Detection of asymptomatic SARS-CoV-2 infections in daycare centers, schools, and companies for regional pandemic containment by a PCR testing laboratory cooperative between July 2021 and June 2022

As an important element in the regional containment of the COVID-19 pandemic a PCR testing laboratory with a cooperative character was founded in spring 2021 to screen for SARS-CoV-2 in the Nuremberg region, Germany. The aim was to detect asymptomatic infections in day care facilities for children, schools, and companies. The laboratory used an established RT-PCR protocol and analyzed approximately 18,500 pools of up to 25 pooled samples each from gargles or swabs ("lollipops") from up to 135 facilities between July 2021 and June 2022. Usually, the participating facilities were informed about positive pools within a few hours. Retention samples from positive pools were usually analyzed on the same day, and the results were reported to the facilities as well as the German Electronic Reporting and Information System (DEMIS). In the laboratory results, both the local incidences and the transition from the Delta- to the Omicron surge in early 2022 were well reflected. It is plausible that about 4,800 secondary infections could be prevented from the approximately 1,570 positive individual samples detected in conjunction with appropriate isolation measures. Such a PCR laboratory, which is characterized by short response times and high flexibility, can thus provide valuable services for regional surveillance of infection incidence.

Detection of SARS-CoV-2 through pool testing for COVID-19: an integrative review

INTRODUCTION

The pool testing technique optimizes the number of tests performed and reduces the delivery time of results, which is an interesting strategy for the health crisis caused by the COVID-19 pandemic. This integrative review investigated studies in which pool testing was carried out for epidemiological or screening purposes to analyze its clinical or cost effectiveness and assessed the applicability of this method in high-, middle-, and low-income countries.

METHODS

This integrative review used primary studies published in the MEDLINE, EMBASE, Literatura Latino-Americana e do Caribe em Ciências da Saúde (LILACS), and Cochrane Library databases.

RESULTS

A total of 435 studies were identified: 35.3% were carried out in Asia, 29.4% in Europe, 29.4% in North America, and 5.9% in Oceania.

CONCLUSIONS

This review suggests that pool testing in the general population may be a useful surveillance strategy to detect new variants of SARS-CoV-2 and to evaluate the period of immunogenicity and global immunity from vaccines.

Pathology Informatics and Robotics Strategies for Improving Efficiency of COVID-19 Pooled Testing

The global rise of the coronavirus disease 2019 pandemic resulted in an exponentially increasing demand for severe acute respiratory syndrome coronavirus 2 testing, which resulted in shortage of reagents worldwide. This shortage has been further worsened by screening of asymptomatic populations such as returning employees, students, and so on, as part of plans to reopen the economy. To optimize the utilization of testing reagents and human resources, pool testing of populations with low prevalence has emerged as a promising strategy. Although pooling is an effective solution to reduce the number of reagents used for testing, the process of pooling samples together and tracking them throughout the entire workflow is challenging. To be effective, samples must be tracked into each pool, pool-tested and reported individually. In this article, we address these challenges using robotics and informatics.

Pool Testing as a Strategy for Prevention of SARS-CoV-2 Outbreaks in Schools: Protocol for a Feasibility Study

BACKGROUND

School closures are a widely implemented strategy for limiting infection spread in the current COVID-19 pandemic. The negative impact of school closures on children and young people is increasingly apparent, however.

OBJECTIVE

We aim to evaluate the feasibility of an infection monitoring program in schools to enable targeted quarantining to replace school closures. The program is currently being implemented in two model schools in Magdeburg, Germany, within the framework of the Study of Coronavirus Outbreak Prevention in Magdeburg Schools (Studie zur Ausbruchsvermeidung von Corona an Magdeburger Schulen [STACAMA]).

