Optimizing screening for acute human immunodeficiency virus infection with pooled nucleic acid amplification tests

Estimating the prevalence of two or more diseases using outcomes from multiplex group testing

When screening a population for infectious diseases, pooling individual specimens (e.g., blood, swabs, urine, etc.) can provide enormous cost savings when compared to testing specimens individually. In the biostatistics literature, testing pools of specimens is commonly known as group testing or pooled testing. Although estimating a population-level prevalence with group testing data has received a large amount of attention, most of this work has focused on applications involving a single disease, such as human immunodeficiency virus. Modern methods of screening now involve testing pools and individuals for multiple diseases simultaneously through the use of multiplex assays. Hou et al. (2017, Biometrics, 73, 656-665) and Hou et al. (2020, Biostatistics, 21, 417-431) recently proposed group testing protocols for multiplex assays and derived relevant case identification characteristics, including the expected number of tests and those which quantify classification accuracy. In this article, we describe Bayesian methods to estimate population-level disease probabilities from implementing these protocols or any other multiplex group testing protocol which might be carried out in practice. Our estimation methods can be used with multiplex assays for two or more diseases while incorporating the possibility of test misclassification for each disease. We use chlamydia and gonorrhea testing data collected at the State Hygienic Laboratory at the University of Iowa to illustrate our work. We also provide an online R resource practitioners can use to implement the methods in this article.

Implementation of large-scale pooled testing to increase rapid molecular diagnostic test coverage for tuberculosis: a retrospective evaluation

In 2021, only 6.4 million of the 10.6 million people with tuberculosis (TB) were diagnosed and treated for the disease. Although the World Health Organization recommends initial diagnostic testing using a rapid sensitive molecular assay, only 38% of people diagnosed with TB benefited from these, due to barriers including the high cost of available assays. Pooled testing has been used as an approach to increase testing efficiency in many resource-constrained situations, such as the COVID-19 pandemic, but it has not yet been widely adopted for TB diagnostic testing. Here we report a retrospective analysis of routine pooled testing of 10,117 sputum specimens using the Xpert MTB/RIF and Xpert MTB/RIF Ultra assays that was performed from July 2020 to February 2022. Pooled testing saved 48% of assays and enabled rapid molecular testing for 4156 additional people as compared to individual testing, with 6.6% of specimens positive for TB. From an in silico analysis, the positive percent agreement of pooled testing in pools of 3 as compared with individual testing for the Xpert MTB/RIF Ultra assay was estimated as 99.4% (95% CI, 96.6% to 100%). These results support the scale-up of pooled testing for efficient TB diagnosis.

Seasonal Patterns in the Frequency of Candidatus Liberibacter Asiaticus in Populations of Diaphorina citri (Hemiptera: Psyllidae) in Florida

Candidatus Liberibacter asiaticus (CLas) is one of the putative causal agents of huanglongbing, which is a serious disease in citrus production. The pathogen is transmitted by Diaphorina citri Kuwayama (Hemiptera: Psyllidae). As an observational study, six groves in central Florida and one grove at the southern tip of Florida were sampled monthly from January 2008 through February 2012 (50 months). The collected psyllids were sorted by sex and abdominal color. Disease prevalence in adults peaked in November, with a minor peak in February. Gray/brown females had the highest prevalence, and blue/green individuals of either sex had the lowest prevalence. CLas prevalence in blue/green females was highly correlated with the prevalence in other sexes and colors. Thus, the underlying causes for seasonal fluctuations in prevalence operated in a similar fashion for all psyllids. The pattern was caused by larger nymphs displacing smaller ones from the optimal feeding sites and immunological robustness in different sex-color morphotypes. Alternative hypotheses were also considered. Improving our understanding of biological interactions and how to sample them will improve management decisions. We agree with other authors that psyllid management is critical year-round.

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.

Multicenter study evaluating novel multi-specimen pooling assay for the detection of SARS-CoV-2: High sensitivity and high throughput testing

BACKGROUND/PURPOSE

Mass screening for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is important to prevent the spread of coronavirus disease 2019 (COVID-19). Pooling samples can increase the number of tests processed. LabTurbo AIO 48 is an automated platform that allows ribonucleic acid extraction and sample analysis on the same instrument. We created a novel pooling assay on this platform for SARS-CoV-2 detection and demonstrated that the pooling strategy increases testing capacity without affecting accuracy and sensitivity.

METHODS

Comparative limit of detection (LoD) assessment was performed on the LabTurbo AIO 48 platform and the current standard detection system based on real-time reverse transcription polymerase chain reaction (rRT-PCR) using 55 clinically positive samples. An additional 330 primary clinical samples were assessed.

RESULTS

Six samples pooled into one reaction tube were detected in approximately 2.5 h using the World Health Organization rRT-PCR protocol. LabTurbo AIO 48 also demonstrated a higher throughput than our reference rRT-PCR assay, with an LoD of 1000 copies/mL. The overall percentage agreement between the methods for the 330 samples was 100%.

CONCLUSION

We created a novel multi-specimen pooling assay using LabTurbo AIO 48 for the robust detection of SARS-CoV-2, allowing high-throughput results; this assay will aid in better control and prevention of COVID-19. The diagnostic assay was cost-effective and time-efficient; thus, the pooling strategy is a practical and effective method for diagnosing large quantities of specimens without compromising precision.

Current strategies for SARS-CoV-2 molecular detection

The molecular detection of SARS-CoV-2 is extremely important for the discovery and prevention of pandemic dissemination. Because SARS-CoV-2 is not always present in the samples that can be collected, the sample chosen for testing has inevitably become the key to the SARS-CoV-2 positive cases screening. The nucleotide amplification strategy mainly includes Q-PCR assays and isothermal amplification assays. The Q-PCR assay is the most used SARS-CoV-2 detection assay. Due to heavy expenditures and other drawbacks, isothermal amplification cannot replace the dominant position of the Q-PCR assay. The antibody-based detection combined with Q-PCR can help to find more positive cases than only using nucleotide amplification-based assays. Pooled testing based on Q-PCR significantly increases efficiency and reduces the cost of massive-scale screening. The endless stream of variants emerging across the world poses a great challenge to SARS-CoV-2 molecular detection. The multi-target assays and several other strategies have proved to be efficient in the detection of mutated SARS-CoV-2 variants. Further research work should concentrate on: (1) identifying more ideal sample plucking strategies, (2) ameliorating the Q-PCR primer and probes targeted toward mutated SARS-CoV-2 variants, (3) exploring more economical and precise isothermal amplification assays, and (4) developing more advanced strategies for antibody/antigen or engineered antibodies to ameliorate the antibody/antigen-based strategy.

Novel application of one-step pooled molecular testing and maximum likelihood approaches to estimate the prevalence of malaria parasitaemia among rapid diagnostic test negative samples in western Kenya

Background

Detection of malaria parasitaemia in samples that are negative by rapid diagnostic tests (RDTs) requires resource-intensive molecular tools. While pooled testing using a two-step strategy provides a cost-saving alternative to the gold standard of individual sample testing, statistical adjustments are needed to improve accuracy of prevalence estimates for a single step pooled testing strategy.

