The End TB Strategy, adopted in 2014, aims to end the TB epidemic by 2035 by reducing TB deaths by 95%. Achieving this goal requires innovative health technologies, better TB prevention and care approaches, and rapid adoption of research-based policies, especially for the most vulnerable populations including children. Annually, 1.2 million children under 15 develop TB, with over 250,000 deaths, occurring in a vast majority in undiagnosed/untreated children. Only 44% of paediatric TB cases are reported, and for children under 5, this drops to 35%. Low case detection is largely due to the paucibacillary nature of the disease and challenges in respiratory sample collection contributing to the low microbiological yield in children. Children with inadequate immunity [e.g. children living with HIV (CLHIV), or those with severe acute malnutrition (SAM)] or severe pneumonia are at higher risk of underdiagnosis and of dying from TB.
The World Health Organization (WHO) has prioritized improved diagnostics in the field of child TB. Currently, in the absence of highly sensitive TB diagnostic tool for children, most children are started on treatment only on the basis of high clinical suspicion. Treatment Decision Algorithms (TDAs) assign scores to clinical and radiographic features or microbiological tests and recommend TB treatment initiation above a pre-defined total score. TDAs enable rapid and uniform treatment decision-making. In 2022, WHO conditionally recommended TDAs for diagnosing pulmonary TB in children under 10 years and suggested two TDAs for use in settings with and without chest X-ray (CXR). Decentralizing childhood TB services is essential to increase access to TB diagnosis and will require strengthening clinical skills and treatment decision-making capacity. Data on the diagnostic accuracy of TDAs, their feasibility, acceptability by end-users, effectiveness, and cost-effectiveness are crucial to update the current WHO policy and operational handbook, national policies, and clinical curricula. A comprehensive TDA-based approach could integrate other specific TDAs developed for CLHIV and those with SAM if they outperform the WHO-suggested TDAs. It would also integrate a disease severity assessment step to enable shorter treatment for non-severe TB cases. These tools should align with healthcare workers’ practices at primary and district levels, supported by digital innovations like clinical decision support systems (CDSS) to improve decentralized TB care quality and delivery.
In this context, the general objective of the Decide-TB project is to generate evidence for the implementation of a comprehensive TDA-based approach for TB in children living in high TB-burden and resource-limited countries, at DH and PHC levels, and to facilitate integration of this evidence within practices and policies.
