Improving Biomarker Based HIV Incidence Estimation in the Treatment Era

2022/03/31 by Ian E. Fellows, Fellows, Ian E., Wolfgang Hladik +9
Immunology and Microbiology · Mathematics · Medicine · #Applications (stat.AP) #FOS: Computer and information sciences #HIV Research and Treatment #HIV/AIDS Research and Interventions #Methodology (stat.ME) #Statistical Methods and Bayesian Inference

paper · pdf · doi:10.48550/arxiv.2204.00048

openalex publication_date 2022/03/31 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Estimating HIV-1 incidence using biomarker assays in cross-sectional surveys is important for understanding the HIV pandemic. However, the utility of these estimates has been limited by uncertainty about what input parameters to use for False Recency Rate (FRR) and Mean Duration of Recent Infection (MDRI) after applying recent infection testing algorithm (RITA). This article shows how testing and diagnosis in a population reduce both FRR and MDRI compared to a treatment-naive population. Using self-reported testing history, a new method is proposed for calculating appropriate context-specific estimates of FRR and MDRI. The result of this is a new formula for incidence that depends only on reference FRR and MDRI parameters derived in an undiagnosed, treatment-naive, non-elite controller, non-AIDS-progressed population.

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