Guidelines for second generation HIV surveillance - World Health ...

Assessing the current level of HIV prevalence in a generalized epidemic
A geographical area classified as having a generalized epidemic should have sufficient data to indicate that
HIV has penetrated sexual networks outside of the traditional key populations at higher risk: sex workers,
men who have sex with men and people who inject drugs. In these settings, combining the level of HIV
prevalence and size of the different risk subpopulations may help you to determine the relative contribution
of different subpopulations to the epidemic.
In some generalized epidemic settings, it might be difficult to allocate resources towards focusing surveillance
and prevention interventions only on populations at higher risk for HIV instead of focusing efforts on the
general population or specific age groups within the population. However, programme interventions among
key populations at increased risk are still recommended and can indeed make a significant impact on a
generalized epidemic.
Tracking the level of HIV prevalence among antenatal clinic attendees
In generalized epidemics, monitoring the level of HIV prevalence among the general population is as
important as measuring the spread.
HIV sentinel surveillance among women attending ANC is an easy way to reach a sample of the general
population (10). ANC attendees are a proxy for the general population. However, women attending ANC
tend to be young (depending on the fertility patterns in the country) and are by definition not using
condoms. Thus, HIV prevalence among ANC attendees may be different from HIV prevalence among the
adult population. HIV prevalence among ANC clients will change if fertility levels change in the country.
However, comparing HIV prevalence among ANC attendees by geographical region is useful for identifying
the hotspots in a country as well as getting a sense of trends over time.
ANC prevalence together with programmatic data can be used to estimate national HIV prevalence using
different tools (11,12). More information about methods and tools is available at http://www.unaids.org/en/
dataanalysis/epidemiology/.
As services for PMTCT are scaled up and coverage reaches over 90%, countries are increasingly considering
substituting data from clinics which provide testing services for mother-to-child transmission (MTCT) for
data from sentinel surveillance among ANC attendees. Several research studies are under way to see how
the transition from the use of ANC data to the use of MTCT data can be done. Further guidance is being
developed based on the experience of some countries.
The role of national population-based surveys in tracking the level of HIV prevalence
National population-based surveys can provide the geographical distribution of risk and prevalence level by
different populations. These surveys are very useful because they combine HIV prevalence information with
many other indicators for each individual respondent. This allows for extensive analysis of factors that are
associated with HIV infection. As shown in Figure 2.2, stratification by different regions can provide insight
into the hotspots of the HIV epidemic.
This kind of survey is useful only in countries with national HIV prevalence levels above 2%. Due to the cost
and complexity of such surveys, they should be implemented only every three to five years, depending on
the level of the HIV epidemic and the cost involved. Technical guidance notes can be found at http://www.
unaids.org/en/media/unaids/contentassets/documents/epidemiology/20101207_HIVtesting_in_surveys_
WG_en.pdf.
There are a few potential biases in these surveys. First, it is important to check refusal rates. People who
know their status or feel they are likely to be infected might refuse to be tested, which could potentially bias
the results. Second, national population surveys focus on individuals living in households, and therefore
exclude people who are in hospitals or who live on the streets. However, this is unlikely to bias the results
unless the population not living in households represents more than 5% of the population.
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