However, the utility of the cross-sectional approach to HIV incidence determination has been hampered because currently available laboratory assays misclassify some chronically-infected persons as recently infected.
This sub-study was focused on the impact of pregnancy on the performance of the BED and avidity assays for cross-sectional HIV incidence determination.
While pregnancy does not generally influence the performance of serologic assays, the impact of pregnancy on the performance of serologic assays for HIV incidence determination has not been investigated.
Effective application of these assays to cross-sectional HIV incidence determination, either alone or in multi-assay algorithms, requires knowledge of the clinical and demographic factors associated with misclassification [12].
It should be noted that aside from assay misclassification, another critically important issue with cross-sectional HIV incidence determination is the whether the samples are representative of the population of interest.
However, studies suggest that these assays may be useful for HIV incidence determination when used in combination along with non-serologic biomarkers, such as HIV viral load or CD4 cell count [6].
Further studies are needed to define the factors that lead to misclassification with these and other serologic assays used for HIV incidence determination and to test whether findings from our study can be generalized to other populations, including those with different prevalent HIV subtypes and strains.
Some studies suggest that changes in HIV dynamics that occur during pregnancy may differ among women of different races [15]; therefore, a woman's race could theoretically affect the level or quality of anti-HIV antibodies and the performance of serologic assays for HIV incidence determination during pregnancy.
Further research is also needed to identify and validate robust, accurate methods for cross-sectional HIV incidence determination that could easily be incorporated into HIV surveillance programs.
In high TB incidence settings, determination of distinct transmission patterns is often indefinable, but may be greatly enhanced by the use of both molecular and conventional epidemiological tools.
