumar Shukla ◽  
Jasminder Kaur Sandhu ◽  
Anamika Ahirwar ◽  
Deepika Ghai ◽  
Priti Maheshwary ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Diagnostic Testing ◽  
The Novel ◽  
Screening Process ◽  
X Ray ◽  
Multiobjective Genetic Algorithm ◽  
Global Pandemic ◽  
Chest X Ray ◽  
Novel Coronavirus ◽  
Fold Cross Validation

COVID-19 is a new disease, caused by the novel coronavirus SARS-CoV-2, that was firstly delineated in humans in 2019.Coronaviruses cause a range of illness in patients varying from common cold to advanced respiratory syndromes such as Severe Acute Respiratory Syndrome (SARS-CoV) and Middle East Respiratory Syndrome (MERS-CoV). The SARS-CoV-2 outbreak has resulted in a global pandemic, and its transmission is increasing at a rapid rate. Diagnostic testing and approaches provide a valuable tool for doctors and support them with the screening process. Automatic COVID-19 identification in chest X-ray images can be useful to test for COVID-19 infection at a good speed. Therefore, in this paper, a framework is designed by using Convolutional Neural Networks (CNN) to diagnose COVID-19 patients using chest X-ray images. A pretrained GoogLeNet is utilized for implementing the transfer learning (i.e., by replacing some sets of final network CNN layers). 20-fold cross-validation is considered to overcome the overfitting quandary. Finally, the multiobjective genetic algorithm is considered to tune the hyperparameters of the proposed COVID-19 identification in chest X-ray images. Extensive experiments show that the proposed COVID-19 identification model obtains remarkably better results and may be utilized for real-time testing of patients.

scholarly journals LATE-PCR for LoC Molecular Diagnostics Devices and Its Application to the Sensitive Detection of SARS-CoV-2

2021 ◽  
Vol 6 (1) ◽  
pp. 43
Author(s):  
Dimitrios Karadimas ◽  
George Tsekenis
Keyword(s):  
Point Of Care ◽  
Low Cost ◽  
Diagnostic Testing ◽  
Heat Denaturation ◽  
Nasopharyngeal Swab ◽  
The Novel ◽  
Rt Pcr ◽  
Qualitative Detection ◽  
Novel Coronavirus ◽  
Real Patients

The emergence of the novel coronavirus, SARS-CoV-2, has highlighted the need for rapid, accurate, and point-of-care diagnostic testing. Lab-on-a-Chip (LoC) devices offer the possibility to run such tests at a low cost, while at the same time permitting the multiplexed detection of several viruses when coupled with microarray detection of the amplified products. Herein, we report the development of a protocol for the qualitative detection of SARS-CoV-2, through the design of appropriate primers that target the evolutionary conserved regions of the virus. The proposed protocol relies on an improved version of asymmetric RT-PCR, the linear-after-the-exponential (LATE)-PCR that uses primers that are deliberately designed for use at unequal concentrations. As a result, LATE-PCR exhibits similar efficiency to symmetric PCR, while promoting accumulation of single-stranded products that can subsequently hybridize to a single-strand DNA probe-spotted microarray. The performance of the developed LATE-PCR protocol was compared to that of symmetric RT-PCR, and validated with the use of artificial viral RNA and nasopharyngeal swab samples from real patients. Furthermore, and in order to illustrate its potential for integration into a biosensor platform, the amplicons were allowed to hybridize with probes that were covalently immobilized onto commercially available functionalized glass, without the need for heat denaturation.

scholarly journals Has the Pandemic Triggered a ‘Paperdemic’? Towards an Assessment of Diagnostic Indicators for COVID-19

2021 ◽  
pp. 28-49
Author(s):  
Ali Muhammad Ali Rushdi ◽  
Hamzah Abdul Majid Serag
Keyword(s):  
Predictive Value ◽  
Diagnostic Testing ◽  
Supporting Evidence ◽  
The Novel ◽  
Scientific Publications ◽  
Widespread Belief ◽  
Novel Method ◽  
Consistency Problem ◽  
Novel Coronavirus ◽  
Sensitivity Specificity

This paper is a preliminary step towards the assessment of an alarming widespread belief that victims of the novel coronavirus SARS-CoV-2 include the quality and accuracy of scientific publications about it. Our initial results suggest that this belief cannot be readily ignored, denied, dismissed or refuted, since some genuine supporting evidence can be forwarded for it. This evidence includes an obvious increase in retractions of papers published about the COVID-19 pandemic plus an extra-ordinary phenomenon of inconsistency that we report herein. In fact, we provide a novel method for validating any purported set of the four most prominent indicators of diagnostic testing (Sensitivity, Specificity, Positive Predictive Value, and Negative Predictive Value), by observing that these indicators constitute three rather than four independent quantities. This observation has virtually been unheard of in the open medical literature, and hence researchers have not taken it into consideration. We define two functions, which serve as consistency criteria, since each of them checks consistency for any set of four numerical values (naturally belonging to the interval [0.0,1.0]) claimed to be the four basic diagnostic indicators. Most of the data we came across in various international journals met our criteria for consistency, but in a few cases, there were obvious unexplained blunders. We explored the same consistency problem for some diagnostic data published in 2020 concerning the ongoing COVID-19 pandemic and observed that the afore-mentioned unexplained blunders tended to be on the rise. A systematic extensive statistical assessment of this presumed tendency is warranted.

