Inferring HIV transmission networks from time-resolved viral phylogenies for epidemiological modelling

Lead Research Organisation: University of Edinburgh
Department Name: Sch of Biological Sciences

Abstract

The HIV epidemic in the UK is growing, both among heterosexuals, which is a relatively new epidemic, and again among gay men, where new infections had previously stabilised. This proposal is intended to develop methods for finding out in what settings most new infections occur. We will use anonymised data on viral sequences to discover whether HIV transmission occurs steadily over time, or whether it occurs in bursts, through networks. Early studies suggest networks are important, so we need to be able to identify the key settings. We will do this by using a computer program which describes ( models ) the epidemic as far as we understand it, including settings such as bars, gyms and the internet, where people can meet sexual partners. The model will allow information from the viral sequence data to help us to predict which will be the most effective links to target to reduce new infections.

Technical Summary

Much understanding of the epidemiology of sexually transmitted infections has come from analysis of sexual network models. These can either describe contacts between individuals or affiliations, where individuals are linked to venues rather than to each other. For genetically diverse pathogens, molecular typing can also inform epidemiological models. For HIV in particular, the high rate of evolution permits time-resolved viral phylogenies to be reconstructed in which transmission clusters can be identified and their size estimated. We propose to develop a statistically rigorous methodology for using time-resolved viral phylogenies to obtain an independent estimate of the transmission network within an infected community. In parallel we will develop models of the sexual mixing of the population through use of affiliation networks. Integrating the two will allow identification of the key elements of the affiliation network that potentiate transmission, as revealed by the structure of the viral transmission network. Development, and subsequent application of this methodology will allow critical features of the sexual contact structure for viral transmission to be identified and for the first time will provide a model with which intervention measures can be tested in the setting of a specific population.

Publications

10 25 50
 
Description Infection Response through Virus Genomics
Amount £5,972,195 (GBP)
Funding ID T5-344 
Organisation Health Innovation Challenge Fund 
Sector Charity/Non Profit
Country United Kingdom
Start 10/2013 
End 09/2016
 
Description Phylogenetic Networks to Address Transmission of HIV
Amount $5,909,061 (USD)
Funding ID OPP1084362 
Organisation Bill and Melinda Gates Foundation 
Sector Charity/Non Profit
Country United States
Start 11/2013 
End 10/2016
 
Title HIV Phylodynamics 
Description Applications of relaxed clock phylogenetics for inference of HIV transmission networks 
Type Of Material Data analysis technique 
Provided To Others? No  
Impact Publications from other groups 
 
Description UKHIVRDB 
Organisation Medical Research Council (MRC)
Department MRC Clinical Trials Unit
Country United Kingdom 
Sector Public 
PI Contribution Analysis of data obtained and collated by the UKHIV Drug Resistance Database
Collaborator Contribution Data
Impact 19956739 19779560 18351795
 
Description Interview (BBC) 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Primary Audience Public/other audiences
Results and Impact Interview on Radio 4 "The World Tonight"

Not known of
Year(s) Of Engagement Activity 2008
 
Description Publication of Research results 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? No
Primary Audience Public/other audiences
Results and Impact Publication of press release in the Daily Star. http://www.dailystar.co.uk/latestnews/view/32513/HIV-spread-in-mini-epidemics-/

Not known of
Year(s) Of Engagement Activity 2008