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Table 2 Estimation of HIV burden in four major Indian states based on correction factors derived from population-based study.

From: Is the HIV burden in India being overestimated?

     Plausible estimate (low) Plausible estimate (high)
     Change needed in antenatal HIV prevalence to estimate population prevalence (% of antenatal HIV prevalence)    Change needed in antenatal HIV prevalence to estimate population prevalence (% of antenatal HIV prevalence)   
State 2005 population 15–49 years* (millions) 2005 median antenatal sentinel surveillance HIV prevalence† (%) 2005 HIV estimate 15–49 years† (millions) To adjust for HIV referrals to public sector hospitals‡ To adjust for the socio-economic profile of public sector hospital users§ To adjust for under-represented high-risk groups¶ Composite correction factor for antenatal HIV prevalence to estimate population prevalence 2005 HIV estimate 15–49 years# (millions) To adjust for HIV referrals to public sector hospitals‡ To adjust for the socio-economic profile of public sector hospital users§ To adjust for under-represented high-risk groups¶ Composite correction factor for antenatal HIV prevalence to estimate population prevalence 2005 HIV estimate 15–49 years# (millions)
Andhra Pradesh 42.7 2.00 1.45 -33 -9 +5 0.63 0.54 -20 -5 +10 0.85 0.73
Karnataka 30.0 1.25 0.64 -33 -8 +8 0.67 0.25 -20 -4 +16 0.92 0.35
Maharashtra 55.0 1.25 1.23 -33 +5 +12 0.84 0.58 -20 +3 +24 1.07 0.73
Tamil Nadu 36.3 0.50 0.37 -33 -14 +20 0.73 0.13 -20 -8 +40 1.12 0.20
Total    3.69      1.50      2.01
  1. *Population in 2005 estimated by calculating the exponential annual growth rate for each state from the 1991 and 2001 censuses [14,15], and using 90% of this annual estimate for growth from 2001 to 2005, except for Tamil Nadu for which the estimate from the last decade was used as the growth rate was already very low between the two censuses.
  2. †Median HIV prevalence and HIV estimate in adults for 2005 as calculated by NACO [2].
  3. ‡In Guntur district the rate in both the lower and upper SLI halves was over 2 times in women who utilised antenatal care at public sector hospitals than the average for each SLI half [5], which can be related to the common practice of referral of HIV positive or suspect persons from the private to the public health system; as this referral pattern is common we assumed it to be broadly similar in the four states but of a lower magnitude than observed in Guntur district; we used a conservative assumption of a 1.5 times increase in HIV prevalence in women utilising care at public sector hospitals due to this referral for our low estimate that would require a 33% downward adjustment of the antenatal HIV prevalence, and used a still more conservative assumption of only a 1.25 times increase in the antenatal HIV prevalence due to referrals for our high estimate that would require a 20% downward adjustment of this HIV prevalence.
  4. §Based on the SLI distribution of women using public sector hospitals for antenatal care in each state (Table 1); if representation of the lower half of SLI was higher for a state, a downward adjustment was calculated for the antenatal HIV prevalence based on what the rate would have been if the two SLI halves were equally represented, and vice versa; in our population- based sample the ratio of HIV prevalence among women in the lower and upper halves of SLI was 2.3, and we used this assumption for our low estimate; we used a more conservative ratio of 1.5 for our high estimate.
  5. ¶Inclusion of under-represented high-risk groups increased our population-based HIV prevalence in Guntur district from 1.72% to 1.79% [5], a small increase of 0.07%; we assumed a population HIV prevalence of 0.1% due to under-represented high-risk groups for our low estimate and 0.2% for our high estimate for Andhra Pradesh, Karnataka and Tamil Nadu; for Maharashtra, due to the possibility of a higher proportion of high-risk groups, we assumed 0.15% and 0.3% rates respectively due to their under-representation; the upward adjustment needed in the antenatal HIV prevalence to accommodate this was calculated by dividing these assumed rates with the median antenatal rate for each state.
  6. #Calculated by multiplying the antenatal HIV prevalence with the composite correction factor and applying this to the total population 15–49 years old.