Please use this identifier to cite or link to this item:
http://ir.mu.ac.ke:8080/jspui/handle/123456789/10229Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Micheni c, Lisa Nkatha | - |
| dc.contributor.author | Wambua, Sammy | - |
| dc.contributor.author | Karani, Magutah | - |
| dc.contributor.author | Nkaiwuatei, Jimmy | - |
| dc.contributor.author | Bazira, Joel | - |
| dc.contributor.author | Sande, Charles | - |
| dc.date.accessioned | 2026-06-19T06:20:27Z | - |
| dc.date.available | 2026-06-19T06:20:27Z | - |
| dc.date.issued | 2026-01 | - |
| dc.identifier.uri | http://ir.mu.ac.ke:8080/jspui/handle/123456789/10229 | - |
| dc.description.abstract | Introduction: Tuberculosis (TB) remains a major global health concern, particularly in low-income countries where the impact is greater. The lack of proper surveillance tools in these countries is a big impediment to effective TB control. Whole-genome sequencing (WGS) has successfully been integrated into routine TB programs in high-income countries and transformed disease surveillance by providing rapid, high-resolution transmission insights, drug resistance profiling, and outbreak detection. However, its uptake in resource-limited settings where TB burden is most prevalent remains limited. Methods: This review examines how WGS is currently being utilised for TB surveillance and highlights the main obstacles to its adoption in limited-resource settings as well as the strategies that could improve its uptake. A literature search was conducted in PubMed, Google Scholar, and the World Health Organisation (WHO) databases with keywords "whole genome sequencing," "tuberculosis," "surveillance," "transmission," and "drug resistance." Studies published between 2015 and 2025 were prioritised, with a focus on applications in highburden settings. Results: Key challenges identified include infrastructural issues whereby 78% of high-burden countries lack adequate sequencing facilities according to WHO 2023 data; financial barriers, with recurring costs surpassing $150 per sample in low-resource settings as compared to $80 in high-income countries, and a shortage of trained personnel with only 2.3 bioinformaticians being available per African country. Other hurdles involve concerns over data sovereignty, weak regulatory frameworks, and ethical dilemmas surrounding privacy and equitable data usage, with only 31% of low-resource countries having genomic data policies. Nevertheless, promising innovations like portable sequencing devices which have a sensitivity of up to 92% and cloud-based platforms that reduce computational needs by 70% offer scalable opportunities for equitable integration. We also highlight partnership models that blend WHO technical guidance, Global Fund financing, and South-South collaborations that could enhance sustainability. Conclusion: To realise the full potential of WGS in TB-endemic regions, a coordinated approach that combines technical advancements with policy changes, ethical data governance, and sustained investment is needed. Tackling these challenges is essential in achieving equitable, genomics-informed TB control that aligns with global TB elimination goals. | en_US |
| dc.description.sponsorship | School of Health and Human Sciences, Pwani University, Kilifi, Kenya b Research Department, Zihi Institute, Nairobi, Kenya c Pwani University Biosciences Research Centre, Pwani University, Kilifi, Kenya d Research and Conservation Support Society (RECOURSE), Kilifi, Kenya e School of Biodiversity, One Health and Veterinary Medicine, University of Glasgow, Glasgow, United Kingdom f Department of Medical Physiology, School of Medicine, Moi University College of Health Sciences, Eldoret, Kenya g Department of Microbiology, Faculty of Medicine, Mbarara University of Science and Technology, Mbarara, Uganda h Centre for Geographic Medicine Research, Kenya Medical Research Institute - Wellcome Trust, Kilifi, Kenya | en_US |
| dc.publisher | Elseiver | en_US |
| dc.subject | Tuberculosis Whole genome sequencing; Genomic surveillance; Low resource settings | en_US |
| dc.title | Bridging the implementation gap: Challenges and opportunities for integrating whole genome sequencing in tuberculosis surveillance in low-resource settings | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | School of Medicine | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Micheni.pdf | 618.73 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.