Modeling the impact of tuberculosis control strategies in highly endemic overcrowded prisons.

Abstract : BACKGROUND: Tuberculosis (TB) in prisons is a major health problem in countries of high and intermediate TB endemicity such as Brazil. For operational reasons, TB control strategies in prisons cannot be compared through population based intervention studies. METHODOLOGY/PRINCIPAL FINDINGS: A mathematical model is proposed to simulate the TB dynamics in prison and evaluate the potential impact on active TB prevalence of several intervention strategies. The TB dynamics with the ongoing program was simulated over a 10 year period in a Rio de Janeiro prison (TB prevalence 4.6 %). Then, a simulation of the DOTS strategy reaching the objective of 70 % of bacteriologically-positive cases detected and 85 % of detected cases cured was performed; this strategy reduced only to 2.8% the average predicted TB prevalence after 5 years. Adding TB detection at entry point to DOTS strategy had no major effect on the predicted active TB prevalence. But, adding further a yearly X-ray mass screening of inmates reduced the predicted active TB prevalence below 1%. Furthermore, according to this model, after applying this strategy during 2 years (three annual screenings), the TB burden would be reduced and the active TB prevalence could be kept at a low level by associating X-ray screening at entry point and DOTS. CONCLUSIONS/SIGNIFICANCE: We have shown that X-ray mass screenings should be considered to control TB in highly endemic prison. Prisons with different levels of TB prevalence could be examined thanks to this model which provides a rational tool for public health deciders.
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PLoS ONE, Public Library of Science, 2008, 3 (5), pp.e2100. 〈10.1371/journal.pone.0002100〉
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Judith Legrand, Alexandra Sanchez, Francoise Le Pont, Luiz Camacho, Bernard Larouze. Modeling the impact of tuberculosis control strategies in highly endemic overcrowded prisons.. PLoS ONE, Public Library of Science, 2008, 3 (5), pp.e2100. 〈10.1371/journal.pone.0002100〉. 〈inserm-00416059〉

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