Application of laboratory methods for estimation of HIV-1 incidence.

ABSTRACT

Estimating HIV-1 incidence (rate of new HIV-1 infections) in various populations is important to understand the current status of transmission dynamics, identify high-risk populations, monitor prevention efforts and target resources on programmes that are most effective in reducing transmissions. Recent developments in our ability to detect and distinguish recent and longterm HIV-1 infections using laboratory tests have made the measurement of HIV-1 incidence realistic and practical. These approaches most commonly rely on the properties of early HIV-1 antibodies after seroconversion as characterized by their levels, antibody avidity/affinity or antibody classes/subclasses or epitope specificity. The sensitive/less-sensitive testing strategy provided simple laboratory tools to detect recent seroconversion in a cross-sectional population. These assays are based on differences in antibody titres in recent versus long-term infections and have been used for sometime for estimating population incidence. However, recent work demonstrated limitations of this approach which included subtype-dependent performance and significant variability of "window periods", precluding its use in many areas of the world. Recently an IgG-Capture BED-EIA was developed in our laboratory which detects the increasing HIV-IgG as proportion of total IgG following seroconversion and can be used to detect recent seroconversion. The format of the assay, which includes a multi-subtype derived antigen, allows high consistency and similar "window periods" in different subtypes. This assay is now available commercially and is made specifically for population estimates of HIV-1 incidence. Due to the presence of divergent HIV-1 subtypes and the rapidly expanding HIV epidemic, it is important that the method selected is robust, performs similarly in different subtypes and is widely applicable for meaningful incidence estimates, trend analysis and comparison between populations.