Optimality of Group Testing with Differential Misclassification

Group testing is a method that can be used to estimate the prevalence of rare infectious diseases,which can effectively save time and reduce costs compared to the method of random sampling.However,previous literature only demonstrated the optimality of group testing strategy while estimating prevalence under some strong assumptions.This article weakens the assumption of misclassification rate in the previous literature,considers the misclassification rate of the infected samples as a differentiable function of the pool size,and explores some optimal properties of group testing for estimating prevalence in the presence of differential misclassification conforming to this assumption.This article theoretically demonstrates that the group testing strategy performs better than the sample by sample procedure in estimating disease prevalence when the total number of sample pools is given or the size of the test population is determined.Numerical simulation experiments were conducted to evaluate the performance of group tests in estimating prevalence in the presence of dilution effect.

SARS-CoV-2 Pooled Testing Methodology for PCR Testing Applied in Private Laboratory in Armenia

Since the beginning of COVID-19 pandemics many countries were facing challenges with testing capacity recourse limitations. Throughout the waves of the pandemic countries were trying to address the existing constrains exploring solutions to increase the testing capacity with more cost-effective approaches. Pooled methodology was one of the methods which many have validated and used. It is evident that in case of pooled sample testing the sensitivity becomes lower, however the variation highly depends on the pool size as well as the incidence rate at the certain point. Armenia as well as many other countries has adopted regulations for mandatory COVID-19 PCR testing for all the travelers. Current study aimed to explore the efficiency of COVID-19 pooled PCR testing for nasopharyngeal swabs of individuals with no symptoms in a time period with good epidemiological state of the infection. Nasopharingeal swab samples from individuals were collected. The manual extraction of RNAs of samples was performed after pooling up to 5 samples. The pools with Cycle Threshold (CT) of < 37 were considered positive and were retested individually. In total 28,015 samples were grouped in 667 pools of which 57 were positive. The total number of positive samples was 65. The median difference (CT-pool–CT samples) was 2.4 (ranging from–3.0 to 8.9). The correlation of CT of pools and positive samples was positive. The correlation coefficient r = 0.84, P < 0.000, 95% CI range 0.7423 to 0.9243). The total economic saving when using pools compared to the individual testing was 72%. The minor difference between CT values of pools and samples can be explained by the dilution effect in the pool. However, the positive correlation between the values as well as the amount of cost saving demonstrate that pooling on nasopharyngeal samples for COVID-19 PCR testing can be a good method for efficient screening with significant resource saving. One of the most important advantages of the proposed method is the fact that samples are pooled prior extraction, which avoids the possibilities with misinterpretation of IC due to low yield of RNA in the extraction process.

Can environmental sustainability be decoupled from economic growth? Empirical evidence from Eastern Europe using the common correlated effect mean group test

The European Union(EU) and Organisation for Economic Co-operation and Development(OECD) aim to develop long-term policies for their respective member countries. Having observed increasing dangers to the environment posed by rising economic growth, they are seeking pathways to enable policy action on economic growth and environmental sustainability. Given the facts in theoretical and empirical studies, this study assessed the validity of the decoupling hypothesis by investigating asymmetricity in the relationship between environmental sustainability and economic growth in nine Eastern European countries from 1998 to 2017 using the cross-section augmented Dickey-Fuller(CADF) unit root, panel corrected standard error(PCSE), common correlated effect mean group(CCEMG), and Dumitrescu Hurlin causality approaches. Both population growth and drinking water are used as controlled variables. The outcomes establish strong cointegration among all the variables of interest. According to the results of CCEMG test, economic growth exerts short-term environmental degradation but has long-term environmental benefits in Eastern Europe;and population growth and drinking water exert a positive effect on environmental sustainability in both the short-and long-run. The results of Dumitrescu Hurlin causality test indicate that environmental sustainability is unidirectionally affected by economic growth. Based on these outcomes, we suggest the following policies:(1) the EU and OECD should implement member-targeted policies on economic growth and fossil-fuel use towards regulating industrial pollution, water use, and population control;and(2) the EU and OECD member countries should invest in environmental technologies through green research and development(R&D) to transform their dirty industrial processes and ensure productive energy use.

Nested Group Testing Procedure

We investigated the false-negative,true-negative,false-positive,and true-positive predictive values from a general group testing procedure for a heterogeneous population.We show that its false(true)-negative predictive value of a specimen is larger(smaller),and the false(true)-positive predictive value is smaller(larger)than that from individual testing procedure,where the former is in aversion.Then we propose a nested group testing procedure,and show that it can keep the sterling characteristics and also improve the false-negative predictive values for a specimen,not larger than that from individual testing.These characteristics are studied from both theoretical and numerical points of view.The nested group testing procedure is better than individual testing on both false-positive and false-negative predictive values,while retains the efficiency as a basic characteristic of a group testing procedure.Applications to Dorfman’s,Halving and Sterrett procedures are discussed.Results from extensive simulation studies and an application to malaria infection in microscopy-negative Malawian women exemplify the findings.

