Simulation of pooled-sample analysis strategies for COVID-19 mass testing

Efficient discovery of antibody binding pairs using a photobleaching strategy for bead encoding

Dye-encoded bead-based assays are widely used for diagnostics. Multiple bead populations are required for multiplexing and can be produced using different dye colors, labeling levels, or combinations of dye ratios. Ready-to-use multiplex bead populations restrict users to specific targets, are costly, or require specialized instrumentation. In-house methods produce few bead plexes or require many fine-tuning steps. To expand bead encoding strategies, we present a simple, safe, and cost-effective bench-top system for generating bead populations using photobleaching. By photobleaching commercially available dye-encoded magnetic beads for different durations, we produce three times as many differentiable bead populations on flow cytometry from a single dye color. Our photobleaching system uses a high-power LED module connected to a light concentrator and a heat sink. The beads are photobleached in solution homogeneously by constant mixing. We demonstrate this photobleaching method can be utilized for cross-testing antibodies, which is the first step in developing immunoassays. The assay uses multiple photobleached encoded beads conjugated with capture antibodies to test many binding pairs simultaneously. To further expand the number of antibodies that can be tested at once, several antibodies were conjugated to the same bead, forming a pooled assay. Our assay predicts the performance of antibody pairs used in ultrasensitive Simoa assays, narrowing the number of cross-tested pairs that need to be tested by at least two-thirds and, therefore, providing a rapid alternative for an initial antibody pair screening. The photobleaching system can be utilized for other applications, such as multiplexing, and for photobleaching other particles in solution.

Comparison of RT-PCR cycle threshold values between individual and pooled SARS-CoV-2 infected nasopharyngeal swab specimens

The molecular reverse transcription-polymerase chain reaction (RT-PCR) testing of respiratory tract swabs has become mandatory to confirm the diagnosis of coronavirus disease 2019 (COVID-19). However, RT-PCR tests are expensive, require standardized equipment, and relatively long testing times, and the sample pooling method has been introduced to solve this issue. The aim of this study was to compare the cycle threshold (Ct) values of the individual sample and pooled sample methods to assess how accurate the pooling method was. Repeat RT-PCR examinations were initially performed to confirm the Ct values for each sample before running the pooled test procedure. Sample extraction and amplification were performed in both assays to detect ORF1ab, N, and E genes with a cut-off point value of Ct <38. Overall, there was no difference in Ct values between individual sample and pooled sample groups at all concentrations (p=0.259) and for all pooled sizes. Only pooled size of five could detect the Ct value in the pooled samples for all concentration samples, including low-concentration sample (Ct values 36 to 38). This study highlighted that pooled RT-PCR testing strategy did not reduce the quality of individually measured RT-PCR Ct values. A pool size of five could provide a practical technique to expand the screening capacity of RT-PCR.

M. Heuvelink G, Wu C, Yang J, Ruktanonchai NW, Qader SH, Ruktanonchai CW, Cleary E, Yao Y, Liu J, Nnanatu CC, Wesolowski A, Cummings DA, Tatem AJ, Lai S. Optimizing the detection of emerging infections using mobility-based spatial sampling

Timely and precise detection of emerging infections is imperative for effective outbreak management and disease control. Human mobility significantly influences the spatial transmission dynamics of infectious diseases. Spatial sampling, integrating the spatial structure of the target, holds promise as an approach for testing allocation in detecting infections, and leveraging information on individuals' movement and contact behavior can enhance targeting precision. This study introduces a spatial sampling framework informed by spatiotemporal analysis of human mobility data, aiming to optimize the allocation of testing resources for detecting emerging infections. Mobility patterns, derived from clustering point-of-interest and travel data, are integrated into four spatial sampling approaches at the community level. We evaluate the proposed mobility-based spatial sampling by analyzing both actual and simulated outbreaks, considering scenarios of transmissibility, intervention timing, and population density in cities. Results indicate that leveraging inter-community movement data and initial case locations, the proposed Case Flow Intensity (CFI) and Case Transmission Intensity (CTI)-informed spatial sampling enhances community-level testing efficiency by reducing the number of individuals screened while maintaining a high accuracy rate in infection identification. Furthermore, the prompt application of CFI and CTI within cities is crucial for effective detection, especially in highly contagious infections within densely populated areas. With the widespread use of human mobility data for infectious disease responses, the proposed theoretical framework extends spatiotemporal data analysis of mobility patterns into spatial sampling, providing a cost-effective solution to optimize testing resource deployment for containing emerging infectious diseases.

An integrated microfluidic platform for nucleic acid testing

This study presents a rapid and versatile low-cost sample-to-answer system for SARS-CoV-2 diagnostics. The system integrates the extraction and purification of nucleic acids, followed by amplification via either reverse transcription-quantitative polymerase chain reaction (RT-qPCR) or reverse transcription loop-mediated isothermal amplification (RT-LAMP). By meeting diverse diagnostic and reagent needs, the platform yields testing results that closely align with those of commercial RT-LAMP and RT‒qPCR systems. Notable advantages of our system include its speed and cost-effectiveness. The assay is completed within 28 min, including sample loading (5 min), ribonucleic acid (RNA) extraction (3 min), and RT-LAMP (20 min). The cost of each assay is ≈ $9.5, and this pricing is competitive against that of Food and Drug Administration (FDA)-approved commercial alternatives. Although some RNA loss during on-chip extraction is observed, the platform maintains a potential limit of detection lower than 297 copies. Portability makes the system particularly useful in environments where centralized laboratories are either unavailable or inconveniently located. Another key feature is the platform's versatility, allowing users to choose between RT‒qPCR or RT‒LAMP tests based on specific requirements.

Clinical performance of AI-integrated risk assessment pooling reveals cost savings even at high prevalence of COVID-19

Individual testing of samples is time- and cost-intensive, particularly during an ongoing pandemic. Better practical alternatives to individual testing can significantly decrease the burden of disease on the healthcare system. Herein, we presented the clinical validation of Segtnan™ on 3929 patients. Segtnan™ is available as a mobile application entailing an AI-integrated personalized risk assessment approach with a novel data-driven equation for pooling of biological samples. The AI was selected from a comparison between 15 machine learning classifiers (highest accuracy = 80.14%) and a feed-forward neural network with an accuracy of 81.38% in predicting the rRT-PCR test results based on a designed survey with minimal clinical questions. Furthermore, we derived a novel pool-size equation from the pooling data of 54 published original studies. The results demonstrated testing capacity increase of 750%, 60%, and 5% at prevalence rates of 0.05%, 22%, and 50%, respectively. Compared to Dorfman's method, our novel equation saved more tests significantly at high prevalence, i.e., 28% (p = 0.006), 40% (p = 0.00001), and 66% (p = 0.02). Lastly, we illustrated the feasibility of the Segtnan™ usage in clinically complex settings like emergency and psychiatric departments.

Optimization of Screening Strategies for COVID-19: Scoping Review

BACKGROUND

COVID-19 screening is an effective nonpharmaceutical intervention for identifying infected individuals and interrupting viral transmission. However, questions have been raised regarding its effectiveness in controlling the spread of novel variants and its high socioeconomic costs. Therefore, the optimization of COVID-19 screening strategies has attracted great attention.

OBJECTIVE

This review aims to summarize the evidence and provide a reference basis for the optimization of screening strategies for the prevention and control of COVID-19.

