Adequate surveillance of hard-to-reach and 'hidden' subpopulations is crucial to containing the HIV epidemic in low prevalence settings and in slowing the rate of transmission in high prevalence settings. For a variety of reasons, however, conventional facility and survey-based surveillance data collection strategies are ineffective for a number of key subpopulations, particularly those whose behaviors are illegal or illicit. This paper critically reviews alternative sampling strategies for undertaking behavioral or biological surveillance surveys of such groups. Non-probability sampling approaches such as facility-based sentinel surveillance and snowball sampling are the simplest to carry out, but are subject to a high risk of sampling/selection bias. Most of the probability sampling methods considered are limited in that they are adequate only under certain circumstances and for some groups. One relatively new method, respondent-driven sampling, an adaptation of chain-referral sampling, appears to be the most promising for general applications. However, as its applicability to HIV surveillance in resource-poor settings has yet to be established, further field trials are needed before a firm conclusion can be reached.
Despite the challenges, the integrated biobehavioural assessment was a huge achievement, and was largely successful in providing previously unavailable information about the HIV situation among populations that are critical to the curtailment of HIV spread in India. Lessons from the first round will be used to evolve the second round into an exercise with increased evaluative capability for Avahan.
Rather than a small set of monofocal outcome measures, scaled programmes require nuanced evaluations that approximate programmatic scale by collecting data with different levels of geographical scope, synthesize multiple data and methods to arrive at a composite picture, and can cope with continuous environmental and programme evolution.
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