Abstract

BackgroundEstimating the size of a high-risk population group is always challenging and is a requisite for planning and policy development. In India, the Bill & Melinda Gates Foundation implemented Avahan, a large-scale HIV prevention programme. As part of Avahan's overall evaluation strategy, two rounds of large-scale cross-sectional integrated behaviour and biological assessment (IBBA) surveys were carried out in 2006 (round 1) and 2009 (round 2) in selected districts in three states. MethodsTwo rounds of IBBA covered 23 female sex worker (FSW) and ten men who have sex with men (MSM) groups across 29 districts in three states. Sizes were estimated using three different methods: capture-recapture (CR), multiplier method (MM), and reverse tracking method (RTM), a technique mathematically similar to the Hansen-Hurwitz method. FindingsAmong the three methods, RTM was applied consistently in all groups in both the rounds. MM and CR were applied in the selected districts owing to the implementation issues and experiences in round 1 of the survey. The results from RTM showed that in Andhra Pradesh, the sizes of the FSW and MSM populations increased between rounds. In Maharashtra, FSW groups showed a decline from round 1 (13 459, 95% CI 13 431–13 487) to round 2 (8955, 8945–8964), whereas the MSM groups in Maharashtra showed an overall increase from round 1 (1498, 1480–1516) to round 2 (2667, 2605–2729). Tamil Nadu had mixed results in both FSW and MSM groups. The results from RTM were much more reliable and accurate compared with those obtained from CR and MM. Estimates from RTM also tended to be close to programme data. InterpretationChanges in high-risk population sizes captured through RTM were much more accurate and tended to be closer to the programme data. Also, in large-scale surveys where the sampling frame is exhaustive, using the RTM method for size estimation seems to be better than other indirect methods. FundingBill & Melinda Gates Foundation.

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