One assay, the BED [ 9], was used in a number of surveys but was found to have a high false recent rate that could lead to erroneous estimates of incidence [ 10].
An ITER scale prototype fast delivery, self-assay storage bed has been developed; this component is designed to maximize the ratio of delivery rate to stored inventory and is undergoing testing.
The most widely used of these assays is the BED capture enzyme immunosorbent assay ('BED test'), in which the optical density varies according to proportion of IgG that is anti-HIV antibody [9].
A mean duration of recency of 155 days for the BED assay was applied to estimate annualized assay-derived incidence rates [42].
These specimens should, in theory, be classified as long-term infections in the BED assay, but approximately 5% of these specimens register false-recent BED results [18], [19].
In particular, the BED assay has been developed for this purpose.
The BED assay was applied to specimens from three cohort studies in Thailand, where CRF01_AE and subtype B' account for the majority of HIV-1 infections.
This analysis is most relevant to the context in which the BED assay is currently widely used: cross-sectional populations with a predominance of longer-term infected people.
Median baseline CD4 cell count did not differ between participants falsely and correctly classified by the BED assay (447 vs. 461 cells/µl, P = 0.77).
Incidence estimates were adjusted to account for HIV positive specimens with missing BED assay test results, and 95% CIs around the estimates were calculated.
To estimate the window period for the combined BED/Ax-AI algorithm, we took the value of the earlier of the two assay threshold crossings (BED or Ax-AI) for each individual, and then averaged across individuals.
