695. Regional and Longitudinal Mapping of Escherichia coli Antibiotic Susceptibility
Session: Poster Abstract Session: Resistance Mechanisms: Gram-Negative
Thursday, October 4, 2018
Room: S Poster Hall
Background: Antimicrobial resistance (AMR) is a serious threat to global health with local implications. AMR varies regionally; however, limited tools are available to aid practitioners in appropriate antibiotic selection based on statewide antimicrobial susceptibilities. The objective of this study was to map E. coli antibiotic susceptibility regionally and longitudinally in Wisconsin.   Methods: Antibiograms from 2009, 2013, and 2015 were collected from health systems, hospitals, and clinics in Wisconsin, resulting in 218 antibiograms representing 201,091 gram-negative isolates. E. coli antibiotic susceptibility percentages were weighted by number of isolates and aggregated by county per year.   Results: Spatial interpolation methods (Inverse Distance Weighted, Kriging) were tested by both county center points and facility geocode where available. Susceptibility data for clinically relevant urinary tract infection antibiotics were interpolated to create geographic visualizations of AMR in Wisconsin. Antibiotics included amoxicillin, trimethoprim/sulfamethoxazole, ciprofloxacin, nitrofurantoin, ampicillin, ampicillin/sulbactam, levofloxacin. The interpolation extends to the furthest health system point in each direction and is presented within state boundaries. Facility geocodes were masked from public display for confidentiality. City names were added for orientation. The mapping depicts regional differences, such as 2015 ampicillin susceptibilities ranging 55% to 64% (Figure 1).  The maps provide a preliminary susceptibility prediction in areas where no AMR data were available. Average susceptibilities were compared across 2009, 2013, and 2015 to map areas with the highest rates of AMR change.   Conclusion: The described mapping provides a novel visualization of AMR across Wisconsin. The maps created will be utilized in continued efforts to improve the functionality of AMR data in clinical practice to optimize antimicrobial choice.                 
Laurel Legenza, PharmD, MS1, Susanne Barnett, PharmD1, Jim Lacy, MS2, Natalee Desotell, MS3, Andrea Eibergen, BS Candidiate2 and Warren Rose, PharmD, MPH4, (1)Pharmacy Practice Division, University of Wisconsin School of Pharmacy, Madison, WI, (2)State Cartographer's Office, University of Wisconsin-Madison Department of Geography, Madison, WI, (3)Yale School of Public Health, New Haven, CT, (4)School of Pharmacy, University of Wisconsin-Madison, Madison, WI

Disclosures:

L. Legenza, None

S. Barnett, None

J. Lacy, None

N. Desotell, None

A. Eibergen, None

W. Rose, None

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