Sensitivity and specificity of pooled versus individual sera in a human immunodeficiency virus antibody prevalence study

Pooled testing efficiency increases with test frequency

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

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.

False Negative Mitigation in Group Testing for COVID-19 Screening

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

COVID-19 prevalence estimation by random sampling in population - optimal sample pooling under varying assumptions about true prevalence

BACKGROUND

The number of confirmed COVID-19 cases divided by population size is used as a coarse measurement for the burden of disease in a population. However, this fraction depends heavily on the sampling intensity and the various test criteria used in different jurisdictions, and many sources indicate that a large fraction of cases tend to go undetected.

METHODS

Estimates of the true prevalence of COVID-19 in a population can be made by random sampling and pooling of RT-PCR tests. Here I use simulations to explore how experiment sample size and degrees of sample pooling impact precision of prevalence estimates and potential for minimizing the total number of tests required to get individual-level diagnostic results.

RESULTS

Sample pooling can greatly reduce the total number of tests required for prevalence estimation. In low-prevalence populations, it is theoretically possible to pool hundreds of samples with only marginal loss of precision. Even when the true prevalence is as high as 10% it can be appropriate to pool up to 15 samples. Sample pooling can be particularly beneficial when the test has imperfect specificity by providing more accurate estimates of the prevalence than an equal number of individual-level tests.

CONCLUSION

Sample pooling should be considered in COVID-19 prevalence estimation efforts.

Pooling of sera for human T-cell lymphotropic virus (HTLV) screening in a time of increasing health care expenditure and limited resources

Identifying the true prevalence of human T-cell lymphotropic virus, mostly type 1 (HTLV-1), and the number of patients with HTLV-1-associated diseases, in addition to introducing HTLV-1/2 serology during the prenatal of pregnant women and in individuals infected with other viruses that share transmission routes with HTLV-1, are actions that could help to recognize the importance of this virus by WHO and national health organizations, and to control its transmission/dissemination. As Brazil is endemic to HTLV and there is an increase in health care expenditure, but resources are limited, any strategy that could reduce the cost of HTLV screening is needed and welcomed. This study aimed to determine whether the strategy of pooling sera for HTLV antibody determination is feasible and reduces the costs. Two enzyme immunoassays (EIA Murex HTLV-I+II, Diasorin, UK, and Gold ELISA HTLV-1+2, REM Ind. Com. Ltda., SP, Brazil), and serum samples that resulted in different levels of HTLV-1/2 antibodies by EIA and of which a volume allowed assay validation were employed for analysis. The diagnostic sensitivity and specificity and Cohen's Kappa value, as well as the accuracy and precision were analyzed. After validating the five-sample pool using the EIA Murex (Cohen's Kappa = 1.0), the technique was employed for individual cost comparison in 2,625 serum samples from populations at risk of HTLV infections (HBV, HCV, and HIV-infected individuals). The results from individual and pooled samples confirmed the diagnostic sensitivity (100%) and specificity (100%) of the pooling and a cost minimization varying from 60.7% to 73.6%. In conclusion, the results of this study suggest the use of pooling sera in sero-epidemiological surveillance studies and possibly in prenatal care screening programs in Brazil.

Bead-Based Multiplex Assay for the Simultaneous Detection of Antibodies to African Swine Fever Virus and Classical Swine Fever Virus

African swine fever (ASF) and Classical swine fever (CSF) are both highly contagious diseases of domestic pigs and wild boar. In the last years, several cases of both diseases have been reported in the Caucasus, Russian Federation and Eastern Europe. Thus, the probability of encountering these two viruses in the same area is increasing. Since differentiation by clinical or post-mortem examination is not possible, laboratory tools for differential diagnosis are required. In the present work, we have developed a triplex bead-based assay using some of the most immunogenic antigens of each virus, for the simultaneous detection of antibodies; i.e. the VP72 and VP30 of ASF virus (ASFV) and the E2 protein of CSF virus (CSFV). The assay was firstly set up and optimized using well characterized reference serum samples specific for each pathogen. Then, a panel of 352 sera from experimentally infected animals with either ASFV or CSFV were analyzed in the multiplex assay. A collection of 253 field negative sera was also included in the study. The results of the multiplex analysis were compared to those obtained by two commercially available ELISAs for detection of antibodies against ASFV or CSFV, and considered in this study as the reference techniques. The data obtained showed values of 97.3% sensitivity and 98.3% specificity for detection of antibodies to ASFV and 95.7% of sensitivity and 99.8% specificity for detection of antibodies to CSFV. This multiplex assay allows the simultaneous and differential detection of antibodies against ASFV and CSFV, providing a valuable tool for surveillance studies. Moreover, this method is rather versatile, offering the possibility of increasing the panel of antigens from other swine diseases that could be of interest for a differential diagnosis along with ASF and CSF.