METHODS

Five pupils per class are pseudorandomly selected twice a week and asked to provide a gargle sample over a 16-week evaluation period. RNA is extracted from each sample individually in a laboratory and pooled according to school class for real-time reverse transcription polymerase chain reaction (rRT-PCR) analysis. Immediate individual sample testing will be carried out in the case of a positive pool test. Individual RNA extraction prior to pooling and application of rRT-PCR result in high test sensitivity. Testing will be performed in strict adherence to data protection standards. All participating pupils will receive a 16-digit study code, which they will be able to use to access their test.

RESULTS

When the study commenced on December 2, 2020, 520 (52%) pupils and their families or guardians had consented to study participation. The study was suspended after four test rounds due to renewed school closures resulting from rising regional infection incidence. Testing resumed when schools reopened on March 8, 2021, at which time consent to participation was provided for 54% of pupils. We will quantitatively and qualitatively evaluate the logistics and acceptability of the program.

CONCLUSIONS

The findings from this study should inform the design of infection surveillance programs in schools based on gargle samples and a PCR-based pool testing procedure, enabling the identification of aspects that may require adaptation before large-scale implementation. Our focus on each step of the logistics and on the experiences of families should enable a robust assessment of the feasibility of such an approach.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

DERR1-10.2196/28673.

False Negative Mitigation in Group Testing for COVID-19 Screening

After lifting the COVID-19 lockdown restrictions and opening businesses, screening is essential to prevent the spread of the virus. Group testing could be a promising candidate for screening to save time and resources. However, due to the high false-negative rate (FNR) of the RT-PCR diagnostic test, we should be cautious about using group testing because a group's false-negative result identifies all the individuals in a group as uninfected. Repeating the test is the best solution to reduce the FNR, and repeats should be integrated with the group-testing method to increase the sensitivity of the test. The simplest way is to replicate the test twice for each group (the 2Rgt method). In this paper, we present a new method for group testing (the groupMix method), which integrates two repeats in the test. Then we introduce the 2-stage sequential version of both the groupMix and the 2Rgt methods. We compare these methods analytically regarding the sensitivity and the average number of tests. The tradeoff between the sensitivity and the average number of tests should be considered when choosing the best method for the screening strategy. We applied the groupMix method to screening 263 people and identified 2 infected individuals by performing 98 tests. This method achieved a 63% saving in the number of tests compared to individual testing. Our experimental results show that in COVID-19 screening, the viral load can be low, and the group size should not be more than 6; otherwise, the FNR increases significantly. A web interface of the groupMix method is publicly available for laboratories to implement this method.

Feasibility, efficiency & effectiveness of pooled sample testing strategy (pooled NAAT) for molecular testing of COVID-19

Background & objectives:

During the current COVID-19 pandemic, a large number of clinical samples were tested by real-time PCR. Pooling the clinical samples before testing can be a good cost-saving and rapid alternative for screening large populations. The aim of this study was to compare the performance characteristics, feasibility and effectiveness of pooling nasal swab and throat swab samples for screening and diagnosis of SARS-CoV-2.

Methods:

The pool testing was applied on a set of samples coming from low COVID-19 positivity areas. A total of 2410 samples were tested in pools of five samples each. A total of five pools of five samples each were generated and tested for E gene.

Results:

Of the total of 482 pools (2410 samples) 24 pools flagged positive. Later on pool de-convolution, a total of 26 samples were detected as positive for COVID-19, leading to positivity of about one per cent in the test population. For the diagnosis of individual samples, the pooling strategies resulted in cost savings of 75 per cent (5 samples per pool).

Interpretation & conclusions:

It was observed that testing samples for COVID-19 by reverse transcription (RT)- PCR after pooling could be a cost-effective method which would save both in manpower and cost especially for resource-poor countries and at a time when test kits were short in supply.

