Behavioural Surveillance Surveys - The Wisdom of Whores

Behavioral data can pinpoint specific
behaviors which need to be changed, and can
also highlight those that are not changing
over time in response to program efforts.
This information should lead to a rethinking
of prevention approaches, and the design
of new, more effective interventions.
Tracking behavior helps evaluate programs
A good behavioral data collection system
will give a picture of changes in sexual and
drug-taking behavior over time, both in the
general population and in groups of people
whose behavior puts them at high risk of
infection. The system will record a reduction
in risky sex just as it will record persistent risk
behavior or shifts in the pattern of risk.
These changes should give an indication of
the success of a package of activities aimed at
promoting safe behavior and reducing the
spread of HIV, both in the general population
and in groups with high risk behavior.
Showing that behavior can and does
change following national efforts to reduce
risky sex and drug taking is essential to
building support for ongoing prevention
activities. BSS data have been used by
UNAIDS and other international bodies
to highlight HIV prevention successes in
countries as varied as Cambodia, India and
Senegal.
Changes in behavior help explain changes in
HIV prevalence
Changing behavior and a consequent
reduction in new infections are just one
possible reason for changes in HIV prevalence.
It is, of course, the most encouraging to those
involved in trying to reduce the spread of the
virus. But without collecting data that show
trends in behavior over time, it is not possible
to ascertain whether behavior change contributes
to changes in prevalence.
When prevalence stabilizes - and even
when it stabilizes at very high levels - there
is often a tendency towards becoming
complacent ; the problem has peaked, it
won’t get any worse. This can be a dangerous
fallacy. Behavioral data showing no change
in risk activities, or continued risk in certain
age groups or sections of the population,
should ring alarm bells even where prevalence
is stabilizing. If there is no reduction in the
risky behaviors that lead to HIV infection,
changes in prevalence may well be due to
other factors such as rising mortality, migration
of those infected, sampling bias or other
measurement errors. None of these constitute
successful prevention efforts.
Although comparisons across regions,
cultures and countries must be made with
extreme caution, behavioral data can also
help explain differences in levels of infection
between one region and another. This is
particularly the case when indicators of risk
behavior are standardized across all studies
and surveys, with the same wording and
reference periods. The use of the same
(or broadly similar) sampling and data
collection methods also greatly increase the
comparability of risk behavior across time
and in different locations.
B EHAV I OR A L S U R V EI L L A NC E SURV EY S CHAPTER 1
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