A new method for estimating HIV incidence from a single cross-sectional survey

Area of Science:

• Epidemiology
• Biostatistics

Background:

• Estimating HIV incidence from cross-sectional data is methodologically challenging.
• Accurate incidence estimation is crucial for understanding and controlling the HIV epidemic.

Purpose of the Study:

• To develop a novel incidence estimator using commonly collected HIV survey data.
• To measure the undiagnosed population and time spent undiagnosed to infer incidence and transmission rates.

Main Methods:

• Developed a new estimator utilizing HIV status and testing history.
• The estimator can be adjusted with ART biomarker and viral load data to correct for self-reporting biases.
• Evaluated the estimator's performance in two large-scale Kenyan HIV surveys.

Main Results:

• The new estimator's point estimates were consistent with assay-derived estimates.
• The estimator achieved significantly smaller standard errors compared to existing methods.
• Demonstrated the estimator's applicability and accuracy in real-world survey data.

Conclusions:

• The developed estimator offers a cost-effective and reliable method for estimating HIV incidence.
• This tool can enhance the understanding of HIV transmission dynamics and inform public health strategies.
• The estimator's ability to incorporate biomarker data improves accuracy in diverse settings.