Table 10.

Methods and findings from studies comparing population-based and sentinel surveillance antenatal HIV prevalence in India.

Location [Reference]	Data collection year(s)	Sampling approach	Participation rate	Sample size (n)	Number of HIV-positive	Population HIV prevalence as % (95% CI)*	Power of sample size to detect difference from antenatal HIV prevalence at 95% confidence level†	Comments
Tamil Nadu: 3 districts [7]	1998	90 rural & urban clusters selected using probability proportional to size; selected households from each cluster invited for medical camp; first 25 adults 15–45 years old from each cluster who came to camp included in study	82.5% for selected households; not mentioned for eligible individuals	1981	34	Age & sex adjusted: 1.80 (0.89–2.71)	17% to detect 20% difference from 1% antenatal HIV prevalence	Selection bias likely due to medical camp sampling approach, making interpretation difficult; Grossly underpowered for reliable comparison with antenatal HIV prevalence
Tamil Nadu: 1 rural sub-district, 1 urban town [8]	1999–2000	120 rural & urban clusters selected using probability proportional to size; 15–40 years old people from randomly selected households included in study	90.9% of 3–40-year-olds; not mentioned for eligible 15–40-year-olds	2870	29	Crude: 1.01 (0.44–1.58)	21% to detect 20% difference from 1% antenatal HIV prevalence	Grossly underpowered for reliable comparison with antenatal HIV prevalence
Karnataka: 1 district [31,32]	2003	10 villages and 20 urban blocks selected with cluster sampling using probability proportional to size; 15–49-year-olds included in study; further details not published	59.8% of 6700 eligible 15–49-year-olds	4008	118	Crude: 2.94 (2.12–3.76)	50% to detect 20% difference from 2.6% antenatal HIV prevalence	Poor participation rate makes interpretation difficult; Underpowered for reliable comparison with antenatal HIV prevalence
Andhra Pradesh: 1 district [This study]	2004–2005	5 subdistricts selected to represent strata in district, from which 66 rural & urban clusters selected randomly; 15–49-year-olds from randomly selected households included in study	91.2% of 13838 eligible 15–49-year-olds	12617	241	Age, sex & rural-urban adjusted: 1.72 (1.35–2.09)	93% to detect 20% difference from 3% antenatal HIV prevalence	Adequately powered for reliable comparison with antenatal HIV prevalence

*Although the two Tamil Nadu papers reported adjusting for cluster design effect, the magnitude of this effect was not reported, and the confidence intervals reported in both these papers are implausibly narrow even if no design effect were considered (cluster design effect widens the confidence interval). The Karnataka study did not report design effect information. Because specific details about cluster design effect in these studies were not available, we used the cluster design effect of 2.44 from our study to calculate the confidence intervals for the other studies, using standard statistical methods [12,24]

†Power calculated assuming cluster design effect of 2.44 for all studies, using standard statistical methods [12,13]; sentinel surveillance antenatal HIV prevalence for comparison as reported in each study.