Accuracy of incidence estimates obtained using the BED-CEIA alone, the avidity assay alone, a two-assay multi assay algorithm (MAA), and two four-assay MAAs in three epidemic scenarios*.

*MAA: multi-assay algorithm; BED-CEIA: BED capture immunoassay (results expressed as normalized optical density units); AI: avidity index (results expressed as a percentage); CD4: CD4 cell count (results expressed as cells/mm3); VL: viral load (results expressed as HIV RNA copies/mL); yrs: years; Rel. bias: relative bias; RMSE: root mean square error. The lower two rows show results for MAAs (see text); for these MAAs, individuals are classified as MAA positive if they have results for all for assays that are below/above the cutoffs indicated.The relative bias (in % of true incidence over 12 months) and precision of incidence estimates (expressed as the root mean square error for log incidence, RMSE) are shown for a 6-month cohort follow-up estimator and four cross-sectional testing algorithms in three different epidemic scenarios. The ranks show the relative ranking of each algorithm among the 403 evaluated algorithms according to precision of incidence estimation (RMSE).