title: HIV infection, antiretroviral therapy, and CD4+ cell count distributions in African populations.
abstract: BACKGROUND
  The variability in CD4+ cell counts within and among human immunodeficiency virus (HIV)-positive and -negative African populations has not been explained but has important implications for understanding the incidence of HIV-related opportunistic infections, especially tuberculosis, in both individuals and populations.
  
  
  METHODS
  In HIV-negative African adults, CD4+ cell counts vary within populations (interquartile ranges [IQRs], 169-603 cells/microL) and among populations (means vary from 699 to 1244 cells/microL), with similarly wide variations in HIV-positive adults. We developed dynamic mathematical models to predict the distribution of CD4+ cell counts in HIV-positive adults using the distribution in HIV-negative adults.
  
  
  RESULTS
  Under the assumption that survival is independent of the CD4+ cell count before seroconversion, we fitted the observed distributions in HIV-positive adults. At a CD4+ cell count of 200 cells/microL, the median life expectancy of HIV-positive Zambians (4.0 years) was predicted to be 1.7 times that of HIV-positive South Africans (2.3 years).
  
  
  CONCLUSIONS
  The model provides a way to estimate the changing distribution of CD4+ cell counts and, hence, the changing incidence of HIV-related opportunistic infections as the epidemic matures. This could substantially improve the planning of health services, including the need and demand for antiretroviral therapy. Better data are needed to test the model and its assumptions more rigorously and to fully understand the variability in CD4+ cell counts within and among populations.
authors.affiliation: Stop TB Department, World Health Organization, Geneva 1211 CH 1211, Switzerland. williamsbg@who.int
authors.forename: Brian G
authors.initials: BG
authors.lastname: Williams
authors.forename: Eline L
authors.initials: EL
authors.lastname: Korenromp
authors.forename: Eleanor
authors.initials: E
authors.lastname: Gouws
authors.forename: George P
authors.initials: GP
authors.lastname: Schmid
authors.forename: Bertran
authors.initials: B
authors.lastname: Auvert
authors.forename: Christopher
authors.initials: C
authors.lastname: Dye
mesh_terms: D000293:Adolescent; D000328:Adult; D000349:Africa / Q000453:epidemiology; D000368:Aged; D000369:Aged, 80 and over; D019380:Anti-HIV Agents / Q000627:therapeutic use*; D018791:CD4 Lymphocyte Count; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000453:epidemiology* / Q000276:immunology* / Q000401:mortality; D006801:Humans; D008297:Male; D008433:Mathematics; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D016019:Survival Analysis
chemical_list: D019380:Anti-HIV Agents