Adjusting the Cut-Off and Maximum Pool Size in RT-qPCR Pool Testing for SARS-CoV-2

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) to detect SARS-CoV-2 RNA is an essential test to monitor the occurrence of COVID-19. A methodology is proposed for the determination of maximum pool size and adjustments of cut-off values of cycle threshold (Ct in RT-qPCR pool testing, to compensate for the dilution caused by pooling. The trade-off between pool size and test sensitivity is stated explicitly. The procedure was designed to ensure that samples that would be detectable in individual testing remain detectable in pool testing. The proposed relaxation in cut-off is dependent on the pool size, allowing a relatively tight correction to avoid loss of detection of positive samples. The methodology was evaluated in a study of pool testing of adults attending a public emergency care unit, reference for COVID-19 in Belo Horizonte, Brazil, and presenting flu-like symptoms. Even samples on the edge of detectability in individual testing were detected correctly. The proposed procedure enhances the consistency of RT-qPCR pool testing by enforcing that the scales of detectability in pool processing and in individual sample processing are compatible. This may enhance the contribution of pool testing to large-scale testing for COVID-19.

Modelling pool testing for SARS-CoV-2: addressing heterogeneity in populations

Amplifying the testing capacity and making better use of testing resources is a crucial measure when fighting any pandemic. A pooled testing strategy for SARS-CoV-2 has theoretically been shown to increase the testing capacity of a country, especially when applied in low prevalence settings. Experimental studies have shown that the sensitivity of reverse transcription-polymerase chain reaction is not affected when implemented in small groups. Previous models estimated the optimum group size as a function of the historical prevalence; however, this implies a homogeneous distribution of the disease within the population. This study aimed to explore whether separating individuals by age groups when pooling samples results in any further savings on test kits or affects the optimum group size estimation compared to Dorfman's pooling, based on historical prevalence. For this evaluation, age groups of interest were defined as 0-19 years, 20-59 years and over 60 years old. Generalisation of Dorfman's pooling was performed by adding statistical weight to the age groups based on the number of confirmed cases and tests performed in the segment. The findings showed that when the pooling samples are based on age groups, there is a decrease in the number of tests per subject needed to diagnose one subject. Although this decrease is minuscule, it might account for considerable savings when applied on a large scale. In addition, the savings are considerably higher in settings where there is a high standard deviation among the positivity rate of the age segments of the general population.

Improved GNSS Localization and Byzantine Detection in UAV Swarms

Many tasks performed by swarms of unmanned aerial vehicles require localization. In many cases, the sensors that take part in the localization process suffer from inherent measurement errors. This problem is amplified when disruptions are added, either endogenously through Byzantine failures of agents within the swarm, or exogenously by some external source, such as a GNSS jammer. In this paper, we first introduce an improved localization method based on distance observation. Then, we devise schemes for detecting Byzantine agents, in scenarios of endogenous disruptions, and for detecting a disrupted area, in case the source of the problem is exogenous. Finally, we apply pool testing techniques to reduce the communication traffic and the computation time of our schemes. The optimal pool size should be chosen carefully, as very small or very large pools may impair the ability to identify the source/s of disruption. A set of simulated experiments demonstrates the effectiveness of our proposed methods, which enable reliable error estimation even amid disruptions. This work is the first, to the best of our knowledge, that embeds identification of endogenous and exogenous disruptions into the localization process.

Pool Testing for COVID-19: Suitable Splitting Procedure and Pool Size for India

Objective:

Coronavirus disease (COVID-19) has emerged as a global pandemic for public health due to the large scale outbreak, therefore there is an urgent need to detect the infected cases quickly and isolate them in order to suppress the further spread of the disease. This study tries to identify a suitable pool testing method and algorithm for COVID-19.

Methods:

This study tries to derive a general equation for the number of tests required for a pooled sample to detect every infected individual in the specific pool. The gain in pool testing over the normal procedure is quantified by the percentage of tests required compared to individual testing.

Results:

The percentage of tests required by the pool testing strategy varies according to the different splitting procedures, the size of the pooled sample, and the probability of an individual being infected in the population. If the probability of infection is 0.05, then for a pool size of 32, only 14 tests are sufficient to detect every infected individual.

Conclusion:

The number of tests required to detect infected individuals by using the pooling method is much lower than individual testing. This may help us with increasing our testing capacity for COVID-19 by testing a large number of individuals in less time with limited resources.

