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The scope and trajectory of today’s escalating antimicrobial resistance (AMR) crisis is inadequately captured by existing surveillance systems, particularly those of lower income settings. AMR surveillance systems typically collate data from routine culture and susceptibility testing performed in diagnostic bacteriology laboratories to support healthcare. Limited access to high quality culture and susceptibility testing results in the dearth of AMR surveillance data, typical of many parts of the world where the infectious disease burden and antimicrobial need are high. Culture and susceptibility testing by traditional techniques is also slow, which limits its value in infection management. Here, we outline hurdles to effective resistance surveillance in many low-income settings and encourage an open attitude towards new and evolving technologies that, if adopted, could close resistance surveillance gaps. Emerging advancements in point-of-care testing, laboratory detection of resistance through or without culture, and in data handling, have the potential to generate resistance data from previously unrepresented locales while simultaneously supporting healthcare. Among them are microfluidic, nucleic acid amplification technology and next-generation sequencing approaches. Other low tech or as yet unidentified innovations could also rapidly accelerate AMR surveillance. Parallel advances in data handling further promise to significantly improve AMR surveillance, and new frameworks that can capture, collate and use alternate data formats may need to be developed. We outline the promise and limitations of such technologies, their potential to leapfrog surveillance over currently available, conventional technologies in use today and early steps that health systems could take towards preparing to adopt them.
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?:doi
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10.1136/bmjgh-2020-003622
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document_parses/pdf_json/f805a76ee3d828243a25abbb57896f8a87d92a00.json
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document_parses/pmc_json/PMC7712442.xml.json
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Leapfrogging laboratories: the promise and pitfalls of high-tech solutions for antimicrobial resistance surveillance in low-income settings
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