Grouping methods for estimating the prevalences of rare traits from complex survey data that preserve confidentiality of respondents

Originally, 2-stage group testing was developed for efficiently screening individuals for a disease. In response to the HIV/AIDS epidemic, 1-stage group testing was adopted for estimating prevalences of a single or multiple traits from testing groups of size q, so individuals were not tested. This paper extends the methodology of 1-stage group testing to surveys with sample weighted complex multistage-cluster designs. Sample weighted-generalized estimating equations are used to estimate the prevalences of categorical traits while accounting for the error rates inherent in the tests. Two difficulties arise when using group testing in complex samples: (1) How does one weight the results of the test on each group as the sample weights will differ among observations in the same group. Furthermore, if the sample weights are related to positivity of the diagnostic test, then group-level weighting is needed to reduce bias in the prevalence estimation; (2) How does one form groups that will allow accurate estimation of the standard errors of prevalence estimates under multistage-cluster sampling allowing for intracluster correlation of the test results. We study 5 different grouping methods to address the weighting and cluster sampling aspects of complex designed samples. Finite sample properties of the estimators of prevalences, variances, and confidence interval coverage for these grouping methods are studied using simulations. National Health and Nutrition Examination Survey data are used to illustrate the methods.

Oral fluid versus blood sampling in group-housed sows and finishing pigs: Feasibility and performance of antibody detection for porcine reproductive and respiratory syndrome virus (PRRSV)

The feasibility of using individual and pen-based oral fluid samples to detect PRRSV antibodies in growing-finishing pigs and group-housed sows was investigated. The diagnostic performances of a commercial oral fluid ELISA (OF-ELISA) and a serum ELISA (SER-ELISA) performed on individual or pooled samples from 5 or 10 pigs and sows was evaluated. The performance of the OF-ELISA was also assessed for pen-based oral fluids. Eight hundred and thirty-four pigs and 1598 sows from 42 PRRSV-infected and 3 PRRSV-negative herds were oral fluid sampled and bled. PRRSV antibodies were detected by an OF-ELISA performed at individual, pool (5 or 10 samples) and pen levels. Serum samples were tested by a SER-ELISA at individual and pool levels. The sensitivity and specificity of ELISAs for individual samples were assessed by Bayesian analysis. The relative diagnostic performance for the pools was calculated by taking individual samples as the gold standard. SER-ELISA and individual OF-ELISA results were used as references for estimating OF-ELISA performance for pen-based samples. Individual oral fluid collection was feasible in all kinds of pigs, whereas pen-based samples were unsuccessful in 40% of the group-housed sow pens. High levels of sensitivity comparable to those of the SER-ELISA were found for the OF-ELISA when performed on individual, 5-sample pool or pen-based samples from pigs or sows. The OF-ELISA lacked specificity for individual samples from sows. Pooling 5 individual oral fluid samples or using pen-based samples increased test specificity.

Composite Sampling Approaches for Bacillus anthracis Surrogate Extracted from Soil

Any release of anthrax spores in the U.S. would require action to decontaminate the site and restore its use and operations as rapidly as possible. The remediation activity would require environmental sampling, both initially to determine the extent of contamination (hazard mapping) and post-decon to determine that the site is free of contamination (clearance sampling). Whether the spore contamination is within a building or outdoors, collecting and analyzing what could be thousands of samples can become the factor that limits the pace of restoring operations. To address this sampling and analysis bottleneck and decrease the time needed to recover from an anthrax contamination event, this study investigates the use of composite sampling. Pooling or compositing of samples is an established technique to reduce the number of analyses required, and its use for anthrax spore sampling has recently been investigated. However, use of composite sampling in an anthrax spore remediation event will require well-documented and accepted methods. In particular, previous composite sampling studies have focused on sampling from hard surfaces; data on soil sampling are required to extend the procedure to outdoor use. Further, we must consider whether combining liquid samples, thus increasing the volume, lowers the sensitivity of detection and produces false negatives. In this study, methods to composite bacterial spore samples from soil are demonstrated. B. subtilis spore suspensions were used as a surrogate for anthrax spores. Two soils (Arizona Test Dust and sterilized potting soil) were contaminated and spore recovery with composites was shown to match individual sample performance. Results show that dilution can be overcome by concentrating bacterial spores using standard filtration methods. This study shows that composite sampling can be a viable method of pooling samples to reduce the number of analysis that must be performed during anthrax spore remediation.

