Published in PLOS One on 2026-09-18, this study is presented as an attributed evidence briefing. The excerpts below are the original researchers’ words, reproduced under their Creative Commons Attribution licence. Health Signal has selected the abstract and, where needed, opening background paragraphs; the complete methods, results, limitations and references remain in the linked paper.
Original authors: Solomon Wireko, Joseph Nyarko, Kristine Harley Arthur-Quayson, Osman Abu, Rebecca Appiah, Mina Ofosu, Alexander Kwarteng, John Gameli Deku, Ebenezer Senu, Zewdu Dememew, Padmapriya Banada
Source: PLOS One • DOI 10.1371/journal.pone.0346447
Read the complete primary study ↗ · Creative Commons Attribution licence
From the researchers
Abstract
Background
Tuberculosis (TB) remains an important public health problem in Ghana, while rifampicin-resistant TB (RR-TB) poses an additional challenge to TB control. Routine molecular diagnostic data can provide useful information on temporal patterns of TB detection and drug resistance, particularly in regions where population-based surveillance data are limited. However, findings from referral facilities may be influenced by referral patterns and access to diagnostic services and should therefore be interpreted within their health-system context.
We conducted a cross-sectional study using historical GeneXpert MTB/RIF data collected from January 2019 to December 2024 at the Upper East Regional Hospital (UERH), a regional referral facility in Bolgatanga, Ghana. Data were extracted from GeneXpert laboratory and TB programme registers for patients tested for presumptive TB. MTB detection and rifampicin resistance were determined from GeneXpert MTB/RIF results. Temporal differences in categorical outcomes were assessed using Pearson’s chi-square test of independence. Multivariable logistic regression was used to identify factors independently associated with rifampicin resistance.
A total of 6,897 GeneXpert MTB/RIF tests were included. The mean age of the tested population was 44.6 ± 20.4 years, and 56.7% were male. MTB was detected in 1,083 tests (15.7%). MTB detection varied significantly across study years (χ² = 28.46, p < 0.001), with positivity ranging from 9.8% in 2022 to 20.9% in 2021. Among MTB-positive tests, 192/1,083 (17.7%) showed rifampicin resistance. The annual proportion of rifampicin resistance ranged from 9.5% in 2020 to 23.1% in 2023 and varied significantly across years (χ² = 27.13, p < 0.001). Low MTB bacterial load was significantly more frequent among rifampicin-resistant cases. In multivariable analysis, female sex was associated with higher odds of rifampicin resistance after adjustment for age and MTB bacterial-load category (aOR = 1.44, 95% CI: 1.02–2.02; p = 0.037), while low MTB bacterial load was independently associated with rifampicin resistance after adjustment for age and sex (aOR = 9.62, 95% CI: 5.77–16.04; p < 0.001).
MTB detection and rifampicin resistance showed substantial year-to-year variation among patients tested at UERH during 2019–2024. The 17.7% rifampicin-resistance proportion represents a hospital-based estimate among MTB-positive GeneXpert-tested cases and should not be interpreted as the population prevalence of RR-TB in the Upper East Region. The observed pattern nevertheless warrants further investigation to determine the contribution of referral patterns, targeted testing, previous treatment, and other programme factors to the high proportion of rifampicin resistance observed at this referral facility.
Introduction
Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB), remains one of the leading causes of morbidity and mortality from an infectious disease worldwide. In 2023, an estimated 10.6 million people developed TB globally, with substantial mortality occurring among both people without HIV and people living with HIV [1]. Despite the availability of effective diagnostic and treatment services, TB continues to disproportionately affect low- and middle-income countries, including countries in sub-Saharan Africa, where delays in diagnosis, incomplete access to health services, and gaps in case detection contribute to continued transmission [1–3].
Reading this evidence
Use the full paper to check the study design, participant selection, comparator and outcome definitions before drawing a practical conclusion. An association does not by itself show cause and effect. A reported performance measure needs its denominator and uncertainty. A finding from a particular facility, sample or time period should retain that scope when it is discussed elsewhere.
This briefing makes the source accessible within the wider technology & industry desk. It does not assess an individual patient or certify a product. When considering relevance to another health system, examine the original authors’ account of context and limitations, then seek local implementation evidence. The related reporting below provides other studies to read alongside this one; it is a topic connection, rather than a claim that their results are directly comparable.
© 2026 Solomon Wireko, Joseph Nyarko, Kristine Harley Arthur-Quayson, Osman Abu, Rebecca Appiah, Mina Ofosu, Alexander Kwarteng, John Gameli Deku, Ebenezer Senu, Zewdu Dememew, Padmapriya Banada. Excerpts reproduced under CC BY. Selection, formatting and contextual notes by Health Signal. The researchers are the authors of the source study, not members of Health Signal’s staff.
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- Evidence brief: Contribution of xpert MTB/RIF assay and Urine LF-LAM for the diagnosis of tuberculosis in children aged 5 – 14 years, at selected health facilities in Ethiopia, 2016 – 2019
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