Methodology: Antibiotic Resistance

Methodology information for antibiotic use is available here.

Resistance Data

ResistanceMap aggregates data on antibiotic resistance from several sources. The data have been harmonized to present similar definitions of resistance across countries and regions to enable comparisons between countries. However, comparing resistance rates between countries should be undertaken with some caution as the breadth of testing varies between countries.

The following sections describe the source of the data, the bacterial species included, and the pathogen-antibiotic combinations used to determine resistance rates.


Sources

The underlying data was obtained from multiple sources in one of two formats: (1) microbiology and test data at isolate level; (2) aggregated data listing at a minimum, the number or percentage of isolates resistant and the number of isolates tested. The following table details the source of data source for each country.

Country

Data source

Argentina

WHONET-Argentina Network and SIREVAII-Argentina Network

Australia

Australian Group of Antimicrobial Resistance (AGAR)

Bahrain

Global Antimicrobial Resistance Surveillance System (GLASS)

Canada

Canadian Antimicrobial Resistance Alliance (CARA)

Chile

Chilean Society of infectious diseases

China

CHINET surveillance

Eastern Europe and Central Asia

Central Asian and Eastern European Surveillance of Antimicrobial Resistance network (CEAESAR)

Ecuador

Reference Laboratory for antimicrobial resistance at the National Institute of Public Health Research (INSPI)

Egypt

Global Antimicrobial Resistance Surveillance System (GLASS)

Europe: Austria, Belgium, Bulgaria Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom

European Antimicrobial Reisstance Surveillance Network (EARS-Net)

Georgia

Global Antimicrobial Resistance Surveillance System (GLASS)

Ghana

Lancet Laboratories Pvt. Ltd

India

SRL Diagnostics

Kenya

A private tertiary hospital

Lebanon

Global Antimicrobial Resistance Surveillance System (GLASS)

Malawi

Queen Elizabeth Central Hospital, Blantyre, Malawi

Malaysia

National Surveillance of Antimicrobial Resistance, Malaysia

Mexico

Hospital Civil de Guadalajara "Fray Antonio Alcalde"

New Zealand

Public Health Surveillance, New Zealand

Pakistan

Chugtai's Laboratory Private Ltd.

Philippines

Antimicrobial Resistance Surveillance Program, Department of Health, Philippines

Republic of Korea

Global Antimicrobial Resistance Surveillance System (GLASS)

South Africa

South Africa Society for Clinical Microbiology

Thailand

National Antimicrobial Resistance Surveillance Center, Thailand (NARST)

Tunisia

Global Antimicrobial Resistance Surveillance System (GLASS)

United States of America

The Surveillance Network (TSN)

Venezuela

Programa Venezolano de Vigilancia de la Resistencia a los Antimicrobianos (PROVENRA).

Vietnam

Viet Nam Resistance (VINARES) Project

Zambia

Global Antimicrobial Resistance Surveillance System (GLASS)

Zimbabwe

Lancet Laboratories Pvt. Ltd

 
Argentina

Aggregated data were obtained from the "WHONET-Argentina Network" and "SIREVAII-Argentina Network". Data were collected from 98 institutions representing all country territories. The data included information on the name of the organism, number of isolates tested and percentage resistance for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations "susceptible", "intermediate", and "resistant" were based on up to date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Australia

Aggregated data were obtained from the Australian Group on Antimicrobial Resistance (AGAR). Data were collected from 26 institutions from each state and the mainland territories. The data included information on the name of the organism, number of isolates tested and percentage resistant for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Bahrain

The data for the Bahrain were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
Canada

Aggregated data for the year 2012 were obtained from Canadian Antimicrobial Resistance Alliance (CARA), which collects data from 15 tertiary care medical centers located in eight of the 10 provinces in Canada. The data included organism name, number of isolates tested and percentage of resistance for selected antibiotics. Isolates collected from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Chile

Aggregated data were obtained from the Chilean Society of infectious diseases. Data were collected from 30 hospitals. The data included information on the name of the organism, number of isolates tested and percentage resistant for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
China