Prevalence estimation subject to misclassification: the mis-substitution bias and some remedies

We consider the problem of estimating the prevalence of a disease under a group testing framework. Because assays are usually imperfect, misclassification of disease status is a major challenge in prevalence estimation. To account for possible misclassification, it is usually assumed that the sensitivity and specificity of the assay are known and independent of the group size. This assumption is often questionable, and substitution of incorrect values of an assay's sensitivity and specificity can result in a large bias in the prevalence estimate, which we refer to as the mis-substitution bias. In this article, we propose simple designs and methods for prevalence estimation that do not require known values of assay sensitivity and specificity. If a gold standard test is available, it can be applied to a validation subsample to yield information on the imperfect assay's sensitivity and specificity. When a gold standard is unavailable, it is possible to estimate assay sensitivity and specificity, either as unknown constants or as specified functions of the group size, from group testing data with varying group size. We develop methods for estimating parameters and for finding or approximating optimal designs, and perform extensive simulation experiments to evaluate and compare the different designs. An example concerning human immunodeficiency virus infection is used to illustrate the validation subsample design.

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.

Optimality of group testing in the presence of misclassification

Several optimality properties of Dorfman's (1943) group testing procedure are derived for estimation of the prevalence of a rare disease whose status is classified with error. Exact ranges of disease prevalence are obtained for which group testing provides more efficient estimation when group size increases.

Logistic regression analysis of biomarker data subject to pooling and dichotomization

There is growing interest in pooling specimens across subjects in epidemiologic studies, especially those involving biomarkers. This paper is concerned with regression analysis of epidemiologic data where a binary exposure is subject to pooling and the pooled measurement is dichotomized to indicate either that no subjects in the pool are exposed or that some are exposed, without revealing further information about the exposed subjects in the latter case. The pooling process may be stratified on the disease status (a binary outcome) and possibly other variables but is otherwise assumed random. We propose methods for estimating parameters in a prospective logistic regression model and illustrate these with data from a population-based case-control study of colorectal cancer. Simulation results show that the proposed methods perform reasonably well in realistic settings and that pooling can lead to sizable gains in cost efficiency. We make recommendations with regard to the choice of design for pooled epidemiologic studies.

Pooled nucleic acid testing to identify antiretroviral treatment failure during HIV infection

BACKGROUND

Pooling strategies have been used to reduce the costs of polymerase chain reaction-based screening for acute HIV infection in populations in which the prevalence of acute infection is low (less than 1%). Only limited research has been done for conditions in which the prevalence of screening positivity is higher (greater than 1%).

METHODS AND RESULTS

We present data on a variety of pooling strategies that incorporate the use of polymerase chain reaction-based quantitative measures to monitor for virologic failure among HIV-infected patients receiving antiretroviral therapy. For a prevalence of virologic failure between 1% and 25%, we demonstrate relative efficiency and accuracy of various strategies. These results could be used to choose the best strategy based on the requirements of individual laboratory and clinical settings such as required turnaround time of results and availability of resources.

CONCLUSIONS

Virologic monitoring during antiretroviral therapy is not currently being performed in many resource-constrained settings largely because of costs. The presented pooling strategies may be used to significantly reduce the cost compared with individual testing, make such monitoring feasible, and limit the development and transmission of HIV drug resistance in resource-constrained settings. They may also be used to design efficient pooling strategies for other settings with quantitative screening measures.

Sensitivity of pooled serum testing for screening antibody of schistosomiasis japonica by IHA in a mountainous area of Yunnan, China

Pooled sample testing (PST) as a strategy for avoiding testing the majority of individual negative samples has been proposed for screening of diseases in low prevalence areas. There has been no standard guideline for PST in screening of Schistosoma japonicum infection of Yunnan, China. To document the optimum pool size with acceptable sensitivity of PST for screening of Schistosoma japonicum infection in this setting, an experimental pooling of each of 31 positive sera by IHA with various numbers of 24 negative sera was done. The results were used to create a statistical model which was subsequently used for simulation to predict sensitivity of the pooled serum tests in the population with varying prevalence and pool size. We found that to keep the sensitivity of PST above 90%, 1:05 should be the maximum dilution, that is, the optimum pool size should not be greater than 6. Antigen will have rather little interference if the prevalence of infection is low e.g. 1% or the antigen:antibody ratio is 1:100 or below. Pooled serum testing by IHA is an acceptable sensitive method for detecting antibody for Schistosoma japonicum infection in this area.

