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Published on: December 7, 2021
Longitudinal phylogenetic surveillance identifies distinct patterns of cluster dynamics
Manon Ragonnet-Cronin1, Marianna Ofner-Agostini, Harriet Merks
1National HIV and Retrovirology Laboratories, Public Health Agency of Canada, Ottawa, Canada.
Journal of Acquired Immune Deficiency Syndromes (1999)
|July 13, 2010
Summary
Newly diagnosed HIV infections, particularly those from non-clustered transmissions, drive epidemic growth. Identifying recent infections using molecular epidemiology can predict future HIV cluster expansion.
Area of Science:
- Molecular epidemiology
- Phylogenetics
- HIV drug resistance
Background:
- Understanding HIV transmission dynamics is crucial for effective public health interventions.
- Longitudinal population-level drug resistance genotype data can provide insights into transmission patterns.
Purpose of the Study:
- To resolve phylogenetic relationships predicting HIV cluster growth using longitudinal drug resistance data.
- To identify factors associated with HIV cluster expansion in British Columbia.
Main Methods:
- Analysis of 971 pol gene sequences from newly diagnosed, drug-naive HIV-positive individuals in British Columbia (2002-2005).
- Phylogenetic inference using Neighbour-Joining analysis to identify clusters.
- BED testing to determine recent infections (<156 days).
Main Results:
- 52 clusters identified among 136 sequences from 2002 infections.
- Aboriginal ethnicity and intravenous drug use correlated with cluster membership.
- Large cluster growth was associated with initially non-clustered and recent infections.
Conclusions:
- Recently infected individuals, especially those from non-clustered infections, are key drivers of HIV epidemic growth.
- Molecular epidemiology tools can predict HIV transmission trends.
- Focusing on recent infections may aid in controlling the HIV epidemic.
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