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Related Experiment Videos

Combining pooling and alternative algorithms in seroprevalence studies

J M Raboud1, C Sherlock, M T Schechter

  • 1Department of Health Care and Epidemiology, University of British Columbia, Canada.

Journal of Clinical Microbiology
|September 1, 1993
PubMed
Summary

Pooling sera for screening and using enzyme immunoassay (EIA) for human immunodeficiency virus (HIV) testing significantly reduces costs without compromising accuracy. This cost-effective HIV screening strategy is particularly beneficial in high-prevalence settings.

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Area of Science:

  • Medical Diagnostics
  • Public Health
  • Epidemiology

Background:

  • Accurate and cost-effective human immunodeficiency virus (HIV) testing is crucial for public health surveillance and clinical management.
  • Various algorithms exist for determining HIV seropositivity, each with different cost and sensitivity profiles.

Purpose of the Study:

  • To compare the costs and sensitivities of six algorithms for determining HIV seropositivity.
  • To evaluate the impact of sample pooling during screening and enzyme immunoassay (EIA) as a confirmatory test on cost-effectiveness and reliability.

Main Methods:

  • Utilized data from two seroprevalence studies and one comparative study of confirmatory algorithms.
  • Evaluated strategies including CBC Recombigen HIV EIA and immunoblotting with radioimmunoprecipitation assay for indeterminate results.

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  • Assessed methods with and without pooling of samples during screening.

    • Main Results:

    • The least expensive algorithm involved pooling sera during screening and using EIA for confirmation.
    • Cost savings were greater with higher HIV prevalence, though savings from pooling diminished as prevalence increased.
    • EIA demonstrated high sensitivity (0.9992) and specificity (0.9977) compared to more complex assays.

    Conclusions:

    • Implementing sample pooling during screening and using EIA as the confirmatory test offers considerable cost savings.
    • These strategies do not negatively impact the statistical reliability of HIV seropositivity estimates.
    • The chosen algorithm provides a cost-effective approach to HIV testing, especially in high-prevalence populations.