Aggregated data were obtained from the CHINET surveillance of bacterial resistance in China. Data were collected from 30 hospitals form 21 difference province or cities. The data included information on the name of the organism, number of isolates tested and percentage resistant for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Eastern Europe and Central Asia

The data for a minority of European countries were obtained from the Central Asian and Eastern European Surveillance of Antimicrobial Resistance network (CAESAR). Data collection was coordinated by the WHO Regional Office for Europe, the European Society of Clinical Microbiology and Infectious Diseases, and the Netherlands National Institute for Public Health and the Environment. Data collection efforts were closely coordinated with ECDC to ensure that data are comparable and compatible. Only data on invasive isolates from blood and cerebrospinal fluid (CSF) were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. However, reported biases and errors makes this data less reliable for cross-country comparison.

 
Ecuador

Aggregated data were obtained from the Reference Laboratory for antimicrobial resistance at the National Institute of Public Health Research (INSPI). The data included information on the name of the organism, number of isolates tested and percentage resistant for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Egypt

The data for the Egypt were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
Europe: Austria, Belgium, Bulgaria Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Latvia, Lithuania, Luxembourg, Malta, Netherlands, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, United Kingdom

The data for the European countries were obtained from the European Antimicrobial Resistance Surveillance Network (EARS-Net) maintained by the European Centre for Disease Prevention and Control (ECDC). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood and CSF were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories, through EARS-Net encourages the use of the European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints. Sample sizes and coverage vary considerably between countries.

 
Georgia

The data for the Georgia were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
Ghana

Aggregated data were obtained Lancet Laboratories. The data includes organism name, number of isolates tested and percentage of resistance for selected antibiotics. Isolates from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
India

Antibiotic resistance data in India were obtained from SRL Diagnostics Limited, Fortis Healthcare Limited, and the Indian Council of Medical Research (ICMR). SRL Diagnostics is a private laboratory network. In 2014, the network included approximately 5,700 collection centers spread across 26 (of 29) states and two (of seven) Union Territories (UTs). The collection centers included private hospitals (tertiary and secondary care), diagnostic laboratories, and home collection agencies. Culture specimens collected were transported to the nearest of four reference laboratories located in four different regions of the country for isolation, organism identification, and antimicrobial susceptibility testing. For each specimen, the following information was obtained: (1) final blood culture result (positive growth or no growth); (2) the identified organism, if culture was positive; (3) the interpreted results for tested antimicrobials (susceptible, intermediate-resistant, or resistant); (4) patient identifier and demographic information (age and gender); (5) collection center information (name of the center, city and state); and (6) the date of specimen collection. Organism identification and antimicrobial susceptibility testing were performed using broth microdilution methodology (MicroScan® panels, Siemens, Sacromento, CA) in all four reference laboratories. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing. Seventy-nine percent of positive cultures were contributed by 20 collection centers, which are private tertiary care hospitals located in seven major cities in six states and one UT. Only data on invasive isolates from blood and cerebrospinal fluid were included in this data. The data include isolates from all age groups. Fortis Healthcare limited is a private hospital network, which includes 12 hospitals. Isolate level data were obtained from 12 hospitals located in various cities across India within this network. The data includes all pathogens isolated from blood and cerebrospinal fluid in 2012. For each specimen, the following information was obtained: (1) the identified organism if culture was positive; (2) the interpreted results for tested antimicrobials (susceptible, intermediate-resistant, or resistant); (3) patient identifier; (4) the dates of specimen collection and date of susceptibility testing; and (5) patient location (ward or intensive care unit). Information on patient gender and age were not available. However, data included specimens collected from both pediatric and adult patients. Categorical result interpretations were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing. Aggregated data were obtained from Indian Council of medical Research (ICMR) AMR surveillance network includes four tertiary care hospitals. The data included information on the name of the organism, number of isolates tested and percentage resistant for selected antibiotics. Specimens from pediatric and adult patients were included, but not differentiated. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Kenya

