Cough assessment is central to the clinical management of respiratory diseases, including tuberculosis (TB), but strategies to objectively and unobtrusively measure cough are lacking. Acoustic epidemiology is an emerging field that uses technology to detect cough sounds and analyze cough patterns to improve health outcomes among people with respiratory conditions linked to cough. This field is increasingly exploring the potential of artificial intelligence (AI) for more advanced applications, such as analyzing cough sounds as a biomarker for disease screening. While much of the data are preliminary, objective cough assessment could potentially transform disease control programs, including TB, and support individual patient management. Here, we present an overview of recent advances in this field and describe how cough assessment, if validated, could support public health programs at various stages of the TB care cascade.

Background

Decentralised molecular testing for tuberculosis could reduce missed diagnoses and losses to follow-up in high-burden settings. The aim of this study was to evaluate the cost and cost-effectiveness of the Xpert Performance Evaluation for Linkage to Tuberculosis Care (XPEL-TB) study strategy, a multicomponent strategy including decentralised molecular testing for tuberculosis, in Uganda.

Methods

We conducted a costing and cost-effectiveness analysis nested in a pragmatic cluster-randomised trial of onsite (decentralised) versus hub-and-spoke (centralised) testing for tuberculosis with Xpert MTB/RIF Ultra (Xpert) in 20 community health centres in Uganda. We collected empirical data on the cost of the XPEL-TB strategy (decentralised Xpert testing, workflow redesign, and performance feedback) and routine tuberculosis testing (onsite smear microscopy with specimen transport for centralised Xpert testing) from the health system perspective. Time-and-motion studies were performed to estimate activity-based service costs. Cost-effectiveness was assessed as the incremental cost (2019 US$) per tuberculosis diagnosis and per 14-day treatment initiation.

Findings

The XPEL-TB study ran from Oct 22, 2018, to March 1, 2020. Effectiveness and cost-effectiveness outcomes were assessed from Dec 1, 2018, to Nov 30, 2019 and included 4867 women and 3139 men. On a per-test basis, the cost of decentralised ($20·46, range $17·85-25·72) and centralised ($18·20, range $16·58-24·25) Xpert testing was similar. However, decentralised testing resulted in more patients receiving appropriate Xpert testing, so the per-patient cost of decentralised testing was higher: $20·28 (range $17·68-25·48) versus $9·59 (range $7·62-14·34). The XPEL-TB strategy was estimated to cost $1332 (95% uncertainty range $763-5558) per incremental tuberculosis diagnosis and $687 ($501-1207) per incremental patient initiating tuberculosis treatment within 14 days. Cost-effectiveness was reduced in sites performing fewer than 150-250 tests annually.

Interpretation

The XPEL-TB strategy facilitated higher rates of Xpert testing for tuberculosis at a similar per-test cost and modest incremental cost per tuberculosis diagnosis and treatment initiation. Decentralised Xpert testing, with appropriate implementation supports, should be scaled up to clinics with sufficient testing volume to support a single-module device.

Funding

The National Heart, Lung, and Blood Institute.