Evaluating smartphone-based cough frequency monitoring for tuberculosis screening and triage in Uganda: A mixed-methods evaluation
4 affiliations
- 1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- 2Uganda Tuberculosis Implementation Research Consortium, Walimu, Kampala, Uganda
- 3Division of Infectious Diseases, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- 4Clinical Epidemiology Unit, Department of Medicine, Makerere University College of Health Sciences, Kampala, Uganda
Abstract
Symptom-based tuberculosis screening usually depends on self-reported cough, which is subjective. Passive smartphone cough monitoring offers a more objective alternative. This study assessed the diagnostic accuracy and implementation feasibility of smartphone-based cough frequency monitoring for identifying likely TB cases in Uganda. Adults (≥15 years) screened in community settings or tested at Kampala health facilities underwent microbiological testing and 48 hours of cough monitoring with the Hyfe Research app. TB status was determined by Xpert MTB/RIF Ultra and culture, with inverse probability weighting to adjust for differential enrollment. Cough frequency was compared between participants with and without TB, and accuracy assessed using weighted ROC curves. Staff interviews, analyzed thematically, explored provider-side implementation challenges. Of 884 enrolled participants, 197 had both valid recordings and TB status (101 community, 96 facility). Median cough frequency was higher among those with TB: 2.2 coughs/hour (IQR 0.8–6.1) vs 0.9 (0.4–2.0) in the community, and 6.7 (2.6–27.5) vs 2.4 (0.9–4.8) in facilities (Wilcoxon P < 0.0001 for both). AUCs were 0.69 (95% CI 0.58–0.79) in the community and 0.76 (95% CI 0.60–0.88) in facilities. For self-reported cough at 90% sensitivity, specificities were 55% (95% CI 29–88%) and 36% (95% CI 17–68%), respectively. Recorded cough frequency correlated moderately with self-reported cough severity, Saint George’s Respiratory Questionnaire scores, and staff-observed coughs. Staff cited device visibility, stigma, and security concerns as barriers. Smartphone-recorded cough frequency was associated with TB status but did not meet accuracy thresholds for stand-alone screening or triage, and implementation problems limited data collection. Addressing these operational barriers will be critical to future development and deployment of cough monitoring tools for TB screening.
Related
- Effect of a Researcher‐Supervised Walking Program With Smartphone‐Based Step Monitoring on Sleep Quality in Older Psychiatric Inpatients: A Randomized Controlled Trial
- Latent tuberculosis infection in focus: Evaluating public concerns, treatment perceptions, and awareness in King Sabatha Dalindyebo Local Municipality, Eastern Cape, South Africa
- Evaluating the acceptability, feasibility, and implementation fidelity of a multipurpose mobile health (mHealth) app used for Tuberculosis (TB) contact tracing by Ward-Based Outreach Teams (WBOTs) in South Africa
- Evaluating miR-122-5p as a biomarker for anti-tuberculosis drug-induced liver injury: diagnostic efficacy and correlation with liver function indicators
- A quasi-experimental study evaluating the effectiveness of a male-specific tuberculosis screening and diagnosis intervention in Uganda (IGNITE).
BibTeX
@article{biche2026evaluating,
title = {{Evaluating smartphone-based cough frequency monitoring for tuberculosis screening and triage in Uganda: A mixed-methods evaluation}},
author = {Patrick Biché and Francis Kayondo and Annet Nalutaaya and James Mukiibi and Mariam Nantale and Joowhan Sung and David W. Dowdy and Achilles Katamba and Emily A. Kendall},
journal = {PLOS Global Public Health},
year = {2026},
month = oct,
doi = {10.1371/journal.pgph.0005201},
url = {https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0005201},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Evaluating smartphone-based cough frequency monitoring for tuberculosis screening and triage in Uganda: A mixed-methods evaluation
AU - Patrick Biché
AU - Francis Kayondo
AU - Annet Nalutaaya
AU - James Mukiibi
AU - Mariam Nantale
AU - Joowhan Sung
AU - David W. Dowdy
AU - Achilles Katamba
AU - Emily A. Kendall
PY - 2026
DA - 2026/10/01
JO - PLOS Global Public Health
DO - 10.1371/journal.pgph.0005201
UR - https://journals.plos.org/globalpublichealth/article?id=10.1371/journal.pgph.0005201
AB - Symptom-based tuberculosis screening usually depends on self-reported cough, which is subjective. Passive smartphone cough monitoring offers a more objective alternative. This study assessed the diagnostic accuracy and implementation feasibility of smartphone-based cough frequency monitoring for identifying likely TB cases in Uganda. Adults (≥15 years) screened in community settings or tested at Kampala health facilities underwent microbiological testing and 48 hours of cough monitoring with the Hyfe Research app. TB status was determined by Xpert MTB/RIF Ultra and culture, with inverse probability weighting to adjust for differential enrollment. Cough frequency was compared between participants with and without TB, and accuracy assessed using weighted ROC curves. Staff interviews, analyzed thematically, explored provider-side implementation challenges. Of 884 enrolled participants, 197 had both valid recordings and TB status (101 community, 96 facility). Median cough frequency was higher among those with TB: 2.2 coughs/hour (IQR 0.8–6.1) vs 0.9 (0.4–2.0) in the community, and 6.7 (2.6–27.5) vs 2.4 (0.9–4.8) in facilities (Wilcoxon P < 0.0001 for both). AUCs were 0.69 (95% CI 0.58–0.79) in the community and 0.76 (95% CI 0.60–0.88) in facilities. For self-reported cough at 90% sensitivity, specificities were 55% (95% CI 29–88%) and 36% (95% CI 17–68%), respectively. Recorded cough frequency correlated moderately with self-reported cough severity, Saint George’s Respiratory Questionnaire scores, and staff-observed coughs. Staff cited device visibility, stigma, and security concerns as barriers. Smartphone-recorded cough frequency was associated with TB status but did not meet accuracy thresholds for stand-alone screening or triage, and implementation problems limited data collection. Addressing these operational barriers will be critical to future development and deployment of cough monitoring tools for TB screening.
SN - 2767-3375
ER -