METHODS

We applied a methodological framework for scoping reviews and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist. We conducted a scoping review of the present publications on the optimization of COVID-19 screening strategies. We searched the PubMed, Web of Science, and Elsevier ScienceDirect databases for publications up to December 31, 2022. English publications related to screening and testing strategies for COVID-19 were included. A data-charting form, jointly developed by 2 reviewers, was used for data extraction according to the optimization directions of the screening strategies.

RESULTS

A total of 2770 unique publications were retrieved from the database search, and 95 abstracts were retained for full-text review. There were 62 studies included in the final review. We summarized the results in 4 major aspects: the screening population (people at various risk conditions such as different regions and occupations; 12/62, 19%), the timing of screening (when the target population is tested before travel or during an outbreak; 12/62, 19%), the frequency of screening (appropriate frequencies for outbreak prevention, outbreak response, or community transmission control; 6/62, 10%), and the screening and detection procedure (the choice of individual or pooled detection and optimization of the pooling approach; 35/62, 56%).

CONCLUSIONS

This review reveals gaps in the optimization of COVID-19 screening strategies and suggests that a number of factors such as prevalence, screening accuracy, effective allocation of resources, and feasibility of strategies should be carefully considered in the development of future screening strategies.

Optimizing campus-wide COVID-19 test notifications with interpretable wastewater time-series features using machine learning models

During the COVID-19 pandemic, wastewater surveillance of the SARS CoV-2 virus has been demonstrated to be effective for population surveillance at the county level down to the building level. At the University of California, San Diego, daily high-resolution wastewater surveillance conducted at the building level is being used to identify potential undiagnosed infections and trigger notification of residents and responsive testing, but the optimal determinants for notifications are unknown. To fill this gap, we propose a pipeline for data processing and identifying features of a series of wastewater test results that can predict the presence of COVID-19 in residences associated with the test sites. Using time series of wastewater results and individual testing results during periods of routine asymptomatic testing among UCSD students from 11/2020 to 11/2021, we develop hierarchical classification/decision tree models to select the most informative wastewater features (patterns of results) which predict individual infections. We find that the best predictor of positive individual level tests in residence buildings is whether or not the wastewater samples were positive in at least 3 of the past 7 days. We also demonstrate that the tree models outperform a wide range of other statistical and machine models in predicting the individual COVID-19 infections while preserving interpretability. Results of this study have been used to refine campus-wide guidelines and email notification systems to alert residents of potential infections.

Optimizing the detection of emerging infections using mobility-based spatial sampling

Background

Timely and precise detection of emerging infections is crucial for effective outbreak management and disease control. Human mobility significantly influences infection risks and transmission dynamics, and spatial sampling is a valuable tool for pinpointing potential infections in specific areas. This study explored spatial sampling methods, informed by various mobility patterns, to optimize the allocation of testing resources for detecting emerging infections.

Methods

Mobility patterns, derived from clustering point-of-interest data and travel data, were integrated into four spatial sampling approaches to detect emerging infections at the community level. To evaluate the effectiveness of the proposed mobility-based spatial sampling, we conducted analyses using actual and simulated outbreaks under different scenarios of transmissibility, intervention timing, and population density in cities.

Results

By leveraging inter-community movement data and initial case locations, the proposed case flow intensity (CFI) and case transmission intensity (CTI)-informed sampling approaches could considerably reduce the number of tests required for both actual and simulated outbreaks. Nonetheless, the prompt use of CFI and CTI within communities is imperative for effective detection, particularly for highly contagious infections in densely populated areas.

Conclusions

The mobility-based spatial sampling approach can substantially improve the efficiency of community-level testing for detecting emerging infections. It achieves this by reducing the number of individuals screened while maintaining a high accuracy rate of infection identification. It represents a cost-effective solution to optimize the deployment of testing resources, when necessary, to contain emerging infectious diseases in diverse settings.

Comparison of Four Active SARS-CoV-2 Surveillance Strategies in Representative Population Sample Points: Two-Factor Factorial Randomized Controlled Trial

BACKGROUND

The COVID-19 pandemic is characterized by rapid increases in infection burden owing to the emergence of new variants with higher transmissibility and immune escape. To date, monitoring the COVID-19 pandemic has mainly relied on passive surveillance, yielding biased epidemiological measures owing to the disproportionate number of undetected asymptomatic cases. Active surveillance could provide accurate estimates of the true prevalence to forecast the evolution of the pandemic, enabling evidence-based decision-making.

OBJECTIVE

This study compared 4 different approaches of active SARS-CoV-2 surveillance focusing on feasibility and epidemiological outcomes.

METHODS

A 2-factor factorial randomized controlled trial was conducted in 2020 in a German district with 700,000 inhabitants. The epidemiological outcome comprised SARS-CoV-2 prevalence and its precision. The 4 study arms combined 2 factors: individuals versus households and direct testing versus testing conditioned on symptom prescreening. Individuals aged ≥7 years were eligible. Altogether, 27,908 addresses from 51 municipalities were randomly allocated to the arms and 15 consecutive recruitment weekdays. Data collection and logistics were highly digitized, and a website in 5 languages enabled low-barrier registration and tracking of results. Gargle sample collection kits were sent by post. Participants collected a gargle sample at home and mailed it to the laboratory. Samples were analyzed with reverse transcription loop-mediated isothermal amplification (RT-LAMP); positive and weak results were confirmed with real-time reverse transcription-polymerase chain reaction (RT-PCR).

RESULTS

Recruitment was conducted between November 18 and December 11, 2020. The response rates in the 4 arms varied between 34.31% (2340/6821) and 41.17% (2043/4962). The prescreening classified 16.61% (1207/7266) of the patients as COVID-19 symptomatic. Altogether, 4232 persons without prescreening and 7623 participating in the prescreening provided 5351 gargle samples, of which 5319 (99.4%) could be analyzed. This yielded 17 confirmed SARS-CoV-2 infections and a combined prevalence of 0.36% (95% CI 0.14%-0.59%) in the arms without prescreening and 0.05% (95% CI 0.00%-0.108%) in the arms with prescreening (initial contacts only). Specifically, we found a prevalence of 0.31% (95% CI 0.06%-0.58%) for individuals and 0.35% (95% CI 0.09%-0.61%) for households, and lower estimates with prescreening (0.07%, 95% CI 0.0%-0.15% for individuals and 0.02%, 95% CI 0.0%-0.06% for households). Asymptomatic infections occurred in 27% (3/11) of the positive cases with symptom data. The 2 arms without prescreening performed the best regarding effectiveness and accuracy.

CONCLUSIONS

This study showed that postal mailing of gargle sample kits and returning home-based self-collected liquid gargle samples followed by high-sensitivity RT-LAMP analysis is a feasible way to conduct active SARS-CoV-2 population surveillance without burdening routine diagnostic testing. Efforts to improve participation rates and integration into the public health system may increase the potential to monitor the course of the pandemic.

TRIAL REGISTRATION

Deutsches Register Klinischer Studien (DRKS) DRKS00023271; https://tinyurl.com/3xenz68a.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.1186/s13063-021-05619-5.

