title: Improved estimates of India's HIV burden in 2006.
abstract: OBJECTIVE
  HIV estimates in India were based on HIV sentinel surveillance (HSS) data and several assumptions. Expansion of sentinel surveillance to all districts and community based HIV prevalence measured by National Family Health Survey-3 (NFHS-3) in 2006 provided opportunity to replace many of the assumptions with evidence based information and improve the HIV estimate closer to reality. This article presents a detailed account of the methodology used for the 2006 HIV burden estimates for India.
  
  
  METHODS
  State-wise adult HIV prevalence among different risk groups observed from HSS 2006 was adjusted for site level variations using a random effects model and for the previous four years the same was back calculated using trend equations derived from a mixed effects logistic regression model based on consistent sites prevalence. The adjusted HIV prevalence among the general population was calibrated to the estimates from NFHS-3. Overall point estimates of adult HIV prevalence in each State for 2002-2006 were derived from the UNAIDS Workbook and projected for the period 1985-2010. The results were put into Spectrum to derive estimates of the number of people living with HIV in all ages and other epidemic impacts.
  
  
  RESULTS
  National adult HIV prevalence was 0.36 per cent (range 0.29-0.46%) and the estimated number of people living with HIV was 2.47 million (range 2.0-3.1 million) in 2006. The national adult HIV prevalence remains stable around 0.4 per cent between 2002 and 2006. The States with the highest estimated prevalence were Manipur, Nagaland and Andhra Pradesh. The States with the highest burden were Andhra Pradesh, Maharashtra, Karnataka and Tamil Nadu.
  
  
  CONCLUSIONS
  The improvement in the 2006 estimates of the HIV burden in India is attributable to the expanded sentinel surveillance and representative data from the population-based survey in 2006, combined with an improved analysis. Despite the downward revision, India continues to face a formidable challenge to provide prevention, treatment and care to those in need.
authors.affiliation: National Institute of Medical Statistics, ICMR, New Delhi, India. arvindpandey@vsnl.net
authors.forename: Arvind
authors.initials: A
authors.lastname: Pandey
authors.forename: Dandu C S
authors.initials: DC
authors.lastname: Reddy
authors.forename: Peter D
authors.initials: PD
authors.lastname: Ghys
authors.forename: Mariamma
authors.initials: M
authors.lastname: Thomas
authors.forename: Damodar
authors.initials: D
authors.lastname: Sahu
authors.forename: Madhulekha
authors.initials: M
authors.lastname: Bhattacharya
authors.forename: Kanchan D
authors.initials: KD
authors.lastname: Maiti
authors.forename: Fred
authors.initials: F
authors.lastname: Arnold
authors.forename: Shashi
authors.initials: S
authors.lastname: Kant
authors.forename: Ajay
authors.initials: A
authors.lastname: Khera
authors.forename: Renu
authors.initials: R
authors.lastname: Garg
mesh_terms: D004812:Epidemiologic Methods; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D007194:India / Q000453:epidemiology; D016015:Logistic Models; D008962:Models, Theoretical; D015995:Prevalence; D018571:Sentinel Surveillance