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

• Individuals may migrate to urban areas for work, acquire HIV, and then return to their home or native
town to receive diagnosis and care.
• The duration of time that sex workers sell sex may be for a few years only, resulting in a high turnover
in the sex worker population.
• Sex workers may continuously move to different geographical units to be considered attractive to a
fresh pool of clients.
• Persons who inject drugs may stop injecting for periods of time.
• Some persons who inject drugs may be targeted for drug detoxification or opioid substitution therapy,
removing them from the pool of current injectors.
• Patterns of injecting can also change due to drug availability or narcotics control policies.
Evaluating a National Surveillance System
These scenarios are common. They will all lead to changes in who is included in the surveys used to
measure biological trends, even if the surveys use the same protocol and sampling process.
Second assumption for the interpretation of HIV prevalence
HIV prevalence at any given point in time represents a combination of old and new infections. However,
disease progression may change over time. That is, the length of time between when a person is infected
with HIV and their death may change. What can cause this
• Widespread use of antiretroviral therapy makes survival time longer and therefore increases prevalence.
• During the early phase of a local epidemic, HIV prevalence rises steeply but the death rate is still low
(no one has yet progressed to advanced HIV). The unstable death rate must be factored in during
interpretation of the prevalence trend.
Important questions for analysing trend data
Answer these questions to interpret the dynamics of the population, as they influence prevalence trends.
This, in turn, has implications for interpreting changes in incidence:
• Is there likely to have been a change in the death rate during this time
• Is the epidemic expanding or has it reached maturity
• Is there evidence to suggest that many people have left or entered the population during this time
• If any of these changes have occurred, have they occurred consistently over several years or have they
occurred suddenly
• Is antiretroviral therapy widely available or becoming so Or have eligibility criteria for starting
antiretroviral therapy changed over time If so, the number of people receiving treatment will be
required to help explain an increase in prevalence.
4.1.3. Step 2: Assess selection bias in surveillance trend data
It is difficult to conduct truly representative surveys of any population. It is common to have various forms of
selection bias. HIV-positive individuals may not be equally likely to be captured in surveillance populations
as HIV-negative individuals. When this happens, the ability to interpret trends is compromised.
Understand potential sources of bias for each survey site and time point before attempting to determine
trends. You want to determine if a consistent type of bias is likely to be common across sites and over time.
Sources of bias that can affect prevalence trends can be grouped into two major categories (Figure 4.4):
• those that are within your control
• those that are not within your control.
The biases within your control generally relate to:
• the rigour applied to the design and implementation of the surveillance protocol
• the quality of data collection.
The biases not within your control result from:
• instability of the population, typically the surveillance target population
• the difficulties of trying to sample them for a survey in a representative way.
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