Modelling the Impact of Different Tuberculosis Control Interventions on the Prevalence of Tuberculosis in an Overcrowded Prison

The aim of this study was to simulate the effects of tuberculosis (TB) treatment strategies interventions in an overcrowded and poorly ventilated prison with both high (5 months) and low (3 years) turnover of inmates against improved environmental conditions. We used a deterministic transmission model to simulate the effects of treatment of latent TB infection and active TB, or the combination of both treatment strategies. Without any intervention, the TB prevalence is estimated to increase to 8.8% for a prison with low turnover of inmates but modestly stabilize at 5.8% for high-turnover prisons in a 10-year period. Reducing overcrowding from 6 to 4 inmates per housing cell and increasing the ventilation rate from 2 to 12 air changes per hour combined with any treatment strategy would further reduce the TB prevalence to as low as 0.98% for a prison with low inmate turnover.

[1]  F. Altice,et al.  Undiagnosed pulmonary tuberculosis among prisoners in Malaysia: an overlooked risk for tuberculosis in the community , 2016, Tropical medicine & international health : TM & IH.

[2]  J. Andrews,et al.  The Impact of Ventilation and Early Diagnosis on Tuberculosis Transmission in Brazilian Prisons. , 2015, The American journal of tropical medicine and hygiene.

[3]  J. Andrews,et al.  Active and latent tuberculosis in Brazilian correctional facilities: a cross-sectional study , 2015, BMC Infectious Diseases.

[4]  F. Altice,et al.  Latent tuberculosis infection in a Malaysian prison: implications for a comprehensive integrated control program in prisons , 2014, BMC Public Health.

[5]  F. Altice,et al.  Prevalence of tuberculosis symptoms and latent tuberculous infection among prisoners in northeastern Malaysia. , 2013, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[6]  C. Bhunu,et al.  Modeling the impact of early therapy for latent tuberculosis patients and its optimal control analysis , 2013, Journal of biological physics.

[7]  Delfim F. M. Torres,et al.  Optimal control for a tuberculosis model with reinfection and post-exposure interventions. , 2013, Mathematical biosciences.

[8]  A. Verster,et al.  Tuberculosis and HIV in people who inject drugs: evidence for action for tuberculosis, HIV, prison and harm reduction services , 2012, Current opinion in HIV and AIDS.

[9]  S. Lawn,et al.  Tuberculosis in a South African prison - a transmission modelling analysis. , 2011, South African medical journal = Suid-Afrikaanse tydskrif vir geneeskunde.

[10]  Martin McKee,et al.  Addressing institutional amplifiers in the dynamics and control of tuberculosis epidemics. , 2011, The American journal of tropical medicine and hygiene.

[11]  Brian G. Williams,et al.  Tuberculosis Incidence in Prisons: A Systematic Review , 2010, PLoS medicine.

[12]  E. Veitch,et al.  The Health Crisis of Tuberculosis in Prisons Extends beyond the Prison Walls , 2010, PLoS medicine.

[13]  L. Podewils,et al.  The role of chronic hepatitis in isoniazid hepatotoxicity during treatment for latent tuberculosis infection. , 2009, The International Journal of Tuberculosis and Lung Disease.

[14]  M. Mckee,et al.  Mass incarceration can explain population increases in TB and multidrug-resistant TB in European and central Asian countries , 2008, Proceedings of the National Academy of Sciences.

[15]  Judith Legrand,et al.  Modeling the Impact of Tuberculosis Control Strategies in Highly Endemic Overcrowded Prisons , 2008, PloS one.

[16]  C. Bhunu,et al.  Tuberculosis Transmission Model with Chemoprophylaxis and Treatment , 2008, Bulletin of mathematical biology.

[17]  S. Basu,et al.  Prevention of nosocomial transmission of extensively drug-resistant tuberculosis in rural South African district hospitals: an epidemiological modelling study , 2007, The Lancet.

[18]  Marion Muehlen,et al.  Implications of partial immunity on the prospects for tuberculosis control by post-exposure interventions. , 2007, Journal of theoretical biology.

[19]  P. Sleigh,et al.  Modelling the transmission of airborne infections in enclosed spaces , 2006, Epidemiology and Infection.

[20]  E. Ziv,et al.  Early therapy for latent tuberculosis infection. , 2001, American journal of epidemiology.

[21]  Christopher Dye,et al.  Prospects for worldwide tuberculosis control under the WHO DOTS strategy , 1998, The Lancet.

[22]  P E Fine,et al.  The natural history of tuberculosis: the implications of age-dependent risks of disease and the role of reinfection , 1997, Epidemiology and Infection.

[23]  S. Radhakrishna,et al.  The development of clinical tuberculosis following infection with tubercle bacilli. 1. A theoretical model for the development of clinical tuberculosis following infection, linking from data on the risk of tuberculous infection and the incidence of clinical tuberculosis in the Netherlands. , 1982, Tubercle.

[24]  C. Dolea,et al.  World Health Organization , 1949, International Organization.

[25]  T Cohen,et al.  Data needs for evidence-based decisions: a tuberculosis modeler's 'wish list'. , 2013, The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease.

[26]  F. Portaels,et al.  Tuberculosis control in prisons : a manual for programme managers , 2000 .