Optimization of group size in pool testing strategy for SARS-CoV-2: A simple mathematical model

Coronavirus disease (Covid‐19) has reached unprecedented pandemic levels and is affecting almost every country in the world. Ramping up the testing capacity of a country supposes an essential public health response to this new outbreak. A pool testing strategy where multiple samples are tested in a single reverse transcriptase‐polymerase chain reaction (RT‐PCR) kit could potentially increase a country's testing capacity. The aim of this study is to propose a simple mathematical model to estimate the optimum number of pooled samples according to the relative prevalence of positive tests in a particular healthcare context, assuming that if a group tests negative, no further testing is done whereas if a group tests positive, all the subjects of the group are retested individually. The model predicts group sizes that range from 11 to 3 subjects. For a prevalence of 10% of positive tests, 40.6% of tests can be saved using testing groups of four subjects. For a 20% prevalence, 17.9% of tests can be saved using groups of three subjects. For higher prevalences, the strategy flattens and loses effectiveness. Pool testing individuals for severe acute respiratory syndrome coronavirus 2 is a valuable strategy that could considerably boost a country's testing capacity. However, further studies are needed to address how large these groups can be, without losing sensitivity on the RT‐PCR. The strategy best works in settings with a low prevalence of positive tests. It is best implemented in subgroups with low clinical suspicion. The model can be adapted to specific prevalences, generating a tailored to the context implementation of the pool testing strategy.

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Increasing testing capacity of a country is a key Public Health strategy in the pandemic.

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A pool testing strategy could potentially increase a country's testing capacity, especially when implemented in lower clinical suspicion groups.

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We provide a mathematical model to estimate the optimum number of subjects to include in a pool test, based on historical prevalences of positive results.

Optimal size of sample pooling for RNA pool testing: An avant-garde for scaling up severe acute respiratory syndrome coronavirus-2 testing

Background and Objectives

Timely diagnosis is essential for the containment of the disease and breaks in the chain of transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The present situation demands the countries to scale up their testing and design innovative strategies to conserve diagnostic kits and reagents. The pooling of samples saves time, workforce and most importantly diagnostic kits and reagents. In the present study, we tried to define the pool size that could be applied with acceptable confidence for testing.

Materials and Methods

We used repeatedly tested positive clinical sample elutes having different levels of SARS CoV 2 RNA and negative sample elutes to prepare seven series of 11 pools each, having pool sizes ranging from 2 to 48 samples to estimate the optimal pool size. Each pool had one positive sample elute in different compositions. All the pools were tested by SARS CoV 2 reverse transcriptase quantitative polymerase chain reaction.

Results

Out of the 77 pools, only 53 (68.8%) were found positive. The sensitivity of pools of 2-48 samples was decreased from 100% (95% confidence interval [CL]; 98.4-100) to 41.41% (95% CL; 34.9-48.1). The maximum size of the pool with acceptable sensitivity (>95%) was found to be of six samples. For the pool size of six samples, the sensitivity was 97.8% and the efficiency of pooling was 0.38.

Conclusions

The pooling of samples is a practical way for scaling up testing and ultimately containing the further spread of the CoV disease 2019 pandemic.

A general regression framework for group testing data, which incorporates pool dilution effects

Group testing, through the use of pooling, has been widely implemented as a more efficient means to screen individuals for infectious diseases. Typically, in these settings, practitioners are tasked with the complimentary goals of both case identification and estimation. For these purposes, many group testing strategies have been proposed, which address issues such as preserving anonymity in estimation studies, quality control, and classification. In general, these strategies require that a significant number of the individuals be retested, either in pools or individually. In order to provide practitioners with a general methodology that can be used to accurately and precisely analyze data of this form, herein, we propose a binary regression framework that can incorporate data arising from any group testing strategy. Further, we relax previously made assumptions regarding testing error rates by relating the diagnostic testing results to the latent biological marker levels of the individuals being tested. We investigate the finite sample performance of our proposed methodology through simulation and by applying our techniques to hepatitis B data collected as part of a study involving Irish prisoners.