Tests in short supply? Try group testing Bilder, Christopher R.; Iwen, Peter C.; Abdalhamid, Baha ...
Significance (Oxford, England),
June 2020, Letnik:
17, Številka:
3
Journal Article
Odprti dostop
Christopher R. Bilder, Peter C. Iwen, Baha Abdalhamid, Joshua M. Tebbs and Christopher S. McMahan explain how, by pooling specimens, testing capacity for SARS‐CoV‐2 can be increased
Christopher R. ...Bilder, Peter C. Iwen, Baha Abdalhamid, Joshua M. Tebbs and Christopher S. McMahan explain how, by pooling specimens, testing capacity for SARS‐CoV‐2 can be increased.
Informative Retesting Bilder, Christopher R.; Tebbs, Joshua M.; Chen, Peng
Journal of the American Statistical Association,
09/2010, Letnik:
105, Številka:
491
Journal Article
Recenzirano
Odprti dostop
In situations where individuals are screened for an infectious disease or other binary characteristic and where resources for testing are limited, group testing can offer substantial benefits. Group ...testing, where subjects are tested in groups (pools) initially, has been successfully applied to problems in blood bank screening, public health, drug discovery, genetics, and many other areas. In these applications, often the goal is to identify each individual as positive or negative using initial group tests and subsequent retests of individuals within positive groups. Many group testing identification procedures have been proposed; however, the vast majority of them fail to incorporate heterogeneity among the individuals being screened. In this paper, we present a new approach to identify positive individuals when covariate information is available on each. This covariate information is used to structure how retesting is implemented within positive groups; therefore, we call this new approach "informative retesting." We derive closed-form expressions and implementation algorithms for the probability mass functions for the number of tests needed to decode positive groups. These informative retesting procedures are illustrated through a number of examples and are applied to chlamydia and gonorrhea testing in Nebraska for the Infertility Prevention Project. Overall, our work shows compelling evidence that informative retesting can dramatically decrease the number of tests while providing accuracy similar to established noninformative retesting procedures. This article has supplementary material online.
Two‐Dimensional Informative Array Testing McMahan, Christopher S.; Tebbs, Joshua M.; Bilder, Christopher R.
Biometrics,
September 2012, Letnik:
68, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Array‐based group‐testing algorithms for case identification are widely used in infectious disease testing, drug discovery, and genetics. In this article, we generalize previous statistical work in ...array testing to account for heterogeneity among individuals being tested. We first derive closed‐form expressions for the expected number of tests (efficiency) and misclassification probabilities (sensitivity, specificity, predictive values) for two‐dimensional array testing in a heterogeneous population. We then propose two “informative” array construction techniques which exploit population heterogeneity in ways that can substantially improve testing efficiency when compared to classical approaches that regard the population as homogeneous. Furthermore, a useful byproduct of our methodology is that misclassification probabilities can be estimated on a per‐individual basis. We illustrate our new procedures using chlamydia and gonorrhea testing data collected in Nebraska as part of the Infertility Prevention Project.
Group testing, where subjects are tested in pools rather than individually, has a long history of successful application in infectious disease screening. In this article, we develop group testing ...regression models to include covariate effects that are best regarded as random. We present approaches to fit mixed effects models using maximum likelihood, investigate likelihood ratio and score tests for variance components, and evaluate small sample performance using simulation. We illustrate our methods using chlamydia and gonorrhea data collected by the state of Nebraska as part of the Infertility Prevention Project.
Abstract Background Targeting glutamatergic dysfunction provides an exciting opportunity to improve cognitive impairment in schizophrenia. One treatment approach has targeted inadequate antioxidant ...defenses at glutamatergic synapses. Animal and human data suggest NMDA antagonists worsen executive cognitive controls — e.g. increase perseverative responses and impair set-shifting. We conducted a preliminary study to test the hypothesis that l -carnosine, an antioxidant and anti-glycation agent which is co-localized and released with glutamate would improve executive dysfunction, a cognitive domain associated with glutamate. Methods Seventy-five symptomatically stable adults with chronic schizophrenia were randomly assigned to l -carnosine as adjunctive treatment (2 g/day) or a matched placebo in a double-blind manner for 3 months. Cognitive domains (executive dysfunction, memory, attention and motor speed) were assessed using a computerized battery at baseline, 4 and 12 weeks, along with psychopathology ratings and safety parameters. Results The l -carnosine group performed significantly faster on non-reversal condition trials of the set-shifting test compared with placebo but reversal reaction times and errors were not significantly different between treatments. On the strategic target detection test, the l -carnosine group displayed significantly improved strategic efficiency and made fewer perseverative errors compared with placebo. Other cognitive tests showed no significant differences between treatments. Psychopathology scores remained stable. The carnosine group reported more adverse events (30%) compared with the placebo group (14%). Laboratory indices remained within acceptable ranges. Conclusions These preliminary findings suggest that l -carnosine merits further consideration as adjunctive treatment to improve executive dysfunction in persons with schizophrenia.
Group testing is frequently used to reduce the costs of screening a large number of individuals for infectious diseases or other binary characteristics in small prevalence situations. In many ...applications, the goals include both identifying individuals as positive or negative and estimating the probability of positivity. The identification aspect leads to additional tests being performed, known as “retests”, beyond those performed for initial groups of individuals. In this paper, we investigate how regression models can be fit to estimate the probability of positivity while also incorporating the extra information from these retests. We present simulation evidence showing that significant gains in efficiency occur by incorporating retesting information, and we further examine which testing protocols are the most efficient to use. Our investigations also demonstrate that some group testing protocols can actually lead to more efficient estimates than individual testing when diagnostic tests are imperfect. The proposed methods are applied retrospectively to chlamydia screening data from the Infertility Prevention Project. We demonstrate that significant cost savings could occur through the use of particular group testing protocols.
Group (pooled) testing is often used to reduce the total number of tests that are needed to screen a large number of individuals for an infectious disease or some other binary characteristic. ...Traditionally, research in group testing has assumed that each individual is independent with the same risk of positivity. More recently, there has been a growing set of literature generalizing previous work in group testing to include heterogeneous populations so that each individual has a different risk of positivity. We investigate the effect of acknowledging population heterogeneity on a commonly used group testing procedure which is known as 'halving'. For this procedure, positive groups are successively split into two equal-sized halves until all groups test negatively or until individual testing occurs. We show that heterogeneity does not affect the mean number of tests when individuals are randomly assigned to subgroups. However, when individuals are assigned to subgroups on the basis of their risk probabilities, we show that our proposed procedures reduce the number of tests by taking advantage of the heterogeneity. This is illustrated by using chlamydia and gonorrhoea screening data from the state of Nebraska.
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