Feasibility of pooled-sample testing for the detection of porcine reproductive and respiratory syndrome virus antibodies on serum samples by ELISA

Surveillance of porcine reproductive and respiratory syndrome (PRRS) in negative sow farms is usually performed by testing for the presence of antibodies against PRRS virus in serum with a commercial ELISA test. The objective of this study was to evaluate the feasibility of pooling serum samples for detection of PRRS virus antibodies by ELISA. The effect of pool size on the sensitivity and specificity of the ELISA test was evaluated by testing true positive samples and false positive samples, respectively, diluted in negative sera. The effect of three different cut-off values for the interpretation of the diagnostic test (0.4, 0.3 and 0.2) was evaluated as well. Furthermore, the obtained sensitivity and specificity estimates were used to calculate the herd sensitivity and herd specificity of surveillance protocols in different scenarios. The results showed that pooling serum samples to detect PRRSV antibodies resulted in a decrease in sensitivity and an increase in specificity, compared to testing individual samples, while the reduction of the s/p cut-off value recommended by the manufacturer (0.4) had the opposite effect. We describe an approach that can increase the herd sensitivity of a surveillance protocol for breeding herds, while maintaining high herd specificity and low testing costs. This can be achieved by sampling a larger number of animals and running the samples in pools. Therefore, the conventional monitoring protocols based on ELISA on individual samples can be improved by using pooled-sample testing.

Evaluation of pooled screening for anti-HCV in two blood services set-ups

OBJECTIVE

Screening blood donations for anti-HCV is only partially performed in many developing countries due to the relatively high costs of testing. The screening expenditures can be reduced by testing donations in pools. This study evaluates the accuracy and feasibility of pooled screening procedure for anti-HCV in blood banks in Israel and the Palestinian Authority.

METHODS

The sensitivity and specificity of tests performed on pool sizes of 6-24 samples were compared to singleton immunoassay testing. All negative samples and those positive for anti-HCV were obtained from the routine work of Magen David Adom Blood Services in Israel and Shifa Hospital blood bank in Palestinian Authority. The experiments were run in parallel with different technologies.

RESULTS

The sensitivity of pooled-testing for anti-HCV by Magen David Adom was 94-97% for verified samples. In the Shifa Hospital, the sensitivity was estimated as 96-97% for non-verified samples. Cost-analysis showed benefits up to $2 per donation screened for anti-HCV in Shifa Hospital.

CONCLUSIONS

We recommend using manually created pools of up to 6 samples when testing for anti-HCV, but at the cost of 3% loss in sensitivity. Pooling can be considered, in countries which do not perform routine screening, due to their limited economic resources.

Evaluation of the dried blood spot filter paper technology and five testing strategies of HIV-1 and HIV-2 infections in West Africa

Simple robust approaches are needed to monitor the prevalence and incidence of HIV in Africa. The aim of this study was to evaluate the use of dried blood spot (DBS) as an alternative to serum or plasma for sentinel surveillance. Paired DBS and blood samples were obtained from 200 patients attending a genito-urinary medicine clinic in West Africa. The gold standard of diagnosis was based on the combination of 3 enzyme-linked immunosorbent assays (ELISA) using serum. The presence of HIV antibodies in eluates of dried blood spots was detected by ELISA, Gelatin Particle Assay (GPA) and Pepti-Lav 1-2 in 5 different testing strategies. All 200 eluates were tested individually, and in addition pools of 5 eluates each were tested. The sensitivity of the testing strategies ranged from 95.0% (83.1 - 99.4%) to 100% and the specificity from 97.5% (93.7 - 99.3%) to 100%. Testing in pools of 5 did not affect sensitivity. Dried blood spots were easy to work with. Test kit and laboratory consumable costs varied between 492 pounds and 1037 pounds (unpooled strategies) and 163 pounds and 421 pounds (pooled). The monospecific ELISAs used in this study are no longer in production; currently available differentiating assays need to be tested. DBS are recommended for sentinel surveillance in Africa.

Use of seroconversion panels to estimate delay in detection of anti-human immunodeficiency virus antibodies by enzyme-linked immunosorbent assay of pooled compared to singleton serum samples

The transfusion of unsafe blood worldwide accounts for 5 to 15% of new human immunodeficiency virus (HIV) infections, most of which occur in sub-Saharan Africa. While developed countries now apply PCR testing of pooled samples, some developing countries still do not have universal screening policies. More efficient low-cost procedures for the screening of pooled samples have the potential to encourage mass screening efforts in resource-poor settings. The aim of this study was to estimate the delay in the detection of HIV antibodies in pooled serum samples compared to that in singleton serum samples by enzyme-linked immunosorbent assay (ELISA) and to evaluate the risk of transfusion-transmitted HIV infection during the window period. Serial blood samples obtained from five HIV seroconversion panels were mixed with HIV-seronegative blood samples to create pools of 6, 12, 16, 24, 32, and 48 samples. The delay in detection of the first anti-HIV antibody-positive sample in tests with pooled samples was calculated for each pool size and compared to that obtained by testing of singleton samples and statistically evaluated by a robust log-linear regression analysis. The risk of a false-negative (FN) result caused by dilution was estimated by use of the incidence risk/window period model. The additional risk of transmission related to ELISA screening of pooled samples for HIV did not exceed 9% of the current risk of an FN result (estimated to be 1/1,067,000). The countries with virus prevalence rates in donors of less than 15% are expected to save up to 30% in the number of tests. ELISA screening of pooled samples could be considered in settings where the testing of blood supplies for HIV is not routinely done.

