XVIII International AIDS Conference


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AIDS and Hansen's disease co-infection in Brazil: epidemiological scenario

A.R. Caruso da Cunha, G.F. Mendes Pereira

Ministry of Health, STD, AIDS and Hepatitis Department, Information and Surveillance Unit, Brasília, Brazil

Background: Given the epidemiological contexts of AIDS and Hansen's Disease in Brazil, with AIDS incidence increasing in the North, Northeast and Middle-west macro-regions of Brazil, exactly where the highest coefficients of detection of Hanson's Disease are found, this paper presents a descriptive analysis of the interaction between the two.
It analyses their temporal and spatial distributions as a function of patient characteristics to identify epidemiological patterns of co-infection occurrence and attempts to quantify the magnitude of the problem.
Methods: Secondary data from the Ministry of Health's Notifiable Diseases Information System (SINAN), Laboratory Test Control System (SISCEL) and System for Logistic Control of Drugs (SICLOM) is used to determine the prevalence of the AIDS-Hansen's Disease co-infection in Brazil.
The population studied was consisted of men and women of all age groups notified to the SINAN and/or registered in the SISCEL and SICLOM, for the period 1980 to 2007, on the basis of the criteria recommended for defining concomitant cases of AIDS and Hansen's Disease.
Results: The co-infection showed temporal progression of the co-infection over the study period. Probabilistic methods identified 1,367 registrations of associations of the two diseases and established prevalence of 0.28% for AIDS/Hansen's disease and 0.38% for Hansen's Disease/AIDS. Accordingly, it is essential to monitor the prevalence and distribution of the AIDS Hansen's Disease association to provide supporting information for decision-making.
Conclusions: The results show the importance of implementing strategies to build health staff capacity to address co-infected patients in an integrated and specific manner avoiding unnecessary and/or unsuitable interventions.
Although the identification is predictive in nature and embodies a certain margin of error like any other forecast, the data point to the likely evolution of the this co-infection indicating the need for measures to reduce risks and consequences.

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