{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Karkman A"],"funding":["Academy of Finland","Vetenskapsrådet","Västra Götalandsregionen"],"pagination":["711"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC7692497"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["3(1)"],"pubmed_abstract":["Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across "],"journal":["Communications biology"],"pubmed_title":["Predicting clinical resistance prevalence using sewage metagenomic data."],"pmcid":["PMC7692497"],"funding_grant_id":["315678","ALFGBG-717901","2018-02835","2018-05771"],"pubmed_authors":["Karkman A","Berglund F","Kristiansson E","Larsson DGJ","Flach CF"],"additional_accession":[]},"is_claimable":false,"name":"Predicting clinical resistance prevalence using sewage metagenomic data.","description":"Antibiotic resistance surveillance through regional and up-to-date testing of clinical isolates is a foundation for implementing effective empirical treatment. Surveillance data also provides an overview of geographical and temporal changes that are invaluable for guiding interventions. Still, due to limited infrastructure and resources, clinical surveillance data is lacking in many parts of the world. Given that sewage is largely made up of human fecal bacteria from many people, sewage epidemiology could provide a cost-efficient strategy to partly fill the current gap in clinical surveillance of antibiotic resistance. Here we explored the potential of sewage metagenomic data to assess clinical antibiotic resistance prevalence using environmental and clinical surveillance data from across ","dates":{"release":"2020-01-01T00:00:00Z","publication":"2020 Nov","modification":"2026-05-02T11:23:19.494Z","creation":"2025-02-19T03:26:40.04Z"},"accession":"S-EPMC7692497","cross_references":{"pubmed":["33244050"],"doi":["10.1038/s42003-020-01439-6"]}}