Pooling Experiments for Blood Screening and Drug Discovery

Pooling experiments date as far back as 1915 and were initially used in dilution studies for estimating the density of organisms in some medium. These early uses of pooling were necessitated by scientific and technical limitations. Today, pooling experiments are driven by the potential cost savings and precision gains that can result, and they are making a substantial impact on blood screening and drug discovery. A general review of pooling experiments is given here, with additional details and discussion of issues and methods for two important application areas, namely, blood testing and drug discovery. The blood testing application is very old, from 1943, yet is still used today, especially for HIV antibody screening. In contrast, the drug discovery application is relatively new, with early uses occurring in the period from the late 1980s to early 1990s. Statistical methods for this latter application are still actively being investigated and developed through both the pharmaceutical industries and academic research. The ability of pooling to investigate synergism offers exciting prospects for the discovery of combination therapies.

Strategies and statistics of sampling for rare individuals

Diverse subdisciplines within entomology recognize the detection of rare individuals as the precursor to effective management of these individuals. Unfortunately, detection methods have often developed on a case-by-case basis, and advances in one subdiscipline have not carried over to similarly related fields. The biology of a particular organism will certainly affect sampling methods, but the underlying principles governing the power of a sampling strategy to detect rare individuals will apply across taxa. Our review of the sampling literature demonstrates the common problem of detecting rare individuals, reviews the fundamentals of probability theory as a foundation for any monitoring program, and discusses the inferences that can be drawn from samples, especially when resources limit sampling efforts. Particular emphasis is placed on binomial-, beta-binomial-, and hypergeometric-based sampling strategies as they pertain to quarantine inspections for exotic pests, veterinary/medical entomology, and insecticide resistance monitoring.

Regression models for disease prevalence with diagnostic tests on pools of serum samples

Whether the aim is to diagnose individuals or estimate prevalence, many epidemiological studies have demonstrated the successful use of tests on pooled sera. These tests detect whether at least one sample in the pool is positive. Although originally designed to reduce diagnostic costs, testing pools also lowers false positive and negative rates in low prevalence settings and yields more precise prevalence estimates. Current methods are aimed at estimating the average population risk from diagnostic tests on pools. In this article, we extend the original class of risk estimators to adjust for covariates recorded on individual pool members. Maximum likelihood theory provides a flexible estimation method that handles different covariate values in the pool, different pool sizes, and errors in test results. In special cases, software for generalized linear models can be used. Pool design has a strong impact on precision and cost efficiency, with covariate-homogeneous pools carrying the largest amount of information. We perform joint pool and sample size calculations using information from individual contributors to the pool and show that a good design can severely reduce cost and yet increase precision. The methods are illustrated using data from a Kenyan surveillance study of HIV. Compared to individual testing, age-homogeneous, optimal-sized pools of average size seven reduce cost to 44% of the original price with virtually no loss in precision.

Pooled-sample testing as a herd-screening tool for detection of bovine viral diarrhea virus persistently infected cattle

The study was conducted to develop methodology for least-cost strategies for using polymerase chain reaction (PCR)/probe testing of pooled blood samples to identify animals in a herd persistently infected with bovine viral diarrhea virus (BVDV). Cost was estimated for 5 protocols using Monte Carlo simulations for herd prevalences of BVDV persistent infection (BVDV-PI) ranging from 0.5% to 3%, assuming a cost for a PCR/probe test of $20. The protocol associated with the least cost per cow involved an initial testing of pools followed by repooling and testing of positive pools. For a herd prevalence of 1%, the least cost per cow was $2.64 (95% prediction interval = $1.72, $3.68), where pool sizes for the initial and repooled testing were 20 and 5 blood samples per pool, respectively. Optimization of the least cost for pooled-sample testing depended on how well a presumed prevalence of BVDV-PI approximated the true prevalence of BVDV infection in the herd. As prevalence increased beyond 3%, the least cost increased, thereby diminishing the competitive benefit of pooled testing. The protocols presented for sample pooling have general application to screening or surveillance using a sensitive diagnostic test to detect very low prevalence diseases or pathogens in flocks or herds.