Adaptive group testing strategy for infectious diseases using social contact graph partitions

Mass testing is essential for identifying infected individuals during an epidemic and allowing healthy individuals to return to normal social activities. However, testing capacity is often insufficient to meet global health needs, especially during newly emerging epidemics. Dorfman's method, a classic group testing technique, helps reduce the number of tests required by pooling the samples of multiple individuals into a single sample for analysis. Dorfman's method does not consider the time dynamics or limits on testing capacity involved in infection detection, and it assumes that individuals are infected independently, ignoring community correlations. To address these limitations, we present an adaptive group testing (AGT) strategy based on graph partitioning, which divides a physical contact network into subgraphs (groups of individuals) and assigns testing priorities based on the social contact characteristics of each subgraph. Our AGT aims to maximize the number of infected individuals detected and minimize the number of tests required. After each testing round (perhaps on a daily basis), the testing priority is increased for each neighboring group of known infected individuals. We also present an enhanced infectious disease transmission model that simulates the dynamic spread of a pathogen and evaluate our AGT strategy using the simulation results. When applied to 13 social contact networks, AGT demonstrates significant performance improvements compared to Dorfman's method and its variations. Our AGT strategy requires fewer tests overall, reduces disease spread, and retains robustness under changes in group size, testing capacity, and other parameters. Testing plays a crucial role in containing and mitigating pandemics by identifying infected individuals and helping to prevent further transmission in families and communities. By identifying infected individuals and helping to prevent further transmission in families and communities, our AGT strategy can have significant implications for public health, providing guidance for policymakers trying to balance economic activity with the need to manage the spread of infection.

Effectiveness of sample pooling strategies for diagnosis of SARS-CoV-2: Specimen pooling vs. RNA elutes pooling

PURPOSE

The pandemic of SARS-CoV-2 or COVID-19 has hugely created an economic imbalance worldwide. With the exponential increase in the number of cases and to keep in check on the community transmission, there is high demand and acute shortage of diagnostic kits. The pooled-sample strategy turns out to be the promising strategy intended to determine the optimal testing for specimens with limited resources and without losing the test sensitivity and specificity. The study was performed with standard molecular biology graded lab equipment, FDA-approved COVID-19 RNA extraction, and SARS-CoV-2 tests kits.

MATERIALS AND METHODS

The study aims to comparatively analyze the pooling strategy of the naso-oropharyngeal specimen sample and RNA extracted from the same patient samples in the pool of 3,5, and 8 with no significant loss in test usability. Another primary focus of the study was detection of low or borderline SARS-CoV-2 positives in the pooling strategy. A total of 300 samples (240 positives and 60 negatives) were tested for 3, 5, and 8 pools of specimen samples and RNA elutes.

RESULTS

The comparative analysis determined the sensitivity for three and five pool strategy to be above 98% and eight pool strategy to be 100%.

CONCLUSION

The RNA elutes pooling strategy concordance rate is better than that of specimen pooling with 100% specificity. Thus, in the substantial crisis of resources with the global pandemic, pooling approaches for SARS-CoV-2 can be practical in a low prevalence rate of 5%.

Optimizing SARS-CoV-2 Pooled Testing Strategies Through Differentiated Pooling for Distinct Groups

Pooled testing has been successfully used to expand SARS-CoV-2 testing, especially in settings requiring high volumes of screening of lower-risk individuals, but efficiency of pooling declines as prevalence rises. We propose a differentiated pooling strategy that independently optimizes pool sizes for distinct groups with different probabilities of infection to further improve the efficiency of pooled testing. We compared the efficiency (results obtained per test kit used) of the differentiated strategy with a traditional pooling strategy in which all samples are processed using uniform pool sizes under a range of scenarios. For most scenarios, differentiated pooling is more efficient than traditional pooling. In scenarios examined here, an improvement in efficiency of up to 3.94 results per test kit could be obtained through differentiated versus traditional pooling, with more likely scenarios resulting in 0.12 to 0.61 additional results per kit. Under circumstances similar to those observed in a university setting, implementation of our strategy could result in an improvement in efficiency between 0.03 to 3.21 results per test kit. Our results can help identify settings, such as universities and workplaces, where differentiated pooling can conserve critical testing resources.

A statistical model for early estimation of the prevalence and severity of an epidemic or pandemic from simple tests for infection confirmation

Epidemics and pandemics require an early estimate of the cumulative infection prevalence, sometimes referred to as the infection "Iceberg," whose tip are the known cases. Accurate early estimates support better disease monitoring, more accurate estimation of infection fatality rate, and an assessment of the risks from asymptomatic individuals. We find the Pivot group, the population sub-group with the highest probability of being detected and confirmed as positively infected. We differentiate infection susceptibility, assumed to be almost uniform across all population sub-groups at this early stage, from the probability of being confirmed positive. The latter is often related to the likelihood of developing symptoms and complications, which differs between sub-groups (e.g., by age, in the case of the COVID-19 pandemic). A key assumption in our method is the almost-random subgroup infection assumption: The risk of initial infection is either almost uniform across all population sub-groups or not higher in the Pivot sub-group. We then present an algorithm that, using the lift value of the pivot sub-group, finds a lower bound for the cumulative infection prevalence in the population, that is, gives a lower bound on the size of the entire infection "Iceberg." We demonstrate our method by applying it to the case of the COVID-19 pandemic. We use UK and Spain serological surveys of COVID-19 in its first year to demonstrate that the data are consistent with our key assumption, at least for the chosen pivot sub-group. Overall, we applied our methods to nine countries or large regions whose data, mainly during the early COVID-19 pandemic phase, were available: Spain, the UK at two different time points, New York State, New York City, Italy, Norway, Sweden, Belgium, and Israel. We established an estimate of the lower bound of the cumulative infection prevalence for each of them. We have also computed the corresponding upper bounds on the infection fatality rates in each country or region. Using our methodology, we have demonstrated that estimating a lower bound for an epidemic's infection prevalence at its early phase is feasible and that the assumptions underlying that estimate are valid. Our methodology is especially helpful when serological data are not yet available to gain an initial assessment on the prevalence scale, and more so for pandemics with an asymptomatic transmission, as is the case with Covid-19.

Accelerating the Laboratory Testing Capacity through Saliva Pooling Prior to Direct RT-qPCR for SARS-CoV-2 Detection

The testing capacity of the laboratory is paramount for better control of the pandemic caused by SARS-CoV-2. The pooling method is promising to increase testing capacity, and the use of direct NAAT-based detection of SARS-CoV-2 on a non-invasive specimen such as saliva will ultimately accelerate the testing capacity. This study aims to validate the pooling-of-four method to quadruple the testing capacity using RNA-extraction-free saliva specimens. In addition, we intend to investigate the preferable stage of pooling, including pre- or post-heating. The compatibility of this approach was also tested on five commercial kits. Saliva specimens stored at -80 °C for several months were proven viable and were used for various tests in this study. Our findings revealed that pooling-of-four specimens had an overall agreement rate of 98.18% with their individual testing. Moreover, we proved that the pooling procedure could be conducted either pre- or post-heating, with no discordance and no significant difference in Ct values generated. When compared to other commercial detection kits, it demonstrated an overall agreement greater than 85%, which exhibits broad compatibility and ensures easy adaptability in clinical settings. This method has been proven reliable and increases the testing capacity up to fourfold.

Effective screening strategies for safe opening of universities under Omicron and Delta variants of COVID-19

As new COVID-19 variants emerge, and disease and population characteristics change, screening strategies may also need to change. We develop a decision-making model that can assist a college to determine an optimal screening strategy based on their characteristics and resources, considering COVID-19 infections/hospitalizations/deaths; peak daily hospitalizations; and the tests required. We also use this tool to generate screening guidelines for the safe opening of college campuses. Our compartmental model simulates disease spread on a hypothetical college campus under co-circulating variants with different disease dynamics, considering: (i) the heterogeneity in disease transmission and outcomes for faculty/staff and students based on vaccination status and level of natural immunity; and (ii) variant- and dose-dependent vaccine efficacy. Using the Spring 2022 academic semester as a case study, we study routine screening strategies, and find that screening the faculty/staff less frequently than the students, and/or the boosted and vaccinated less frequently than the unvaccinated, may avert a higher number of infections per test, compared to universal screening of the entire population at a common frequency. We also discuss key policy issues, including the need to revisit the mitigation objective over time, effective strategies that are informed by booster coverage, and if and when screening alone can compensate for low booster coverage.

