The most recent South African National HIV Prevalence, Incidence and Behaviour Survey conducted in 2012 incorporated new tools for generating greater information about the current state of the HIV epidemic from the national household survey. The results from the direct HIV incidence estimates from the multi-assay recent infection algorithm from the survey and estimates from more conventional modelling approaches to estimating incidence were found to generate fairly similar results. The 2012 household survey data also provided an opportunity to externally validate model projections over time.
SACEMA has been very active in refining the use of laboratory tests for identifying recent infection (in particular of HIV) for the purpose of estimating disease incidence. We have just published a conceptual analysis of the notion of ‘test optimisation’ in a surveillance context, which should help clarify some persistent confusion that has hindered discourse in this area for years.
Biomarker-based incidence estimation can be consistently adapted to a general context without the strong assumptions of previous work.
There are a number of approaches for estimating HIV incidence, with varying tractability, complexity and limitations. In recent years, there has been considerable interest in estimating HIV incidence from single cross-sectional surveys testing for ‘recent infection’ through laboratory-measured host or viral biomarkers. In a survey, the sizes of the HIV-negative, ‘recently infected’ and ‘non-recently infected’ populations can be measured, and incidence estimated using knowledge of the dynamics of the ‘recent infection’ biomarker. However, two key obstacles to cross-sectional biomarker-based incidence surveillance remain: the lack of standardisation of terminology and methodology, and poor characteristics, and characterisation, of currently available tests.