Pooled testing efficiency increases with test frequency

Pooled testing increases efficiency by grouping individual samples and testing the combined sample, such that many individuals can be cleared with one negative test. This short paper demonstrates that pooled testing is particularly advantageous in the setting of pandemics, given repeated testing, rapid spread, and uncertain risk. Repeated testing mechanically lowers the infection probability at the time of the next test by removing positives from the population. This effect alone means that increasing frequency by x times only increases expected tests by around x. However, this calculation omits a further benefit of frequent testing: Removing infections from the population lowers intragroup transmission, which lowers infection probability and generates further efficiency. For this reason, increasing testing frequency can paradoxically reduce total testing cost. Our calculations are based on the assumption that infection rates are known, but predicting these rates is challenging in a fast-moving pandemic. However, given that frequent testing naturally suppresses the mean and variance of infection rates, we show that our results are very robust to uncertainty and misprediction. Finally, we note that efficiency further increases given natural sampling pools (e.g., workplaces, classrooms) that induce correlated risk via local transmission. We conclude that frequent pooled testing using natural groupings is a cost-effective way to provide consistent testing of a population to suppress infection risk in a pandemic.

Creation and Operation of a COVID-19 Pooled Testing Collection Site Prior to a CTC Rotation

ABSTRACT Introduction This brief report describes the process, used by the 1st Infantry Division (1ID) and Irwin Army Community Hospital (IACH) at Fort Riley, Kansas, for conducting pooled testing collection of over 2,500 Soldiers prior to a large-scale exercise involving multiple units. Materials and Methods The authors captured after action review comments on the process and results of their pooled specimen collection site. Pooled specimen test results were reviewed and classified according to Aberdeen Proving Ground criteria to determine the percentage of successful and failed pooled specimens. Results 1ID and IACH performed pooled testing collection and shipment of 2,684 specimens divided into 298 pools over 6 flight manifests. Of the 298 pooled specimens, 4 (1.34%) were found to be inconclusive or invalid, and the other 294 (98.7%) had sufficient number of human cells to be certified as SARS-CoV-2 (COVID-19) positive or COVID-19 not detected. Conclusion Pooled testing collection is a complex process that may continue to be a requirement for mass screening of COVID-19 prior to military operations. While planning should be tailored to the specific mission and unit, key factors that the authors feel are required for pooled testing to be successful in any situation are standardized training and personnel continuity, quality assurance, administrative oversight by the unit, and collaboration and communication between all involved entities.

Diagnostic accuracy of pooling urine, anorectal, and oropharyngeal specimens for the detection of Chlamydia trachomatis and Neisseria gonorrhoeae: a systematic review and meta-analysis

Background Screening for Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) at genital and extragenital sites is needed for most key populations, but molecular diagnostic tests for CT/NG are costly. We aimed to determine the accuracy of pooled samples from multiple anatomic sites from one individual to detect CT/NG using the testing of a single sample from one anatomic site as the reference. Methods In this systematic review and meta-analysis, we searched five databases for articles published from January 1, 2000, to February 4, 2021. Studies were included if they contained original data describing the diagnostic accuracy of pooled testing compared with single samples, resource use, benefits and harms of pooling, acceptability, and impact on health equity. We present the pooled sensitivities and specificities for CT and NG using a bivariate mixed-effects logistic regression model. The study protocol is registered in PROSPERO, an international database of prospectively registered systematic reviews (CRD42021240793). We used GRADE to evaluate the quality of evidence. Results Our search yielded 7814 studies, with 17 eligible studies included in our review. Most studies were conducted in high-income countries (82.6%, 14/17) and focused on men who have sex with men (70.6%, 12/17). Fourteen studies provided 15 estimates for the meta-analysis for CT with data from 5891 individuals. The pooled sensitivity for multisite pooling for CT was 93.1% [95% confidence intervals (CI) 90.5–95.0], I2=43.3, and pooled specificity was 99.4% [99.0–99.6], I2=52.9. Thirteen studies provided 14 estimates for the meta-analysis for NG with data from 6565 individuals. The pooled sensitivity for multisite pooling for NG was 94.1% [95% CI 90.9–96.3], I2=68.4, and pooled specificity was 99.6% [99.1–99.8], I2=83.6. Studies report significant cost savings (by two thirds to a third). Conclusion Multisite pooled testing is a promising approach to improve testing coverage for CT/NG in resource-constrained settings with a small compromise in sensitivity but with a potential for significant cost savings.

Rapid Review: Diagnostic Accuracy of Pooled Testing versus Individual Testing Using RT-PCR for SARS-CoV-2 for Screening and Surveillance of Individuals with Suspected COVID-19