Isolate level data were obtained from a private tertiary care teaching hospital. The data includes all pathogens isolated from blood and cerebrospinal fluid in 2012. For each specimen, the following information was obtained: (1) the identified organism if culture was positive; (2) the interpreted results for tested antimicrobials (susceptible, intermediate-resistant, or resistant); (3) patient identifier; (4) the dates of specimen collection and date of susceptibility testing; and (5) patient location (ward or intensive care unit). Information on patient gender and age were not available. However, data included specimens collected from both pediatric and adult patients. Categorical result interpretations were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Lebanon

The data for the Lebanon were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
Malawi

Aggregated data was obtained from a surveillance study of blood cultures that were routinely taken from adult and paediatric patients with fever or suspicion of sepsis admitted to Queen Elizabeth Central Hospital, Blantyre, Malawi from 1998 to 2016. The hospital served an urban population of 920,000 in 2016, with 1,000 beds, although occupancy often exceeds capacity. The hospital admits about 10,000 adults and 30,000 children each year. Antimicrobial susceptibility tests were done by the disc diffusion method according to British Society of Antimicrobial Chemotherapy guidelines. For more details see: Musicha et al. (2017) "Trends in antimicrobial resistance in bloodstream infection isolates at a large urban hospital in Malawi (1998-2016): a surveillance study" The Lancet Infectious Diseases 17(10):1042-1052.

 
Malaysia

Aggregated data were obtained from National Surveillance of Antimicrobial Resistance, Malaysia. Data were collected from 41 hospitals distributed in 13 states of Malaysia. Data were available only if at least 30 isolates were tested for resistance for a specific bug-drug combination The data included information on the name of the organism, number of isolates tested and percentage resistance for selected antibiotics. Specimens from both pediatric and adult patients were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up to date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Mexico

Aggregated data were obtained from Hospital Civil de Guadalajara "Fray Antonio Alcalde. The data included information on the name of the organism, number of isolates tested and percentage resistance for selected antibiotics. Specimens from both pediatric and adult patients were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up to date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
New Zealand

Aggregated data were obtained from the Public Health Surveillance Program, New Zealand. Data were collected from 25 hospital and community laboratories. The data included information on the name of the organism, number of isolates tested and percentage resistance for selected antibiotics. Data were available only if at least 100 isolates were tested for resistance for a specific bug-drug combination. Specimens from both pediatric and adult patients were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up to date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Pakistan

For each specimen, the following information was obtained: the identified organism; the interpreted results for tested antimicrobials (susceptible, intermediate-resistant, or resistant); demographic information (age and gender); the date of specimen collection.. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing. Only data on invasive isolates from blood and cerebrospinal fluid were included in this data. The data include isolates from all age groups.

 
Philippines

Aggregated data were obtained from Antimicrobial Resistance Surveillance Program, Department of Health, Philippines. Data were collected from 24 sentinel sites hospital bacteriology laboratories located in 16 regions of the Philippines. The data included information on the name of the organism, number of isolates tested and percentage resistance for selected antibiotics. Specimens from both pediatric and adult patients were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up to date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Republic of Korea

The data for the Republic of Korea were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
South Africa

Isolate data data were obtained from both the public and private sectors representing almost the entire health facilities in the country. Public sector data were obtained from the National Health Laboratory Service (NHLS) and private sector data were obtained from South African Society for Clinical Microbiology (SASCM). SASCM collates data from four private-sector reference laboratories (Ampath, Lancet, Vermaak and Partners, Pathcare) representing all regions of the country. The following pathogens were included in the NHLS and SASCM data: E.coli, Klebsiella pneumoniae, Acinetobacter baumannii complex, Staphylococcus aureus, Pseudomonas aeruginosa, Enterobacter cloacae complex, Enterococcus faecium/faecalis. Isolates from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing. All laboratories have an External Quality Assurance program for quality checks and all private laboratories and the majority of NHLS laboratories are SANAS (South African National Accreditation Society) accredited. Data were omitted for those hospitals that tested less than 30 ESKAPE pathogens for a particular antimicrobial agent.

