Extending Bayesian back-calculation to estimate age and time specific HIV incidence

Area of Science:

• Epidemiology
• Biostatistics
• Public Health

Background:

• CD4-based multi-state back-calculation methods are crucial for HIV epidemic surveillance.
• Existing methods estimate HIV incidence and diagnosis rates but often lack age-specificity.
• Understanding age-specific rates is vital for effective public health interventions.

Purpose of the Study:

• To extend existing back-calculation methods to estimate age- and time-specific HIV incidence and diagnosis rates.
• To enable the identification of specific age-groups at higher risk of HIV infection.
• To provide a framework for deriving other key epidemiological quantities.

Main Methods:

• Development of CD4-based multi-state back-calculation models incorporating age-specific parameters.
• Utilizing bivariate splines for non-parametric modeling of latent age- and time-specific incidence.
• Simulation studies to assess the performance of different spline approaches.
• Application of the method to real-world HIV surveillance data.

Main Results:

• Successful joint estimation of age- and time-specific HIV incidence and diagnosis rates.
• Demonstration of the method's ability to identify high-risk age groups.
• Validation of the approach through simulation studies.
• Illustration on data from the HIV epidemic among men who have sex with men in England and Wales.

Conclusions:

• The developed age-specific back-calculation method enhances HIV epidemic monitoring.
• This approach provides crucial insights for targeted public health strategies and resource allocation.
• The method offers a robust tool for epidemiological analysis of HIV surveillance data.