Tuberculosis (TB) rates among prisoners are more than 20 times that of the general population in Brazil, yet there are limited data available to facilitate the development of effective interventions in this high-transmission setting. We aimed to assess risk factors for TB infection and evaluate the yield of mass screening for active disease among inmates.
We administered a questionnaire and tuberculin skin test (TST) to a population-based sample of inmates from 12 prisons in Central-West Brazil and collected sera for HIV testing and two sputum samples for smear microscopy and culture from participants reporting a cough of any duration. Hierarchical Poisson regression models were used to evaluate factors associated with latent tuberculosis infection (LTBI).
We recruited 3,380 inmates, of which 2,861 (84.6%) were males from 8 prisons, and 519 (15.4%) were females from 4 prisons. Among the 1,020 (30%) subjects who reported a cough, we obtained sputum from 691 (68%) and identified 31 cases of active TB for a point prevalence of 917 (95% CI, 623–1302) per 100,000 prisoners. Evaluation of the two sputum smear samples failed to identify 74% of the TB cases, and 29% of the cases reported less than 2 weeks of symptoms. Obtaining a second culture identified an additional 7 (24%) cases. The prevalences of LTBI were 22.5% and 11.7% for male and female prisoners, respectively and duration of incarceration (in years) was associated with LTBI in male and female in the multivariable model (1.04, 95% CI, 1.01-1.07 and 1.34, 95% CI, 1.06-1.70, respectively). The prevalence of LTBI is 8.6% among newly incarcerated inmates, among whom LTBI prevalence significantly increased by 5% with each year of incarceration.
Although the overall LTBI prevalence among inmates in Central-West Brazil is low, tuberculosis incidence is high (>1,800/100,00), likely due to the high force of infection among a largely susceptible inmate population. Efforts to reduce transmission in prisons may require mass screening for active TB, utilizing sputum culture in case-detection protocols.
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