Assessing tuberculosis control priorities in high-burden settings: a modelling approach
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VESGA, Juan Fernando, ALEXANDRU, Sofia, VÎLC, Valentina, KRUDU, V., BIVOL, Stela, CELAN, Cristina. Assessing tuberculosis control priorities in high-burden settings: a modelling approach. In: The Lancet Global Health, 2019, vol. 7, pp. 585-595. ISSN 2214-109X. DOI: https://doi.org/10.1016/S2214-109X(19)30037-3
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The Lancet Global Health
Volumul 7 / 2019 / ISSN 2214-109X

Assessing tuberculosis control priorities in high-burden settings: a modelling approach

DOI:https://doi.org/10.1016/S2214-109X(19)30037-3

Pag. 585-595

Vesga Juan Fernando1, Alexandru Sofia2, Vîlc Valentina2, Krudu V.2, Bivol Stela3, Celan Cristina4
 
1 Imperial College London,
2 Institute of Phtysiopneumology „Chiril Draganiuc”,
3 Center for Health Policies and Studies,
4 Center for Health Policies and Studies (PAS)
 
 
Disponibil în IBN: 22 aprilie 2019


Rezumat

Background: In the context of WHO's End TB strategy, there is a need to focus future control efforts on those interventions and innovations that would be most effective in accelerating declines in tuberculosis burden. Using a modelling approach to link the tuberculosis care cascade to transmission, we aimed to identify which improvements in the cascade would yield the greatest effect on incidence and mortality. Methods: We engaged with national tuberculosis programmes in three country settings (India, Kenya, and Moldova) as illustrative examples of settings with a large private sector (India), a high HIV burden (Kenya), and a high burden of multidrug resistance (Moldova). We collated WHO country burden estimates, routine surveillance data, and tuberculosis prevalence surveys from 2011 (for India) and 2016 (for Kenya). Linking the tuberculosis care cascade to tuberculosis transmission using a mathematical model with Bayesian melding in each setting, we examined which cascade shortfalls would have the greatest effect on incidence and mortality, and how the cascade could be used to monitor future control efforts. Findings: Modelling suggests that combined measures to strengthen the care cascade could reduce cumulative tuberculosis incidence by 38% (95% Bayesian credible intervals 27–43) in India, 31% (25–41) in Kenya, and 27% (17–41) in Moldova between 2018 and 2035. For both incidence and mortality, modelling suggests that the most important cascade losses are the proportion of patients visiting the private health-care sector in India, missed diagnosis in health-care settings in Kenya, and drug sensitivity testing in Moldova. In all settings, the most influential delay is the interval before a patient's first presentation for care. In future interventions, the proportion of individuals with tuberculosis who are on high-quality treatment could offer a more robust monitoring tool than routine notifications of tuberculosis. Interpretation: Linked to transmission, the care cascade can be valuable, not only for improving patient outcomes but also in identifying and monitoring programmatic priorities to reduce tuberculosis incidence and mortality. Funding: US Agency for International Development, Stop TB Partnership, UK Medical Research Council, and Department for International Development.