Author
Listed:
- Timothy B Hallett
- Basia Zaba
- Jim Todd
- Ben Lopman
- Wambura Mwita
- Sam Biraro
- Simon Gregson
- J Ties Boerma
- on behalf of the ALPHA Network
Abstract
Background: HIV surveillance of generalised epidemics in Africa primarily relies on prevalence at antenatal clinics, but estimates of incidence in the general population would be more useful. Repeated cross-sectional measures of HIV prevalence are now becoming available for general populations in many countries, and we aim to develop and validate methods that use these data to estimate HIV incidence. Methods and Findings: Two methods were developed that decompose observed changes in prevalence between two serosurveys into the contributions of new infections and mortality. Method 1 uses cohort mortality rates, and method 2 uses information on survival after infection. The performance of these two methods was assessed using simulated data from a mathematical model and actual data from three community-based cohort studies in Africa. Comparison with simulated data indicated that these methods can accurately estimates incidence rates and changes in incidence in a variety of epidemic conditions. Method 1 is simple to implement but relies on locally appropriate mortality data, whilst method 2 can make use of the same survival distribution in a wide range of scenarios. The estimates from both methods are within the 95% confidence intervals of almost all actual measurements of HIV incidence in adults and young people, and the patterns of incidence over age are correctly captured. Conclusions: It is possible to estimate incidence from cross-sectional prevalence data with sufficient accuracy to monitor the HIV epidemic. Although these methods will theoretically work in any context, we have able to test them only in southern and eastern Africa, where HIV epidemics are mature and generalised. The choice of method will depend on the local availability of HIV mortality data. Timothy Hallett and colleagues develop and test two user-friendly methods to estimate HIV incidence based on changes in cross-sectional prevalence, using either mortality rates or survival after infection. Background.: More than 25 million people have died from AIDS and about 33 million people are currently infected with human immunodeficiency virus (HIV, the virus that causes AIDS). Faced with this threat to human health, governments and international agencies are working together to halt the AIDS epidemic. An important part of this effort is HIV surveillance. The spread of HIV needs to be monitored to assess the impact of interventions (for example, the provision of antiretroviral drugs) and to plan for current and future health care needs. HIV surveillance in countries where the epidemic has spread beyond specific groups into the whole population (a generalized epidemic) has mainly relied on determining the prevalence of HIV infection (the fraction of the population that is infected) among women attending antenatal clinics. Recently, however, household health surveys (for example, the Demographic and Health Surveys) have begun to use blood testing for antibodies to the AIDS virus (serological testing) to provide more accurate estimates of HIV prevalence in the general adult population. Why Was This Study Done?: Although prevalence estimates provide useful information about the HIV epidemic, another important indicator is incidence—the number of new infections occurring during a specific time period. Incidence measurements provide more information about temporal changes in the epidemic and transmission patterns and allow public-health experts to make better predictions of future health care needs. But, whereas prevalence can be measured with anonymized serological surveys, individuals would have to be identified and followed up in repeat serological surveys to provide a direct measurement of incidence. This is expensive and hard to achieve in many settings. In this study, therefore, the researchers develop and validate two mathematical methods to estimate HIV incidence in generalized HIV epidemics from prevalence data. What Did the Researchers Do and Find?: Changes in the fraction of the population living with HIV (prevalence) can occur not only because of changes in the rate of new infections (incidence), but also because mortality rates are much higher for infected individuals than others. The researchers' methods disentangle the contributions to HIV prevalence (as measured in serological surveys) made by new infections from those due to deaths from AIDS and other causes. Their first method incorporates information on death rates collected in cohort studies of HIV infection (cohort studies investigate outcomes in groups of people); their second method uses information on survival after HIV infection, also collected in long-running cohort studies. The accuracy of both methods was assessed using computer-simulated data and actual data on HIV prevalence and incidence collected in three community-based cohort studies in Zimbabwe and Uganda (countries with generalized but declining HIV epidemics) and Tanzania (a country with a generalized, stable epidemic). Both methods provided accurate estimates of HIV incidence from the simulated data. Using the data collected in Africa, the mean difference between actual measurements of incidence and the estimate provided by method 1 was 19%; for method 2 it was 14%. In addition, the measured and estimated incidences were in good agreement for all age groups. What Do These Findings Mean?: These findings suggest HIV incidence rates can be estimated from repeat surveys of prevalence with sufficient accuracy to monitor the HIV epidemic. The accuracy of the estimates across all age groups is particularly important because knowledge of the age-related risk pattern provides the information on transmission patterns that is needed to design effective intervention programs. Because these methods were tested using data only from southern and eastern Africa where the HIV epidemic is mature and generalized, they may not work as well in regions where the epidemic is restricted to subsets of the population. Other factors that might affect their accuracy include the amount of international migration and the uptake of antiretroviral therapies. Nevertheless, with the increased availability of serial measurements of serological prevalence, these new methods for estimating HIV incidence from HIV prevalence could prove extremely useful for monitoring the progress of national HIV epidemics and for guiding HIV control programs. The authors include spreadsheets that can be used to calculate incidence by either method from consecutive survey data. Additional Information.: Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0050080.
Suggested Citation
Timothy B Hallett & Basia Zaba & Jim Todd & Ben Lopman & Wambura Mwita & Sam Biraro & Simon Gregson & J Ties Boerma & on behalf of the ALPHA Network, 2008.
"Estimating Incidence from Prevalence in Generalised HIV Epidemics: Methods and Validation,"
PLOS Medicine, Public Library of Science, vol. 5(4), pages 1-12, April.
Handle:
RePEc:plo:pmed00:0050080
DOI: 10.1371/journal.pmed.0050080
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