Enhancing resilience in construction against infectious diseases using stochastic multi-agent approach

To recover from the adverse impacts of COVID-19 on construction and to avoid further losses to the industry in future pandemics, the resilience of construction industry needs to be enhanced against infectious diseases. Currently, there is a gap for modelling frameworks to simulate the spread of infectious diseases in construction projects at micro-level and to test interventions' effectiveness for data-informed decision-making. Here, this gap is addressed by developing a simulation framework using stochastic agent-based modelling, which enables construction researchers and practitioners to simulate and limit the spread of infectious diseases in construction projects. This is specifically important, since the results of a building project case-study reveals that, in comparison to the general population, infectious diseases may spread faster among construction workers and fatalities can be significantly higher. The proposed framework motivates future research on micro-level modelling of infectious diseases and efforts for intervening the spread of diseases in construction projects.

Strategies for Scaling up SARS-CoV-2 Molecular Testing Capacity

Scaling up SARS-CoV-2 testing during the COVID-19 pandemic was critical to maintaining clinical operations and an open society. Pooled testing and automation were two critical strategies used by laboratories to meet the unprecedented demand. Here, we review these and other cutting-edge strategies that sought to expand SARS-CoV-2 testing capacity while maintaining high individual test performance.

Evaluation of conventional and point-of-care real-time RT-PCR tests for the detection of SARS-CoV-2 through a pooled testing strategy

Background

The rapid identification and isolation of individuals infected with SARS‐CoV‐2 are fundamental countermeasures for the efficient control of the COVID‐19 pandemic, which has affected millions of people around the world. Real‐time RT‐PCR is one of the most commonly applied reference methods for virus detection, and the use of pooled testing has been proposed as an effective way to increase the throughput of routine diagnostic tests. However, the clinical applicability of different types of real‐time RT‐PCR tests in a given group size remains inconclusive due to inconsistent regional disease prevalence and test demands.

Methods

In this study, the performance of one dual‐target conventional and two point‐of‐care real‐time RT‐PCR tests in a 5‐specimen pooled testing strategy for the detection of SARS‐COV‐2 was evaluated.

Results

We demonstrated the proof of concept that all of these real‐time RT‐PCR tests could feasibly detect SARS‐CoV‐2 from nasopharyngeal and oropharyngeal specimens that contain viral RNA loads in the range of 3.48 × 10⁵ to 3.42 × 10² copies/ml through pooled testing in a group size of 5 with overall positive percent agreement (pooling vs. individual testing) ranging from 100% to 93.75%. Furthermore, the two POC real‐time RT‐PCR tests exhibited comparable sensitivity to that of the dual‐target conventional one when clinical specimens were tested individually.

Conclusion

Our findings support the feasibility of using real‐time RT‐PCR tests developed as a variety of platforms in routine laboratory detection of suspected COVID‐19 cases through a pooled testing strategy that is beneficial to increasing the daily diagnostic capacity.

Anticipating human resilience and vulnerability on the path to 2030: What can we learn from COVID-19?

The COVID-19 pandemic is causing unprecedented damage to our society and economy, globally impacting progress towards the SDGs. The integrated perspective that Agenda 2030 calls for is ever more important for understanding the vulnerability of our eco-socio-economic systems and for designing policies for enhanced resilience. Since the emergence of COVID-19, countries and international institutions have strengthened their monitoring systems to produce timely data on infections, fostering data-driven decision-making often without the support of systemic-based simulation models. Evidence from the initial phases of the pandemic indicates that countries that were able to implement effective policies before the number of cases grew large (e.g. Australia) managed to contain COVID-19 to a much greater extent than others. We argue that prior systemic knowledge of a phenomenon provides the essential information to correctly interpret data, develop a better understanding of the emerging behavioural patterns and potentially develop early qualitative awareness of how to react promptly in the early phases of destructive phenomena, eventually providing the ground for building more effective simulation models capable of better anticipating the effects of policies. This is even more important as, on its path to 2030, humanity will face other challenges of similar dynamic nature. Chief among these is Climate Change. In this paper, we show how a Systems Thinking and System Dynamics modelling approach is useful for developing a better understanding of these and other issues, and how systemic lessons learned from the COVID-19 case can help decision makers anticipate the destructive dynamics of Climate Change by improving perceptions of the potential impacts of reinforcing feedback and delays, ultimately leading to more timely interventions to achieve the SDGs and mitigate Climate Change risks.

Benefits of integrated screening and vaccination for infection control

IMPORTANCE

Screening and vaccination are essential in the fight against infectious diseases, but need to be integrated and customized based on community and disease characteristics.

OBJECTIVE

To develop effective screening and vaccination strategies, customized for a college campus, to reduce COVID-19 infections, hospitalizations, deaths, and peak hospitalizations.

DESIGN, SETTING, AND PARTICIPANTS

We construct a compartmental model of disease spread under vaccination and routine screening, and study the efficacy of four mitigation strategies (routine screening only, vaccination only, vaccination with partial or full routine screening), and a no-intervention strategy. The study setting is a hypothetical college campus of 5,000 students and 455 faculty members during the Fall 2021 academic semester, when the Delta variant was the predominant strain. For sensitivity analysis, we vary the screening frequency, daily vaccination rate, initial vaccine coverage, and screening and vaccination compliance; and consider scenarios that represent low/medium/high transmission and test efficacy. Model parameters come from publicly available or published sources.

RESULTS

With low initial vaccine coverage (30% in our study), even aggressive vaccination and screening result in a high number of infections: 1,020 to 2,040 (1,530 to 2,480) with routine daily (every other day) screening of the unvaccinated; 280 to 900 with daily screening extended to the newly vaccinated in base- and worst-case scenarios, which respectively consider reproduction numbers of 4.75 and 6.75 for the Delta variant.

CONCLUSION

Integrated vaccination and routine screening can allow for a safe opening of a college when both the vaccine effectiveness and the initial vaccine coverage are sufficiently high. The interventions need to be customized considering the initial vaccine coverage, estimated compliance, screening and vaccination capacity, disease transmission and adverse outcome rates, and the number of infections/peak hospitalizations the college is willing to tolerate.

Cost analysis of coronavirus disease 2019 test strategies using pooled reverse transcriptase-polymerase chain reaction technique

Background

This study aimed to compare the testing strategies for COVID‐19 (i.e., individual, simple pooling, and matrix pooling) in terms of cost.

Methods

We simulated the total expenditures of each testing strategy for running 10,000 tests. Three parameters were used: positive rate (PR), pool size, and test cost. We compared the total testing costs under two hypothetical scenarios in South Korea. We also simulated country‐specific circumstances in India, South Africa, South Korea, the UK, and the USA.

Results

At extreme PRs of 0.01% and 10%, simple pooling was the most economic option and resulted in cost reductions of 98.0% (pool size ≥80) and 36.7% (pool size = 3), respectively. At moderate PRs of 0.1%, 1%, 2%, and 5%, the matrix pooling strategy was the most economic option and resulted in cost reductions of 97.0% (pool size ≥88), 86.1% (pool size = 22), 77.9% (pool size = 14), and 59.2% (pool size = 7), respectively. In both hypothetical scenarios of South Korea, simple pooling costs less than matrix pooling. However, the preferable options for achieving cost savings differed depending on each country's cost per test and PRs.

