Year: 2025
Type: article
Abstract: Around half of people identified with tuberculosis (TB) during prevalence surveys do not report symptoms, prompting increased interest in the public health implications of asymptomatic TB (aTB), as distinct from symptomatic TB (sTB). A recent World Health Organization report proposes investigating the optimal treatment for aTB, stratifying notification data by symptom status, and publishing incidence estimates based on sTB. We have concerns that the proposed use of aTB/sTB case definitions for surveillance, burden estimation, and clinical management is not supported by evidence. Although TB symptoms are linked to disease severity, we show that self-reported symptoms are an inadequate classifier of disease state, heavily influenced by context and substantial interviewer variability, and TB symptoms may frequently have alternative causes. We advocate for the adoption of more robust measures of severity, better reflecting underlying pathophysiology. Research on the TB disease spectrum should prioritize more objective severity metrics, alongside or instead of symptom-based classification.
Source: Clinical Infectious Diseases
DOI: 10.1093/cid/ciaf611
Institutions: London School of Hygiene & Tropical Medicine, Malawi-Liverpool-Wellcome Trust Clinical Research Programme, University of Glasgow, Universidade Federal de Mato Grosso do Sul, Vrije Universiteit Amsterdam, LMU Klinikum, Biomedical Research and Training Institute, Institut für Infektions- und Tropenmedizin, Ludwig-Maximilians-Universität München
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $4,763
Awards: Advancing epidemiological methods for surveillance of Mycobacterium tuberculosis infection: new approaches to direct case finding, prevention, and measure vaccine effectiveness, G7982722214, Using mathematical modelling & empirical trial data to improve the impact & cost-effectiveness of community-wide active case finding on TB incidence
OpenAlex ID: W4417198238
