There is a need for incidence assays that accurately estimate HIV incidence based on cross-sectional specimens. Viral diversity-based assays have shown promises but are not particularly accurate. We hypothesize that certain viral genetic regions are more predictive of recent infection than others and aim to improve assay accuracy by using classification algorithms that focus on highly informative regions (HIRs).
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