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Using the detuned assay to determine HIV incidence in Ontario: Results and methodologic perspectives

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  1. Using the detuned assay to determine HIV incidence in Ontario: Results and methodologic perspectives Robert S. Remis, Carol Major, Carol Swantee, Margaret Fearon, Evelyn Wallace, Elaine Whittingham Department of Public Health Sciences, University of Toronto HIV Laboratory, Laboratory Services, Ontario Ministry of Health and Long-Term Care Public Health Branch, Ontario Ministry of Health and Long-Term Care STAHRS WorkshopCenters for Disease Control Albany, New York, USA, November 14-16, 2001

  2. Acknowledgements • At the HIV Laboratory • Lisa Santangelo and Cindi Farina, data collection • Lynda Healey, detuned assay • Elaine McFarlane, data entry screens • Len Neglia, mailout of questionnaires • Regional PHLs, mailout of questionnaires • Physicians who prescribe HIV testing, supplementary data • Frank McGee, AIDS Bureau for base funding • Ontario HIV Treatment Network for initial project funding • CIDPC, Health Canada for continued project funding

  3. Introduction • Serodiagnostic data useful for surveillance • However, • persons who test may not be representative • data quality often poor • Unbiased estimates of HIV incidence and prevalence cannot be derived directly

  4. Introduction • Testing of HIV-positive specimens using less sensitive (“detuned”) assay permits the identification of persons who recently seroconverted; • Can calculate HIV incidence density, a critical indicator otherwise difficult to measure

  5. Study objectives • Determine the number of persons newly testing positive for HIV • Determine the distribution of exposure category among newly diagnosed HIV-infected persons • Estimate HIV incidence density among persons undergoing HIV testing

  6. Data collection and management • Questionnaire sent with HIV-positive results and 1:200 sample of HIV-negative results • Coolect data on risk factors for HIV infection and HIV test history • Questionnaire returned by mail, fax or telephone interview • Data entered in Microsoft Access

  7. Laboratory methods • Modified Abbott 3A11 EIA kit (Oct 1999-Oct 2000) • Serum diluted to 1:20,000 • Incubation period reduced to 30 minutes • Cut-off value increased • Organon-Teknika (Oct 2000-Jul 2001) • Similar principle to Abbott EIA • Allows use of variable cut-off value reflecting varying “window period”

  8. Data analysis • Numerator • Non-reactive (discordant specimens) without risk factors imputed to NIR specimens based on reclassification from LES • Initially, imputed as proportion of those with risk factor information • Denominators (testers) handled similarly • Incidence density = • NR * 100 Testers * (t / 365)

  9. Study questionnaires mailed and returned, Oct 1999 - Dec 2000

  10. Exposure category classified according to HIV test requisition, returned questionnaires and modeled distribution, HIV-positives

  11. Exposure category Incidence per 100 p-y MSM MSM-IDU IDU 2.34 1.82 0.44 HR hetero LR hetero 0.22 0.04 Incidence (per 100 py) by exposure categoryOntario, Oct 1999 - Jul 2001

  12. MSM MSM-IDU IDU Toronto Ottawa Other 3.38 0.82 1.38 6.32 18.1 0.24 0.51 1.36 0.24 Ontario 2.34 1.82 0.44 Incidence (per 100 py) amomg MSM, MSM-IDU and IDU by health region,Ontario, Oct 1999 – Jul 2001

  13. HR hetero LR hetero Toronto Ottawa Other 0.26 0.17 0.21 0.04 0.07 0.02 Ontario 0.22 0.04 Incidence (per 100 py) among LR and HR heterosexual by health regionOntario, Oct 1999 - Jul 2001

  14. Incidence (per 100 py) among MSM by health region and study period, Ontario, Oct 1999 - Jul 2001

  15. Incidence (per 100 py) among IDU by health region and study period, Ontario, Oct 1999 - Jul 2001

  16. HIV incidence by age group, selected exposure categories

  17. Incidence calculated for selected exposure categoriesusing different "window" periods with the OT assay, Jan-Jul 2001

  18. Interpretation • Number of discordant samples and HIV tests by exposure category were modeled • Interpretation of HIV incidence must incorporate knowledge of patterns in HIV test seeking behaviours • Observed HIV incidence likely higher than for actual population

  19. Methodologic issues 1 • Risk factors unknown for significant proportion of both HIV-positive and HIV-negative testers • Distribution of those with unknown risk factors different than that among those with known risk factors

  20. Methodologic issues 2 • Testers may include persons with risk behaviours in distant past • This would tend to underestimate HIV incidence

  21. Methodologic issues 3 • For MSM, analysis with varying “window period” in later samples showed substantial decrease in estimated HIV incidence with longer interval but not for other groups • Likely due to increased probability of HIV testing related to isolated high risk exposures and seroconversion illness

  22. Conclusions • Detuned assay a powerful tool to estimate HIV incidence at low cost • However, further work is required to develop methodolgic approaches to account for missing data, unrepresentative samples and sources of bias related to HIV testing behaviours