ANALYSIS ON EPITOPES OF IGM WITH MONOCLONAL ANTI-ISOTYPIC AND ANTI-IDIOTYPIC ANTIBODIES AGAINST IgM FROM B-CLL

A double antibodies additivity ELISA test was employed to identify the epltopes which can be recognized by monoclonal antibodies (McAbs) against IgM from B chronic lymphocyte leukemia (B-CLL). The computer grouping programme analysis showed that 4 and- isotypic MaAbs could be divided into two groups and 10 anti- idiotype McAbs could be divided into four groups. The result was consistent with that of the indirect sandwich ELISA and inhibition ELISA test. It suggested that there were at least 6 distinct IgM epitopes which can react specifically with 14 McAbs. Our study indicated that the combination of the additivity ELISA test and the computer grouping programme analysis is of help in studying the relationship of the structure and function of antigen.

rapid strep testing in children with recently treated streptococcal pharyngitis

Importance:The use of the rapid antigen-detection test(RADT)has become the standard of care in the early diagnosis of group A beta-hemolytic Streptococcus(GAS)pharyngitis.Concern has been expressed over increased false positives when the child had been treated recently for GAS pharyngitis,resulting in over use of antibiotics.Objective:To determine if the false positive rate for RADT is increased in children recently treated for GAS pharyngitis.Methods:We conducted a prospective study to evaluate 300 children from a private practice with acute pharyngitis who were treated for GAS pharyngitis within the preceding 28 days(study group)compared to 306 children of comparable age who had not been previously treated(control group).RADT and throat culture were performed on all children presenting with signs and symptoms of acute pharyngitis.The false positive and false negative rates were determined and compared in both groups.results:The false positive rate of 11.5%(23/200)in the study group was significantly higher than the false positive rate of 0 in the control group.False positives were more likely to occur in younger children.Interpretation:These data would indicate that while RADT is reliable in most children,it can lead to over treatment in children who have been recently treated for GAS.In children treated in the preceding 28 days for GAS pharyngitis,the presence of infection should be determined with a throat culture only.Treatment based on a positive RADT should be reserved for children not recently treated for GAS pharyngitis.

Modelling the utility of group testing for public health surveillance

In epidemic or pandemic situations,resources for testing the infection status of individuals may be scarce.Although group testing can help to significantly increase testing capabilities,the(repeated)testing of entire populations can exceed the resources of any country.We thus propose an extension of the theory of group testing that takes into account the fact that definitely specifying the infection status of each individual is impossible.Our theory builds on assigning to each individual an infection status(healthy/infected),as well as an associated cost function for erroneous assignments.This cost function is versatile,e.g.,it could take into account that false negative assignments are worse than false positive assignments and that false assignments in critical areas,such as health care workers,are more severe than in the general population.Based on this model,we study the optimal use of a limited number of tests to minimize the expected cost.More specifically,we utilize information-theoretic methods to give a lower bound on the expected cost and describe simple strategies that can significantly reduce the expected cost over currently known strategies.A detailed example is provided to illustrate our theory.

A Group Testing Problem on a n- Item Set Containing Two Defective Ones

In this paper we study a group testing model ФX, Y,, XY. In other words, we consider a n-item set containing exactly two defective ones. The purpose of this paper is to find out the two defective items with a worst-case minimum number of tests, each of which will indicates whether the subset being tested contains all good （normal） items or not and in the latter case, it is not sure that the tested subset is of one defective （bad） item or two. Based on the M-sharp algorithm obtained in the previous paper and some combinatorial skills, we derive an almost optimal algorithm for the so called n-problem.

A New Algorithm for a Group Testing Problem on a n-Coin Set Containing One Defective One

In this paper we study further on a group testing problem of identifying the defective from a n-coin set containing one defective coin with a balance without weight. The defective coin is not of the same weight as each of the normal ones. We derive a new testing algorithm which can tell out the defective from the n-coin set with the worst-case minimum number of tests.

GROUP CONTINGENCY TEST FOR TWO OR SEVERAL INDEPENDENT SAMPLES

This paper proposes a new and distribution-free test called ＂Group Contingency＂ test （GC, for short） for testing two or several independent samples. Compared with traditional nonparametric tests, GC test tends to explore more information based on samples, and it＇s location-, scale-, and shapesensitive. The authors conduct some simulation studies comparing GC test with Wilcoxon rank sum test （W）, Kolmogorov-Smirnov test （KS） and Wald-Wolfowitz runs test （WW） for two sample case, and with Kruskal-Wallis （KW） for testing several samples. Simulation results reveal that GC test usually outperforms other methods.

Design and verification of on-chip debug circuit based on JTAG

An on-chip debug circuit based on Joint Test Action Group(JTAG)interface for L-digital signal processor(L-DSP)is proposed,which has debug functions such as storage resource access,central processing unit(CPU)pipeline control,hardware breakpoint/observation point,and parameter statistics.Compared with traditional debug mode,the proposed debug circuit completes direct transmission of data between peripherals and memory by adding data test-direct memory access(DT-DMA)module,which improves debug efficiency greatly.The proposed circuit was designed in a 0.18μm complementary metal-oxide-semiconductor(CMOS)process with an area of 167234.76μm~2 and a power consumption of 8.89 mW.And the proposed debug circuit and L-DSP were verified under a field programmable gate array(FPGA).Experimental results show that the proposed circuit has complete debug functions and the rate of DT-DMA for transferring debug data is three times faster than the CPU.