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Undiagnosed HIV in Australia

Undiagnosed HIV in Australia. David Wilson Head, Surveillance & Evaluation National Centre in HIV Epidemiology and Clinical Research University of New South Wales Sydney, Australia. How large is the undiagnosed population?. Important for understanding transmission sources

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Undiagnosed HIV in Australia

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  1. Undiagnosed HIV in Australia David Wilson Head, Surveillance & EvaluationNational Centre in HIV Epidemiology and Clinical Research University of New South WalesSydney, Australia

  2. How large is the undiagnosed population? • Important for understanding transmission sources • Highest transmission rate • Impact on community viral load • Motivating testing campaigns • Planning for treatment needs Undiagnosed population ? Diagnosed PLHIV PLHIV receiving ART CD4 > 500 CD4 350-500 CD4 200-350 CD4 < 200 Majority under regular clinical care

  3. What do we know? • Not much • National HIV surveillance is primarily based on notifications of diagnoses • Opposite of undiagnosed infections

  4. Methods • Broadly two approaches • Based on prevalence surveys • Data from regular prevalence surveys in different population groups • Estimated population sizes of each group • Based on reported HIV and AIDS cases • Data on diagnoses including • CD4 count at Dx, AIDS diagnosis within 3 months, deaths • Prevalence studies not routinely carried out in Australia

  5. Suck it and see (2008, Burnet) • 745 men from gay venues • 100 HIV+ overall (13.4% prevalence) • 20% had unrecognised HIV • 61 HIV+ /639 from social venues (9.6%) • Discussion around expanding GCPSto include biological component • Like IBBS / ANSPS

  6. Health In Men (2008, NCHECR) • Aimed to recruit HIV- men in Sydney: 6/2001 – 23/2004 • 1435 men • 9 (0.6%) HIV+ • HIV prevalence of 10-15% implies • ~ 5-12% undiagnosed infections

  7. Method of estimating unDx infections through reported cases • Estimate historical incidence and current incidence • Uncertainty with current incidence • Infer current prevalence • Cumulative incidence minus estimated deaths • Estimate undiagnosed infections

  8. Method of estimating unDx infections through reported cases • Estimate historical incidence and current incidence • Traditional back-projection methods (using AIDS cases) no longer relevant • Modified back-projection methods (adjust for ART) • HIV diagnoses per calendar quarter • Assays to differentiate recent and longstanding infection • Assumed time intervals from infection to diagnosis, differing between population groups • Adjust data on AIDS cases by their CD4 count given known rate of AIDS for each CD4 • Assume distribution of CD4 among unDx same as distribution of CD4 at Dx

  9. Backprojections • Estimate undiagnosed infections in Australia • 10-15% (Wand et al; Mallitt et al)

  10. New method based on CD4 at diagnosis • CD4 count not obtained within 3 months of HIV diagnosis

  11. New method based on CD4 at diagnosis • Impute CD4 count for cases with missing data

  12. Distribution of CD4 count in HIV-uninfected people

  13. Stage of disease at diagnosis: CD4 count

  14. Stage of disease at diagnosis: CD4 count

  15. Review and meta-analysis: annual decline

  16. Change in CD4 over time Rate of decline based on square root of CD4 count

  17. Estimated distribution of time from infection to diagnosis • Calculate for any CD4 count at diagnosis • Simulate back-projection of likely time of infection

  18. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  19. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis Distribute all cases to likely infection time

  20. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  21. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  22. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  23. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  24. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis Distribution of year of incidence for 2009 diagnoses

  25. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  26. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis • 29 new infections expected to be diagnosed after 2010 • 13 in 2011 • 7 in 2012 • 4 in 2013 • 2 in 2014 etc 2002 incident cases

  27. Estimating undiagnosed infections and incidence from CD4 counts at diagnosis

  28. Data gaps and actions • 10-20% • But not based on any solid data • Gaps • Enough data for approach 2 but not utilised fully • Large prevalence study would be ideal (approach 1) • Attach to GCPS • In ANSPS ask about believed HIV status • Need to extend to heterosexual population • CALD community (survey design hopefully to start)

  29. International settings for comparison • Australia • 10-20% (uncertain) • USA • 48% (Glynn et al) • 25% (Stekler et al; Branson et al) • UK • 44% (Dodds et al) • Sub-Saharan Africa • 60-90%

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