Comparing different technologies for active TB case-finding among the homeless: A transmission-dynamic modelling study

Tendai Mugwagwa*, Helen R. Stagg, Ibrahim Abubakar, Peter White

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)

Abstract

Homeless persons have elevated risk of tuberculosis (TB) and are under-served by conventional health services. Approaches to active case-finding (ACF) and treatment tailored to their needs are required. A transmission-dynamic model was developed to assess the effectiveness and efficiency of screening with mobile Chest X-ray, GeneXpert, or both. Effectiveness of ACF depends upon the prevalence of infection in the population (which determines screening 'yield'), patient willingness to wait for GeneXpert results, and treatment adherence. ACF is efficient when TB prevalence exceeds 78/100,000 and 46% of drug sensitive TB cases and 33% of multi-drug resistant TB cases complete treatment. This threshold increases to 92/100,000 if additional post-ACF enhanced case management (ECM) increases treatment completion to 85%. Generally, the most efficient option is one-step screening of all patients with GeneXpert, but if too many patients (>27% without ECM, >19% with ECM) are unwilling to wait the 90 minutes required then two-step screening using chest X-ray (which is rapid) followed by GeneXpert for confirmation of TB is the most efficient option. Targeted ACF and support services benefit health through early successful treatment and averting TB transmission and disease. The optimal strategy is setting-specific, requiring careful consideration of patients' needs regarding testing and treatment.

Original languageEnglish
Article number1433
JournalScientific Reports
Volume8
Issue number1
DOIs
Publication statusPublished - 1 Dec 2018

Bibliographical note

Funding Information:
P.J.W. thanks the Medical Research Council (MRC) for Centre funding (MR/K010174/1). P.J.W. and T.M. thank the NIHR Health Protection Research Unit in Modelling Methodology at Imperial College London, in partnership with Public Health England, for funding (HPRU-2012-10080). I.A. was supported by NIHR, the Department of Health Policy Research Programme (015/0307), and the MRC. This report is independent research supported by the National Institute for Health Research (Post Doctoral Fellowship, Dr Helen Stagg, PDF-2014-07-008). The views expressed are those of the authors and not necessarily those of the Department of Health, MRC, NHS, NIHR or Public Health England. The funders of this study had no role in study design; data collection, analysis, or interpretation; or writing of the report. The corresponding author had full access to all the data in the study and the final responsibility to submit for publication.

Publisher Copyright:
© 2018 The Author(s).

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