Babu Rajendran N.Arieti F.Mena-Benítez C.A.Galia L.Tebon M.Alvarez J.Gladstone B.P.Collineau L.De Angelis G.Duro R.Gaze W.Göpel S.Kanj S.S.Käsbohrer A.Limmathurotsakul D.Lopez de Abechuco E.Mazzolini E.Mutters N.T.Pezzani M.D.Presterl E.Renk H.Rodríguez-Baño J.Săndulescu O.Scali F.Skov R.Velavan T.P.Vuong C.Tacconelli E.Adegnika A.A.Avery L.Bonten M.Cassini A.Chauvin C.Compri M.Damborg P.De Greeff S.Del Toro M.D.Filter M.Franklin A.Gonzalez-Zorn B.Grave K.Hocquet D.Hoelzle L.E.Kalanxhi E.Laxminarayan R.Leibovici L.Malhotra-Kumar S.Mendelson M.Paul M.Muñoz Madero C.Murri R.Piddock L.J.V.Ruesen C.Sanguinetti M.Schilling T.Schrijver R.Schwaber M.J.Scudeller L.Torumkuney D.Van Boeckel T.Vanderhaeghen W.Voss A.Wozniak T.Mahidol University2023-05-192023-05-192023-03-01The Lancet Regional Health - Europe Vol.26 (2023)https://repository.li.mahidol.ac.th/handle/20.500.14594/82384Strategic and standardised approaches to analysis and reporting of surveillance data are essential to inform antimicrobial resistance (AMR) mitigation measures, including antibiotic policies. Targeted guidance on linking full-scale AMR and antimicrobial consumption (AMC)/antimicrobial residues (AR) surveillance data from the human, animal, and environmental sectors is currently needed. This paper describes the initiative whereby a multidisciplinary panel of experts (56 from 20 countries—52 high income, 4 upper middle or lower income), representing all three sectors, elaborated proposals for structuring and reporting full-scale AMR and AMC/AR surveillance data across the three sectors. An evidence-supported, modified Delphi approach was adopted to reach consensus among the experts for dissemination frequency, language, and overall structure of reporting; core elements and metrics for AMC/AR data; core elements and metrics for AMR data. The recommendations can support multisectoral national and regional plans on antimicrobials policy to reduce resistance rates applying a One Health approach.MedicineEPI-Net One Health reporting guideline for antimicrobial consumption and resistance surveillance data: a Delphi approachReviewSCOPUS10.1016/j.lanepe.2022.1005632-s2.0-8514529727926667762