1. Estimation of the number of people with undiagnosed HIV infection in a country Andrew Phillips, UCL, London HIV in Europe Meeting 2 November 2009, Stockholm.

2. Approaches to estimation of the number of people with undiagnosed HIV infection in a country - based on prevalence surveys - based on reported numbers of HIV diagnoses - based on reported simultaneous HIV/AIDS cases

3. Approaches to estimation of the number of people with undiagnosed HIV infection in a country - based on prevalence surveys - based on reported numbers of HIV diagnoses - based on reported simultaneous HIV/AIDS cases

4. Divide population into categories according to risk MSM IDU Africans MSM

5. Assess HIV Prevalence in the risk category MSM IDU Africans HIV prevalence MSM

6. Estimate number of people in the risk category (size) MSM IDU Africans HIV prevalence x Size MSM

7. Multiply to give estimated number with HIV MSM IDU Africans HIV prevalence x Size = Number with HIV MSM

8. Subtract the number with diagnosed HIV IDU Africans Number with HIV – Number with diagnosed HIV MSM

9. ….to give the number with undiagnosed HIV IDU Africans Number with HIV – Number with diagnosed HIV = Number with undiagnosed HIV MSM

10. Add estimates across risk categories IDU Africans Number with HIV – Number with diagnosed HIV = Number with undiagnosed HIV MSM + + +

11. IDU Africans HIV prevalence x Size = Number with HIV MSM Alternative Approach

12. MSM IDU Africans Undiagnosed HIV prevalence x Size = Number with undiagnosed HIV MSM

13. Approach based on prevalence surveys Issues to consider What risk categories to divide population into ? How to estimate the size of each category ? What prevalence to assume for those not falling into any of the selected ‘risk’ categories ? Are the prevalence surveys based on representative samples of the risk category ?

14. Is prevalence survey based on representative sample of the risk group of the size estimated ? Level of risk activity HighLow Sexual risk activity in MSM HIV prevalence

15. Is prevalence survey based on representative sample of the risk group of the size estimated ? Level of risk activity High Low Prevalence survey performed in this group -If applied to all MSM will result in over-estimation of HIV prevalence HIV prevalence Sexual risk activity in MSM

16. Is prevalence survey based on representative sample of the risk group of the size estimated ? Level of risk activity HighLow Sexual risk activity in MSM HIV prevalence Divide MSM into two categories: high and low risk – one prevalence survey in each

17. Approach based on prevalence surveys Advantages - Assumptions are explicit and effect of changing them can be investigated - Can provide up-to-date estimates - Avoids assumptions involved in other methods

18. Approaches to estimation of the number of people with undiagnosed HIV infection in a country - based on prevalence surveys - based on reported numbers of HIV diagnoses - based on reported simultaneous HIV/AIDS cases

19. Original “back-calculation” approach, before availability of treatment Calendar year Number of AIDS cases diagnosed

20. Original “back-calculation” approach, before availability of treatment Calendar year What can this tell us about how many people were infected and when they were infected ? Observed number of AIDS cases diagnosed

21. Curve linking infection to AIDS, without treatment Expected number of new AIDS cases per year after 1000 people infected - illustration Number of new AIDS cases per year 2 3 10 25 40 65 80 90 100 100 100 90 80 70 55 30 25 15 10 5 5 Years from infection 0 5 10 15 20 Curve known from seroconverter cohorts

22. 2 3 10 25 40 65 80 90 100 100 100 90 80 70 55 30 2 3 10 25 40 65 80 90 100 100 100 90 80 70 2 3 10 25 40 65 80 90 100 100 100 2 3 12 28 50 92 123 165 205 230 265 270 270 260 235 200 t0t0 t0t0 t2t2 t0t0 t1t1 Numbers of AIDS cases expected over time if 1000 people infected at t 0, t 1 and t 2 Assume a certain number of people infected in each year, and calculate the expected number of AIDS cases by year - how close is this to the observed number ? Adjust the assumed number infected in each year to give the best fit to the observed number of AIDS cases