scholarly journals Scalable and Resilient SARS-CoV-2 testing in an Academic Centre

2020 ◽  
Keyword(s):  
Web Application ◽  
Healthcare Workers ◽  
Data Science ◽  
Diagnostic Testing ◽  
Lavage Fluid ◽  
Turnaround Time ◽  
The Novel ◽  
Diagnostic Laboratory ◽  
Novel Coronavirus ◽  
Online Web

AbstractThe emergence of the novel coronavirus SARS-CoV-2 has led to a pandemic infecting more than two million people worldwide in less than four months, posing a major threat to healthcare systems. This is compounded by the shortage of available tests causing numerous healthcare workers to unnecessarily self-isolate. We provide a roadmap instructing how a research institute can be repurposed in the midst of this crisis, in collaboration with partner hospitals and an established diagnostic laboratory, harnessing existing expertise in virus handling, robotics, PCR, and data science to derive a rapid, high throughput diagnostic testing pipeline for detecting SARS-CoV-2 in patients with suspected COVID-19. The pipeline is used to detect SARS-CoV-2 from combined nose-throat swabs and endotracheal secretions/ bronchoalveolar lavage fluid. Notably, it relies on a series of in-house buffers for virus inactivation and the extraction of viral RNA, thereby reducing the dependency on commercial suppliers at times of global shortage. We use a commercial RT-PCR assay, from BGI, and results are reported with a bespoke online web application that integrates with the healthcare digital system. This strategy facilitates the remote reporting of thousands of samples a day with a turnaround time of under 24 hours, universally applicable to laboratories worldwide.

scholarly journals Group Testing for SARS-CoV-2 Allows for Up to 10-Fold Efficiency Increase Across Realistic Scenarios and Testing Strategies

2021 ◽  
Vol 9 ◽  
Author(s):  
Claudio M. Verdun ◽  
Tim Fuchs ◽  
Pavol Harar ◽  
Dennis Elbrächter ◽  
David S. Fischer ◽  
...  
Keyword(s):  
Infection Rate ◽  
Web Application ◽  
Diagnostic Testing ◽  
Group Testing ◽  
Population Heterogeneity ◽  
Testing Procedures ◽  
Testing Strategies ◽  
Specificity And Sensitivity ◽  
Novel Coronavirus ◽  
Dilution Effects

Background: Due to the ongoing COVID-19 pandemic, demand for diagnostic testing has increased drastically, resulting in shortages of necessary materials to conduct the tests and overwhelming the capacity of testing laboratories. The supply scarcity and capacity limits affect test administration: priority must be given to hospitalized patients and symptomatic individuals, which can prevent the identification of asymptomatic and presymptomatic individuals and hence effective tracking and tracing policies. We describe optimized group testing strategies applicable to SARS-CoV-2 tests in scenarios tailored to the current COVID-19 pandemic and assess significant gains compared to individual testing.Methods: We account for biochemically realistic scenarios in the context of dilution effects on SARS-CoV-2 samples and consider evidence on specificity and sensitivity of PCR-based tests for the novel coronavirus. Because of the current uncertainty and the temporal and spatial changes in the prevalence regime, we provide analysis for several realistic scenarios and propose fast and reliable strategies for massive testing procedures.Key Findings: We find significant efficiency gaps between different group testing strategies in realistic scenarios for SARS-CoV-2 testing, highlighting the need for an informed decision of the pooling protocol depending on estimated prevalence, target specificity, and high- vs. low-risk population. For example, using one of the presented methods, all 1.47 million inhabitants of Munich, Germany, could be tested using only around 141 thousand tests if the infection rate is below 0.4% is assumed. Using 1 million tests, the 6.69 million inhabitants from the city of Rio de Janeiro, Brazil, could be tested as long as the infection rate does not exceed 1%. Moreover, we provide an interactive web application, available at www.grouptexting.com, for visualizing the different strategies and designing pooling schemes according to specific prevalence scenarios and test configurations.Interpretation: Altogether, this work may help provide a basis for an efficient upscaling of current testing procedures, which takes the population heterogeneity into account and is fine-grained towards the desired study populations, e.g., mild/asymptomatic individuals vs. symptomatic ones but also mixtures thereof.Funding: German Science Foundation (DFG), German Federal Ministry of Education and Research (BMBF), Chan Zuckerberg Initiative DAF, and Austrian Science Fund (FWF).

scholarly journals The Right Kind of Pooled Testing for the Novel Coronavirus: First, Do No Harm

2020 ◽  
Vol 110 (12) ◽  
pp. 1772-1773
Author(s):  
Eugene Litvak ◽  
Susan Dentzer ◽  
Marcello Pagano
Keyword(s):  
The Novel ◽  
Pooled Testing ◽  
Do No Harm ◽  
Novel Coronavirus ◽  
The Right
Sign in / Sign up

Export Citation Format

Share Document