Back

Exploring trade-offs in diagnostic algorithm, population coverage, and duration of community screening for tuberculosis

Horton, K. C.; Richards, A. S.; Schwalb, A.; Houben, R. M. G. J.

2025-08-26 public and global health
10.1101/2025.08.22.25334237 medRxiv
Show abstract

BackgroundCurrent tuberculosis (TB) prevention and care strategies have failed to reduce disease burden at the pace required to meet global targets. Community screening may enable more rapid declines in TB burden, but evidence is limited. We used mathematical modelling to evaluate trade-offs in diagnostic algorithm, population coverage, and duration of screening. Methods and FindingsWe used a TB model, which recognised symptomatic and asymptomatic infectious TB (defined by whether an individual reported symptoms at screening), as well as non-infectious TB. We simulated diagnostic algorithms targeting symptomatic infectious TB (prolonged cough with confirmatory Xpert Ultra), infectious TB (Xpert Ultra), or all TB (chest X-ray), and we varied population coverage and duration. Main outcomes were estimated reduction in symptomatic TB incidence and TB mortality over a 10-year horizon. Maximum coverage (100%) and duration (five rounds) was projected to reduce symptomatic TB incidence by 26.9% (22.8-31.5%) with the algorithm targeting symptomatic TB and 74.0% (68.5-79.1%) with the algorithm targeting infectious TB. However, incidence rebounded at the end of screening, erasing 9.8% and 15.9%, respectively, of those reductions within five years. The algorithm targeting all TB showed higher potential for rapid reductions - over 98% - with negligible rebound; however, low diagnostic accuracy of current tools led to prohibitive overdiagnosis, with 7.2 false positives per true positive in a single round of screening targeting all TB. Screening algorithms targeting broader disease definitions generally achieved greater impact with lower population coverage and/or duration. Findings were broadly similar for mortality. ConclusionsWe show substantial reductions in TB morbidity and mortality can be achieved by community screening, highlighting the importance of symptom-agnostic algorithms and the need to balance population coverage and duration. To maximise and sustain epidemiological impact, diagnostic tools and treatment regimens for individuals with non-infectious TB are needed.

Matching journals

The top 7 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.