Edinburgh Research Explorer

Transmission Network Parameters Estimated From HIV Sequences for a Nationwide Epidemic

Research output: Contribution to journalArticle

Related Edinburgh Organisations

Open Access permissions



  • Download as Adobe PDF

    Rights statement: This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/ 3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

    Final published version, 398 KB, PDF document

Original languageEnglish
Pages (from-to)1463-1469
Number of pages7
JournalThe Journal of Infectious Diseases
Issue number9
Publication statusPublished - Nov 2011


Many studies of sexual behavior have shown that individuals vary greatly in their number of sexual partners over time, but it has proved difficult to obtain parameter estimates relating to the dynamics of human immunodeficiency virus (HIV) transmission except in small-scale contact tracing studies. Recent developments in molecular phylodynamics have provided new routes to obtain these parameter estimates, and current clinical practice provides suitable data for entire infected populations.

A phylodynamic analysis was performed on partial pol gene sequences obtained for routine clinical care from 14 560 individuals, representing approximately 60% of the HIV-positive men who have sex with men (MSM) under care in the United Kingdom.

Among individuals linked to others in the data set, 29% are linked to only 1 individual, 41% are linked to 2–10 individuals, and 29% are linked to ≥10 individuals. The right-skewed degree distribution can be approximated by a power law, but the data are best fitted by a Waring distribution for all time depths. For time depths of 5–7 years, the distribution parameter ρ lies within the range that indicates infinite variance.

The transmission network among UK MSM is characterized by preferential association such that a randomly distributed intervention would not be expected to stop the epidemic.

Download statistics

No data available

ID: 1866017