Informative Dorfman Screening

Abstract

Summary Since the early 1940s, group testing (pooled testing) has been used to reduce costs in a variety of applications, including infectious disease screening, drug discovery, and genetics. In such applications, the goal is often to classify individuals as positive or negative using initial group testing results and the subsequent process of decoding of positive pools. Many decoding algorithms have been proposed, but most fail to acknowledge, and to further exploit, the heterogeneous nature of the individuals being screened. In this paper, we use individuals’ risk probabilities to formulate new informative decoding algorithms which implement Dorfman retesting in a heterogeneous population. We introduce the concept of “thresholding” to classify individuals as “high” or “low risk,” so that separate, risk-specific algorithms may be used, while simultaneously identifying pool sizes that minimize the expected number of tests. When compared to competing algorithms which treat the population as homogeneous, we show that significant gains in testing efficiency can be realized with virtually no loss in screening accuracy. An important additional benefit is that our new procedures are easy to implement. We apply our methods to chlamydia and gonorrhea data collected recently in Nebraska as part of the Infertility Prevention Project.

Optimal Group Testing Designs for Estimating Prevalence with Uncertain Testing Errors

“…In the following, we set the number of simulation replications to N = 10000, and set the prespecified values of the test parameters to match the Chlamydia study from Nebraska, the United States (McMahan et al, 2012, Table 1). They prespecified the prevalence to be 0.07, and the sensitivity and specificity to be 0.93 and 0.96 for female’s swab specimens.…”

Current Trends in the detection of Acute HIV Infection among Blood Donors: Reliability of Pooled Nucleic Acid Amplification Technology and the Need for Population Specific Algorithms: A Systematic Review

“…In contrast, of those anti-HIV repeat reactive samples that tested NAAT nonreactive and Western blot negative or indeterminate, 98.5% had an Abbott ELISA signal-cutoff ratio less than 15 [15]. The need for an optimized and realistic algorithm and pool size that is cost effective, for different settings and incidences via-as-vis methodology (such as hard spinning), taking into account HIV 1 genetic diversity, primerprobe mismatch and platforms as summarized in Table 6 below, cannot be over emphasized [16][17][18][19][20][21][22][23]26,27,[36][37][38][39][40][41][42][43][44][45]. Cannillo et al recently, reported that CAD as the most frequent cardiac complication in HIV patients (particularly those with low CD4 and high viral load) treated with HAART.…”

“…The need for population specific NAAT algorithm and optimization of assays and pool sizes including modelling and simulation cannot be over emphasized [15,17,19,31]. Tang and Ou have summarized various molecular diagnostic techniques, their application, turnaround time, including blood donor screening in a review [18].…”

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

“…Group testing procedures save cost and time and have wide spread applications, including blood screening (Dorfman 1943; Finucan 1964; Gastwirth and Johnson 1994; Litvak, Tu, and Pagano 1994; Delaigle and Hall 2012; McMahan, Tebbs, and Bilder 2012; Tebbs, McMahan, and Bilder 2013), quality control in product testing (Sobel and Groll 1959, 1966), computation biology (De Bonis, Gasieniec, and Vaccaro 2005), DNA screening (Du and Hwang 2006; Golan, Erlich, and Rosset 2012), and photon detection (van den Berg et al 2013). According to Hughes-Oliver (2006), group testing began as early as 1915, when it was used in dilution studies for estimating the density of organisms in a biological medium.…”