Antimicrobial Resistance Surveillance: Data Harmonisation and Data Selection within Secondary Data Use

• Published in: Antibiotics (Basel) Vol. 13; no. 7; p. 656
• Main Authors: Bleischwitz, Sinja, Winkelmann, Tristan Salomon, Pfeifer, Yvonne, Fischer, Martin Alexander, Pfennigwerth, Niels, Hammerl, Jens André, Binsker, Ulrike, Hans, Jörg B., Gatermann, Sören, Käsbohrer, Annemarie, Werner, Guido, Kreienbrock, Lothar
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.07.2024
• Subjects: Analysis; Animal human relations; Animals; Antibacterial agents; Antibiotics; Antimicrobial agents; Antimicrobial resistance; Bacteria; Carbapenems; Case studies; cluster analysis; Colistin; Data analysis; Data collection; Data management; Drug resistance; Drug resistance in microorganisms; E coli; Enterobacteriaceae; Epidemiology; Food; Food sources; Genomes; Health aspects; Information management; Laboratories; molecular surveillance; Monitoring systems; multidrug resistance; One Health; Public health; Statistical analysis; Surveillance; Surveillance systems; Tetracycline; Tetracyclines; Variables; Germany
• ISSN: 2079-6382; 2079-6382
• DOI: 10.3390/antibiotics13070656

Resistance to last-resort antibiotics is a global threat to public health. Therefore, surveillance and monitoring systems for antimicrobial resistance should be established on a national and international scale. For the development of a One Health surveillance system, we collected exemplary data on carbapenem and colistin-resistant bacterial isolates from human, animal, food, and environmental sources. We pooled secondary data from routine screenings, hospital outbreak investigations, and studies on antimicrobial resistance. For a joint One Health evaluation, this study incorporates epidemiological metadata with phenotypic resistance information and molecular data on the isolate level. To harmonise the heterogeneous original information for the intended use, we developed a generic strategy. By defining and categorising variables, followed by plausibility checks, we created a catalogue for prospective data collections and applied it to our dataset, enabling us to perform preliminary descriptive statistical analyses. This study shows the complexity of data management using heterogeneous secondary data pools and gives an insight into the early stages of the development of an AMR surveillance programme using secondary data.