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

Penulis: Wulan, Wahyu Nawang; Yunihastuti, Evy; Arlinda, Dona; Merati, Tuti Parwati; Wisaksana, Rudi
Informasi
JurnaliScience, Iscience
PenerbitElsevier Inc., Iscience 26 (10), 2023
Volume & EdisiVol. 26,Edisi 10
Halaman -
Tahun Publikasi2023
ISSN25890042
eISSN2589-0042
Jenis SumberScopus
Sitasi
Scopus: 3
Google Scholar: 3
PubMed: 3
Abstrak
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. © 2023
Dokumen & Tautan

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