 
Thailand

Aggregated data were obtained from the National Antimicrobial Resistance Surveillance Center, Thailand (NARST). Data were collected from 26 institutions from each state and mainland territories. The data includes organism name, number of isolates tested and percentage of resistance for selected antibiotics. Isolates from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Tunisia

The data for the Tunisia were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
United States of America

Data for the United States was obtained from The Surveillance Network (TSN), the Center for Disease Control's National Healthcare Safety Network, and ResistanceMap Surveillance Network. Isolate level data was obtained from The Surveillance Network (TSN) for the years 1999-June 2012. TSN is an electronic repository of antimicrobial drug susceptibility data from a national network of >300 microbiology laboratories in the United States. Participating laboratories are geographically dispersed and make up a nationally representative sample based on patient population and number of beds. Patient isolates are tested on site as part of routine diagnostic testing for susceptibility to different antimicrobial agents by using standards established by the Clinical and Laboratory Standards Institute and approved by the US Food and Drug Administration. Results are then filtered to remove repeat isolates and identify microbiologically atypical results for confirmation or verification before being included in the TSN database. Data from the database have been used extensively to evaluate antimicrobial drug resistance patterns and trends (see references). CDC's National Healthcare Safety Network is a healthcare-associated infection (HAI) tracking system. Hospitals provide data and antimicrobial susceptibility information to the CDC regarding hospital-acquired infections for a select group of pathogens. ResistanceMap Surveillance Network (RSN) is an isolate-level surveillance system that obtains antimicrobial drug susceptibility data from a network of hospitals across the United States. Patient isolates are tested on site as part of routine diagnostic testing for susceptibility to different antimicrobial agents by using standards established by the Clinical and Laboratory Standards Institute and approved by the US Food and Drug Administration. Results are then filtered to remove repeat isolates.

 
Venezuela

Aggregated data were obtained from PROVENRA. Data were collected from 51 institutions. The data includes organism name, number of isolates tested and percentage of resistance for selected antibiotics. Isolates from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Vietnam

Aggregated data were obtained from 16 hospitals, which are part of the VINARES project, for a one-year period (November 2012 to October 2013). For selected pathogens of interest, the data included information on organism name, number of isolates tested, percentage of resistance for selected antibiotics and 95% confidence intervals for the resistance rates. Specimens from both pediatric and adult patients were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.

 
Zambia

The data for the Zambia were obtained from the Global Antimicrobial Resistance Surveillance System (GLASS) maintained by the World Health Organization (WHO). Data are collected at the national level under the responsibility of each participating country, and include data from several types of health-care facilities (e.g. university or specialized hospitals; general and district hospitals; rehabilitation centers; nursing homes). Only invasive isolates from blood were included and the interpreted results were based on the clinical breakpoint criteria used by the local laboratories. Sample sizes and coverage vary considerably between countries.

 
Zimbabwe

Aggregated data were obtained Lancet Laboratories. The data includes organism name, number of isolates tested and percentage of resistance for selected antibiotics. Isolates from both pediatric and adult sources were included. Categorical result interpretations ("susceptible", "intermediate", and "resistant") were based on up-to-date Clinical Laboratory Standards Institute (CLSI) criteria at the time of testing.


Bacterial Species

Depending on the country, resistance data is currently available for all or some of the following bacterial species:

  • Acinetobacter baumannii
  • Enterobacter aerogenes/cloacae
  • Enterococcus faecalis
  • Enterococcus faecium
  • Escherichia coli
  • Klebsiella pneumoniae
  • Pseudomonas aeruginosa
  • Salmonella Paratyphi
  • Salmonella Typhi
  • Staphylococcus aureus
  • Streptococcus pneumoniae

Isolates were classified as susceptible (S), intermediate (I), or resistant (R). Clinical and Laboratory Standards Institute (CLSI) or European Committee on Antimicrobial Susceptibility Testing (EUCAST) breakpoints were used for antimicrobial susceptibility testing in the laboratories contributing the data. For example, laboratories in the United States use CLSI guidelines, while European countries use EUCAST guidelines.