Methods

A random sample of 4670 malaria RDT negative dried blood spot samples were selected from a mass testing and treatment trial in Asembo, Gem, and Karemo, western Kenya. Samples were tested for malaria individually and in pools of five, 934 pools, by one-step quantitative polymerase chain reaction (qPCR). Maximum likelihood approaches were used to estimate subpatent parasitaemia (RDT-negative, qPCR-positive) prevalence by pooling, assuming poolwise sensitivity and specificity was either 100% (strategy A) or imperfect (strategy B). To improve and illustrate the practicality of this estimation approach, a validation study was constructed from pools allocated at random into main (734 pools) and validation (200 pools) subsets. Prevalence was estimated using strategies A and B and an inverse-variance weighted estimator and estimates were weighted to account for differential sampling rates by area.

Results

The prevalence of subpatent parasitaemia was 14.5% (95% CI 13.6–15.3%) by individual qPCR, 9.5% (95% CI (8.5–10.5%) by strategy A, and 13.9% (95% CI 12.6–15.2%) by strategy B. In the validation study, the prevalence by individual qPCR was 13.5% (95% CI 12.4–14.7%) in the main subset, 8.9% (95% CI 7.9–9.9%) by strategy A, 11.4% (95% CI 9.9–12.9%) by strategy B, and 12.8% (95% CI 11.2–14.3%) using inverse-variance weighted estimator from poolwise validation. Pooling, including a 20% validation subset, reduced costs by 52% compared to individual testing.

Conclusions

Compared to individual testing, a one-step pooled testing strategy with an internal validation subset can provide accurate prevalence estimates of PCR-positivity among RDT-negatives at a lower cost.

A rapid One-Pot RNA isolation method for simplified clinical detection of SARS-COV-2 infection in India

Background

With the rapid increase in COVID-19 cases and the discovery of new viral variants within India over multiple waves, the expensive reagents and time-consuming sample pretreatment required for qPCR analysis have led to slower detection of the disease. The vast Indian population demands an inexpensive and competent sample preparation strategy for rapid detection of the disease facilitating early and efficient containment of the disease.

Methods

In this study, we have surveyed the spread of COVID-19 infection over Faridabad, Haryana, India for 6 months. We also devised a simple single-step method for total RNA extraction using a single tube and compared its efficacy with the commercially available RNA isolation kits.

Findings

Our findings suggest that determining Ct values for samples subjected to the One Pot RNA extraction method was as efficient as the commercially available kits but delivers a subtle advantage in a way, by minimizing the cost, labor and sample preparation time.

Conclusion

This novel crude RNA extraction method is stable and capable of operating in developing countries like India for low resource settings, without the use of expensive reagents and instruments. Additionally, this method can be further adapted to pooling samples strategies owing to its high sensitivity.

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.

Subsampling and DNA pooling can increase gains through genomic selection in switchgrass

Genomic selection (GS) can accelerate breeding cycles in perennial crops such as the bioenergy grass switchgrass (Panicum virgatum L.). The sequencing costs of GS can be reduced by pooling DNA samples in the training population (TP), only sequencing TP phenotypic outliers, or pooling candidate population (CP) samples. These strategies were simulated for two traits (spring vigor and anthesis date) in three breeding populations. Sequencing only the outlier 50% of the TP phenotype distribution resulted in a penalty of <5% of the predictive ability, measured using cross-validation. Predictive ability also decreased when sequencing progressively fewer TP DNA pools, but TPs constructed from only two phenotypically contrasting DNA samples retained a mean of >80% predictive ability relative to individual TP sequencing. Novel group testing methods allowed greater than one CP individual to be screened per sequenced DNA sample but resulted in a predictive ability penalty. To determine the impact of reduced sequencing, genetic gain was calculated for seven GS scenarios with variable sequencing budgets. Reduced TP sequencing and most CP pooling methods were superior to individual sequence-based GS when sequencing resources were restricted (2,000 DNA samples per 5-yr cycle). Only one scenario was superior to individual sequencing when sequencing budgets were large (8,000 DNA samples per 5-yr cycle). This study highlights multiple routes for reduced sequencing costs in GS.

Generalized additive regression for group testing data

In screening applications involving low-prevalence diseases, pooling specimens (e.g., urine, blood, swabs, etc.) through group testing can be far more cost effective than testing specimens individually. Estimation is a common goal in such applications and typically involves modeling the probability of disease as a function of available covariates. In recent years, several authors have developed regression methods to accommodate the complex structure of group testing data but often under the assumption that covariate effects are linear. Although linearity is a reasonable assumption in some applications, it can lead to model misspecification and biased inference in others. To offer a more flexible framework, we propose a Bayesian generalized additive regression approach to model the individual-level probability of disease with potentially misclassified group testing data. Our approach can be used to analyze data arising from any group testing protocol with the goal of estimating multiple unknown smooth functions of covariates, standard linear effects for other covariates, and assay classification accuracy probabilities. We illustrate the methods in this article using group testing data on chlamydia infection in Iowa.

Application of dried blood spot sample pooling strategies for Plasmodium 18S rRNA biomarker testing to facilitate identification of infected persons in large-scale epidemiological studies

Background

Plasmodium 18S rRNA is a sensitive biomarker for detecting Plasmodium infection in human blood. Dried blood spots (DBS) are a practical sample type for malaria field studies to collect, store, and transport large quantities of blood samples for diagnostic testing. Pooled testing is a common way to reduce reagent costs and labour. This study examined performance of the Plasmodium 18S rRNA biomarker assay for DBS, improved assay sensitivity for pooled samples, and created graphical user interface (GUI) programmes for facilitating optimal pooling.

Methods

DBS samples of varied parasite densities from clinical specimens, Plasmodium falciparum in vitro culture, and P. falciparum Armored RNA® were tested using the Plasmodium 18S rRNA quantitative triplex reverse transcription polymerase chain reaction (qRT-PCR) assay and a simplified duplex assay. DBS sample precision, linearity, limit of detection (LoD) and stability at varied storage temperatures were evaluated. Novel GUIs were created to model two-stage hierarchy, square matrix, and three-stage hierarchy pooling strategies with samples of varying positivity rates and estimated test counts. Seventy-eight DBS samples from persons residing in endemic regions with sub-patent infections were tested in pools and deconvoluted to identify positive cases.

Results

Assay performance showed linearity for DBS from 4 × 10⁷ to 5 × 10² parasites/mL with strong correlation to liquid blood samples (r² > 0.96). There was a minor quantitative reduction in DBS rRNA copies/mL compared to liquid blood samples. Analytical sensitivity for DBS was estimated 5.3 log copies 18S rRNA/mL blood (28 estimated parasites/mL). Properly preserved DBS demonstrated minimal degradation of 18S rRNA when stored at ambient temperatures for one month. A simplified duplex qRT-PCR assay omitting the human mRNA target showed improved analytical sensitivity, 1 parasite/mL blood, and was optimized for pooling. Optimal pooling sizes varied depending on prevalence. A pilot DBS study of the two-stage hierarchy pooling scheme corroborated results previously determined by testing individual DBS.

