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Additional Information about Infectious Diseases
Published in Lyle D. Broemeling, Bayesian Analysis of Infectious Diseases, 2021
When the prevalence of the disease is minimal, say less than 15%, group testing results in an important reduction in the number of tests performed. Group testing is also used in a large variety of applications, including blood screening for infectious diseases, sexually transmitted diseases, bacterial infection of food, and compound discovery for use in the development of new pharmaceuticals. Group testing was also employed for the investigation for the influenza pandemic (H1N1) of 2009.
Perspective on Clinical Trials for Dermal Drug Delivery Systems
Published in Tapash K. Ghosh, Dermal Drug Delivery, 2020
John T. Farrar, Shamir N. Kalaria
It is also quite common to restrict our initial testing to groups of people considered to be a lower risk, which tends to exclude children, pregnant women and the elderly. While this may make sense from the perspective of reducing the risk to these populations, it also prevents us from learning about the efficacy and potential side effects in these populations. This has important implications for the use of any therapy in these more vulnerable populations. Significant controversy still surrounds the best way to accomplish specific group testing, but there is no question that clinical trial evidence for efficacy and safety is an important and yet under achieved goal for these populations.
Some Statistical Procedures for Biomarker Measurements Subject to Instrumental Limitations
Published in Albert Vexler, Alan D. Hutson, Xiwei Chen, Statistical Testing Strategies in the Health Sciences, 2017
Albert Vexler, Alan D. Hutson, Xiwei Chen
Group testing is extensively used to reduce the cost of screening individuals for infectious diseases, and has since been expanded extensively to include more general statistical methodology when the data have to be gathered through grouping. In the context of group testing for rare abnormalities, Delaigle and Hall (2012) developed efficient nonparametric predictors for homogeneous pooled data and demonstrated that the optimal rates of convergence can be achieved. The method was shown to have the same convergence rate as in the case of no pooling when the level of pooling is moderate and a different convergence rate from that of an optimal estimator by no more than a logarithmic factor in the setting of “overpooling.” This approach improves on the random pooling nonparametric predictor, enables more accurate identification of vulnerable categories of people, and can lead to subsequent studies that can assist individuals who are particularly vulnerable to infection. The authors illustrated the practical performance of the method via simulated examples and an application to the National Health and Nutrition Examination Survey (NHANES) study, a large health and nutrition survey collected in the United States.
The efficient design of Nested Group Testing algorithms for disease identification in clustered data
Published in Journal of Applied Statistics, 2023
Ana F. Best, Yaakov Malinovsky, Paul S. Albert
Group testing has been used since the 1940s to reduce the cost of screening a population for disease, among other medical, industrial, and agricultural applications. One simple design [1] pools and tests individuals’ samples in groups; individual samples are then only tested if their pool is positive overall. For rare diseases, this procedure allows all cases in the population to be identified, using far fewer tests than the population size. Substantial research has introduced more sophisticated (and efficient) designs and improved the efficiency of established designs, e.g. through optimization of group sizes, under both frequentist and Bayesian paradigms [2–6]. A large body of research has addressed the impact of misclassification on group testing [7–10].
Influence and involvement of support people in adolescent and young adult HIV testing
Published in AIDS Care, 2019
Jillian Neary, Anjuli D. Wagner, Cyrus Mugo, Peter M. Mutiti, David Bukusi, Grace C. John-Stewart, Dalton C. Wamalwa, Pamela K. Kohler, Jennifer A. Slyker
Young adults were primarily influenced by peers and partners to test and were more likely to be accompanied by partners compared to adolescents. Partner involvement in the testing experience was common; 57% of partners were present for disclosure of results, suggesting that the test visit is an important interventional opportunity for counselors to assist with early disclosure and building social and emotional support from the moment of learning one’s results. Group testing is also common in this clinic, where many students present together for testing after school but complete testing individually. Promotion of group presentation for testing may be an intervention that merits further investigation to increase uptake of AYA HTS.
Pilot study of an occupational healthcare program to assess the SARS-CoV-2 infection and immune status of employees in a large pharmaceutical company
Published in Current Medical Research and Opinion, 2021
Petra C. Moroni-Zentgraf, Christoph Keller, Mazyar Mahmoudi, Kimberley Kallsen, Christoph C. Eschenfelder, Ralf Sigmund, Hanns Walter Müller, Patrick Baum, Bertram Boos, Michael Schneider, Egbert Mundt
The pilot was performed as a two-group testing program according to COVID-19 history: (i) known and recovered from COVID-19 and (ii) unknown COVID-19 history. This design enabled comparison of test results between a group known to have had COVID-19 (COVID-19 known positive [COVID-19kp]) and a group with unknown history, but potentially infected unknowingly in the past (COVID-19uk). Testing schedule and subsequent actions were determined by participants’ status, which included not infected, acutely ill/infectious, or recovered/immune (Figure 1 and Supplementary Table S1). Four regular visits were scheduled at approximately 2-week intervals (see Supplementary Appendix).