1197. Frequency of Antimicrobial Resistance in Shiga Toxin-Producing Escherichia coli (STEC) and Non-Typhoidal Salmonella (NTS) Clinical Infections and Association with Epidemiological Factors
Session: Poster Abstract Session: Enteric Infections and Diagnostics
Friday, October 6, 2017
Room: Poster Hall CD
Background:

STEC and NTS are leading causes of foodborne infections in the US. Monitoring resistance in these pathogens is essential to understand the distribution of resistance profiles and because of the high likelihood of horizontal transfer of resistance genes to other pathogens. Data involving resistance in clinical STEC and NTS isolates from Michigan is lacking.

Methods:

Clinical STEC (n=353) and NTS (n= 148) isolates from the MDHHS (2010-2014) were examined for resistance using disk diffusion, E-test or broth microdilution. Case information and epidemiological data for STEC isolates was extracted and associations with resistant infections were determined using chi square tests in SAS 9.3 and EpiInfo™ 7.

Results:

Overall, 31 (8.8%, n=353) STEC isolates were resistant to at least one antibiotic; high frequencies of resistance were observed for ampicillin (7.4%) and trimethoprim-sulfamethoxazole (4.0%). Resistance to ciprofloxacin (0.28%) and all three drug classes (0.28%) was less common. Preliminary results indicate that O157 resistance to ampicillin (4.8%) and trimethoprim-sulfamethoxazole (3.4%) was higher in Michigan compared to national frequencies (ampicillin= 2.7%, trimethoprim-sulfamethoxazole= 1.5%). Higher resistance frequencies were also observed in counties with high (11.3%) versus low (7.7%) antibiotic prescription rates. For NTS, 23 (15.5%) isolates were resistant to ≥1 antibiotic. Resistance varied by serotype with high frequencies in Typhimurium (20%, n=20), Newport (17.6%, n=17) and Enteritidis (4.8%, n=42); 11 (7.4%) NTS isolates were resistant to ≥3 antimicrobial classes.

Conclusion:

Continuous monitoring of resistance in clinical STEC and NTS is warranted due to their importance as food pathogens. The identification of risk factors for resistance is crucial to develop alternative prevention practices to reduce the health burden of resistant infections in Michigan, which is not part of the FoodNet surveillance network.

Sanjana Mukherjee, MS1, Rebekah Mosci, MS2, Chase Anderson, -2, Brian Snyder, BS2, James Collins, MPH, RS3, James Rudrik, PhD4 and Shannon D. Manning, PhD5, (1)Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI, (2)Michigan State University, East Lansing, MI, (3)Michigan Department of Health and Human Services, Lansing, MI, (4)Michigan Department of Community Health, Lansing, MI, (5)Department of Microbiology and Molecular Genetics, Michigan State University, East Lansing, MI

Disclosures:

S. Mukherjee, None

R. Mosci, None

C. Anderson, None

B. Snyder, None

J. Collins, None

J. Rudrik, None

S. D. Manning, None

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