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

How to deal with data aggregation issues
• Consider the question that this type of analysis intends to answer. Is a prevalence estimate for a larger
geographial unit required Or is it of greater interest to understand how the epidemic in a particular area
or key population is changing Consider how to extrapolate HIV prevalence from areas represented by
sentinel or survey sites to areas where direct measures of HIV prevalence are not available. For example,
you may decide to assign prevalence from a site located within an epidemiological zone to the total
population in that zone.
• Can prevalence be weighted according to the size of the population in the different geographical units
that are part of a larger geographical unit Simply pooling the data from multiple sites, either by crude or
weighted averages, will probably not be adequate for estimating the prevalence of a large geographical
unit. Even if one looks at trend data, it may not be sufficient to pool data from consistent sites if the
trend is attributed to an epidemic in a large geographical unit. If there are multiple epidemiological
zones in the large geographical unit, describing an overall trend may not be meaningful if the epidemic
is expanding in one zone but is stable in other zones.
Evaluating a National Surveillance System
Inconsistent surveillance sites
Most countries start their HIV surveillance systems in areas where the epidemic is most visible, where:
• the epidemic is most mature
• HIV prevalence levels are highest.
Over time, the number of surveillance sites expands to cover the country more uniformly. Newer sites often
are located where there are less severe epidemics.
What are the issues
When you are aggregating data to develop a trend, you will need to decide whether to include:
• only sites that have data for all years, or
• all sites, regardless of when surveillance was started.
When you combine data from new sites to the trend analysis, you are likely to dilute the overall prevalence
compared to the old sites that have been in the surveillance system longest. This may indicate a decline
when actually there is no decline.
Also, sentinel sites may be removed or added into surveillance rounds from year to year. These changes
may be caused by:
• inconsistent availability of resources
• changes in persons in charge of surveillance who may make different decisions about surveillance
priorities.
The effect of this scenario on trend is less clear.
How to deal with issues of inconsistent surveillance sites
There are two methods for dealing with inconsistent surveillance sites:
• look at trends for older and newer sites separately within the same epidemiological zone, or
• consider the pattern of consistent trends across different sites or epidemiological zones (do not pool
results). This may be more informative and better summarize the trajectory of the epidemic in a large
geographical unit.
Consistency in the trends observed when you break up the data in different ways suggests real changes in
the epidemic.
Think about why trends appear the way they do
When you are interpreting HIV prevalence trends, ask yourself the possible reasons why the trends appear
the way they do. Two examples of explanations for trends observed in real data are given in Figures A.2
and A.3 below.
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