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

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).

Download Full-text

Group testing for SARS-CoV-2 allows for up to 10-fold efficiency increase across realistic scenarios and testing strategies

10.1101/2020.04.30.20085290 ◽

2020 ◽

Cited By ~ 4

Author(s):

Claudio M. Verdun ◽

Tim Fuchs ◽

Pavol Harar ◽

Dennis Elbrächter ◽

David S. Fischer ◽

...

Keyword(s):

Infection Rate ◽

Web Application ◽

Group Testing ◽

Cross Sectional ◽

Testing Procedures ◽

Fine Grained ◽

Testing Strategies ◽

Care Workers ◽

Efficiency Increase ◽

Study Population

AbstractWe provide a comparison of general strategies for group testing in view of their application to medical diagnosis in the current COVID-19 pandemic. 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 an infection rate up to 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%. Altogether this work may help provide a basis for efficient upscaling of current testing procedures, fine grained towards the desired study population, e.g. cross-sectional versus health-care workers and adapted mixtures thereof. For comparative visualization and querying of the precomputed results we provide an interactive web application. The source code for computation is open and freely available.

Download Full-text

Pooling of coronavirus tests under unknown prevalence

Epidemiology and Infection ◽

10.1017/s0950268820001752 ◽

2020 ◽

Vol 148 ◽

Cited By ~ 2

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.

Download Full-text

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

10.1101/2020.04.19.20071373 ◽

2020 ◽

Cited By ~ 6

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.

Download Full-text

Remarks on pooling Coronavirus tests

10.1101/2020.06.08.20125781 ◽

2020 ◽

Cited By ~ 1

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.

Download Full-text

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

Open Forum Infectious Diseases ◽

10.1093/ofid/ofaa439.651 ◽

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

Download Full-text

Pooled testing with replication as a mass testing strategy for the COVID-19 pandemics

Scientific Reports ◽

10.1038/s41598-021-83104-4 ◽

2021 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Julius Žilinskas ◽

Algirdas Lančinskas ◽

Mario R. Guarracino

Keyword(s):

Real Time ◽

Real Time Pcr ◽

Group Testing ◽

Testing Strategy ◽

Testing Technique ◽

Testing Procedures ◽

Pooled Testing ◽

Replication Scheme ◽

Speed Up ◽

Multiple Patients

AbstractDuring the COVID-19 pandemic it is essential to test as many people as possible, in order to detect early outbreaks of the infection. Present testing solutions are based on the extraction of RNA from patients using oropharyngeal and nasopharyngeal swabs, and then testing with real-time PCR for the presence of specific RNA filaments identifying the virus. This approach is limited by the availability of reactants, trained technicians and laboratories. One of the ways to speed up the testing procedures is a group testing, where the swabs of multiple patients are grouped together and tested. In this paper we propose to use the group testing technique in conjunction with an advanced replication scheme in which each patient is allocated in two or more groups to reduce the total numbers of tests and to allow testing of even larger numbers of people. Under mild assumptions, a 13 × average reduction of tests can be achieved compared to individual testing without delay in time.

Download Full-text

Short-Term Prediction of COVID-19 Cases Using Machine Learning Models

Applied Sciences ◽

10.3390/app11094266 ◽

2021 ◽

Vol 11 (9) ◽

pp. 4266

Author(s):

Md. Shahriare Satu ◽

Koushik Chandra Howlader ◽

Mufti Mahmud ◽

M. Shamim Kaiser ◽

Sheikh Mohammad Shariful Islam ◽

...

Keyword(s):

Machine Learning ◽

Web Application ◽

Learning Models ◽

Short Term ◽

Infected People ◽

Infected Case ◽

First Case ◽

Novel Coronavirus ◽

Short Term Prediction ◽

Machine Learning Models

The first case in Bangladesh of the novel coronavirus disease (COVID-19) was reported on 8 March 2020, with the number of confirmed cases rapidly rising to over 175,000 by July 2020. In the absence of effective treatment, an essential tool of health policy is the modeling and forecasting of the progress of the pandemic. We, therefore, developed a cloud-based machine learning short-term forecasting model for Bangladesh, in which several regression-based machine learning models were applied to infected case data to estimate the number of COVID-19-infected people over the following seven days. This approach can accurately forecast the number of infected cases daily by training the prior 25 days sample data recorded on our web application. The outcomes of these efforts could aid the development and assessment of prevention strategies and identify factors that most affect the spread of COVID-19 infection in Bangladesh.

Download Full-text

Herd Diagnostic Testing Strategies

Bovine Reproduction ◽

10.1002/9781119602484.ch43 ◽

2021 ◽

pp. 526-531

Author(s):

Robert L. Larson

Keyword(s):

Diagnostic Testing ◽

Testing Strategies

Download Full-text

Harnessing testing strategies and public health measures to avert COVID-19 outbreaks during ocean cruises

Scientific Reports ◽

10.1038/s41598-021-95032-4 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Gerardo Chowell ◽

Sushma Dahal ◽

Raquel Bono ◽

Kenji Mizumoto

Keyword(s):

Public Health ◽

Cost Effective ◽

Contact Network ◽

Social Distancing ◽

Individual Level ◽

Health Measures ◽

Testing Strategies ◽

Novel Coronavirus ◽

The Individual ◽

The Impact

AbstractTo ensure the safe operation of schools, workplaces, nursing homes, and other businesses during COVID-19 pandemic there is an urgent need to develop cost-effective public health strategies. Here we focus on the cruise industry which was hit early by the COVID-19 pandemic, with more than 40 cruise ships reporting COVID-19 infections. We apply mathematical modeling to assess the impact of testing strategies together with social distancing protocols on the spread of the novel coronavirus during ocean cruises using an individual-level stochastic model of the transmission dynamics of COVID-19. We model the contact network, the potential importation of cases arising during shore excursions, the temporal course of infectivity at the individual level, the effects of social distancing strategies, different testing scenarios characterized by the test’s sensitivity profile, and testing frequency. Our findings indicate that PCR testing at embarkation and daily testing of all individuals aboard, together with increased social distancing and other public health measures, should allow for rapid detection and isolation of COVID-19 infections and dramatically reducing the probability of onboard COVID-19 community spread. In contrast, relying only on PCR testing at embarkation would not be sufficient to avert outbreaks, even when implementing substantial levels of social distancing measures.

Download Full-text