P C Hill1, C Dye2, K Viney3, K Tabutoa4, T Kienene4, K Bissell5, B G Williams6, R Zachariah7, B J Marais8, A D Harries5. 1. <label>*</label>Centre for International Health, Department of Preventive and Social Medicine, Faculty of Medicine, University of Otago, Dunedin, New Zealand; 2. <label><sup>†</sup></label>HIV/AIDS, Tuberculosis, Malaria & Neglected Tropical Diseases Cluster, World Health Organization, Geneva, Switzerland; 3. <label><sup>‡</sup></label>Public Health Division, Secretariat of the Pacific Community, Noumea Cedex, New Caledonia; 4. <label><sup>§</sup></label>National Tuberculosis Control Programme, Ministry of Health and Medical Services, Republic of Kiribati; 5. <label><sup>¶</sup></label>International Union Against Tuberculosis and Lung Disease, Paris, France; 6. <label>*</label>*South African Centre for Epidemiological Modelling and Analysis, Cape Town, South Africa; 7. <label><sup>††</sup></label>Médecins Sans Frontières, Brussels Operational Centre, Luxembourg, Belgium; 8. <label><sup>‡‡</sup></label>Sydney Emerging Infectious Disease and Biosecurity Institute and Centre for Research Excellence in Tuberculosis, University of Sydney, Sydney, New South Wales, Australia;
Abstract
SETTING: The global target of tuberculosis (TB) elimination by 2050 requires new approaches. Active case finding plus mass prophylactic treatment has been disappointing. We consider mass full anti-tuberculosis treatment as an approach to TB elimination in Kiribati, a Pacific Island nation, with a persistent epidemic of high TB incidence. OBJECTIVE: To construct a mathematical model to predict whether mass treatment with a full course of anti-tuberculosis drugs might eliminate TB from the defined population of the Republic of Kiribati. METHODS: We constructed a seven-state compartmental model of the life cycle of Mycobacterium tuberculosis in which active TB disease arises from the progression of infection, reinfection, reactivation and relapse, while distinguishing infectious from non-infectious disease. We evaluated the effects of 5-yearly mass treatment using a range of parameter values to generate outcomes in uncertainty analysis. RESULTS: Assuming population-wide treatment effectiveness for latent tuberculous infection and active TB of ⩾90%, annual TB incidence is expected to fall sharply at each 5-yearly round of treatment, approaching elimination in two decades. The model showed that the incidence rate is sensitive to the relapse rate after successful treatment of TB. CONCLUSION: Mass treatment may help to eliminate TB, at least for discrete or geographically isolated populations.
SETTING: The global target of tuberculosis (TB) elimination by 2050 requires new approaches. Active case finding plus mass prophylactic treatment has been disappointing. We consider mass full anti-tuberculosis treatment as an approach to TB elimination in Kiribati, a Pacific Island nation, with a persistent epidemic of high TB incidence. OBJECTIVE: To construct a mathematical model to predict whether mass treatment with a full course of anti-tuberculosis drugs might eliminate TB from the defined population of the Republic of Kiribati. METHODS: We constructed a seven-state compartmental model of the life cycle of Mycobacterium tuberculosis in which active TB disease arises from the progression of infection, reinfection, reactivation and relapse, while distinguishing infectious from non-infectious disease. We evaluated the effects of 5-yearly mass treatment using a range of parameter values to generate outcomes in uncertainty analysis. RESULTS: Assuming population-wide treatment effectiveness for latent tuberculous infection and active TB of ⩾90%, annual TB incidence is expected to fall sharply at each 5-yearly round of treatment, approaching elimination in two decades. The model showed that the incidence rate is sensitive to the relapse rate after successful treatment of TB. CONCLUSION: Mass treatment may help to eliminate TB, at least for discrete or geographically isolated populations.
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