Conclusions

Both pooling strategies resulted in notable cost reductions compared with individual testing in most scenarios pertinent to real‐life situations. The appropriate type of testing strategy should be chosen by considering the PR of COVID‐19 in the community and the test cost while using an appropriate pooling size such as five specimens.

Evaluation of SARS-CoV-2 genome detection by real-time PCR assay using pooled specimens

Objective: To evaluate SARS-CoV-2 genome detection using pooled samples by RT-qPCR assay, compared to individual samples. Method: At first all samples were tested individually using two commercial methods targeting ORF1ab, NP and E genes. Then, four experimental groups of samples were pooled and evaluated using the same detection methods. Findings: Compared to the individual sample testing, the sample pooling conserved the sensitivity of the detection in all groups of pooled samples when the Ct value in single test was lower than 33. Conclusion: Specimen pooling may fail to detect positive samples with high Ct values. However, in scarcity of reagents or in population surveys, it could be considered as an alternative method in low prevalence settings.

Pooled sample testing for COVID-19 diagnosis: Evaluation of bi-directional matrix pooling strategies

In the on-going COVID-19 pandemic, pooled testing of samples by RT-PCR has been recommended at certain scenarios to increase labs’ testing capacity and reduce cost of testing. This paper describes the evaluation of bi-directional matrix pooling strategies with clinical samples in a 5 × 5 and 10 × 10 matrix. Nasopharyngeal swab samples in viral transport medium (VTM) previously tested (positive or negative) by real time RT-PCR for SARS-CoV-2 were used for these experiments. Ten sets of 5 × 5 (250 samples) and ten sets of 10 × 10 (1000 samples) pooling of samples in both directions was done with known positive samples introduced at random positions. Extracted nucleic acid was tested for SARS-CoV-2 E-gene by RT-PCR. Sensitivity or concordance and feasibility of matrix pooling were assessed in comparison to direct RT-PCR testing. In comparison to direct testing, the overall concordance was 86.6% for 5 × 5 pooling, 73.3% for 10 × 10 with 200 µL extraction volume and 86.6% for 10 × 10 with 400 µL extraction volume. Bi-directional matrix pooling can be adopted with advantage over conventional direct or pool testing for COVID-19 by RT-PCR under the following conditions: i) sample positivity rate of ≤ 5%, ii) matrix pool size of 8–10 samples, iii) use of min. 40 µL VTM from each sample and iv) utilization of automated liquid handling equipment, if available, for sample addition to avoid human errors.

Comparison of Extraction-based and Elution-based Polymerase Chain Reaction Testing, and Automated and Rapid Antigen Testing for the Diagnosis of Severe Acute Respiratory Syndrome Coronavirus 2

We aimed to compare the differences in testing performance of extraction‐based polymerase chain reaction (PCR) assays, elution‐based direct PCR assay, and rapid antigen detection tests for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2). We used nasopharyngeal swab samples of patients with coronavirus disease 2019 (COVID‐19). We used the MagNA Pure 24 System (Roche Diagnostics K.K.) or magLEAD 12gC (Precision System Science Co., Ltd.) for RNA extraction, mixed the concentrates with either the LightMix Modular SARS‐CoV PCR mixture (Roche Diagnostics K.K.) or Takara SARS‐CoV‐2 direct PCR detection kit (Takara Bio Inc.), and amplified it using COBAS® z480 (Roche Diagnostics K.K.). For elution‐based PCR, we directly applied clinical samples to the Takara SARS‐CoV‐2 direct PCR detection kit before the same amplification step. Additionally, we performed Espline SARS‐CoV‐2 (Fuji Rebio Co., Ltd.) for rapid diagnostic test (RDT), and used Lumipulse SARS‐CoV‐2 antigen (Fuji Rebio Co., Ltd.) and Elecsys SARS‐CoV‐2 antigen (Roche Diagnostics K.K.) for automated antigen tests (ATs). Extraction‐based and elution‐based PCR tests detected the virus up to 214–216 and 210 times dilution, respectively. ATs remained positive up to 24–26 times dilution, while RDT became negative after 22 dilutions. For 153 positive samples, positivity rates of the extraction‐based PCR assay were 85.6% to 98.0%, while that of the elution‐based PCR assay was 73.2%. Based on the RNA concentration process, extraction‐based PCR assays were superior to elution‐based direct PCR assays for detecting SARS‐CoV‐2.

Pooled testing of traced contacts under superspreading dynamics

Testing is recommended for all close contacts of confirmed COVID-19 patients. However, existing pooled testing methods are oblivious to the circumstances of contagion provided by contact tracing. Here, we build upon a well-known semi-adaptive pooled testing method, Dorfman's method with imperfect tests, and derive a simple pooled testing method based on dynamic programming that is specifically designed to use information provided by contact tracing. Experiments using a variety of reproduction numbers and dispersion levels, including those estimated in the context of the COVID-19 pandemic, show that the pools found using our method result in a significantly lower number of tests than those found using Dorfman's method. Our method provides the greatest competitive advantage when the number of contacts of an infected individual is small, or the distribution of secondary infections is highly overdispersed. Moreover, it maintains this competitive advantage under imperfect contact tracing and significant levels of dilution.

Assessment of performance and implementation characteristics of rapid point of care SARS-CoV-2 antigen testing

Background: The COVID-19 pandemic has resulted in a need for rapid identification of infectious cases. Testing barriers have prohibited adequate screening for SARS-CoV-2, resulting in significant delays in commencement of treatment and outbreak control measures. This study aimed to generate evidence on the performance and implementation characteristics of the BD Veritor™ Plus System rapid antigen test as compared to reverse transcription polymerase chain reaction (RT-PCR) for diagnosis of SARS-CoV-2 in Kenya. Methods: This was a field test performance evaluation in adults undergoing testing for SARS-CoV-2. Recruited participants were classified as SARS-CoV-2-positive based on RT-PCR carried out on nasopharyngeal swabs. Antigen tests were performed with simultaneous RT-PCR on 272 participants, allowing estimation of sensitivity, specificity, positive and negative predictive values for the rapid antigen test. Implementation characteristics were assessed. Results: We enrolled 97 PCR negative symptomatic and 128 PCR negative asymptomatic, and 28 PCR positive symptomatic and 19 PCR positive asymptomatic participants. Compared to RT-PCR, the sensitivity of the rapid antigen test was 94% (95% confidence interval [CI] 86.6 to 100.0) while the specificity was 98% (95% CI 96 to 100). There was no association between sensitivity and symptom status, or between the cycle threshold value and sensitivity of the BD Veritor. The rapid test had a quick turnaround time, required minimal resources, and laboratory personnel conducting testing found it easier to use than RT-PCR. The relatively high sensitivity of BD Veritor may be partially attributed to shortages of RT-PCR testing materials, resulting in specimen analysis delays and potential degradation of viral genetic material. Therefore, in resource-constrained settings, rapid antigen tests may perform better than the reference RT-PCR, resulting in prompt institution of isolation and treatment measures.  Conclusion: The BD Veritor rapid antigen test’s high sensitivity should be interpreted with consideration to the challenges occasioned by RT-PCR testing in resource-constrained settings.

A network-based group testing strategy for colleges

Group testing has recently become a matter of vital importance for efficiently and rapidly identifying the spread of Covid-19. In particular, we focus on college towns due to their density, observability, and significance for school reopenings. We propose a novel group testing strategy which requires only local information about the underlying transmission network. By using cellphone data from over 190,000 agents, we construct a mobility network and run extensive data-driven simulations to evaluate the efficacy of four different testing strategies. Our results demonstrate that our group testing method is more effective than three other baseline strategies for reducing disease spread with fewer tests.