Use of binomial group testing in tests of hypotheses for classification or quantitative covariables

In group testing, the test unit consists of a group of individuals. If the group test is positive, then one or more individuals in the group are assumed to be positive. A group observation in binomial group testing can be, say, the test result (positive or negative) for a pool of blood samples that come from several different individuals. It has been shown that, when the proportion (p) of infected individuals is low, group testing is often preferable to individual testing for identifying infected individuals and for estimating proportions of those infected. We extend the potential applications of group testing to hypothesis-testing problems wherein one wants to test for a relationship between p and a classification or quantitative covariable. Asymptotic relative efficiencies (AREs) of tests based on group testing versus the usual individual testing are obtained. The Pitman ARE strongly favors group testing in many cases. Small-sample results from simulation studies are given and are consistent with the large-sample (asymptotic) findings. We illustrate the potential advantages of group testing in hypothesis testing using HIV-1 seroprevalence data.

Blood screening by nucleic acid amplification technology: current issues, future challenges

BACKGROUND

Nucleic acid amplification technology (NAT) is presently being evaluated in US clinical trials to determine the safety and efficacy of mini-pool testing for human immunodeficiency virus (HIV) and hepatitis C virus (HCV) RNA in the blood-donor population. Although the risk for transfusion-transmitted HIV and HCV infection is extremely low, there is still a small chance that blood donated by infected individuals before seroconversion can escape detection by current antibody-based assays.

METHODS

This report describes the amplification technologies being used and reviews several issues surrounding NAT-based blood screening. The performance features of NAT and current enzyme immunoassay technologies are compared, and the benefits of NAT in reducing transfusion-transmitted infections are discussed.

CONCLUSIONS

The current US clinical trials of mini-pool NAT testing for HIV and HCV RNA have successfully identified preseroconversion infectious blood units. Although the current NAT-based screening systems are semiautomated, mini-pool testing represents an unprecedented innovation among government and nongovernment agencies in the highly regulated blood transfusion industry. Despite cost-effectiveness issues, based on the public perception of infectious diseases acquired through blood transfusion, NAT-based screening of the blood supply is expected to become a standard in transfusion medicine.

Estimating the prevalence of infectious agents using pooled samples: biometrical considerations

Pooled testing of units is a common approach in the prevalence estimation of infectious agents, which leads to a reduction of total costs of diagnostic testing. We examine how the pool size affects the statistical properties of the prevalence estimator r. Exact formulae are used to determine bias and precision of r. It is shown that with moderate pool sizes the (upward) bias of r is negligible. If there is no diagnostic error, the random error of r increases slightly with higher pool sizes, whereas if sensitivity and specificity are lower than 1, pooling may markedly decrease the random error of r. Another reason why pooling may be beneficial (and even indispensable) is that it greatly reduces the huge bias that can result if the assumed values of the sensitivity and specificity of the diagnostic test are not equal to the true values. The numerical calculations show that, in case of prevalence rates of up to 5% and total sample sizes of n > or = 500, pool sizes of about 10 to 20 are generally satisfactory from a statistical view-point. The methodological advantages and disadvantages of more complicated pooling strategies involving repeated testing of units are discussed.

Group testing in presence of classification errors

We modify Dorfman's and Sterrett's group testing protocols to make them suitable for testing blood samples for the presence of HIV antibodies, as well as for many industrial applications, when false negatives cannot be tolerated. We first propose that test kit sensitivity be increased to nearly 100 per cent by altering the reactive versus non-reactive threshold. Subsequently, group and repeat testing are used with a careful selection of group size and the number of times a test is repeated, in order to maximize efficiency while keeping the false positive predictive value (FPPV) within a specified limit. Numerical calculations show that our testing protocol is efficient, has low procedural complexity and keeps both types of classification errors below specified tolerance limits.

Robustness of group testing in the estimation of proportions

In binomial group testing, unlike one-at-a-time testing, the test unit consists of a group of individuals, and each group is declared to be defective or nondefective. A defective group is one that is presumed to include one or more defective (e.g., infected, positive) individuals and a nondefective group to contain only nondefective individuals. The usual binomial model considers the individuals being grouped as independent and identically distributed Bernoulli random variables. Under the binomial model and presuming that groups are tested and classified without error, it has been shown that, when the proportion of defective individuals is low, group testing is often preferable to individual testing for identifying infected individuals and for estimating proportions of defectives. We discuss the robustness of group testing for estimating proportions when the underlying assumptions of (i) no testing errors and (ii) independent individuals are violated. To evaluate the effect of these model violations, two dilution-effect models and a serial correlation model are considered. Group testing proved to be quite robust to serial correlation. In the presence of a dilution effect, smaller group sizes should be used, but most of the benefits of group testing can still be realized.