23. Original “back-calculation” approach, before availability of treatment Estimated number of people infected (incidence curve) Observed number of AIDS cases diagnosed Calendar year From the incidence curve it was possible to work out the number estimated to be living with HIV by subtracting the number of deaths

24. Revised back-calculation approach Question changes… How many people must be infected, and when must they have been infected, in order to produce the numbers of new AIDS we have observed ? How many people must be infected, and when must they have been infected, and what must the probability of getting diagnosed have been, in order to produce the numbers of new HIV diagnoses we have observed ? infectionAIDS infectionHIV diagnosis from: to:

25. Curve linking infection to HIV diagnosis Expected number of HIV diagnoses per year after 1000 people infected Number of HIV diagnoses Years from infection 0 5 10 15 20 145 145 145 125 100 85 70 50 40 30 15 10 8 7 6 5 4 3 2 2 2 1 Curve unknown

26. Curve will differ by calendar year – more testing in more recent years Number of HIV diagnoses Years from infection 0 5 10 15 20 Infected in 2000 Infected in 1995 Curve linking infection to HIV diagnosis

27. No. of people New diagnoses Inferring incidence of new infections and the diagnosis rate from the number of new diagnoses Diagnosis rate

28. Diagnosis rate New infections No. of people New diagnoses Inferring incidence of new infections and the diagnosis rate from the number of new diagnoses Diagnosis rate

29. Diagnosis rate New infections No. of people New diagnoses Inferring incidence of new infections and the diagnosis rate from the number of new diagnoses Diagnosis rate

30. Approaches based on reported numbers of HIV diagnoses and AIDS cases Advantages - Based on routine case reporting data only – does not require prevalence studies - Can tell us about the predicted time from infection of those undiagnosed

31. Approaches to estimation of the number of people with undiagnosed HIV infection in a country - based on prevalence surveys - based on reported numbers of HIV diagnoses - based on reported simultaneous HIV/AIDS cases

32. Table. Example calculation. n = total number undiagnosed. CD4 count Distribution of CD4 count Incidence of AIDS (/year) Expected no. of simultaneous HIV/AIDS diagnoses per year 0-490.031.00n × 0.03 × 1.00 50-1990.150.20n × 0.15 × 0.20 200-3490.220.05n × 0.22 × 0.05 350-4990.250.02n × 0.25 × 0.02 500-6490.200.015 n × 0.20 × 0.015 650-0.150.008n × 0.15 × 0.008 Total-1.00n × 0.080 n = number of people with undiagnosed HIV Approach based on reported simultaneous HIV/AIDS cases Observed number of simultaneous HIV/AIDS diagnoses = n x 0.080

33. Issues to consider - Distribution of CD4 count in undiagnosed - Under-diagnosis and under-reporting of AIDS Approach based on reported simultaneous HIV/AIDS cases

34. Advantages - Uses information on CD4 count at diagnosis - Particularly well suited to estimating number of undiagnosed people with low CD4 count See poster: Lodwick et al PE 18.1/5 Approach based on reported simultaneous HIV/AIDS cases

35. Summary and Conclusions Countries need to know the number of people living with HIV in various risk groups as a starting point for planning prevention measures and clinical care needs. This requires estimation of the number with undiagnosed HIV. At least three different types of approach exist. Each has advantages and disadvantages. Since they use different data they should provide independent estimates. If it is possible to use all approaches this will provide the greatest insight. Simple guidance is needed for countries on how to use the various approaches.

36. How to implement ? - Dynamic iterative approach - produce document on guidance for countries on methods for estimating prevalence of undiagnosed infection, given current state of the field - through ECDC, try to enourage countries to implement estimation - this should help to stimulate more complete collection of surveillance data - this process will be part of an ongoing process of evaluating the relative value of alternative approaches - the guidance document on methods will evolve to include more extensive data modelling approaches

37. Acknowledgements Useful discussions with Daniela de Angelis Paul Birrell Valerie Delpech Matthew Law Caroline Sabin Jens Lundgren Colette Smith Alison Rodger Rebecca Lodwick Geoff Garnett Lodwick et al - poster PE 18.1/5, EACS, Cologne