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.

Evaluation of Sample Pooling for SARS-CoV-2 Detection in Nasopharyngeal Swab and Saliva Samples with the Idylla SARS-CoV-2 Test

Due to increased demand for testing, as well as restricted supply chain resources, testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection continues to face many hurdles. Pooling several samples has been proposed as an alternative approach to address these issues. We investigated the feasibility of pooling nasopharyngeal swab (NPS) or saliva samples for SARS-CoV-2 testing with a commercial assay (Idylla SARS-CoV-2 test; Biocartis). We evaluated the 10-pool and 20-pool approaches for 149 subjects, with 30 positive samples and 119 negative samples. The 10-pool approach had sensitivity of 78.95% (95% confidence interval [CI], 54.43% to 93.95%) and specificity of 100% (95% CI, 71.51% to 100%), whereas the 20-pool approach had sensitivity of 55.56% (95% CI, 21.20% to 86.30%) and specificity of 100% (95% CI, 25% to 100%). No significant difference was observed between the results obtained with pooled NPS and saliva samples. Given the rapidity, full automation, and practical advantages of the Idylla SARS-CoV-2 assay, pooling of 10 samples has the potential to significantly increase testing capacity for both NPS and saliva samples, with good sensitivity.

IMPORTANCE To control outbreaks of coronavirus disease 2019 (COVID-19) and to avoid reagent shortages, testing strategies must be adapted and maintained for the foreseeable future. We analyzed the feasibility of pooling NPS and saliva samples for SARS-CoV-2 testing with the Idylla SARS-CoV-2 test, and we found that sensitivity was dependent on the pool size. The SARS-CoV-2 testing capacity with both NPS and saliva samples could be significantly expanded by pooling 10 samples; however, pooling 20 samples resulted in lower sensitivity.

Optimizing and evaluating PCR-based pooled screening during COVID-19 pandemics

Population screening played a substantial role in safely reopening the economy and avoiding new outbreaks of COVID-19. PCR-based pooled screening makes it possible to test the population with limited resources by pooling multiple individual samples. Our study compared different population-wide screening methods as transmission-mitigating interventions, including pooled PCR, individual PCR, and antigen screening. Incorporating testing-isolation process and individual-level viral load trajectories into an epidemic model, we further studied the impacts of testing-isolation on test sensitivities. Results show that the testing-isolation process could maintain a stable test sensitivity during the outbreak by removing most infected individuals, especially during the epidemic decline. Moreover, we compared the efficiency, accuracy, and cost of different screening methods during the pandemic. Our results show that PCR-based pooled screening is cost-effective in reversing the pandemic at low prevalence. When the prevalence is high, PCR-based pooled screening may not stop the outbreak. In contrast, antigen screening with sufficient frequency could reverse the epidemic, despite the high cost and the large numbers of false positives in the screening process.

Tracking SARS-CoV-2: Novel Trends and Diagnostic Strategies

The COVID-19 pandemic has had an enormous impact on economies and health systems globally, therefore a top priority is the development of increasingly better diagnostic and surveillance alternatives to slow down the spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In order to establish massive testing and contact tracing policies, it is crucial to have a clear view of the diagnostic options available and their principal advantages and drawbacks. Although classical molecular methods such as RT-qPCR are broadly used, diagnostic alternatives based on technologies such as LAMP, antigen, serological testing, or the application of novel technologies such as CRISPR-Cas for diagnostics, are also discussed. The present review also discusses the most important automation strategies employed to increase testing capability. Several serological-based diagnostic kits are presented, as well as novel nanotechnology-based diagnostic methods. In summary, this review provides a clear diagnostic landscape of the most relevant tools to track COVID-19.

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.

Pooled Testing Strategies for SARS-CoV-2 diagnosis: A comprehensive review

SARS-CoV-2 has surged across the globe causing the ongoing COVID-19 pandemic. Systematic testing to facilitate index case isolation and contact tracing is needed for efficient containment of viral spread. The major bottleneck in leveraging testing capacity has been the lack of diagnostic resources. Pooled testing is a potential approach that could reduce cost and usage of test kits. This method involves pooling individual samples and testing them 'en bloc'. Only if the pool tests positive, retesting of individual samples is performed. Upon reviewing recent articles on this strategy employed in various SARS-CoV-2 testing scenarios, we found substantial diversity emphasizing the requirement of a common protocol. In this article, we review various theoretically simulated and clinically validated pooled testing models and propose practical guidelines on applying this strategy for large scale screening. If implemented properly, the proposed approach could contribute to proper utilization of testing resources and flattening of infection curve.

Effectiveness and cost-effectiveness of four different strategies for SARS-CoV-2 surveillance in the general population (CoV-Surv Study): study protocol for a two-factorial randomized controlled multi-arm trial with cluster sampling

BACKGROUND

To achieve higher effectiveness in population-based SARS-CoV-2 surveillance and to reliably predict the course of an outbreak, screening, and monitoring of infected individuals without major symptoms (about 40% of the population) will be necessary. While current testing capacities are also used to identify such asymptomatic cases, this rather passive approach is not suitable in generating reliable population-based estimates of the prevalence of asymptomatic carriers to allow any dependable predictions on the course of the pandemic.

METHODS

This trial implements a two-factorial, randomized, controlled, multi-arm, prospective, interventional, single-blinded design with cluster sampling and four study arms, each representing a different SARS-CoV-2 testing and surveillance strategy based on individuals' self-collection of saliva samples which are then sent to and analyzed by a laboratory. The targeted sample size for the trial is 10,000 saliva samples equally allocated to the four study arms (2500 participants per arm). Strategies differ with respect to tested population groups (individuals vs. all household members) and testing approach (without vs. with pre-screening survey). The trial is complemented by an economic evaluation and qualitative assessment of user experiences. Primary outcomes include costs per completely screened person, costs per positive case, positive detection rate, and precision of positive detection rate.

DISCUSSION

Systems for active surveillance of the general population will gain more importance in the context of pandemics and related disease prevention efforts. The pandemic parameters derived from such active surveillance with routine population monitoring therefore not only enable a prospective assessment of the short-term course of a pandemic, but also a more targeted and thus more effective use of local and short-term countermeasures.

TRIAL REGISTRATION

ClinicalTrials.gov DRKS00023271 . Registered November 30, 2020, with the German Clinical Trials Register (Deutsches Register Klinischer Studien).

Modelling the utility of group testing for public health surveillance

In epidemic or pandemic situations, resources for testing the infection status of individuals may be scarce. Although group testing can help to significantly increase testing capabilities, the (repeated) testing of entire populations can exceed the resources of any country. We thus propose an extension of the theory of group testing that takes into account the fact that definitely specifying the infection status of each individual is impossible. Our theory builds on assigning to each individual an infection status (healthy/infected), as well as an associated cost function for erroneous assignments. This cost function is versatile, e.g., it could take into account that false negative assignments are worse than false positive assignments and that false assignments in critical areas, such as health care workers, are more severe than in the general population. Based on this model, we study the optimal use of a limited number of tests to minimize the expected cost. More specifically, we utilize information-theoretic methods to give a lower bound on the expected cost and describe simple strategies that can significantly reduce the expected cost over currently known strategies. A detailed example is provided to illustrate our theory.

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).