Pooling sera to reduce the cost of HIV surveillance: a feasibility study in a rural Kenyan district

Seroprevalence studies are crucial in HIV control programs but too expensive at district level. We evaluated the applicability of pooling sera and how it can reduce cost and affect accuracy at district level. 740 samples collected from antenatal clinic attendants for a sentinel survey in a rural Kenyan district were screened individually and in pools of 10. The seroprevalence when measured individually was 7.30%, while the calculated seroprevalence from pooled testing was 7.49%. Pooling was practicable and reduced costs by 62% for a marginal loss of accuracy. It is a useful tool in increasing the affordability of surveillance at district level. A pool size of 8 would have resulted in optimal cost reduction at minimal loss of accuracy.

Unlinked anonymous HIV screening of pregnant women in a low-prevalence population

Unlinked anonymous screening was optimized and used for a survey of HIV prevalence in Finland. In 1993, 66,170 serum samples, covering more than 99% of pregnant women in the country were tested in pools of 5 sera. The pools tested were coded but it was possible to trace the region from where the samples had been collected. A total of 5 positive samples were found corresponding to a prevalence of 1/13,000 (0.01%) which is in accordance with prevalence estimates from earlier serosurveys and the national HIV registry. Information from voluntary regional HIV-testing programmes for pregnant women indicated that probably at least 3 of these positive cases had been identified by voluntary testing. Nine commercial EIAs were evaluated to investigate the effect of pooling on sensitivity and specificity of anti-HIV detection. Only 3 EIAs detected all pools with known positive samples. Individual sera from repeatedly positive pools were tested using the same EIA and positive results were confirmed by Western blot. This algorithm saved more than 80% of the cost compared to the conventional test algorithm used in diagnostic laboratories. The savings were mainly due to the reduced number of primary and supplemental tests.

Pooling blood donor samples to reduce the cost of HIV-1 antibody testing

Accurate, low cost testing of donated blood is a goal of the global effort to reduce the spread of the human immunodeficiency virus (HIV-1). We describe a modified enzyme immunoassay (EIA) method for detecting HIV-1 antibody (anti-HIV-1) in 15-sample pools. In this preliminary study, the modified EIA was as sensitive for detecting weakly seropositive samples, and as specific for testing HIV-1 Western blot-negative or Western blot-indeterminate results, as testing individual samples by the standard EIA. A simulation of field operations was conducted using pools of blood donor samples collected in the United States and in Shanghai, People's Republic of China. Implementation of the modified EIA method and testing 15-sample pools for anti-HIV-1 is a reliable strategy for reducing the cost of large scale testing of donated blood for anti-HIV-1 in areas of low seroprevalence.

Risk of human immunodeficiency virus infection for emergency department workers. Italian Study Group on Occupational Risk of HIV Infection

To evaluate the risk of human immunodeficiency virus (HIV) exposure among emergency department workers (EDWs) and their ability to identify HIV-infected patients, a seroprevalence study was performed in March 1991 in the emergency departments (EDs) of six Italian urban hospitals. At each visit, patients aged 18-65 years were asked to undergo fingerstick blood sampling for anonymous, unlinked HIV testing performed on blood adsorbed filter paper collection cards. Demographic characteristics, known or suspected HIV risk factors, and occupational exposures reported by the EDWs during the patient's visit were recorded. On 9,457 consecutive visits, 9,005 samples (95%) were tested and 65 (0.7%) were HIV positive. ED staff failed to identify 59% of HIV-infected patients. The rate of occupational exposures was 0.13/100 visits. As it is impossible to predict the HIV status of patients attending EDs, adherence to universal precautions and the development of safer devices should be utilized to minimize the risk of blood-borne infections in EDWs.

Studies of AIDS and HIV surveillance. Screening tests: can we get more by doing less?

Estimating the prevalence of the human immunodeficiency virus (HIV) in a group is challenging; this is especially so when the prevalence is small. One reason is that the presence of measurement errors resulting from the limited precision of tests makes estimation, using traditional methods, impossible in some screening situations. Measurement error is real, ignoring it leads to severe bias, and inference about the prevalence becomes unsatisfactory. Indeed, in a low prevalence situation the expected number of false positives is very high, often even higher than the number of true positives. The second reason is that in the low prevalence areas the large sample is needed in order to obtain non-zero estimate. This is usually a very costly, and often unrealistic, solution. This paper considers the advantages and disadvantages of pooled testing as an alternative solution to this problem. We show that by pooling sera samples we not only achieve a cost saving but also, which is counterintuitive, an increase in the estimation accuracy. We also discuss the statistical issues associated with the resulting estimator.

