title: Have the explosive HIV epidemics in sub-Saharan Africa been driven by higher community viral load?
abstract: OBJECTIVE
  The HIV epidemic has carved contrasting trajectories around the world with sub-Saharan Africa (SSA) being most affected. We hypothesized that mean HIV-1 plasma RNA viral loads are higher in SSA than other areas, and that these elevated levels may contribute to the scale of epidemics in this region.
  
  
  METHODS
  To evaluate this hypothesis, we constructed a database of means of 71,668 viral load measurements from 44 cohorts in seven regions of the world. We used linear regression statistical models to estimate differences in viral load between regions. We also constructed and analyzed a mathematical model to describe the impact of the regional viral load differences on HIV epidemic trajectory.
  
  
  RESULTS
  We found substantial regional viral load heterogeneity. The mean viral load in SSA was 0.58 log(10) copies/ml higher than in North America (95% confidence interval 0.45-0.71); this represents about a four-fold increase. The highest mean viral loads were found in Southern and East Africa, whereas in Asia, Europe, North America, and South America, mean viral loads were comparable. Mathematical modeling indicated that conservatively 14% of HIV infections in a representative population in Kenya could be attributed to the enhanced infectiousness of patients with heightened viral load.
  
  
  CONCLUSIONS
  We conclude that community viral load appears to be higher in SSA than in other regions and this may be a central driver of the massive HIV epidemics in this region. The elevated viral loads in SSA may reflect, among other factors, the high burden of co-infections or the preponderance of HIV-1 subtype C infection.
authors.affiliation: aInfectious Disease Epidemiology Group, Weill Cornell Medical College - Qatar, Cornell University, Qatar Foundation - Education City, Doha, Qatar bDepartment of Public Health, Weill Cornell Medical College, Cornell University, New York, New York cVaccine and Infectious Disease Division dClinical Research Division, Fred Hutchinson Cancer Research Centre, Seattle, Washington eDepartment of Global Health fDepartment of Medicine gDepartment of Biostatistics hDepartment of Epidemiology, Schools of Medicine and Public Health, University of Washington, Seattle, Washington, USA iMRC Tropical Epidemiology Group, Faculty of Epidemiology and Population Health, London School of Hygiene & Tropical Medicine, London, UK jDepartment of Biostatistics kEmerging Pathogens Institute, Colleges of Public Health and Medicine, University of Florida, Gainesville, Florida, USA. *These authors contributed equally to this study.
authors.forename: Laith J
authors.initials: LJ
authors.lastname: Abu-Raddad
authors.forename: Ruanne V
authors.initials: RV
authors.lastname: Barnabas
authors.forename: Holly
authors.initials: H
authors.lastname: Janes
authors.forename: Helen A
authors.initials: HA
authors.lastname: Weiss
authors.forename: James G
authors.initials: JG
authors.lastname: Kublin
authors.forename: Ira M
authors.initials: IM
authors.lastname: Longini
authors.forename: Judith N
authors.initials: JN
authors.lastname: Wasserheit
mesh_terms: D017954:Africa South of the Sahara / Q000453:epidemiology; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000821:virology*; D015497:HIV-1 / Q000302:isolation & purification*; D006801:Humans; D008297:Male; D008962:Models, Theoretical; D011247:Pregnancy; D012367:RNA, Viral / Q000097:blood; D019562:Viral Load
chemical_list: D012367:RNA, Viral