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

Appendix A: Interpret prevalence trends
across multiple sites
You will commonly find two problems related to analysing data from multiple sites when interpreting data
on biological or behavioural trends:
• improper aggregation – combining small samples improperly
• inconsistent survey sites.
Improper aggregation
When looking at trend data, it is tempting to pool data from multiple sites to obtain a larger sample size.
The larger sample sizes are convenient because you are trying to detect statistically significant trends over
time, but this is not the best solution.
What are the issues
The disadvantage of pooling or aggregating data across sites is that the differences between the sites are
obscured. Your result may not be meaningful and may even be misleading.
What is gained in sample size by aggregating data may be lost in the inability to see potentially important
local patterns. Figure A.1 illustrates how the conclusions drawn from a combined trend line for all sites is
different from those of the individual sites.
• The combined-sites trend line misses the rising prevalence in site A and the overall higher prevalence
in site B.
• It also misses the decline in prevalence in site D.
• Some of the fluctuations in the individual trend lines, such as at site F, are likely to be the result of small
sample sizes. Those effects are smoothed out when the data are aggregated.
Figure A.1. Comparing the trend lines of all sites pooled versus individual sites
0.07
HIV prevalence
0.06
0.05
0.04
0.03
0.02
Site A
Site B
Site C
Site D
Site E
Site F
All Sites
0.01
0.0
1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
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