Conclusions

The Plasmodium 18S rRNA biomarker assay can be applied to DBS collected in field studies. The simplified Plasmodium qRT-PCR assay and GUIs have been established to provide efficient means to test large quantities of DBS samples.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12936-021-03907-8.

Prediction-driven pooled testing methods: Application to HIV treatment monitoring in Rakai, Uganda

Chronic medical conditions often necessitate regular testing for proper treatment. Regular testing of all afflicted individuals may not be feasible due to limited resources, as is true with HIV monitoring in resource-limited settings. Pooled testing methods have been developed in order to allow regular testing for all while reducing resource burden. However, the most commonly used methods do not make use of covariate information predictive of treatment failure, which could improve performance. We propose and evaluate four prediction-driven pooled testing methods that incorporate covariate information to improve pooled testing performance. We then compare these methods in the HIV treatment management setting to current methods with respect to testing efficiency, sensitivity, and number of testing rounds using simulated data and data collected in Rakai, Uganda. Results show that the prediction-driven methods increase efficiency by up to 20% compared with current methods while maintaining equivalent sensitivity and reducing number of testing rounds by up to 70%. When predictions were incorrect, the performance of prediction-based matrix methods remained robust. The best performing method using our motivating data from Rakai was a prediction-driven hybrid method, maintaining sensitivity over 96% and efficiency over 75% in likely scenarios. If these methods perform similarly in the field, they may contribute to improving mortality and reducing transmission in resource-limited settings. Although we evaluate our proposed pooling methods in the HIV treatment setting, they can be applied to any setting that necessitates testing of a quantitative biomarker for a threshold-based decision.

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).

Efficient and effective single-step screening of individual samples for SARS-CoV-2 RNA using multi-dimensional pooling and Bayesian inference

Rapid and widespread implementation of infectious disease surveillance is a critical component in the response to novel health threats. Molecular assays are the preferred method to detect a broad range of viral pathogens with high sensitivity and specificity. The implementation of molecular assay testing in a rapidly evolving public health emergency, such as the ongoing COVID-19 pandemic, can be hindered by resource availability or technical constraints. We present a screening strategy that is easily scaled up to support a sustained large volume of testing over long periods of time. This non-adaptive pooled-sample screening protocol employs Bayesian inference to yield a reportable outcome for each individual sample in a single testing step (no confirmation of positive results required). The proposed method is validated using clinical specimens tested using a real-time reverse transcription polymerase chain reaction test for SARS-CoV-2. This screening protocol has substantial advantages for its implementation, including higher sample throughput, faster time to results, no need to retrieve previously screened samples from storage to undergo retesting, and excellent performance of the algorithm's sensitivity and specificity compared with the individual test's metrics.

Array testing for multiplex assays

Group testing involves pooling individual specimens (e.g., blood, urine, swabs, etc.) and testing the pools for the presence of disease. When the proportion of diseased individuals is small, group testing can greatly reduce the number of tests needed to screen a population. Statistical research in group testing has traditionally focused on applications for a single disease. However, blood service organizations and large-scale disease surveillance programs are increasingly moving towards the use of multiplex assays, which measure multiple disease biomarkers at once. Tebbs and others (2013, Two-stage hierarchical group testing for multiple infections with application to the Infertility Prevention Project. Biometrics69, 1064-1073) and Hou and others (2017, Hierarchical group testing for multiple infections. Biometrics73, 656-665) were the first to examine hierarchical group testing case identification procedures for multiple diseases. In this article, we propose new non-hierarchical procedures which utilize two-dimensional arrays. We derive closed-form expressions for the expected number of tests per individual and classification accuracy probabilities and show that array testing can be more efficient than hierarchical procedures when screening individuals for multiple diseases at once. We illustrate the potential of using array testing in the detection of chlamydia and gonorrhea for a statewide screening program in Iowa. Finally, we describe an R/Shiny application that will help practitioners identify the best multiple-disease case identification algorithm.

Systematic Review of Pooling Sputum as an Efficient Method for Xpert MTB/RIF Tuberculosis Testing during the COVID-19 Pandemic

GeneXpert-based testing with Xpert MTB/RIF or Ultra assays is essential for tuberculosis diagnosis. However, testing may be affected by cartridge and staff shortages. More efficient testing strategies could help, especially during the coronavirus disease pandemic. We searched the literature to systematically review whether GeneXpert-based testing of pooled sputum samples achieves sensitivity and specificity similar to testing individual samples; this method could potentially save time and preserve the limited supply of cartridges. From 6 publications, we found 2-sample pools using Xpert MTB/RIF had 87.5% and 96.0% sensitivity (average sensitivity 94%; 95% CI 89.0%–98.0%) (2 studies). Four-sample pools averaged 91% sensitivity with Xpert MTB/RIF (2 studies) and 98% with Ultra (2 studies); combining >4 samples resulted in lower sensitivity. Two studies reported that pooling achieved 99%–100% specificity and 27%–31% in cartridge savings. Our results show that pooling may improve efficiency of GeneXpert-based testing.

Incorporating the dilution effect in group testing regression

When screening for infectious diseases, group testing has proven to be a cost efficient alternative to individual level testing. Cost savings are realized by testing pools of individual specimens (eg, blood, urine, saliva, and so on) rather than by testing the specimens separately. However, a common concern that arises in group testing is the so-called "dilution effect." This occurs if the signal from a positive individual's specimen is diluted past an assay's threshold of detection when it is pooled with multiple negative specimens. In this article, we propose a new statistical framework for group testing data that merges estimation and case identification, which are often treated separately in the literature. Our approach considers analyzing continuous biomarker levels (eg, antibody levels, antigen concentrations, and so on) from pooled samples to estimate both a binary regression model for the probability of disease and the biomarker distributions for cases and controls. To increase case identification accuracy, we then show how estimates of the biomarker distributions can be used to select diagnostic thresholds on a pool-by-pool basis. Our proposals are evaluated through numerical studies and are illustrated using hepatitis B virus data collected on a prison population in Ireland.

Gichuki B, Njuguna S, Riako D, Mutua S, Gitonga JN, Sein Y, Bartilol B, Mwangi SJ, O. Omuoyo D, M. Morobe J, de Laurent ZR, Bejon P, Ochola-Oyier LI, Tsofa B. Pooled testing conserves SARS-CoV-2 laboratory resources and improves test turn-around time: experience on the Kenyan Coast

Background. International recommendations for the control of the coronavirus disease 2019 (COVID-19) pandemic emphasize the central role of laboratory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent, at scale. The availability of testing reagents, laboratory equipment and qualified staff are important bottlenecks to achieving this. Elsewhere, pooled testing (i.e. combining multiple samples in the same reaction) has been suggested to increase testing capacities in the pandemic period. Methods. We discuss our experience with SARS-CoV-2 pooled testing using real-time reverse transcription polymerase chain reaction (RT-PCR) on the Kenyan Coast. Results. In mid-May, 2020, our RT-PCR testing capacity for SARS-CoV-2 was improved by ~100% as a result of adoption of a six-sample pooled testing strategy. This was accompanied with a concomitant saving of ~50% of SARS-CoV-2 laboratory test kits at both the RNA extraction and RT-PCR stages. However, pooled testing came with a slight decline of test sensitivity. The RT-PCR cycle threshold value (ΔCt) was ~1.59 higher for samples tested in pools compared to samples tested singly. Conclusions. Pooled testing is a useful strategy to increase SARS-CoV-2 laboratory testing capacity especially in low-income settings.

