Literature DB >> 2124494

Successful use of pooled sera to determine HIV-1 seroprevalence in Zaire with development of cost-efficiency models.

F Behets1, S Bertozzi, M Kasali, M Kashamuka, L Atikala, C Brown, R W Ryder, T C Quinn.   

Abstract

To determine the accuracy and cost efficiency of pooling sera prior to HIV-1 testing, sera from 8,000 Kinshasa factory workers and their spouses were screened individually (2.44% seropositive) and in 800 pools of 10 sera each. There were no false-negative or false-positive pools, resulting in a calculated seroprevalence estimate of 2.42%. Further testing of all sera in positive pools can identify HIV-positive individuals. These applications were modeled to compare the cost-efficiency of pooling with individual testing under different conditions. The results suggest that pooling provides an alternative test format for use in both developing and industrialized countries when the seroprevalence and/or the marginal cost of obtaining a sample are sufficiently low. For our cohort, testing only the pools for seroprevalence estimation resulted in a 78% cost saving compared with individual testing; pooling with subsequent identification of individual seropositives represented a 56% cost reduction.

Entities:  

Keywords:  Africa; Africa South Of The Sahara; Cost Benefit Analysis; Developing Countries; Diseases; Evaluation; Examinations And Diagnoses; French Speaking Africa; Hiv Infections; Laboratory Examinations And Diagnoses; Measurement; Middle Africa; Models, Theoretical; Prevalence; Quantitative Evaluation; Research Methodology; Viral Diseases; Zaire

Mesh:

Year:  1990        PMID: 2124494     DOI: 10.1097/00002030-199008000-00004

Source DB:  PubMed          Journal:  AIDS        ISSN: 0269-9370            Impact factor:   4.177


  13 in total

Review 1.  AIDS policy modeling for the 21st century: an overview of key issues.

Authors:  M S Rauner; M L Brandeau
Journal:  Health Care Manag Sci       Date:  2001-09

2.  Blood screening by nucleic acid amplification technology: current issues, future challenges.

Authors:  J L Gallarda; E Dragon
Journal:  Mol Diagn       Date:  2000-03

3.  Optimal pooled testing.

Authors:  Brett A Saraniti
Journal:  Health Care Manag Sci       Date:  2006-05

4.  Optimizing screening for acute human immunodeficiency virus infection with pooled nucleic acid amplification tests.

Authors:  Daniel J Westreich; Michael G Hudgens; Susan A Fiscus; Christopher D Pilcher
Journal:  J Clin Microbiol       Date:  2008-03-19       Impact factor: 5.948

5.  Pooling urine samples for ligase chain reaction screening for genital Chlamydia trachomatis infection in asymptomatic women.

Authors:  K A Kacena; S B Quinn; M R Howell; G E Madico; T C Quinn; C A Gaydos
Journal:  J Clin Microbiol       Date:  1998-02       Impact factor: 5.948

6.  Prevalence estimation subject to misclassification: the mis-substitution bias and some remedies.

Authors:  Zhiwei Zhang; Chunling Liu; Sungduk Kim; Aiyi Liu
Journal:  Stat Med       Date:  2014-07-18       Impact factor: 2.373

7.  Pooled nucleic acid testing to identify antiretroviral treatment failure during HIV infection.

Authors:  Susanne May; Anthony Gamst; Richard Haubrich; Constance Benson; Davey M Smith
Journal:  J Acquir Immune Defic Syndr       Date:  2010-02       Impact factor: 3.731

8.  Combining pooling and alternative algorithms in seroprevalence studies.

Authors:  J M Raboud; C Sherlock; M T Schechter; D G Lepine; M V O'Shaughnessy
Journal:  J Clin Microbiol       Date:  1993-09       Impact factor: 5.948

9.  Use of pooled residual laboratory sera to assess human immunodeficiency virus prevalence among patients in Italy. The Italian Study Group on Occupational Risk of HIV infection.

Authors:  V Puro; E Lo Presti; R Trombetta; A Benedetto; G P Leonetti; A Spano; G Ippolito
Journal:  Eur J Clin Microbiol Infect Dis       Date:  1994-03       Impact factor: 3.267

10.  Prediction-driven pooled testing methods: Application to HIV treatment monitoring in Rakai, Uganda.

Authors:  Adam Brand; Susanne May; James P Hughes; Gertrude Nakigozi; Steven J Reynolds; Erin E Gabriel
Journal:  Stat Med       Date:  2021-05-28       Impact factor: 2.497

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