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Group testing regression model estimation when case identification is a goal
Boan Zhang1, Christopher R Bilder, Joshua M Tebbs
1Department of Statistics, University of Nebraska-Lincoln, Lincoln, NE 68583, USA.
Biometrical Journal. Biometrische Zeitschrift
|February 13, 2013
Summary
Group testing effectively identifies individuals and estimates disease probability, especially with imperfect tests. Incorporating retest data significantly improves screening efficiency and reduces costs.
Area of Science:
- Biostatistics
- Epidemiology
- Public Health
Background:
- Group testing is a cost-effective strategy for screening large populations with low prevalence of diseases.
- Traditional group testing aims to identify positive individuals and estimate disease prevalence.
- Retesting, or performing additional tests, provides extra information but is often not fully utilized in statistical models.
Purpose of the Study:
- To investigate the use of regression models to incorporate retest information for improved estimation of positivity probability.
- To evaluate the efficiency of different group testing protocols, including those with retests.
- To assess the impact of imperfect diagnostic tests on group testing efficiency.
Main Methods:
- Development of regression models to integrate data from initial group tests and subsequent retests.
- Simulation studies to compare the efficiency of proposed methods against traditional approaches.
- Retrospective analysis of chlamydia screening data from the Infertility Prevention Project.
Main Results:
- Incorporating retest information into regression models leads to significant gains in estimation efficiency.
- Certain group testing protocols, especially with imperfect diagnostic tests, can be more efficient than individual testing.
- The proposed methods demonstrate potential for substantial cost savings in real-world screening programs.
Conclusions:
- Regression models effectively leverage retest data for more precise estimation of disease probability in group testing scenarios.
- Optimized group testing protocols can enhance screening efficiency and reduce costs, even with imperfect diagnostic accuracy.
- The findings support the adoption of advanced group testing strategies for public health screening programs.
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