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

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

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

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

Group Testing for Severe Acute Respiratory Syndrome- Coronavirus 2 to Enable Rapid Scale-up of Testing and Real-Time Surveillance of Incidence

High-throughput molecular testing for severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) may be enabled by group testing in which pools of specimens are screened, and individual specimens tested only after a pool tests positive. Several laboratories have recently published examples of pooling strategies applied to SARS-CoV-2 specimens, but overall guidance on efficient pooling strategies is lacking. Therefore we developed a model of the efficiency and accuracy of specimen pooling algorithms based on available data on SAR-CoV-2 viral dynamics. For a fixed number of tests, we estimate that programs using group testing could screen 2-20 times as many specimens compared with individual testing, increase the total number of true positive infections identified, and improve the positive predictive value of results. We compare outcomes that may be expected in different testing situations and provide general recommendations for group testing implementation. A free, publicly-available Web calculator is provided to help inform laboratory decisions on SARS-CoV-2 pooling algorithms.

Pooled testing: A tool to increase efficiency of infant HIV diagnosis and virological monitoring

Background

Pooled testing, or pooling, has been used for decades to efficiently diagnose relatively rare conditions, such as infection in blood donors. Programmes for the prevention of mother-to-child transmission of HIV and for antiretroviral therapy (ART) are being rolled out in much of Africa and are largely successful. This increases the need for early infant diagnosis (EID) of HIV using qualitative nucleic acid testing and for virological monitoring of patients on ART using viral load testing. While numbers of patients needing testing are increasing, infant HIV infections and ART failures are becoming rarer, opening an opportunity for pooled testing approaches.

Aim

This review highlights the need for universal EID and viral load coverage as well as the challenges faced. We introduce the concept of pooled testing and highlight some important considerations before giving an overview of studies exploring pooled testing for EID and virological monitoring.

Results

For ART monitoring, pooling has been shown to be accurate and efficient; for EID it has not been tried although modelling shows it to be promising. The final part attempts to place pooling into the context of current mother-to-child transmission of HIV and ART programmes and their expected trajectories over the next years.

Conclusion

Several points warrant consideration: pre-selection to exclude samples with an elevated pre-test probability of positivity from pooled testing, the use of dried blood or plasma spots, and choosing a pooling strategy that is both practically feasible and economical. Finally, novel ideas are suggested to make pooling even more attractive.

Gichuki B, Njuguna S, Riako D, Mutua S, Gitonga JN, Sein Y, Bartilol B, Mwangi SJ, O. Omuoyo D, M. Morobe J, de Laurent ZR, Bejon P, Ochola-Oyier LI, Tsofa B. Pooled testing conserves SARS-CoV-2 laboratory resources and improves test turn-around time: experience on the Kenyan Coast

Background. International recommendations for the control of the coronavirus disease 2019 (COVID-19) pandemic emphasize the central role of laboratory testing for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent, at scale. The availability of testing reagents, laboratory equipment and qualified staff are important bottlenecks to achieving this. Elsewhere, pooled testing (i.e. combining multiple samples in the same reaction) has been suggested to increase testing capacities in the pandemic period. Methods. We discuss our experience with SARS-CoV-2 pooled testing using real-time reverse transcription polymerase chain reaction (RT-PCR) on the Kenyan Coast. Results. In mid-May, 2020, our RT-PCR testing capacity for SARS-CoV-2 was improved by ~100% as a result of adoption of a six-sample pooled testing strategy. This was accompanied with a concomitant saving of ~50% of SARS-CoV-2 laboratory test kits at both the RNA extraction and RT-PCR stages. However, pooled testing came with a slight decline of test sensitivity. The RT-PCR cycle threshold value (ΔCt) was ~1.59 higher for samples tested in pools compared to samples tested singly. Conclusions. Pooled testing is a useful strategy to increase SARS-CoV-2 laboratory testing capacity especially in low-income settings.

Determination of Varying Group Sizes for Pooling Procedure

Pooling is an attractive strategy in screening infected specimens, especially for rare diseases. An essential step of performing the pooled test is to determine the group size. Sometimes, equal group size is not appropriate due to population heterogeneity. In this case, varying group sizes are preferred and could be determined while individual information is available. In this study, we propose a sequential procedure to determine varying group sizes through fully utilizing available information. This procedure is data driven. Simulations show that it has good performance in estimating parameters.

Geographical heterogeneity in prevalence of subclinical malaria infections at sentinel endemic sites of Myanmar

BACKGROUND

The malaria burden of Myanmar still remains high within the Greater Mekong Subregion of Southeast Asia. An important indicator of progress towards malaria elimination is the prevalence of parasite infections in endemic populations. Information about malaria epidemiology is mostly derived from reports of confirmed acute malaria cases through passive case detection, whereas the prevalence of baseline subclinical malaria infections is much less known.

METHODS

In this study, cross-sectional surveys were conducted during the rainy season of 2017 in four townships (Bilin, Thabeikkyin, Banmauk and Paletwa) of Myanmar with divergent annual malaria incidences. A total of 1991 volunteers were recruited from local villages and Plasmodium subclinical infections were estimated by light microscopy (LM), rapid diagnostic tests (RDTs) and nested PCR. The nested PCR analysis was performed with a modified pooling strategy that was optimized based on an initial estimate the infection prevalence.

RESULTS

The overall malaria infection prevalence based on all methods was 13.9% (277/1991) and it differed drastically among the townships, with Paletwa in the western border having the highest infection rate (22.9%) and Thabeikkyin in central Myanmar having the lowest (3.9%). As expected, nested PCR was the most sensitive and identified 226 (11.4%) individuals with parasite infections. Among the parasite species, Plasmodium vivax was the most prevalent in all locations, while Plasmodium falciparum also accounted for 32% of infections in the western township Paletwa. Two RDTs based on the detection of the hrp2 antigen detected a total of 103 P. falciparum infections, and the ultrasensitive RDT detected 20% more P. falciparum infections than the conventional RDT. In contrast, LM missed the majority of the subclinical infections and only identified 14 Plasmodium infections.

CONCLUSIONS

Cross-sectional surveys identified considerable levels of asymptomatic Plasmodium infections in endemic populations of Myanmar with P. vivax becoming the predominant parasite species. Geographical heterogeneity of subclinical infections calls for active surveillance of parasite infections in endemic areas. The pooling scheme designed for nested PCR analysis offers a more practical strategy for large-scale epidemiological studies of parasite prevalence. Such information is important for decision-makers to put forward a more realistic action plan for malaria elimination.

Randomized Controlled Pilot Study of Antiretrovirals and a Behavioral Intervention for Persons With Acute HIV Infection: Opportunity for Interrupting Transmission

BACKGROUND

Persons with acute HIV infection (AHI) have heightened transmission risk. We evaluated potential transmission reduction using behavioral and biomedical interventions in a randomized controlled pilot study in Malawi.

