Pooled testing for HIV prevalence estimation: exploiting the dilution effect

Area of Science:

• Epidemiology
• Biostatistics
• Infectious Disease Surveillance

Background:

• Pooled testing, or group testing, is an efficient strategy for disease prevalence estimation.
• Current pooled testing methods for HIV often rely on binary (positive/negative) test results, potentially losing valuable information.
• HIV test outcomes are inherently continuous, and simplifying them to dichotomous results can reduce accuracy.

Purpose of the Study:

• To develop a novel parametric pooled testing procedure that utilizes continuous HIV test outcomes.
• To improve the accuracy and cost-efficiency of HIV prevalence estimation compared to existing methods.
• To address the information loss associated with dichotomizing continuous HIV test results.

Main Methods:

• Development of a parametric procedure incorporating a hierarchical pooling model.
• Estimation of HIV prevalence using a likelihood equation.
• Solution of the likelihood equation via an iterative algorithm.
• Validation through a simulation study.

Main Results:

• The proposed procedure accurately estimates HIV prevalence.
• The method achieves high accuracy at a significantly reduced cost compared to existing procedures.
• Utilizing continuous outcomes preserves information lost in dichotomous approaches.

Conclusions:

• The developed parametric pooled testing procedure offers a more accurate and cost-effective approach to HIV prevalence estimation.
• Leveraging continuous HIV test results in pooled testing enhances the precision of prevalence estimates.
• This method represents a significant advancement in HIV surveillance strategies.