Background. Pooled testing has been implemented on a limited scale, mainly for screening and surveillance in populations with a low prevalence of COVID-19 to save on limited resources. Objective. To determine the diagnostic accuracy of pooled compared with individual RT-PCR testing for SARS-CoV-2 in individuals suspected of COVID-19. Methods. We searched websites of living CPGs on COVID-19 (Australian COVID-19, COVID NMA, CEBM Oxford), Philippine DOH HTA, databases (PubMed, CENTRAL, medRXIV/bioRXIV), and Clinicaltrials.gov for studies that used pooled testing on individuals suspected of COVID-19. When appropriate, we pooled data for sensitivity and specificity and obtained the range and median of other data, such as positive predictive value and resource savings. We did a priori subgroup analysis for pool size, presence or absence of symptoms and use case, type of specimen, cutoff for positivity, type of kit, and post hoc subgroup analysis for method of pooling and timing of processing. Results. We included 21 studies: 6 diagnostic accuracy studies, and 15 clinical validation studies. Studies had varying populations, index test kit and performance characteristics, positivity rate (0.02 to 15%), and pool size (5 to 16). There was moderate pooled sensitivity, 81% (95% CI 72, 88; I2=73.6%; 6 studies, 776 pools) and high pooled specificity, 99% (95% CI, 98 to 100; I2=1.84%; 5 studies, 666 pools). Positive predictive value based on 21 studies ranged from 67% to 100%. Resource savings in the number of test kits used ranged from 49 to 89%. Identified harms of pooled testing were delayed turnaround time for positive samples and laboratory errors. Conclusion. There is moderate sensitivity and high specificity with pooled testing for the screening of individuals with suspected COVID-19. We recommend further studies to validate the utility based on community prevalence and other test variables.

Missing two key parameters in the pooled testing strategy

The pooled testing strategy [1] misses two key parameters, the infection prevalence p and its variance mentioned many times in the paper as the key determinants of any pooled testing strategy. For illustrating their methods, the authors used p from other studies that employed individual tests. It turned that that no statistical estimators for p and its variance have ever been derived for testing data of pooled samples since the first formulation of testing strategies based on pooled sampled in 1943 [2]. Here I derive the maximum likelihood estimators for p and its variance based on tests of pooled samples. This should result in significant saving in time, resource, and costs.

Pooled Testing and Its Applications in the COVID-19 Pandemic

When testing for a disease such as COVID-19, the standard method is individual testing: we take a sample from each individual and test these samples separately. An alternative is pooled testing (or ‘group testing’), where samples are mixed together in different pools, and those pooled samples are tested. When the prevalence of the disease is low and the accuracy of the test is fairly high, pooled testing strategies can be more efficient than individual testing. In this chapter, we discuss the mathematics of pooled testing and its uses during pandemics, in particular the COVID-19 pandemic. We analyse some one- and two-stage pooling strategies under perfect and imperfect tests, and consider the practical issues in the application of such protocols.

Rapid design and implementation of an adaptive pooling workflow for SARS-CoV-2 testing in an NHS diagnostic laboratory: a proof-of-concept study

Background: Diagnostic laboratories are currently required to provide routine testing of asymptomatic staff and patients as a part of their clinical screening for SARS-CoV-2 infection. However, these cohorts display very different disease prevalence from symptomatic individuals and testing capacity for asymptomatic screening is often limited. Group testing is frequently proposed as a possible solution to address this; however, proposals neglect the technical and operational feasibility of implementation in a front-line diagnostic laboratory. Methods: Between October and December 2020, as a seven-week proof of concept, we took into account scientific, technical and operational feasibility to design and implement an adaptive pooling strategy in an NHS diagnostic laboratory in London (UK). We assessed the impact of pooling on analytical sensitivity and modelled the impact of prevalence on pooling strategy. We then considered the operational constraints to model the potential gains in capacity and the requirements for additional staff and infrastructure. Finally, we developed a LIMS-agnostic laboratory automation workflow and software solution and tested the technical feasibility of our adaptive pooling workflow. Results: First, we determined the analytical sensitivity of the implemented SARS-CoV-2 assay to be 250 copies/mL. We then determined that, in a setting with limited analyser capacity, the testing capacity could be increased by two-fold with pooling, however, in a setting with limited reagents, this could rise to a five-fold increase. These capacity increases could be realized with modest additional resource and staffing requirements whilst utilizing up to 76% fewer plastic consumables and 90% fewer reagents. Finally, we successfully implemented a plate-based pooling workflow and tested 920 patient samples using the reagents that would usually be required to process just 222 samples. Conclusions: Adaptive pooled testing is a scientifically, technically and operationally feasible solution to increase testing capacity in frontline NHS diagnostic laboratories.

COVID-19 Testing and Diagnostics: A Review of Commercialized Technologies for Cost, Convenience and Quality of Tests

Population-scale and rapid testing for SARS-CoV-2 continues to be a priority for several parts of the world. We revisit the in vitro technology platforms for COVID-19 testing and diagnostics—molecular tests and rapid antigen tests, serology or antibody tests, and tests for the management of COVID-19 patients. Within each category of tests, we review the commercialized testing platforms, their analyzing systems, specimen collection protocols, testing methodologies, supply chain logistics, and related attributes. Our discussion is essentially focused on test products that have been granted emergency use authorization by the FDA to detect and diagnose COVID-19 infections. Different strategies for scaled-up and faster screening are covered here, such as pooled testing, screening programs, and surveillance testing. The near-term challenges lie in detecting subtle infectivity profiles, mapping the transmission dynamics of new variants, lowering the cost for testing, training a large healthcare workforce, and providing test kits for the masses. Through this review, we try to understand the feasibility of universal access to COVID-19 testing and diagnostics in the near future while being cognizant of the implicit tradeoffs during the development and distribution cycles of new testing platforms.