The data presented on ResistanceMap include only invasive isolates obtained from blood, cerebrospinal fluid or both. In addition, all non-susceptible isolates (I+R) are classified as resistant and the data is presented for a pathogen only when 30 or more isolates were tested against an antibiotic. Some countries do not have data for every pathogen-antibiotic combination listed, and for certain combinations, only a few countries have data. For instance, India is currently the only country with Salmonella data available.

For each data point we calculated the 95% confidence interval using the Wilson score method for binomial data.


Pathogen-Antibiotic combinations

Antibiotics were classified into several groups as needed to compensate for the lack of susceptibility data on every antibiotic and to facilitate examination of resistance based on clinical relevance. Antibiotic groups are often classes of antibiotics, but not always. Resistance to an antibiotic group was defined as non-susceptibility to at least one antimicrobial agent in that group though not all isolates were tested against every antibiotic in a group.

The pathogens and the groupings of antibiotic agents against which they are tested are listed in the following table.

Pathogen

(countries for which data is available)

Antibiotic group

Antibiotic agents

Acinetobacter baumannii

(India, South Africa, Thailand, USA, Vietnam)

Amikacin

Amikacin

Aminoglycosides

Gentamicin, Tobramycin

Ampicillin-sulbactam

Ampicillin-sulbactam

Carbapenems

Imipenem, Meropenem 

Ceftazidime

Ceftazidime

Fluoroquinolones

Ciprofloxacin, Levofloxacin

Glycylcyclines

Tigecycline

Polymyxins

Colistin (Polymyxin E), Polymyxin B

Enterobacter aerogenes/cloacae

(India, South Africa, Thailand)

Aminoglycosides

Gentamicin, Tobramycin, Amikacin

Amoxicillin-clavulanate

Amoxicillin-clavulanate

Carbapenems

Imipenem, Meropenem

Cephalosporins (3rd gen)

Cefotaxime, Ceftriaxone, Ceftazidime

Fluoroquinolones

Ciprofloxacin, Ofloxacin, Levofloxacin

Glycylcyclines

Tigecycline

Piperacillin-tazobactam

Piperacillin-tazobactam

Polymyxins

Colistin (Polymyxin E), Polymyxin B

Enterococcus faecalis

(Australia, Europe, India, South Africa, Thailand, United States)

Aminoglycosides (high-level)

Gentamicin (high-level)

Aminopenicillins

Amoxicillin, Ampicillin

Vancomycin

Vancomycin

Enterococcus faecium

(Australia, Europe, India, South Africa, Thailand, United States)

Aminoglycosides (high-level)

Gentamicin (high-level)

Aminopenicillins

Amoxicillin, Ampicillin

Vancomycin

Vancomycin

Escherichia coli

(All countries)

Aminoglycosides

Gentamicin, Tobramycin, Amikacin

Aminopenicillins

Amoxicillin, Ampicillin

Amoxicillin-clavulanate

Amoxicillin-clavulanate

Carbapenems

Imipenem, Meropenem

Cephalosporins (3rd gen)

Cefotaxime, Ceftriaxone, Ceftazidime

Fluoroquinolones

Ciprofloxacin, Ofloxacin, Levofloxacin, Moxifloxacin, Norfloxacin

Glycylcyclines

Tigecycline

Piperacillin-tazobactam

Piperacillin-tazobactam

Polymyxins

Colistin (Polymyxin E), Polymyxin B

Klebsiella pneumoniae

(All countries)

Aminoglycosides

Gentamicin, Tobramycin, Netilmicin, Amikacin

Amoxicillin-clavulanate

Amoxicillin-clavulanate

Carbapenems

Imipenem, Meropenem

Cephalosporins (3rd gen)

Cefotaxime, Ceftriaxone, Ceftazidime

Fluoroquinolones

Ciprofloxacin, Ofloxacin, Levofloxacin, Moxifloxacin, Norfloxacin

Glycylcyclines

Tigecycline

Piperacillin-tazobactam

Piperacillin-tazobactam

Polymyxins

Colistin (Polymyxin E), Polymyxin B

Pseudomonas aeruginosa

(Canada, Europe, South Africa, Thailand, USA, Vietnam)

