Antibiotic Resistance
Resistance trends vary between microorganism-antibiotic combinations. While methicillin resistance is decreasing in Staphylococcus aureus, increasing trends have been observed for quinolones, third- and fourth-generation cephalosporins, and, although at a much lower level, carbapenems in Enterobacterales (E. coli and K. pneumoniae).
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CRE: Carbapenem-resistant Enterobacterales
ESCR-E.coli: Extended-spectrum cephalosporin-resistant Escherichia coli
ESCR-K.pneumoniae: Extended-spectrum cephalosporin resistant Klebsiella pneumoniae
FQR-E.coli: Fluoroquinolone-resistant Escherichia coli
MRSA: Methicillin-resistant Staphylococcus aureus
VRE: Vancomycin-resistant Enterococcus faecium
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Since 2010, the highest incidence rates have been observed for fluoroquinolone-resistant and extended-spectrum cephalosporin-resistant Escherichia coli. Increasing incidence rates have been observed for third- and fourth-generation cephalosporin-resistant Klebsiella pneumoniae and carbapenem-resistant Enterobacterales.
Select a region of interest from the drop-down menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover.
CRE: Carbapenem-resistant Enterobacterales
ESCR-E.coli: Extended-spectrum cephalosporin-resistant Escherichia coli
ESCR-K.pneumoniae: Extended-spectrum cephalosporin resistant Klebsiella pneumoniae
FQR-E.coli: Fluoroquinolone-resistant Escherichia coli
MRSA: Methicillin-resistant Staphylococcus aureus
VRE: Vancomycin-resistant Enterococcus faecium
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The number of infections, disability-adjusted life years (DALYs), and deaths attributable to 16 antibiotic-resistant bacteria have been estimated for Switzerland. Third-generation cephalosporin-resistant Escherichia coli consistently accounts for the largest share of the estimated burden. A comprehensive assessment of the burden of antibiotic resistance in Switzerland was published in Eurosurveillance in 2023.
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DALYs: Disability-Adjusted Life Years
ColRACI: Colistin-resistant Acinetobacter spp.
CRACI: Carbapenem-resistant Acinetobacter spp.
MDRACI: Multidrug-resistant Acinetobacter spp.
VRE: Vancomycin-resistant Enterococcus faecium
ColREC: Colistin-resistant Escherichia coli
CREC: Carbapenem-resistant E. coli
3GCREC: Third-generation cephalosporin-resistant E. coli
ColRKP: Colistin-resistant Klebsiella pneumoniae
CRKP: Carbapenem-resistant K. pneumoniae
3GCRKP: Third-generation cephalosporin-resistant K. pneumoniae
ColRPA: Colistin-resistant Pseudomonas aeruginosa
CRPA: Carbapenem-resistant P. aeruginosa
MDRPA: Multidrug-resistant P. aeruginosa
MRSA: Methicillin-resistant Staphylococcus aureus
PRSP: Penicillin-resistant Streptococcus pneumoniae
PMRSP: Penicillin- and macrolide-resistant S. pneumoniae
The methodology of Cassini et al. 2018 (1) was adapted to estimate the number of infections, DALYs, and deaths in Switzerland. Regionally stratified bacteremia data from the ANRESIS database were used as the basis. Infections other than bloodstream infections (e.g., urinary tract infections, surgical site infections) were estimated using a point prevalence study and included in the calculation. As in Cassini et al., we used the “Burden of Communicable Disease in Europe Toolkit” to estimate the outputs, based on 10,000 Monte Carlo simulations.
Important note: The methodology used for these figures differs slightly from the methodology published in Eurosurveillance (2). That is, in the approach presented here, isolates classified as intermediate (“susceptible with increased exposure”) were excluded from the estimates. Therefore, the estimates shown here are somewhat lower.
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A stable resistance situation is currently observed for this microorganism, which is intrinsically resistant to numerous antibiotics.