METHODS

Persons were randomized 1:2:2 to standard counseling (SC), 5-session behavioral intervention (BI), or behavioral intervention plus 12 weeks of antiretrovirals (ARVs; BIA). All were followed for 26-52 weeks and, regardless of arm, referred for treatment according to Malawi-ARV guidelines. Participants were asked to refer partners for testing.

RESULTS

Among 46 persons (9 SC, 18 BI, 19 BIA), the average age was 28; 61% were male. The median viral load (VL) was 5.9 log copies/mL at enrollment. 67% (10/15) of BIA participants were suppressed (<1000 copies/mL) at week 12 vs 25% BI and 50% SC (P = .07). Although the mean number of reported condomless sexual acts in the past week decreased from baseline across all arms (1.5 vs 0.3 acts), 36% experienced incident sexually transmitted infection by 52 weeks (12% SC, 28% BI, 18% BIA). Forty-one percent (19/46) of participants referred partners (44% SC, 44% BI, 37% BIA); 15 of the partners were HIV-infected.

CONCLUSIONS

Diagnosis of AHI facilitates behavioral and biomedical risk reduction strategies during a high-transmission period that begins years before people are typically identified and started on ARVs. Sexually transmitted infection incidence in this cohort suggests ongoing risk behaviors, reinforcing the importance of early intervention with ARVs to reduce transmission. Early diagnosis coupled with standard AHI counseling and early ARV referral quickly suppresses viremia, may effectively change behavior, and could have tremendous public health benefit in reducing onward transmission.

Group testing case identification with biomarker information

Screening procedures for infectious diseases, such as HIV, often involve pooling individual specimens together and testing the pools. For diseases with low prevalence, group testing (or pooled testing) can be used to classify individuals as diseased or not while providing considerable cost savings when compared to testing specimens individually. The pooling literature is replete with group testing case identification algorithms including Dorfman testing, higher-stage hierarchical procedures, and array testing. Although these algorithms are usually evaluated on the basis of the expected number of tests and classification accuracy, most evaluations in the literature do not account for the continuous nature of the testing responses and thus invoke potentially restrictive assumptions to characterize an algorithm's performance. Commonly used case identification algorithms in group testing are considered and are evaluated by taking a different approach. Instead of treating testing responses as binary random variables (i.e., diseased/not), evaluations are made by exploiting an assay's underlying continuous biomarker distributions for positive and negative individuals. In doing so, a general framework to describe the operating characteristics of group testing case identification algorithms is provided when these distributions are known. The methodology is illustrated using two HIV testing examples taken from the pooling literature.

Improved HIV-1 Viral Load Monitoring Capacity Using Pooled Testing With Marker-Assisted Deconvolution

OBJECTIVE

Improve pooled viral load (VL) testing to increase HIV treatment monitoring capacity, particularly relevant for resource-limited settings.

DESIGN

We developed marker-assisted mini-pooling with algorithm (mMPA), a new VL pooling deconvolution strategy that uses information from low-cost, routinely collected clinical markers to determine an efficient order of sequential individual VL testing and dictates when the sequential testing can be stopped.

METHODS

We simulated the use of pooled testing to ascertain virological failure status on 918 participants from 3 studies conducted at the Academic Model Providing Access to Healthcare in Eldoret, Kenya, and estimated the number of assays needed when using mMPA and other pooling methods. We also evaluated the impact of practical factors, such as specific markers used, prevalence of virological failure, pool size, VL measurement error, and assay detection cutoffs on mMPA, other pooling methods, and single testing.

RESULTS

Using CD4 count as a marker to assist deconvolution, mMPA significantly reduces the number of VL assays by 52% [confidence interval (CI): 48% to 57%], 40% (CI: 38% to 42%), and 19% (CI: 15% to 22%) compared with individual testing, simple mini-pooling, and mini-pooling with algorithm, respectively. mMPA has higher sensitivity and negative/positive predictive values than mini-pooling with algorithm, and comparable high specificity. Further improvement is achieved with additional clinical markers, such as age and time on therapy, with or without CD4 values. mMPA performance depends on prevalence of virological failure and pool size but is insensitive to VL measurement error and VL assay detection cutoffs.

CONCLUSIONS

mMPA can substantially increase the capacity of VL monitoring.

Group testing regression models with dilution submodels

Group testing, where specimens are tested initially in pools, is widely used to screen individuals for sexually transmitted diseases. However, a common problem encountered in practice is that group testing can increase the number of false negative test results. This occurs primarily when positive individual specimens within a pool are diluted by negative ones, resulting in positive pools testing negatively. If the goal is to estimate a population-level regression model relating individual disease status to observed covariates, severe bias can result if an adjustment for dilution is not made. Recognizing this as a critical issue, recent binary regression approaches in group testing have utilized continuous biomarker information to acknowledge the effect of dilution. In this paper, we have the same overall goal but take a different approach. We augment existing group testing regression models (that assume no dilution) with a parametric dilution submodel for pool-level sensitivity and estimate all parameters using maximum likelihood. An advantage of our approach is that it does not rely on external biomarker test data, which may not be available in surveillance studies. Furthermore, unlike previous approaches, our framework allows one to formally test whether dilution is present based on the observed group testing data. We use simulation to illustrate the performance of our estimation and inference methods, and we apply these methods to 2 infectious disease data sets.

Detection of new HIV infections in a multicentre HIV antiretroviral pre-exposure prophylaxis trial

BACKGROUND

Monthly specimens collected from FEM-PrEP-a Phase III trial [1] were investigated for the detection of acute HIV (AHI) infection.

OBJECTIVES

To evaluate the efficiency of the study-specific HIV algorithm in detecting AHI, and the performance of each of the serological and molecular tests used in diagnosing new infections, and their contribution to narrowing the window period.

STUDY DESIGN

A total of 83 pre-seroconversion specimens from 61 seroconverters from the FEM-PrEP trial were further analyzed in a sub-study. During the trial, HIV seroconversion was diagnosed on site using a testing algorithm with simple/rapid tests (SRTs) and confirmed with a gold standard testing algorithm (see short communication: Fig. 1). The infection date was determined more accurately by the use of standard ELISAs and Nucleic Acid Amplification Tests (NAAT) in a look-back procedure. For this sub-study, the international central laboratory repeated the study algorithm using SRTs.

RESULTS

A total of 83 pre-seroconversions specimens from 61 seroconverters were analyzed in a look-back procedure. RNA was detected in 35/61 seroconverters at the visit before the seroconversion visit as determined at the study sites. Four seroconversion dates were inaccurate at one study site as the international central laboratory detected the HIV infection one visit earlier using the same test algorithm. Using the gold standard, an additional seroconversion was detected at an earlier visit. The combined antigen/antibody and the single antigen test had a higher sensitivity compared to the SRTs in detecting acute infections.

CONCLUSIONS

In the FEM-PrEP trial, the international central laboratory detected a small number of seroconversions one month earlier than the study sites using the same study algorithm. Standard tests are still the most sensitive tests in detecting pre-seroconversion or acute HIV infection, but they are costly, time consuming and not recommended for use on-site in a clinical trial.

