Development of a multiassay algorithm (MAA) to identify recent HIV infection in newly diagnosed individuals in Indonesia

iScience. 2023 Sep 21;26(10):107986. doi: 10.1016/j.isci.2023.107986. eCollection 2023 Oct 20.

Abstract

Ongoing HIV transmission is a public health priority in Indonesia. We developed a new multiassay algorithm (MAA) to identify recent HIV infection. The MAA is a sequential decision tree based on multiple biomarkers, starting with CD4+ T cells >200/μL, followed by plasma viral load (pVL) > 1,000 copies/ml, avidity index (AI) < 0 · 7, and pol ambiguity <0 · 47%. Plasma from 140 HIV-infected adults from 19 hospitals across Indonesia (January 2018 - June 2020) was studied, consisting of a training set (N = 60) of longstanding infection (>12-month) and a test set (N = 80) of newly diagnosed (≤1-month) antiretroviral (ARV) drug naive individuals. Ten of eighty (12 · 5%) newly diagnosed individuals were classified as recent infections. Drug resistance mutations (DRMs) against reverse transcriptase inhibitors were identified in two individuals: one infected with HIV subtype C (K219Q, V179T) and the other with CRF01_AE (V179D). Ongoing HIV transmission, including infections with DRMs, is substantial in Indonesia.

Keywords: Computer science; Health sciences; Medicine.