Dataset Information

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

ABSTRACT:

Background

The BED Capture Enzyme Immunoassay, believed to distinguish recent HIV infections, is being used to estimate HIV incidence, although an important property of the test--how specificity changes with time since infection--has not been not measured.

Methods

We construct hypothetical scenarios for the performance of BED test, consistent with current knowledge, and explore how this could influence errors in BED estimates of incidence using a mathematical model of six African countries. The model is also used to determine the conditions and the sample sizes required for the BED test to reliably detect trends in HIV incidence.

Results

If the chance of misclassification by BED increases with time since infection, the overall proportion of individuals misclassified could vary widely between countries, over time, and across age-groups, in a manner determined by the historic course of the epidemic and the age-pattern of incidence. Under some circumstances, changes in BED estimates over time can approximately track actual changes in incidence, but large sample sizes (50,000+) will be required for recorded changes to be statistically significant.

Conclusions

The relationship between BED test specificity and time since infection has not been fully measured, but, if it decreases, errors in estimates of incidence could vary by place, time and age-group. This means that post-assay adjustment procedures using parameters from different populations or at different times may not be valid. Further research is urgently needed into the properties of the BED test, and the rate of misclassification in a wide range of populations.

SUBMITTER: Hallett TB

PROVIDER: S-EPMC2684620 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Publications

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

Hallett Timothy B TB Ghys Peter P Bärnighausen Till T Yan Ping P Garnett Geoff P GP

PloS one 20090528 5

<h4>Background</h4>The BED Capture Enzyme Immunoassay, believed to distinguish recent HIV infections, is being used to estimate HIV incidence, although an important property of the test--how specificity changes with time since infection--has not been not measured.<h4>Methods</h4>We construct hypothetical scenarios for the performance of BED test, consistent with current knowledge, and explore how this could influence errors in BED estimates of incidence using a mathematical model of six African ...[more]

PMID: 19479050

Similar Datasets

Project description:IntroductionTo close gaps in HIV prevention and care, knowledge about locations and populations most affected by HIV is essential. Here, we provide subnational and sub-population estimates of three key HIV epidemiological indicators, which have been unavailable for most settings.MethodsWe used surveillance data on newly diagnosed HIV cases from 2004 to 2014 and back-calculation modelling to estimate in France, at national and subnational levels, by exposure group and country of birth: the numbers of new HIV infections, the times to diagnosis, the numbers of undiagnosed HIV infections. The denominators used for rate calculations at national and subnational levels were based on population size (aged 18 to 64) estimates produced by the French National Institute of Statistics and Economic Studies and the latest national surveys on sexual behaviour and drug use.ResultsWe estimated that, in 2014, national HIV incidence was 0.17‰ (95% confidence intervals (CI): 0.16 to 0.18) or 6607 (95% CI: 6057 to 7196) adults, undiagnosed HIV prevalence was 0.64‰ (95% CI: 0.57 to 0.70) or 24,197 (95% CI: 22,296 to 25,944) adults and median time to diagnosis over the 2011 to 2014 period was 3.3 years (interquartile range: 1.2 to 5.7). Three mainland regions, including the Paris region, out of the 27 French regions accounted for 56% of the total number of new and undiagnosed infections. Incidence and undiagnosed prevalence rates were 2- to 10-fold higher than the national rates in three overseas regions and in the Paris region (p-values < 0.001). Rates of incidence and undiagnosed prevalence were higher than the national rates for the following populations (p-values < 0.001): born-abroad men who have sex with men (MSM) (respectively, 108- and 78-fold), French-born MSM (62- and 44-fold), born-abroad persons who inject drugs (14- and 18-fold), sub-Saharan African-born heterosexuals (women 15- and 15-fold, men 11- and 13-fold). Importantly, affected populations varied from one region to another, and in regions apparently less impacted by HIV, some populations could be as impacted as those living in most impacted regions.ConclusionsIn France, some regions and populations have been most impacted by HIV. Subnational and sub-population estimates of key indicators are not only essential to adapt, design implement and evaluate tailored HIV interventions in France, but also elsewhere where similar heterogeneity is likely to exist.

Dataset Information

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

Background

Methods

Results

Conclusions

Publications

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

Similar Datasets

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