title: Statistical detection of geographic clusters of resistant Escherichia coli in a regional network with WHONET and SaTScan.
abstract: While antimicrobial resistance threatens the prevention, treatment, and control of infectious diseases, systematic analysis of routine microbiology laboratory test results worldwide can alert new threats and promote timely response. This study explores statistical algorithms for recognizing geographic clustering of multi-resistant microbes within a healthcare network and monitoring the dissemination of new strains over time.
  
  
  
  Escherichia coli antimicrobial susceptibility data from a three-year period stored in WHONET were analyzed across ten facilities in a healthcare network utilizing SaTScan's spatial multinomial model with two models for defining geographic proximity. We explored geographic clustering of multi-resistance phenotypes within the network and changes in clustering over time.
  
  
  
  Geographic clustering identified from both latitude/longitude and non-parametric facility groupings geographic models were similar, while the latter was offers greater flexibility and generalizability. Iterative application of the clustering algorithms suggested the possible recognition of the initial appearance of invasive E. coli ST131 in the clinical database of a single hospital and subsequent dissemination to others.
  
  
  
  Systematic analysis of routine antimicrobial resistance susceptibility test results supports the recognition of geographic clustering of microbial phenotypic subpopulations with WHONET and SaTScan, and iterative application of these algorithms can detect the initial appearance in and dissemination across a region prompting early investigation, response, and containment measures.
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.|b London School of Hygiene and Tropical Medicine , Faculty of Infectious and Tropical Diseases and Faculty of Public Health and Policy , London , UK.
authors.forename: Rachel
authors.initials: R
authors.lastname: Park
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.|c Harvard Medical School , Department of Medicine , Boston , MA , USA.
authors.forename: Thomas F
authors.initials: TF
authors.lastname: O'Brien
authors.affiliation: d University of California Irvine School of Medicine , Division of Infectious Diseases and Health Policy Research Institute , Orange , CA , USA.
authors.forename: Susan S
authors.initials: SS
authors.lastname: Huang
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.|e Harvard Pilgrim Health Care and Harvard Medical School , Department of Population Medicine , Boston , MA , USA.
authors.forename: Meghan A
authors.initials: MA
authors.lastname: Baker
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.
authors.forename: Deborah S
authors.initials: DS
authors.lastname: Yokoe
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.|c Harvard Medical School , Department of Medicine , Boston , MA , USA.|e Harvard Pilgrim Health Care and Harvard Medical School , Department of Population Medicine , Boston , MA , USA.
authors.forename: Martin
authors.initials: M
authors.lastname: Kulldorff
authors.affiliation: f Premier, Inc ., Safety Solutions , Charlotte , NC , USA.
authors.forename: Craig
authors.initials: C
authors.lastname: Barrett
authors.affiliation: g Mountain States Health Alliance, Department of Infection Prevention , Johnson City , TN , USA.
authors.forename: Jamie
authors.initials: J
authors.lastname: Swift
authors.affiliation: a Brigham and Women's Hospital, Department of Medicine , Division of Infectious Diseases , Boston , MA , USA.|c Harvard Medical School , Department of Medicine , Boston , MA , USA.
authors.forename: John
authors.initials: J
authors.lastname: Stelling
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000008:administration & dosage / Q000627:therapeutic use; D016000:Cluster Analysis; D003428:Cross Infection / Q000453:epidemiology* / Q000382:microbiology / Q000517:prevention & control; D003430:Cross-Sectional Studies; D004196:Disease Outbreaks / Q000517:prevention & control / Q000706:statistics & numerical data*; D024881:Drug Resistance, Bacterial; D004926:Escherichia coli / Q000187:drug effects / Q000302:isolation & purification*; D004927:Escherichia coli Infections / Q000188:drug therapy / Q000453:epidemiology* / Q000382:microbiology* / Q000517:prevention & control; D005843:Geography; D006801:Humans; D008826:Microbial Sensitivity Tests; D008962:Models, Theoretical
chemical_list: D000900:Anti-Bacterial Agents
keywords: Escherichia coli; Escherichia coli ST131; Geographic clustering; SaTScan; WHONET; antimicrobial resistance; outbreak detection