Supporting scale-up of COVID-19 RT-PCR testing processes with discrete event simulation

Testing is critical to mitigating the COVID-19 pandemic, but testing capacity has fallen short of the need in the United States and elsewhere, and long wait times have impeded rapid isolation of cases. Operational challenges such as supply problems and personnel shortages have led to these bottlenecks and inhibited the scale-up of testing to needed levels. This paper uses operational simulations to facilitate rapid scale-up of testing capacity during this public health emergency. Specifically, discrete event simulation models were developed to represent the RT-PCR testing process in a large University of Maryland testing center, which retrofitted high-throughput molecular testing capacity to meet pandemic demands in a partnership with the State of Maryland. The simulation models support analyses that identify process steps which create bottlenecks, and evaluate “what-if” scenarios for process changes that could expand testing capacity. This enables virtual experimentation to understand the trade-offs associated with different interventions that increase testing capacity, allowing the identification of solutions that have high leverage at a feasible and acceptable cost. For example, using a virucidal collection medium which enables safe discarding of swabs at the point of collection removed a time-consuming “deswabbing” step (a primary bottleneck in this laboratory) and nearly doubled the testing capacity. The models are also used to estimate the impact of demand variability on laboratory performance and the minimum equipment and personnel required to meet various target capacities, assisting in scale-up for any laboratories following the same process steps. In sum, the results demonstrate that by using simulation modeling of the operations of SARS-CoV-2 RT-PCR testing, preparedness planners are able to identify high-leverage process changes to increase testing capacity.

Trends of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody prevalence in selected regions across Ghana

Background: We set out to estimate the community-level exposure to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Ghana. Methods: Phased seroprevalence studies of 2729 participants at selected locations across Ghana were conducted. Phase I (August 2020) sampled 1305 individuals at major markets/lorry stations, shopping malls, hospitals and research institutions involved in coronavirus disease 2019 (COVID-19) work. The study utilized a lateral flow rapid diagnostic test (RDT) which detected IgM and IgG antibodies against SARS-CoV-2 nucleocapsid protein. Results: During Phase I, 252/1305 (19%) tested positive for IgM or IgG or both. Exposure was significantly higher at markets/lorry stations (26.9%) compared to malls (9.4%), with 41–60-year group demonstrating highest seropositivity (27.2%). Exposure was higher in participants with no formal education (26.2%) than those with tertiary education (13.1%); and higher in informally employed workers (24.0%) than those in the formal sector (15.0%). Results from phases II and III, in October and December 2020 respectively, implied either reduced transmissions or loss of antibody expression in some participants. The Upper East region showed the lowest seropositivity (2%). Phase IV, in February 2021, showed doubled seropositivity in the upper income bracket (26.2%) since August 2020, reflective of Ghana’s second wave of symptomatic COVID-19 cases. This suggested that high transmission rates had overcome the initial socioeconomic stratification of exposure risk. Reflective of second wave hospitalisation trends, the 21-40 age group demonstrated modal seropositivity (24.9) in Phase IV whilst 40-60 years and 60+ previously demonstrated highest prevalence. Conclusions: Overall, the data indicates higher COVID-19 seroprevalence than officially acknowledged, likely implying a considerably lower-case fatality rate than the current national figure of 0.84%. The data also suggests that COVID-19 is predominantly asymptomatic COVID-19 in Ghana. The observed trends mimic clinical trends of infection and imply that the methodology used was appropriate.

Positively Correlated Samples Save Pooled Testing Costs

The group testing approach, which achieves significant cost reduction over the individual testing approach, has received a lot of interest lately for massive testing of COVID-19. Many studies simply assume samples mixed in a group are independent. However, this assumption may not be reasonable for a contagious disease like COVID-19. Specifically, people within a family tend to infect each other and thus are likely to be positively correlated. By exploiting positive correlation, we make the following two main contributions. One is to provide a rigorous proof that further cost reduction can be achieved by using the Dorfman two-stage method when samples within a group are positively correlated. The other is to propose a hierarchical agglomerative algorithm for pooled testing with a social graph, where an edge in the social graph connects frequent social contacts between two persons. Such an algorithm leads to notable cost reduction (roughly 20-35%) compared to random pooling when the Dorfman two-stage algorithm is applied.

Lessons from countries implementing find, test, trace, isolation and support policies in the rapid response of the COVID-19 pandemic: a systematic review

OBJECTIVE

To systematically learn lessons from the experiences of countries implementing find, test, trace, isolate, support (FTTIS) in the first wave of the COVID-19 pandemic.

DESIGN, DATA SOURCES AND ELIGIBILITY CRITERIA

We searched MEDLINE (PubMed), Cochrane Library, SCOPUS and JSTOR, initially between 31 May 2019 and 21 January 2021. Research articles and reviews on the use of contact tracing, testing, self-isolation and quarantine for COVID-19 management were included in the review.

DATA EXTRACTION AND SYNTHESIS

We extracted information including study objective, design, methods, main findings and implications. These were tabulated and a narrative synthesis was undertaken given the diverse research designs, methods and implications.

RESULTS

We identified and included 118 eligible studies. We identified the core elements of an effective find, test, trace, isolate, support (FTTIS) system needed to interrupt the spread of a novel infectious disease, where treatment or vaccination was not yet available, as pertained in the initial stages of the COVID-19 pandemic. We report methods used to shorten case finding time, improve accuracy and efficiency of tests, coordinate stakeholders and actors involved in an FTTIS system, support individuals isolating and make appropriate use of digital tools.

CONCLUSIONS

We identified in our systematic review the key components of an FTTIS system. These include border controls, restricted entry, inbound traveller quarantine and comprehensive case finding; repeated testing to minimise false diagnoses and pooled testing in resource-limited circumstances; extended quarantine period and the use of digital tools for contact tracing and self-isolation. Support for mental or physical health and livelihoods is needed for individuals undergoing self-isolation/quarantine. An integrated system with rolling-wave planning can best use effective FTTIS tools to respond to the fast-changing COVID-19 pandemic. Results of the review may inform countries considering implementing these measures.

A simplified alternative diagnostic algorithm for SARS-CoV-2 suspected symptomatic patients and confirmed close contacts (asymptomatic): A consensus of Latin American experts

INTRODUCTION

Latin America accounts for one-quarter of global COVID-19 cases and one-third of deaths. Inequalities in the region lead to barriers regarding the best use of diagnostic tests during the pandemic. There is a need for a simplified guideline, considering the region's health resources' low availability, international guidelines, medical literature, and local expertise.

METHODS

Nine experts from Latin American countries developed a simplified algorithm for COVID-19 diagnosis, using a modified Delphi method. Twenty-four questions related to diagnostic settings were proposed, followed by discussion of the literature and experts' experience.

RESULTS

The algorithm considers three timeframes (≤7 days, 8-13 days, and ≥ 14 days) and discusses diagnostic options for each one. SARS-CoV-2 rRT-PCR is the test of choice from day 1 to day 14 after symptom onset or close contact, although antigen testing may be used in particular situations, from days 5 to 7. Antibody assays may be used for confirmation, mainly after day 14. If the clinical suspicion is very high, but other tests are negative, these assays may be used as an adjunct to decision-making from day 8 to day 13.

CONCLUSION

The proposed algorithm aims to support COVID-19 diagnosis decision-making in Latin America.

