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AIDS-Related Tuberculosis in Rio de Janeiro, Brazil Antonio G F Pacheco.

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Presentation on theme: "AIDS-Related Tuberculosis in Rio de Janeiro, Brazil Antonio G F Pacheco."— Presentation transcript:

1 AIDS-Related Tuberculosis in Rio de Janeiro, Brazil Antonio G F Pacheco

2 Objective The objective of this study was to assess the impact that widespread availability of HAART has on AIDS-related TB at a population level –i.e., is HAART reducing the community burden of AIDS-related TB?

3 Background Tuberculosis (TB) is an important complication of HIV infection in Brazil ~7,000 new TB cases every year in Rio (> 100/100,000) DOTS implemented gradually since 1997 Currently 52% DOTS population coverage –35 health care units

4 Background Brazil provides HAART free of charge to all patients who meet clinical criteria In Rio de Janeiro city, more than 22,000 individuals are receiving ART currently at 56 public health services HAART was effectively available since 1997 but other treatments were available since 1991

5 Methods – Data Sources SINAN-TB –System of mandatory report of TB, since 1995 SINAN-AIDS –System of mandatory report of AIDS, since 1982 SIM –System of mandatory report of mortality, since 1995

6 Methods - TB Case Definition Confirmed case –Two positive smears; or –Positive culture Non-confirmed case –Clinical and epidemiological criteria; and –X-Ray alterations; and –Improvement after TB treatment Both types included in analyses

7 Methods - AIDS Case Definition One out of four conditions: –HIV+ and one AIDS defining illness – Modified CDC criteria –HIV+ and CD4 counts < 350/mm 3 –HIV+ and 10+ points by the RJ/Caracas criteria –AIDS as underlying COD Changes over time: –1992 – inclusion of the RJ/Caracas criteria –1995 – inclusion of cases based on death certificate –1998 – inclusion of CD4 count criterion

8 Methods – Co-infection detection Linkage –SINAN-AIDS and SINAN-TB Criteria –First name and last name adapted Soundex Patients and mothers (when available) –String similarity index (Gestalt algorithm) –Date of birth (allowing errors) –Algorithm written in Python –Sensitivity ~ 92% –Specificity ~ 99%

9 Methods – Linkage details Modified soundex –Letter H at the beginning of word –SS, SC, Ç String comparison: Gestalt method –By sub-fractions off the larger matching chunk –Developed by John W. Ratcliff and John A. Obershelp (1983) –We use indexes > 0.8 to be acceptable DOB –Up to 1 mistake –Day/month swap

10 Methods Co-infection Definitions –AIDS cases who developed TB up to 1 year after AIDS (no recurrence) Up to 30 days Between 30 days and 1 year –Analysis from 1995 to 2004 Temporal Trends –Descriptive –GAM with cubic splines Quasipoisson (rates) Quasibinomial (proportions)

11 Results 90,806 cases of TB 16,891 cases of AIDS –2,160 reported with TB 3,125 cases of co-infection within 1 year –3.45% of all TB patients –18.5% of all AIDS patients –2,436 within 30 days (75%) –689 between 30 days and 1 year

12 Results

13 Results

14 Results

15 Results

16 Conclusions Burden of AIDS-related TB in Rio – HAART may be impacting on decrease Seems to have a limit Very similar pattern with AIDS-related death rates

17 Conclusions Possible explanations: –TB occurs before patients get HAART –Increasing population of patients on HAART Remain at risk for developing TB Additional approaches to controlling TB will be necessary

18 Limitations No AIDS prevalence over time –No adequate denominator for TB after AIDS Database linkage is not perfect –Theres no reason to believe that sensitivity changed over time Models to infer time trends

19 Methods – Linkage details Eg.: Pennsylvania x Pencilvaneya –Finds the largest chunk lvan – 4 characters in common – 4x2 = 8 –Now compare the lefts (Pennsy x Penci) and the rights (ia and eya) Pen – 3x2 = 6 (and thats it – nsy and ci have no character in common a – 1x2 = 2 (and thats it) –Total – 8+6+2 = 16/total of characters (24) = 0.667

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