TY - JOUR
T1 - Innovations in genomic antimicrobial resistance surveillance
AU - SEDRIC Genomics Surveillance Working Group
AU - Wheeler, Nicole E.
AU - Price, Vivien
AU - Cunningham-Oakes, Edward
AU - Tsang, Kara K.
AU - Nunn, Jamie G.
AU - Midega, Janet T.
AU - Anjum, Muna F.
AU - Wade, Matthew J.
AU - Feasey, Nicholas A.
AU - Peacock, Sharon J.
AU - Jauneikaite, Elita
AU - Baker, Kate S.
N1 - Publisher Copyright:
© 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license
PY - 2023/12
Y1 - 2023/12
N2 - Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance and epidemiology; however, routine adoption of these technologies is challenging, particularly in low-income and middle-income countries. As part of a wider series of workshops and online consultations, a group of experts in AMR pathogen genomics and computational tool development conducted a situational analysis, identifying the following under-used innovations in genomic AMR surveillance: clinical metagenomics, environmental metagenomics, gene or plasmid tracking, and machine learning. The group recommended developing cost-effective use cases for each approach and mapping data outputs to clinical outcomes of interest to justify additional investment in capacity, training, and staff required to implement these technologies. Harmonisation and standardisation of methods, and the creation of equitable data sharing and governance frameworks, will facilitate successful implementation of these innovations.
AB - Whole-genome sequencing of antimicrobial-resistant pathogens is increasingly being used for antimicrobial resistance (AMR) surveillance, particularly in high-income countries. Innovations in genome sequencing and analysis technologies promise to revolutionise AMR surveillance and epidemiology; however, routine adoption of these technologies is challenging, particularly in low-income and middle-income countries. As part of a wider series of workshops and online consultations, a group of experts in AMR pathogen genomics and computational tool development conducted a situational analysis, identifying the following under-used innovations in genomic AMR surveillance: clinical metagenomics, environmental metagenomics, gene or plasmid tracking, and machine learning. The group recommended developing cost-effective use cases for each approach and mapping data outputs to clinical outcomes of interest to justify additional investment in capacity, training, and staff required to implement these technologies. Harmonisation and standardisation of methods, and the creation of equitable data sharing and governance frameworks, will facilitate successful implementation of these innovations.
UR - http://www.scopus.com/inward/record.url?scp=85176914838&partnerID=8YFLogxK
U2 - 10.1016/S2666-5247(23)00285-9
DO - 10.1016/S2666-5247(23)00285-9
M3 - Review article
AN - SCOPUS:85176914838
SN - 2666-5247
VL - 4
SP - e1063-e1070
JO - The Lancet Microbe
JF - The Lancet Microbe
IS - 12
ER -