Critical Aspects Concerning the Development of a Pooling Approach for SARS-CoV-2 Diagnosis Using Large-Scale PCR Testing

The primary approach to controlling the spread of the pandemic SARS-CoV-2 is to diagnose and isolate the infected people quickly. Our paper aimed to investigate the efficiency and the reliability of a hierarchical pooling approach for large-scale PCR testing for SARS-CoV-2 diagnosis. To identify the best conditions for the pooling approach for SARS-CoV-2 diagnosis by RT-qPCR, we investigated four manual methods for both RNA extraction and PCR assessment targeting one or more of the RdRp, N, S, and ORF1a genes, by using two PCR devices and an automated flux for SARS-CoV-2 detection. We determined the most efficient and accurate diagnostic assay, taking into account multiple parameters. The optimal pool size calculation included the prevalence of SARS-CoV-2, the assay sensitivity of 95%, an assay specificity of 100%, and a range of pool sizes of 5 to 15 samples. Our investigation revealed that the most efficient and accurate procedure for detecting the SARS-CoV-2 has a detection limit of 2.5 copies/PCR reaction. This pooling approach proved to be efficient and accurate in detecting SARS-CoV-2 for all samples with individual quantification cycle (Cq) values lower than 35, accounting for more than 94% of all positive specimens. Our data could serve as a comprehensive practical guide for SARS-CoV-2 diagnostic centers planning to address such a pooling strategy.

Diagnostics for SARS-CoV-2 infections

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread to nearly every corner of the globe, causing societal instability. The resultant coronavirus disease 2019 (COVID-19) leads to fever, sore throat, cough, chest and muscle pain, dyspnoea, confusion, anosmia, ageusia and headache. These can progress to life-threatening respiratory insufficiency, also affecting the heart, kidney, liver and nervous systems. The diagnosis of SARS-CoV-2 infection is often confused with that of influenza and seasonal upper respiratory tract viral infections. Due to available treatment strategies and required containments, rapid diagnosis is mandated. This Review brings clarity to the rapidly growing body of available and in-development diagnostic tests, including nanomaterial-based tools. It serves as a resource guide for scientists, physicians, students and the public at large.

Evaluation of pooling of samples for testing SARS-CoV- 2 for mass screening of COVID-19

BACKGROUND

The current pandemic of the SARS-CoV-2 virus, widely known as COVID-19, has affected millions of people around the world. The World Health Organization (WHO) has recommended vigorous testing to differentiate SARS-CoV-2 from other respiratory infections to aid in guiding appropriate care and management. Situations like this have demanded robust testing strategies and pooled testing of samples for SARS-CoV-2 virus has provided the solution to mass screening of people for COVID-19. A pooled testing strategy can be very effective in testing when resources are limited, yet it comes with its own limitations. These benefits and limitations need critical consideration when it comes to testing highly infectious diseases like COVID-19.

METHODS

This study evaluated the pooled testing of nasopharyngeal swabs for SARS-COV-2 by comparing the sensitivity of individual sample testing with 4-and 8-pool sample testing. Median cycle threshold (Ct) values were compared, and the precision of pooled testing was assessed through an inter- and intra-assay of pooled samples. Coefficient of variance was calculated for inter- and intra-assay variability.

RESULTS

The sensitivity becomes considerably lower when the samples are pooled. There is a high percentage of false negative reports with larger sample pool size and when the patient viral load is low or weak positive samples. High variability was seen in the intra- and inter-assay, especially among weak positive samples and when more number of samples are pooled together.

CONCLUSION

As COVID - 19 infection numbers and need for testing remain high, we must meticulously evaluate the testing strategy for each country depending on its testing capacity, infrastructure, economic strength, and need to determine the optimal balance on the cost-effective strategy of resource saving and risk/ cost of missing positive patients.

A reduction of the number of assays and turnaround time by optimizing polymerase chain reaction (PCR) pooled testing for SARS-CoV-2

Early detection of the severe acute respiratory syndrome coronavirus 2 infection can decrease the spread of the disease and provide therapeutic options promptly in affected individuals. However, the diagnosis by reverse‐transcription polymerase chain reaction is costly and time‐consuming. Several methods of group testing have been developed to overcome this problem. The proposed strategy offers optimization of group testing according to the available resources by decreasing not only the number of the assays but also the turnaround time. The initial classification of the samples would be done according to the intention of testing defined as diagnostic or screening/surveillance, achieving the best possible homogeneity. The proposed stratification of pooling is based on branching (divisions) and depth (levels of re‐pooling) of the original group in association with the estimated probability of a positive sample. The dilutional effect of the grouped samples has also been considered. The margins of minimum and maximum conservation of assays of pooled specimens are calculated and the optimum strategy can be selected in association with the probability of positive samples in the original group. This algorithm intends to be a useful tool for group testing offering a choice of strategies according to the requirements.

Evaluating the efficiency of specimen (sample) pooling for real-time PCR based diagnosis of COVID-19

Purpose

This study is aims at evaluating the efficacy and sensitivity of specimen pooling for testing of SARS-CoV-2 virus to determine the accuracy, resource savings, and identification of borderline positive cases without impacting the accuracy of the testing.

Method

This study was conducted between August and October 2020, we performed COVID-19 testing by RT-PCR on the samples from varying prevalence of rural population (non-hot spot) referred to COVID laboratory, in the first step, the samples were collated into pools of 5 or 10. These pools were tested by RT-PCR. Negative pools were reported as negative whereas positive pools of 5 and 10 were then de-convoluted and each sample was tested individually.

Results

In the present study, we tested 1580 samples in 158 pools of 10 and 17,515 samples in 3503 pools of 5. Among 10 samples pool, 11 (13%) pools flagged positive in the first step. In the second step, among 11 pools (110 samples) de-convoluted strategy was followed in which 10 individual samples came positive. Among 5 samples pool, 164 (13%) pools flagged positive in the first step. In the second step, among 164 pools (820 samples) de-convoluted strategy was followed in which 171 individual samples came positive. The pooled sample testing strategy saves substantial resources and time during surge testing and enhanced pandemic surveillance. This approach requires around 76%–93% fewer tests in low to moderate prevalence settings and group sizes up to 5–10 in a population, compared to individual testing.

Conclusion

Pooled sample RT- PCR analysis strategies can save substantial resources and time for COVID-19 mass testing in comparison with individual testing without compromising the quality of outcome of the test. In particular, the pooled sample approach can facilitate mass screening in the early asymptomatic stages of COVID-19 infections.

Group testing as a strategy for COVID-19 epidemiological monitoring and community surveillance

We propose an analysis and applications of sample pooling to the epidemiologic monitoring of COVID-19. We first introduce a model of the RT-qPCR process used to test for the presence of virus in a sample and construct a statistical model for the viral load in a typical infected individual inspired by large-scale clinical datasets. We present an application of group testing for the prevention of epidemic outbreak in closed connected communities. We then propose a method for the measure of the prevalence in a population taking into account the increased number of false negatives associated with the group testing method.

Sample pooling as a strategy for community monitoring for SARS-CoV-2

Sample pooling strategy was intended to determine the optimal parameters for group testing of pooled specimens for the detection of SARS-CoV-2 and process them without significant loss of test usability. Standard molecular diagnostic laboratory equipment, and commercially available centrifugal filters, RNA isolation kits and SARS Cov2 PCR tests were used. The basic idea was to combine and concentrate several samples to the maximal volume, which can be extracted with the single extraction column. Out of 16 tested pools, 12 were positive with cycle threshold (Ct) values within 0.5 and 3.01 Ct of the original individual specimens. The analysis of 112 specimens determined that 12 pools were positive, followed by identification of 6 positive individual specimens among the 112 tested. This testing was accomplished with the use of 16 extractions/PCR tests, resulting in saving of 96 reactions but adding the 40 centrifugal filters. The present study demonstrated that pool testing could detect even up to a single positive sample with Ct value as high as 34. According to the standard protocols, reagents and equipment, this pooling method can be applied easily in current clinical testing laboratories.