In theory, assessing progress in reducing the occurrence of new infections is best done through monitoring changes in incidence over time. However, in practice, prevalence data rather than incidence data are available.

In analysing prevalence data of people who inject drugs for the assessment of prevention programme impact, it is desirable not to restrict analysis to young people but to report on those persons who are newly initiated to behaviours that put them at risk for infection (e.g. by restricting the analysis to people who have initiated injecting drug use within the last year). This type of analysis also has the advantage of not being affected by the effect of ART in increasing survival and thereby increasing prevalence.

If prevalence estimates are available disaggregated by greater than and less than one year of injecting drugs countries are strongly encouraged to report this disaggregation in their Country Progress Report, and to use the comments field for this indicator in the reporting tool to present disaggregated estimates.

Due to difficulties in accessing people who inject drugs, biases in sero-surveillance data are likely to be far more significant than in data from a more general population, such as women attending antenatal clinics. If there are concerns about the data, these concerns should be reflected in the interpretation.

An understanding of how the sampled population(s) relate to any larger population(s) sharing similar risk behaviours is critical to the interpretation of this indicator. The period during which people belong to a key population is more closely associated with the risk of acquiring HIV than age. Therefore, it is desirable not to restrict analysis to young people but to report on other age groups as well.

Trends in HIV prevalence among people who inject drugs in the capital city will provide a useful indication of HIV-prevention programme performance in that city. However, it will not be representative of the situation in the country as a whole.

The addition of new sentinel sites will increase the samples representativeness and will therefore give a more robust point estimate of HIV prevalence. However, the addition of new sentinel sites reduces the comparability of values. As such it is important to use consistent sites when undertaking trend analyses.