190 likes | 312 Views
AIDS-Related Tuberculosis in Rio de Janeiro, Brazil. Antonio G F Pacheco. 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?.
E N D
AIDS-Related Tuberculosis in Rio de Janeiro, Brazil Antonio G F Pacheco
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?
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
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
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
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
Methods - AIDS Case Definition • One out of four conditions: • HIV+ and one AIDS defining illness – Modified CDC criteria • HIV+ and CD4 counts < 350/mm3 • 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
Methods – Co-infection detection • Linkage • SINAN-AIDS and SINAN-TB • Criteria • First name and last name adapted Soundex • Patient’s and mother’s (when available) • String similarity index (‘Gestalt’ algorithm) • Date of birth (allowing errors) • Algorithm written in Python • Sensitivity ~ 92% • Specificity ~ 99%
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
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)
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
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
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
Limitations • No AIDS prevalence over time • No adequate denominator for TB after AIDS • Database linkage is not perfect • There’s no reason to believe that sensitivity changed over time • Models to infer time trends
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 that’s it – ‘nsy’ and ‘ci’ have no character in common • ‘a’ – 1x2 = 2 (and that’s it) • Total – 8+6+2 = 16/total of characters (24) = 0.667