Higher HIV-1 incidence and genetic complexity along main roads in Rakai District, Uganda

J Acquir Immune Defic Syndr. 2006 Dec 1;43(4):440-5. doi: 10.1097/01.qai.0000243053.80945.f0.

Abstract

Objective: To determine the association between the incidence of HIV-1 infection and the genetic complexity of HIV-1 strains in 2 geographic strata within Rakai District, Uganda.

Methods: Study volunteers with recent HIV-1 infections during the period 1997 through 2003 were recruited from 10 communities that were geographically stratified as a main road trading center (n = 5) or a secondary road trading village (n = 5). Cryopreserved plasma was available from 384 volunteers and was the source of viral RNA for genotyping by the multiregion hybridization assay. Hazard ratios (HRs) for a single HIV subtype, a recombinant form, or dual infection for gender and geographic strata were obtained using Cox proportional hazards analysis.

Results: The HIV-1 incidence rate during the period 1999 through 2002 was 1.3 per 100 person-years (PYs) in the trading centers and 1.1 per 100 PYs in the trading villages. The HR for infection with an HIV-1 recombinant strain in trading centers relative to trading villages was 2.3 (95% confidence interval [CI]: 1.0 to 6.7). Among those who changed residence between village strata, the HR for a recombinant HIV-1 infection was 8.1 (95% CI: 0.4 to 47.7).

Conclusions: HIV-1 incidence and genetic complexity are associated with geographic strata and population mobility in Rakai District and are important variables to be considered in planning and recruitment for vaccine trials.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Female
  • Genetic Variation*
  • HIV Infections / epidemiology*
  • HIV Infections / virology
  • HIV-1 / classification*
  • HIV-1 / genetics*
  • Humans
  • Incidence
  • Male
  • Middle Aged
  • Molecular Epidemiology
  • Multivariate Analysis
  • Recombination, Genetic
  • Regression Analysis
  • Uganda / epidemiology