Implementing molecular tuberculosis diagnostic methods in limited-resource and high-burden countries
Tuberculosis (TB) is one of the deadliest infectious diseases in the world with more than a million people dying of TB each year. Accurate and timely TB diagnosis has the potential to alleviate the global TB burden; therefore, one of the pillars of the End TB Strategy developed by the World Health...
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Main Authors: | , , , , |
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Format: | Article PeerReviewed |
Language: | English |
Published: |
European Respiratory Society
2022
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Subjects: | |
Online Access: | https://repository.ugm.ac.id/278792/1/Saktiawati_KKMK.pdf https://repository.ugm.ac.id/278792/ https://breathe.ersjournals.com/content/18/4/220226 https://doi.org/10.1183/20734735.0226-2022 |
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Institution: | Universitas Gadjah Mada |
Language: | English |
Summary: | Tuberculosis (TB) is one of the deadliest infectious diseases in the world with more than a million people
dying of TB each year. Accurate and timely TB diagnosis has the potential to alleviate the global TB burden; therefore, one of the pillars of the End TB Strategy developed by the World Health Organization (WHO) is the early diagnosis of TB, including universal drug-susceptibility testing (DST). The WHO emphasises the importance of DST before treatment initiation, using molecular WHO-recommended rapid diagnostic tests (mWRDs). Currently available mWRDs are nucleic acid amplification tests, line probe assays, whole genome
sequencing, and targeted next-generation sequencing. However, implementing the sequencing mWRDs in routine laboratories in low-income countries is constrained by the existing infrastructure, high cost, the specialised skills needed, data storage, and the current delay in results compared with other routine methods. These limitations are pronounced in resource-limited settings, which often have a high TB burden and need for innovative TB diagnostic technologies. In this article we propose several possible solutions, like adapting infrastructure capacity to needs, advocating for lowering costs, building bioinformatics and laboratory capacity, and increasing the use of open-access resources for software and publications. |
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