Advances in Molecular Diagnosis of Malaria

Malaria is a mosquito-borne disease caused by five species of Plasmodium parasites. Accurate diagnosis of malaria plays an essential part in malaria control. With traditional diagnostic methodologies, malaria control programs have achieved remarkable success during the past decade, and are now heading toward malaria elimination in many areas. This new situation, however, calls for novel diagnostics with improved sensitivity, throughput, and reduced cost for active screening of malaria parasites, as all transfected individuals have to be identified in order to block transmission. In this chapter, we provide a brief introduction of malaria, the requirement of diagnostic advances in the age of malaria elimination, and a comprehensive overview of the currently available molecular malaria diagnostics, ranging from well-known tests to platforms in early stages of evaluation. We also discussed several practical issues for the application of molecular tests in malaria identification.

Incorporating Acute HIV Screening into Routine HIV Testing at Sexually Transmitted Infection Clinics, and HIV Testing and Counseling Centers in Lilongwe, Malawi

Background and Objectives:

Integrating acute HIV-infection (AHI) testing into clinical settings is critical to prevent transmission, and realize potential treatment-as-prevention benefits. We evaluated acceptability of AHI testing and compared AHI prevalence at sexually transmitted infection (STI) clinics and HIV testing and counseling (HTC) clinics in Lilongwe, Malawi.

Methods:

We conducted HIV RNA testing for HIV-seronegative patients visiting STI and HTC clinics. AHI was defined as positive RNA and negative/discordant rapid antibody tests. We evaluated demographic, behavioral, and transmission-risk differences between STI and HTC patients and assessed performance of a risk-score for targeted screening.

Results:

Nearly two-thirds (62.8%, 9280/14,755) of eligible patients consented to AHI testing. We identified 59 persons with AHI (prevalence = 0.64%)–a 0.9% case-identification increase. Prevalence was higher at STI [1.03% (44/4255)] than at HTC clinics [0.3% (15/5025), P < 0.01], accounting for 2.3% of new diagnoses vs 0.3% at HTC clinic. Median viral load (VL) was 758,050 copies per milliliter; 25% (15/59) had VL ≥10,000,000 copies per milliliter. Median VL was higher at STI (1,000,000 copies/mL) compared with HTC (153,125 copies/mL, P = 0.2). Among persons with AHI, those tested at STI clinics were more likely to report genital sores compared with those tested at HTC clinics (54.6% vs 6.7%, P < 0.01). The risk score algorithm performed well in identifying persons with AHI at HTC clinics (sensitivity = 73%, specificity = 89%).

Conclusions:

The majority of patients consented to AHI testing. AHI prevalence was substantially higher in STI clinics than HTC clinics. Remarkably high VLs and concomitant genital scores demonstrate the potential for transmission. Universal AHI screening at STI clinics, and targeted screening at HTC centers, should be considered.

Primary HIV infection: a medical and public health emergency requiring rapid specialist management

Primary HIV infection (PHI) refers to the first six months following HIV acquisition and represents a unique opportunity for expedited diagnosis, and consideration of rapid antiretroviral therapy (ART) initiation to improve immune function, reduce the size of the viral reservoir and limit the risk of onward viral transmission. Failure to diagnose and rapidly treat individuals with PHI has significant individual and public health implications. The Strategic Timing of AntiRetroviral Treatment trial recently identified a clinical benefit of immediate ART over deferral of treatment according to CD4 count threshold, and has led to rapid changes in World Health Organization and specialist national guidelines. For all individuals living with HIV, the offer of immediate therapy irrespective of CD4 count is now recommended. This paper summarises the presentation and management of PHI, incorporating current research and guideline changes and discusses the role of PHI in onward transmission.

Ten Years of Screening and Testing for Acute HIV Infection in North Carolina

OBJECTIVE

To describe demographic and behavioral characteristics of persons with acute HIV infection (AHI) over time.

METHODS

We conducted a retrospective assessment of AHI identified through the Screening and Tracing Active Transmission (STAT) program from 2003 to 2012 in North Carolina (NC). AHI was identified using pooled nucleic acid amplification for antibody negative samples and individual HIV-1 RNA for antibody indeterminate samples. The STAT program provides rapid notification and evaluation. We compared STAT-collected demographic and risk characteristics with all persons requesting tests and all non-AHI diagnoses from the NC State Laboratory of Public Health.

RESULTS

The STAT Program identified 236 AHI cases representing 3.4% (95% confidence interval: 3.0% to 3.9%) of all HIV diagnoses. AHI cases were similar to those diagnosed during established HIV. On pretest risk-assessments, AHI cases were predominately black (69.1%), male (80.1%), young (46.8% < 25 years), and men who have sex with men (MSM) (51.7%). Per postdiagnosis interviews, the median age decreased from 35 (interquartile range 25-42) to 27 (interquartile range 22-37) years, and the proportion <25 years increased from 23.8% to 45.2% (trend P = 0.04) between 2003 and 2012. AHI men were more likely to report MSM risk post-diagnosis than on pretest risk-assessments (64%-82.9%; P < 0.0001). Post-diagnosis report of MSM risk in men with AHI increased from 71.4% to 96.2%.

CONCLUSIONS

In NC, 3.4% of individuals diagnosed with HIV infection have AHI. AHI screening provides a real-time source of incidence trends, improves the diagnostic yield of HIV testing, and offers an opportunity to limit onward transmission.

Efficient Identification of HIV Serodiscordant Couples by Existing HIV Testing Programs in South Brazil

Objective

To examine the feasibility of identifying HIV negative at risk individuals in HIV serodiscordant couples, during voluntary HIV testing in South Brazil.

Methods

We surveyed HIV testers at 4 public testing sites in Rio Grande do Sul. We obtained information on risk behaviors and sexual partnerships. HIV testing and testing for recent infection were performed; HIV prevalence and risk behaviors were assessed among subjects who reported having a steady partner who was HIV positive (serodiscordant group) and compared with the general testing population.

Results

Among 3100 patients, 490 (15.8%) reported being in a steady relationship with an HIV positive partner. New HIV infections were diagnosed in 23% of the serodiscordant group (vs. 13% in the general population, p = 0.01); among newly positive subjects, recent HIV infections were more frequent (23/86, 26.7%) among testers with positive partners than among the general testing group (52/334; 15.6%; p = 0.016). Less than half of the serodiscordant testers reported having used a condom during the last sexual intercourse with their HIV-positive partner. Participants with inconsistent condom use with steady partner were four times more likely to test positive for HIV compared to those who reported always using condoms with the steady partner (OR: 4.2; 95% CI: 2.3 to 7.5).

Conclusion

It is highly feasible to identify large numbers of HIV susceptible individuals who are in HIV serodiscordant relationships in South Brazil testing sites. Condom use within HIV serodiscordant couples is low in this setting, suggesting urgent need for biomedical prevention strategies to reduce HIV transmission.

