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Group testing is a useful method that has broad applications in medicine, engineering, and even in airport security control. Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to…

Other Statistics · Statistics 2017-04-17 Yaakov Malinovsky

Group testing was conceived during World War II to identify soldiers infected with syphilis using as few tests as possible, and it has attracted renewed interest during the COVID-19 pandemic. A long-standing assumption in the probabilistic…

Social and Information Networks · Computer Science 2022-11-18 Surin Ahn , Wei-Ning Chen , Ayfer Ozgur

We study the problem of identifying defective units in a finite population of \( n \) units, where each unit \( i \) is independently defective with known probability \( p_i \). This setting is referred to as the \emph{Generalized Group…

Statistics Theory · Mathematics 2025-06-23 Yaakov Malinovsky , Viktor Skorniakov

When the infection prevalence of a disease is low, Dorfman showed 80 years ago that testing groups of people can prove more efficient than testing people individually. Our goal in this paper is to propose new group testing algorithms that…

Methodology · Statistics 2020-07-23 Marco Cuturi , Olivier Teboul , Quentin Berthet , Arnaud Doucet , Jean-Philippe Vert

We consider the problem of identifying infected individuals in a population of size N. We introduce a group testing approach that uses significantly fewer than N tests when infection prevalence is low. The most common approach to group…

Applications · Statistics 2022-01-03 Paolo Bertolotti , Ali Jadbabaie

We consider the quantitative group testing problem where the objective is to identify defective items in a given population based on results of tests performed on subsets of the population. Under the quantitative group testing model, the…

Information Theory · Computer Science 2017-10-24 Chao Wang , Qing Zhao , Chen-Nee Chuah

Consider a finite population of $N$ items, where item $i$ has a probability $p_i$ to be defective. The goal is to identify all items by means of group testing. This is the generalized group testing problem (hereafter GGTP). In the case of…

Other Statistics · Statistics 2020-02-28 Yaakov Malinovsky

Accurate detection of infected individuals is one of the critical steps in stopping any pandemic. When the underlying infection rate of the disease is low, testing people in groups, instead of testing each individual in the population, can…

This article reviews a class of adaptive group testing procedures that operate under a probabilistic model assumption as follows. Consider a set of $N$ items, where item $i$ has the probability $p$ ($p_i$ in the generalized group testing)…

Methodology · Statistics 2021-02-19 Yaakov Malinovsky , Paul S. Albert

Choosing an optimal strategy for hierarchical group testing is an important problem for practitioners who are interested in disease screening with limited resources. For example, when screening for infectious diseases in large populations,…

Methodology · Statistics 2020-02-27 Yaakov Malinovsky , Gregory Haber , Paul S. Albert

In this paper, we propose a computer-oriented method of construction of optimal group sequential hypothesis tests with variable group sizes. In particular, for independent and identically distributed observations we obtain the form of…

Methodology · Statistics 2023-03-30 Andrey Novikov

Group sequential design (GSD) is widely used in clinical trials in which correlated tests of multiple hypotheses are used. Multiple primary objectives resulting in tests with known correlations include evaluating 1) multiple experimental…

Methodology · Statistics 2021-03-22 Keaven M. Anderson , Zifang Guo , Jing Zhao , Linda Z. Sun

In applications of group testing in networks, e.g. identifying individuals who are infected by a disease spread over a network, exploiting correlation among network nodes provides fundamental opportunities in reducing the number of tests…

Information Theory · Computer Science 2023-03-21 Hesam Nikpey , Jungyeol Kim , Xingran Chen , Saswati Sarkar , Shirin Saeedi Bidokhti

In the group testing problem the aim is to identify a small set of $k\sim n^\theta$ infected individuals out of a population size $n$, $0<\theta<1$. We avail ourselves of a test procedure capable of testing groups of individuals, with the…

Discrete Mathematics · Computer Science 2021-05-14 Amin Coja-Oghlan , Oliver Gebhard , Max Hahn-Klimroth , Philipp Loick

The study in group testing aims to develop strategies to identify a small set of defective items among a large population using a few pooled tests. The established techniques have been highly beneficial in a broad spectrum of applications…

Information Theory · Computer Science 2025-01-23 Venkata Gandikota , Nikita Polyanskii , Haodong Yang

The group testing problem is concerned with identifying a small set of infected individuals in a large population. At our disposal is a testing procedure that allows us to test several individuals together. In an idealized setting, a test…

Information Theory · Computer Science 2023-09-19 Oliver Gebhard , Oliver Johnson , Philipp Loick , Maurice Rolvien

We consider dynamical group testing problem with a community structure. With a discrete-time SIR (susceptible, infectious, recovered) model, we use Dorfman's two-step group testing approach to identify infections, and step in whenever…

Methodology · Statistics 2022-01-21 Mustafa Doger , Sennur Ulukus

The use of group testing to locate all instances of disease in a large population of blood samples was first considered seventy years ago. Since then, several methods have been used to approximate the minimum expected number of tests. The…

Applications · Statistics 2015-03-24 Seth Zimmerman

Originally suggested for the blood testing problem by Dorfman in 1943, an idea of Group Testing (GT) has found many applications in other fields as well. Among many (binomial) GT procedures introduced since then, in 1990, Yao and Hwang…

Statistics Theory · Mathematics 2025-06-23 Viktor Skorniakov , Ugnė Čižikovienė

To generalize inferences from a randomized trial to the target population of all trial-eligible individuals, investigators can use nested trial designs, where the randomized individuals are nested within a cohort of trial-eligible…

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