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Retrovirus Life Cycles

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Updated: Aug 13, 2025

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Published on: September 26, 2011

Insights into HIV-1 Transmission Dynamics Using Routinely Collected Data in the Mid-Atlantic United States.

Seble G Kassaye¹, Zehava Grossman^2,3, Priyanka Vengurlekar¹

¹Department of Medicine, Georgetown University, Washington, DC 20057, USA.

|January 21, 2023

Summary

This summary is machine-generated.

Molecular epidemiology of HIV sequences and viral load data reveals transmission clusters. Combining phylogenetic analysis with viral load data enhances HIV contact tracing and prevention efforts.

Keywords:

HIV drug resistance clinical and phylogenetic data combined contact tracing tool molecular epidemiology phylogenetic analysis regional transmission dynamics transmission networks

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Last Updated: Aug 13, 2025

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Amplifying and Quantifying HIV-1 RNA in HIV Infected Individuals with Viral Loads Below the Limit of Detection by Standard Clinical Assays

Published on: September 26, 2011

Genotypic Inference of HIV-1 Tropism Using Population-based Sequencing of V3

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Published on: December 27, 2010

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Prediction of HIV-1 Coreceptor Usage Tropism by Sequence Analysis using a Genotypic Approach

Published on: December 1, 2011

Area of Science:

Molecular epidemiology
Virology
Public Health

Background:

Molecular epidemiology offers insights into HIV transmission dynamics.
Routine clinical data can be leveraged for epidemiological studies.
Understanding transmission patterns is crucial for public health interventions.

Purpose of the Study:

To assess the utility of analyzing HIV sequences and viral load (VL) data from routine clinical care for characterizing HIV transmission.
To identify HIV transmission clusters using phylogenetic methods.
To evaluate the combined utility of phylogenetic inference and VL data for enhanced contact tracing.

Main Methods:

HIV-1 pol sequences were analyzed using phylogenetic methods (ClustalW, REGA, IQTree, ClusterPicker, BEAST).
Transmission clusters were defined by genetic distance (≤3%) and bootstrap support (≥90%).
Early HIV infection was indicated by nucleotide ambiguity (≤0.5%).
Descriptive statistics and comparative tests (chi-square, t-test) were used.

Main Results:

Analysis of 2775 adults (2014-2015) revealed 193 HIV transmission clusters involving 456 individuals.
Cluster members were more likely to be male, younger, and have early-stage HIV infection compared to non-cluster individuals.
A significant proportion of clusters (22.3%) spanned multiple jurisdictions.
Individuals in larger clusters (≥4) and those not in clusters showed higher viral loads compared to individuals in smaller clusters (2-3).

Conclusions:

HIV sequence data from clinical care provide valuable insights into regional transmission dynamics.
Integrating HIV-1 VL data with phylogenetic analysis enhances contact tracing effectiveness.
Trans-jurisdictional collaboration is essential for optimizing HIV prevention and control strategies to end the epidemic.