Rapid, Fully Automated Digital Immunoassay for p24 Protein with the Sensitivity of Nucleic Acid Amplification for Detecting Acute HIV Infection

BACKGROUND

Nucleic acid testing (NAT) has become the standard for high sensitivity in detecting low levels of virus. However, adoption of NAT can be cost prohibitive in low-resource settings where access to extreme sensitivity could be clinically advantageous for early detection of infection. We report development and preliminary validation of a simple, low-cost, fully automated digital p24 antigen immunoassay with the sensitivity of quantitative NAT viral load (NAT-VL) methods for detection of acute HIV infection.

METHODS

We developed an investigational 69-min immunoassay for p24 capsid protein for use on a novel digital analyzer on the basis of single-molecule-array technology. We evaluated the assay for sensitivity by dilution of standardized preparations of p24, cultured HIV, and preseroconversion samples. We characterized analytical performance and concordance with 2 NAT-VL methods and 2 contemporary p24 Ag/Ab combination immunoassays with dilutions of viral isolates and samples from the earliest stages of HIV infection.

RESULTS

Analytical sensitivity was 0.0025 ng/L p24, equivalent to 60 HIV RNA copies/mL. The limit of quantification was 0.0076 ng/L, and imprecision across 10 runs was <10% for samples as low as 0.09 ng/L. Clinical specificity was 95.1%. Sensitivity concordance vs NAT-VL on dilutions of preseroconversion samples and Group M viral isolates was 100%.

CONCLUSIONS

The digital immunoassay exhibited >4000-fold greater sensitivity than contemporary immunoassays for p24 and sensitivity equivalent to that of NAT methods for early detection of HIV. The data indicate that NAT-level sensitivity for acute HIV infection is possible with a simple, low-cost digital immunoassay.

How can we better identify early HIV infections?

PURPOSE OF REVIEW

Detection of early HIV infections (EHIs), including acute HIV infection (AHI), is important for individual health, prevention of HIV transmission, and measurement of HIV incidence. We describe markers of EHI, diagnostic strategies for detecting these markers, and ways to incorporate these strategies into diagnostic and HIV incidence algorithms.

RECENT FINDINGS

For individual diagnosis in the USA and Europe, laboratory-based diagnostic algorithms increasingly incorporate fourth-generation HIV antigen tests, allowing for earlier detection. In some sub-Saharan African settings, symptom-based screening is being explored to identify subsets of persons at high risk for AHI. Point-of-care diagnostics designed for AHI detection are in the pipeline and, if validated, represent an opportunity for real-time AHI diagnosis. At the population level, multiassay algorithms are promising new strategies for estimating HIV incidence on the basis of several assays applied to cross-sectional samples. These algorithms can be developed to optimize performance, in addition to cost and logistical considerations.

SUMMARY

There are important recent advances in detection of EHIs at the individual and population levels. Applying optimal combinations of tests in diagnostic and HIV incidence algorithms is urgently needed to support the multiple goals derived from enhanced detection and discrimination of EHIs.

Testing Pooled Sputum with Xpert MTB/RIF for Diagnosis of Pulmonary Tuberculosis To Increase Affordability in Low-Income Countries

Tuberculosis (TB) is a global public health problem, with the highest burden occurring in low-income countries. In these countries, the use of more sensitive diagnostics, such as Xpert MTB/RIF (Xpert), is still limited by costs. A cost-saving strategy to diagnose other diseases is to pool samples from various individuals and test them with single tests. The samples in positive pool samples are then retested individually to identify the patients with the disease. We assessed a pooled testing strategy to optimize the affordability of Xpert for the diagnosis of TB. Adults with presumptive TB attending hospitals or identified by canvassing of households in Abuja, Nigeria, were asked to provide sputum for individual and pooled (4 per pool) testing. The agreement of the results of testing of individual and pooled samples and costs were assessed. A total of 738 individuals submitted samples, with 115 (16%) being Mycobacterium tuberculosis positive. Valid Xpert results for individual and pooled samples were available for 718 specimens. Of these, testing of pooled samples detected 109 (96%) of 114 individual M. tuberculosis-positive samples, with the overall agreement being 99%. Xpert semiquantitative M. tuberculosis levels had a positive correlation with the smear grades, and the individual sample-positive/pooled sample-negative results were likely due to the M. tuberculosis concentration being below the detection limit. The strategy reduced cartridge costs by 31%. Savings were higher with samples from individuals recruited in the community, where the proportion of positive specimens was low. The results of testing of pooled samples had a high level of agreement with the results of testing of individual samples, and use of the pooled testing strategy reduced costs and has the potential to increase the affordability of Xpert in countries with limited resources.

Cost-effective pooling of DNA from nasopharyngeal swab samples for large-scale detection of bacteria by real-time PCR

We investigated the potential of pooling DNA from nasopharyngeal specimens to reduce the cost of real-time PCR (RT-PCR) for bacterial detection. Lyophilization is required to reconcentrate DNA. This strategy yields a high specificity (86%) and a high sensitivity (96%). We estimate that compared to individual testing, 37% fewer RT-PCR tests are needed.

A Note on the Minimax Solution for the Two-Stage Group Testing Problem

Group testing is an active area of current research and has important applications in medicine, biotechnology, genetics, and product testing. There have been recent advances in design and estimation, but the simple Dorfman procedure introduced by R. Dorfman in 1943 is widely used in practice. In many practical situations, the exact value of the probability p of being affected is unknown. We present both minimax and Bayesian solutions for the group size problem when p is unknown. For unbounded p, we show that the minimax solution for group size is 8, while using a Bayesian strategy with Jeffreys' prior results in a group size of 13. We also present solutions when p is bounded from above. For the practitioner, we propose strong justification for using a group size of between 8 and 13 when a constraint on p is not incorporated and provide useable code for computing the minimax group size under a constrained p.

Pooled nucleic acid testing increases the diagnostic yield of acute HIV infections in a high-risk population compared to 3rd and 4th generation HIV enzyme immunoassays

OBJECTIVES

We compared a 3rd generation (gen) and two 4th gen HIV enzyme immunoassays (EIA) to pooled nucleic acid testing (PNAT) for the identification of pre- and early seroconversion acute HIV infection (AHI).

STUDY DESIGN

9550 specimens from males >18 year from clinics attended by men who have sex with men were tested by Siemens ADVIA Centaur(®) HIV 1/O/2 (3rd gen) and HIV Combo (4th gen), as well as by Abbott ARCHITECT(®) HIV Ag/Ab Combo (4th gen). Third gen non-reactive specimens were also tested by Roche COBAS(®) Ampliprep/COBAS® TaqMan HIV-1 Test v.2 in pools of 24 samples. Sensitivity and specificity of the three EIAs for AHI detection were compared.

RESULTS

7348 persons contributed 9435 specimens and had no evidence of HIV infection, 79 (94 specimens) had established HIV infection, 6 (9 specimens) had pre-seroconversion AHI and 9 (12 specimens) had early seroconversion AHI. Pre-seroconversion AHI cases were not detected by 3rd gen EIA, whereas 2/6 (33.3%) were detected by Siemens 4th gen, 4/6 (66.7%) by Abbott 4th gen and 6/6 (100%) by PNAT. All three EIAs and PNAT detected all individuals with early seroconversion AHI. Overall sensitivity/specificity for the EIAs relative to WB or NAT resolved infection status was 93.6%/99.9% for Siemens 3rd gen, 95.7%/99.7% for Siemens 4th gen and 97.9%/99.2% for Abbott 4th gen.

