Despite the range of resources directed at understanding the HIV pandemic over the past 25 years, surprisingly little is known about how HIV infection spreads through populations. Unlike some other infectious diseases, acute infection with HIV is difficult to identify. HIV disease most often manifests years after the transmission event. Together with the special challenges involved in determining exposures related to sexual behavior or drug use, all of these factors have made it difficult to apply the tools of traditional epidemiologic investigation. Recent antibody testing strategies to identify incident HIV for surveillance programs have met with limited success . Key questions that remain unanswered by empirical data include the role of acute infections in sustaining the current pandemic, and the effects of antiretroviral treatment programs on transmission of drug-resistant and drug-susceptible strains of HIV. Without really understanding how HIV spreads, it is difficult to optimize prevention or control strategies.
As effective anti-HIV therapies emerged over the past decade, clinical care and surveillance programs have increasingly emphasized the importance of testing for resistance to antiretroviral drugs. This most commonly involves sequencing of viral genes for resistance mutations. The rapid expansion of this HIV genotyping has predictably resulted in creation of vast databases that now contain viral sequence information. The new study by Andrew Leigh Brown and colleagues in this issue of PLoS Medicine  shows that modern analytic tools may yield important new insights into HIV transmission dynamics from the information routinely collected in such sequence databases.
Linked Research Article
This Perspective discusses the following new study published in PLoS Medicine:
Lewis F, Hughes GJ, Rambaut A, Pozniak A, Leigh Brown AJ (2008) Episodic sexual transmission of HIV revealed by molecular phylodynamics. PLoS Med 5(3): e50. doi:10.1371/journal.pmed.0050050
Using viral genotype data from HIV drug resistance testing at a London clinic, Andrew Leigh Brown and colleagues derive the structure of the transmission network through phylogenetic analysis.