Use of pooled residual laboratory sera to assess human immunodeficiency virus prevalence among patients in Italy. The Italian Study Group on Occupational Risk of HIV infection

An anonymous unlinked seroprevalence study of human immunodeficiency virus (HIV) infection was performed by testing pools of ten sera remaining from specimens submitted consecutively to clinical pathology laboratories at 18 Italian public hospitals during four consecutive days in April 1991. Sera from positive pools were retested individually by three different enzyme immunoassays (EIAs) and considered positive if reactive by all three assays. Only the sera with discordant EIA results were retested by Western blot. Of a total of 22,590 sera, 278 were HIV positive (1.2%). The highest rates were seen in hospitals located in metropolitan areas (1.5%), in infectious disease departments (28%) and in drug addiction treatment units (28%); among men aged 21-30 (4.6%) and 31-40 years (4%); and among women aged 21-30 years (1.6%). The distribution of seropositive patients by gender and age group suggests an increasing role of heterosexual transmissions of the infection. The presence of anti-HIV antibodies in sera from patients of both sexes, in all age groups, and from all clinical settings reinforces the need for health care workers to adhere to universal precautions issued to prevent occupational bloodborne infections.

Are seroepidemiological surveys for human immunodeficiency virus infection based on tests on pools of serum specimens accurate and cost-effective?

Serum specimens (n = 17668) from UK antenatal patients in the Thames Regions were tested by Wellcozyme HIV 1/2 EIA singly and in pools of 6, 12 and 24: 35 (0.2%, 1 in 505) were confirmed as anti-HIV positive. The pools of 12 were also tested for anti-HIV 1/2 by IAF Biochem, Behring and Diagnostics Pasteur EIAs. All 35 positive specimens were easily detectable after pooling in groups of 12. The false positive rate for Wellcozyme was nearly halved compared with individual testing (1 in 309 false positive compared with 1 in 174). For the other assays false positive rates on pools of 12 were: IAF Biochem 1 in 193, Behring 1 in 140, Diagnostics Pasteur 1 in 1547. Twenty-two known anti-HIV 2-positive sera were detected by all four EIAs when diluted as in pools of 6 and 12, but by only three EIAs in pools of 24 and 48. Pooling in groups of 6 did not seem to delay detection of HIV 1 seroconversion, but pooling in groups of 12, 24 and 48 might delay it by 1, 2 and 3 weeks respectively. For this study the effect of pooling in groups of 12 would have been a reagent saving of 87-91% and a labour saving of about 50%. Because of the low HIV incidence and rarity of specimens collected around seroconversion in UK, little, if any, loss of sensitivity would result from it. Pooling in groups of 12 has therefore been chosen for the screening of anonymous antenatal specimens in the UK.

Reducing the cost of HIV antibody testing

Available tests to detect antibody to human immunodeficiency virus (HIV) have a range of applications, and injudicious selection and inappropriate use can add a significant financial burden to budgets for AIDS programmes in developing countries. There are several ways by which the cost of HIV antibody testing can be reduced; they include use of tests appropriate for existing laboratory capabilities; adoption of cost-effective testing strategies; pooling of serum samples before testing; and ensuring best possible purchase prices. Each approach can significantly reduce the cost of HIV antibody testing alone or in combination, which increases the potential sustainability of antibody testing programmes, even in settings of limited resources.

Beyond simple pooling for HIV screening

We discuss some theoretical features underlying the successful uses of pooling in testing HIV seroprevalence. In particular it is shown that there is a scaling relation for the distribution of positive sera among the pools. A multi-stage pooling method consisting of repeatedly halving the positive pools is proposed. Concentrating on the number of tests required for screening all positive individuals the method is shown to be highly efficient in low prevalence situations.

Successful use of pooled sera to estimate HIV antibody seroprevalence and eliminate all positive cases

Pooling specimens when testing them in large numbers can save scarce resources and several earlier reports have indicated this to be a feasible strategy. In an HIV antibody mass screening test carried out in our laboratory, we used Dorfman's two-stage model. We sought to establish the optimal number of specimens in a pool, and to achieve maximum efficiency while maintaining both sensitivity and specificity. Before testing for HIV antibody, five positive samples were placed in a set of 1012 sera in a double blind manner, one positive sample into a second set of 1012 sera and none in a third set. The positive rate was assumed to be 0.2% for each set of 1012 sera. As indicated by our model, 22 individual serum samples were placed into each of 46 pools which, when tested by particle agglutination assays, lead to the identification of all positive samples. We concluded that the prevalence rate can be estimated in the first stage, 95% confidence intervals were given, and the efficiency rate could be calculated for the identification of all infected specimens in a large number of samples showing low prevalence rates.