CONCLUSIONS

While both 4th gen EIAs demonstrated improved sensitivity for AHI compared to 3rd gen EIA, PNAT identified more AHI cases than either 4th gen assay. PNAT is likely to remain a useful strategy to identify AHI in high-risk populations.

Comparison of microscopy, nested-PCR, and Real-Time-PCR assays using high-throughput screening of pooled samples for diagnosis of malaria in asymptomatic carriers from areas of endemicity in Myanmar

Asymptomatic infection is an important obstacle for controlling disease in countries where malaria is endemic. Because asymptomatic carriers do not seek treatment for their infections, they can have high levels of gametocytes and constitute a reservoir available for new infection. We employed a sample pooling/PCR-based molecular detection strategy for screening malaria infection in residents from areas of Myanmar where malaria is endemic. Blood samples (n = 1,552) were collected from residents in three areas of malaria endemicity (Kayin State, Bago, and Tanintharyi regions) of Myanmar. Two nested PCR and real-time PCR assays showed that asymptomatic infection was detected in about 1.0% to 9.4% of residents from the surveyed areas. The sensitivities of the two nested PCR and real-time PCR techniques were higher than that of microscopy examination (sensitivity, 100% versus 26.4%; kappa values, 0.2 to 0.5). Among the three regions, parasite-positive samples were highly detected in subjects from the Bago and Tanintharyi regions. Active surveillance of residents from regions of intense malaria transmission would reduce the risk of morbidity and mitigate transmission to the population in these areas of endemicity. Our data demonstrate that PCR-based molecular techniques are more efficient than microscopy for nationwide surveillance of malaria in countries where malaria is endemic.

Identifying rare variants with optimal depth of coverage and cost-effective overlapping pool sequencing

Genome-wide association studies have identified hundreds of genetic variants associated with complex diseases although most variants identified so far explain only a small proportion of heritability, suggesting that rare variants are responsible for missing heritability. Identification of rare variants through large-scale resequencing becomes increasing important but still prohibitively expensive despite the rapid decline in the sequencing costs. Nevertheless, group testing based overlapping pool sequencing in which pooled rather than individual samples are sequenced will greatly reduces the efforts of sample preparation as well as the costs to screen for rare variants. Here, we proposed an overlapping pool sequencing to screen rare variants with optimal sequencing depth and a corresponding cost model. We formulated a model to compute the optimal depth for sufficient observations of variants in pooled sequencing. Utilizing shifted transversal design algorithm, appropriate parameters for overlapping pool sequencing could be selected to minimize cost and guarantee accuracy. Due to the mixing constraint and high depth for pooled sequencing, results showed that it was more cost-effective to divide a large population into smaller blocks which were tested using optimized strategies independently. Finally, we conducted an experiment to screen variant carriers with frequency equaled 1%. With simulated pools and publicly available human exome sequencing data, the experiment achieved 99.93% accuracy. Utilizing overlapping pool sequencing, the cost for screening variant carriers with frequency equaled 1% in 200 diploid individuals dropped to at least 66% at which target sequencing region was set to 30 Mb.

Improved confidence intervals of a small probability from pooled testing with misclassification

This article concerns construction of confidence intervals for the prevalence of a rare disease using Dorfman's pooled testing procedure when the disease status is classified with an imperfect biomarker. Such an interval can be derived by converting a confidence interval for the probability that a group is tested positive. Wald confidence intervals based on a normal approximation are shown to be inefficient in terms of coverage probability, even for relatively large number of pools. A few alternatives are proposed and their performance is investigated in terms of coverage probability and length of intervals.

Finding those at risk: acute HIV infection in Newark, NJ

BACKGROUND

A screening strategy combining rapid HIV-1/2 (HIV) antibody testing with pooled HIV-1 RNA testing increases identification of HIV infections, but may have other limitations that restrict its usefulness to all but the highest incidence populations.

OBJECTIVE

By combining rapid antibody detection and pooled nucleic acid amplification testing (NAAT) testing, we sought to improve detection of early HIV-1 infections in an urban Newark, NJ hospital setting.

STUDY DESIGN

Pooled NAAT HIV-1 RNA testing was offered to emergency department patients and outpatients being screened for HIV antibodies by fingerstick-rapid HIV testing. For those negative by rapid HIV and agreeing to NAAT testing, pooled plasma samples were prepared and sent to the University of Washington where real-time reverse transcription-polymerase chain reaction (RT-PCR) amplification was performed.

RESULTS

Of 13,226 individuals screened, 6381 had rapid antibody testing alone, and 6845 agreed to add NAAT HIV screening. Rapid testing identified 115 antibody positive individuals. Pooled NAAT increased HIV-1 case detection by 7.0% identifying 8 additional cases. Overall, acute HIV infection yield was 0.12%. While males represent only 48.1% of those tested by NAAT, all samples that screened positive for HIV-1 RNA were obtained from men.

CONCLUSION

HIV-1 RNA testing of pooled, HIV antibody-negative specimens permits identification of recent infections. In Newark, pooled NAAT increased HIV-1 case detection and provided an opportunity to focus on treatment and prevention messages for those most at risk of transmitting infection. Although constrained by client willingness to participate in testing associated with a need to return to receive further results, use of pooled NAAT improved early infection sensitivity.

Detection of acute HIV-1 infections utilizing NAAT technology in Dallas, Texas

BACKGROUND

The detection of an acute human immunodeficiency virus infection (AHI) is vital in the fight against the spread of HIV to uninfected partners. Detection early after transmission is critical because the virus is replicating at a high level and is undetectable by serological markers. Nucleic acid amplification testing can detect HIV-1 RNA 10-12 days after exposure.

OBJECTIVE

Provide Dallas County Public Health Department the ability to detect an AHI and maintain a three day turn-around-time for a reactive specimen.

STUDY DESIGN

The population includes patients requesting HIV testing at various clinics throughout the state of Texas. Analyze various pool sizes for the pooling of specimens with the Aptima HIV-1 RNA qualitative assay to detect an acute HIV infection. Modify the HIV testing algorithm to include the detection of an acute HIV infection without delaying reporting results to original submitters. Perform a study to compare the detection of HIV in various HIV assays (3rd generation EIA assay, 4th generation EIA assay, HIV-1 RNA NAAT). Perform public health follow-up on patients who are confirmed to have an acute HIV infection with a goal of preventing the spread to uninfected partners.

RESULTS

A pooling protocol was validated and performed concurrently with the EIA to maintain a reactive result released after three days of collection. Of the 148,888 (2009-2012) specimens screened for HIV, 161 AHIs were detected and the public health follow-up identified an additional 13 new HIV infections that had been a contact to one of the AHIs.

CONCLUSION

Without the advancement in technology, patients could have received a negative or indeterminate test prior to implementing the NAAT, resulting in a delay in diagnosis and potential spread to uninfected partners. Improving the detection of an AHI is crucial in preventing the spread of the virus.