title: A simpler tool for estimation of HIV incidence from cross-sectional, age-specific prevalence data.
abstract: BACKGROUND
  HIV incidence estimates are crucial in understanding and predicting the HIV/AIDS epidemic and identifying sub-populations and regions most at risk for the epidemic. However, incidence estimation is a challenge due to the nature of the disease and type of data available. This paper aims to present a simple and creative HIV incidence estimation method for resource constrained settings with scarce data.
  
  
  METHODS
  The authors developed a simple user-friendly non-iterative spreadsheet estimation method, which can produce incidence estimates by age group using observed cross-sectional, age-specific HIV prevalence. Data from two prospective FHI microbicide Phase III clinical trials in Nigeria were used to validate the spreadsheet method. Since both the clinical trials involved condom use promotion to reduce HIV risk, the authors also used the AVERT software to estimate the extent of incidence reduction due to the intervention.
  
  
  RESULTS
  The spreadsheet incidence estimates after accounting for AVERT adjusted reductions, for age groups 18-20, 21-25 and 26-30 were: 1.69%, 0.96% and 1.12% in the SAVVY trial, and 2.11%, 1.47% and 1.28% in the CS trial respectively. The corresponding actual observed incidence rates were 1.62%, 2.39%, and 1.13% in the SAVVY trial and 1.93%, 1.78% and 1.40% in the CS trial.
  
  
  CONCLUSIONS
  Comparisons of the spreadsheet-estimated incidence with the actual incidence from the clinical trials demonstrated that the method is reasonably accurate in its estimation. Because of the method's limitations it should not be used to evaluate HIV/AIDS prevention interventions or without understanding the direction of the bias in the case of an evolving HIV epidemic.
authors.affiliation: University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.
authors.forename: Suja S
authors.initials: SS
authors.lastname: Rajan
authors.forename: David
authors.initials: D
authors.lastname: Sokal
mesh_terms: D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D000367:Age Factors; D017280:Condoms / Q000706:statistics & numerical data / Q000600:supply & distribution; D003376:Counseling / Q000706:statistics & numerical data / Q000600:supply & distribution; D003430:Cross-Sectional Studies; D005260:Female; D015658:HIV Infections / Q000150:complications / Q000453:epidemiology* / Q000517:prevention & control; D006801:Humans; D015994:Incidence; D016013:Likelihood Functions; D008875:Middle Aged; D015233:Models, Statistical; D009549:Nigeria / Q000453:epidemiology; D011159:Population Surveillance / Q000379:methods*; D015995:Prevalence; D011446:Prospective Studies; D040242:Risk Reduction Behavior; D012725:Sexual Behavior