India harbours the world’s largest burden of tuberculosis, with approximately 27% of the estimated global burden. Although considerable measures have been taken since the roll-out of the End TB strategy, in 2015, to increase case detection and improve treatment quality, the overall quality of care remains poor and estimates on incidence remain highly uncertain, because of the poor notification rates, especially from the private healthcare sector, where nearly half of all individuals seek care.
In 2017, India’s National Strategic Plan for Tuberculosis Elimination brought forward extremely ambitious targets of an 80% reduction in incidence by 2025. The first step of the plan proposes a scale-up of case-detection through active case-finding, in order to increase case notification rates and reduce the diagnostic and treatment initiation delays, often associated with tuberculosis care.
The evidence for the value of active case-finding interventions for tuberculosis, however, is mixed and highlights a substantial geographical imbalance of studies. A recent systematic review has encouraged the implementation of targeted active case-finding interventions, suggesting these may have an important effect on the prevalence of disease. Despite this, there remains some scepticism around these interventions, which can be costly and difficult to implement on a large scale, and because of the diverse number of factors that can affect their impact.
This thesis aims to investigate the value of routine active case-finding interventions in high-burden settings, implemented using available tools for screening and diagnosis. Epidemiological data is used in the development of the mathematical models used in the analyses, and costing information is included to allow an estimation of the financial implications of this undertaking.