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CDC

Antimicrobial Resistance

Cephalosporin-resistant E. coli

% Resistant in 2024

27.7% Resistant

Number of Resistant Isolates of the Total Number of Isolates Tested In 2024

4,108 Resistant

/ 14,842 Tested

% Resistant by Patient Age in 2024

Pediatric:
25.4% Resistant
Adult:
27.8% Resistant

Pathogen Profile

Cephalosporin-resistant E. coli

E. coli cause pneumonia, urinary tract infections, and bloodstream infections in hospitalized patients. Resistance to extended spectrum cephalosporins among some E. coli makes infections with such bacteria difficult to treat.

Current Threat Report

Threat LevelSerious

Estimated Cases197,400

Estimated Deaths9,100

Healthcare Costs (USD)$1.2 B

Source: COVID-19: U.S. Impact on Antimicrobial Resistance, Special Report 2024

Years Included
2011 - 2024
Resources

Geographic Locations

Antimicrobial resistance varies by location, driven by a number of factors, including antibiotic use and infection control practices in individual healthcare facilities, the underlying health and age of the patient population, and regional spread from nearby locations.

Percent Cephalosporin resistance Among E. coli by State Map

This map shows the variation in % cephalosporin resistance among E. coli causing all event types in 2024.

Percent Cephalosporin resistance Among E. coli by State

Percent Cephalosporin resistance Among by State
Locationvalue
Alabama32.4
Alaska9.4
Arizona22.4
Arkansas25.9
California38.1
Colorado21.8
Connecticut31.3
Delaware18.4
District of Columbia31.6
Florida30.7
Georgia33.9
Hawaii28.8
Idaho9
Illinois26.3
Indiana16.4
Iowa17.6
Kansas22
Kentucky22.5
Louisiana19.8
Maine18.9
Maryland31.1
Massachusetts32.3
Michigan25
Minnesota20.6
Mississippi31.7
Missouri20.3
Montana20.4
Nebraska28.1
Nevada28.7
New Hampshire6.5
New Jersey30.1
New Mexico15.1
New York29.6
North Carolina22.9
North Dakota11.1
Ohio26.7
Oklahoma26.7
Oregon18.6
Pennsylvania20.1
Puerto Rico45.2
Rhode Island26.5
South Carolina20.9
South Dakota14.8
Tennessee26.6
Texas31.6
Utah25.9
Vermont31.4
Virginia26.2
Washington27.7
West Virginia32.5
Wisconsin16.7
WyomingInsufficient Data

Percent Cephalosporin resistance Among E. coli by State List

Geography

Geography
statevalue
United States27.7%
Alabama32.4%
Alaska9.4%
Arizona22.4%
Arkansas25.9%
California38.1%
Colorado21.8%
Connecticut31.3%
Delaware18.4%
District of Columbia31.6%

Changes Over Time in Cephalosporin resistance Among E. coli

This graph displays percent antimicrobial resistance from 2011 to 2024 for all event types. Blank areas of the chart represent 0% resistance, indicating that zero resistant pathogens were reported for the selected year, phenotype, and HAI type. “Insufficient data” indicates that less than 20 pathogens were isolated and tested for resistance.

Due to definition changes, caution should be used when reviewing this phenotype over time.

Changes Over Time in Cephalosporin resistance Among E. coli
Year% Resistant
201113.9
201213.6
201315.7
201416.3
201519.4
201620.2
201720.9
201821.2
201922
202024.7
202123.9
202224.6
202326.7
202427.7

Healthcare Facility Type

The setting or type of healthcare facility can influence the types of procedures and prevention measures that are related to healthcare-associated infections and antimicrobial resistance.

Cephalosporin resistance Among E. coli by Hospital Type

This graph displays percent antimicrobial resistance by hospital type in 2024.

Percent resistant Among E. coli by Hospital Type

Percent resistant Among E. coli by Hospital Type
Hospital Type% Resistant
General Acute Care Hospitals27.6
Long Term Acute Care Hospitals39.3
Inpatient Rehabilitation Facilities19.4

Footnotes

  • HAIs include Catheter-associated Urinary Tract Infections (CAUTI), Central Line-associated Bloodstream Infections (CLABSI), and Surgical Site Infections (SSI).
  • CI (Confidence Interval) - The national, regional, and state-level data included in Antimicrobial Resistance information are displayed with 95% confidence intervals around the percent resistance, which were calculated using a mid-P exact test and are an indication of precision.
  • Map legends are classified using the Jenks Natural Breaks method.
  • The definition for this phenotype underwent changes in 2021. For more information, refer to the AR&PSP Phenotype Definitions.