Clinical and epidemiological profile of tuberculosis in an urban area with high human development index in southeastern Brazil. Time series study

Abstract

CONTEXT AND OBJECTIVE: In the twenty-first century, tuberculosis remains a serious public health problem in Brazil. The aim here was to characterize tuberculosis in a municipality with a high human development index (HDI), based on clinical and epidemiological variables. DESIGN AND SETTING: Epidemiological study with analysis of incidence that included 533 new cases of tuberculosis in the municipality of Araraquara, São Paulo, reported to the Brazilian Notifiable Diseases Information System (SINAN) between 2002 and 2011. METHODS: To identify trends, this period was divided into two five-year periods (2002-2006 and 2007-2011). The incidence rates were compared using ratios and confidence intervals. RESULTS: The incidence of tuberculosis was 26.82 cases per 100,000 inhabitants, and decreased by 22% between the two periods, which was statistically significant. Cases were more prevalent among men (72.61%) and among adults between 30 and 59 years of age with non-specialized professions and low education levels. There was a statistically significant reduction in cases among individuals over 50. The age group with highest incidence was 50-59 years in the first period and 30-39 years in the second. Total recovery occurred in more than 70%. There was a reduction in the number of diagnoses made within primary care and an increase within public hospital care between the two periods. The most common coinfections were AIDS and hepatitis C. CONCLUSIONS: The incidence of tuberculosis in this municipality was lower than the national incidence, with a declining trend and a high cure rate, and the main coinfections were AIDS and hepatitis C. IMedical Doctor, Doctor and Adjunct Professor,

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“…Using mathematical models to explore the pattern of incidence had been developed in infectious diseases control. For example, time series analysis was used for hand, foot, and mouth disease and TB [9,10], autoregressive integrated moving average (ARIMA) model for hepatitis A and in uenza [11,12], temporal analysis for TB and human immunode ciency virus (TB/HIV) co-infection [13]. Different models are suitable for different data characteristics.…”