Amikacin

Amikacin

Aminoglycosides

Gentamicin, Tobramycin

Carbapenems

Imipenem, Meropenem

Ceftazidime

Ceftazidime

Fluoroquinolones

Ciprofloxacin, Levofloxacin

Piperacillin-tazobactam

Piperacillin-tazobactam

Polymyxins

Colistin (Polymyxin E), Polymyxin B

Salmonella Typhi/Paratyphi

(India)

Aminopenicillins

Ampicillin

Carbapenems

Imipenem, Meropenem

Cephalosporins (3rd gen)

Cefotaxime, Ceftriaxone

Fluoroquinolones

Ciprofloxacin, Levofloxacin

Macrolides

Azithromycin

Tetracyclines

Tetracycline

Trimethoprim-sulfamethoxazole

Trimethoprim-sulfamethoxazole

Staphylococcus aureus

(Australia, Canada, Europe, South Africa, Thailand, USA, Vietnam)

Linezolid

Linezolid

Oxacillin (MRSA)

Methicillin, Oxacillin, Cefoxitin, Flucloxacillin, Cloxacillin, Dicloxacillin

Rifampicin

Rifampicin

Vancomycin

Vancomycin

Streptococcus pneumoniae

(Canada, Europe, Thailand, USA)

Macrolides

Erythromycin, Clarithromycin, Azithromycin

Penicillins

Penicillin

Antibiotic Use Methodology page

References

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Flamm RK, Weaver MK, Thornsberry C, Jones ME, Karlowsky JA, Sahm DF. Factors associated with relative rates of antibiotic resistance in Pseudomonas aeruginosa isolates tested in clinical laboratories in the United States from 1999 to 2002. Antimicrob Agents Chemother. 2004;48:2431-6. DOI: 10.1128/AAC.48.7.2431-2436.2004


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Karlowsky JA, Draghi DC, Jones ME, Thornsberry C, Friedland IR, Sahm DF. Surveillance for antimicrobial susceptibility among clinical isolates of Pseudomonas aeruginosa and Acinetobacter baumannii from hospitalized patients in the United States, 1998 to 2001. Antimicrob Agents Chemother. 2003;47:1681-8. DOI: 10.1128/AAC.47.5.1681-1688.2003


Sahm DF, Marsilio MK, Piazza G. Antimicrobial resistance in key bloodstream bacterial isolates: electronic surveillance with the surveillance network database-USA. Clin Infect Dis. 1999;29:259-63. DOI: 10.1086/520195


Styers D, Sheehan DJ, Hogan P, Sahm DF. Laboratory-based surveillance of current antimicrobial resistance patterns and trends among Staphylococcus aureus: 2005 status in the United States. Ann Clin Microbiol Antimicrob. 2006;5:2. DOI: 10.1186/1476-0711-5-2


May, Larissa, Eili Y. Klein, Richard E. Rothman, and Ramanan Laxminarayan (2014) "Trends in Antibiotic Resistance in Coagulase Negative Staphylococci, United States, 1999-2012" Antimicrobial Agents and Chemotherapy 58(3): 1404-1409. DOI: 10.1128/AAC.01908-13


Klein, Eili Y., Lova Sun, David L. Smith, Ramanan Laxminarayan (2013) "The changing epidemiology of methicillin-resistant Staphylococcus aureus in the United States: A national observational study" The American Journal of Epidemiology 177(7): 666-674. DOI: 10.1093/aje/kws273


Braykov, Nikolay, Michael R. Eber, Eili Y. Klein, Daniel J. Morgan, and Ramanan Laxminarayan (2013) "Trends in resistance to carbapenems and third-generation cephalosporins among clinical isolates of Klebsiella pneumoniae in the United States, 1999-2010" Infection Control Hospital Epidemiology 34(3):259-68. DOI: 10.1086/669523


Sun, Lova, Eili Y. Klein, and Ramanan Laxminarayan (2012) "Seasonality and Temporal Correlation between Community Antibiotic Use and Resistance in the United States" Clinical Infectious Diseases 55(5):687-694. DOI: 10.1093/cid/cis509