Infections caused by Acinetobacter spp. are mainly observed in hospital environments, particularly in intensive care units, and in already weakened patients. These microorganisms can cause respiratory, urinary tract and wound infections, as well as septicaemia and meningitis. The resistance situation in Switzerland has been stable for more than 10 years. Unlike in other European countries, an increase in carbapenem resistance has not been observed.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart, a toolbar appears, which allows zooming or showing data on hover.
CI 95%: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. For incidence rates, it may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Aspergillus species are ubiquitous in nature and can cause a wide range of diseases in humans.
Aspergillus species can cause life-threatening invasive aspergillosis in immunocompromised hosts. Infections are most frequently caused by Aspergillus fumigatus. Nevertheless, non-fumigatus Aspergillus spp. are increasingly reported. Additionally, azole resistance in A. fumigatus has emerged worldwide, being associated with a high mortality rate in immunocompromised hosts.
Select a species of interest from the drop-down menu. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover. Species distributions can be shown as percentages or as absolute numbers (the latter may increase over time as the ANRESIS network grows).
95% CI: 95% confidence interval
For this analysis all isolates tested against the corresponding antifungal (category) were considered. If multiple antifungal within the same antifungal category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Concerning the stacked bar chart: When deduplicating, only the antifungal-microorganism combination with the highest N was considered. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Campylobacter usually are acquired through contaminated food, particularly undercooked poultry.
Infections may cause diarrhoea, but may also be asymptomatic. In most cases, antibiotic therapy is not necessary. Overall, resistance rates are higher in C. coli than in C. jejuni and for fluoroquinolones than for macrolides.
Select a species of interest from the drop-down menu. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover. Species distributions can be shown as percentages or as absolute numbers (the latter may increase over time as the ANRESIS network grows).
95% CI: 95% confidence interval
For this analysis all isolates tested against the corresponding antibiotic (category) were considered. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Concerning the stacked bar chart: When deduplicating, only the antibiotic-microorganism combination with the highest N was considered. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Enterococci are part of the intestinal flora and are low in pathogenicity. E. faecalis and E. faecium are the most important species causing human infections. They are often involved in mixed infections, particularly in hospital environments, where they can also cause severe infections. Vancomycin resistance in E. faecium (VRE) is increasing worldwide and is continuously monitored in Switzerland.
Enterococcus faecalis is the most common species of enterococci in human infections. It remains susceptible to most antibiotics, including aminopenicillins, and vancomycin resistance is rare.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Enterococcus faecium mainly occur in hospital-acquired infections. They are usually resistant to aminopenicillins, and show higher resistance rates to most antibiotics than Enterococcus faecalis.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart, a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The VRE epidemiology is very dynamic.
Although invasive VRE (vancomycin-resistant E. faecium) infections remain uncommon, VRE are highly relevant to infection prevention because they can cause regional or institutional outbreaks.
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VRE: Vancomycin-resistant Enterococcus faecium
H1 and H2: First (January-June) and second (July-December) six months of the year
Only E. faecium were considered for this analysis. From every patient the most invasive isolate which was sampled within one calendar year was included. Results are reported as delivered by laboratories, only hospitalized patients are considered. Screening samples are defined as sample locations “anal”, “faeces”, “intact skin” or “mucosa-swab”. Results may be influenced by the changing number of laboratories participating.
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The resistance to third- and fourth-generation cephalosporins has steadily increased since 2004.
Escherichia coli are among the most frequent microorganisms in both the hospital and the ambulatory setting. E. coli colonises the intestinal tract and often causes urinary tract infections, pyelitis and bacteremia.
Fluoroquinolone resistance increased markedly between 2004 and 2010, rising from 10% to 19%, but has since stabilised. As fluoroquinolone consumption is an important trigger for fluoroquinolone resistance in E. coli, these antibiotics should only be used in exceptional cases to treat uncomplicated lower urinary tract infections.
Resistance rates to 3rd/4th generation cephalosporins were steadily increasing since 2004. This increase was observed in both the inpatient and the outpatient setting. E. coli which are resistant to 3rd/4th generation cephalosporins have been found in numerous settings, including among people returning from foreign travel, in animals or in water bodies.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The resistance rate to third- and fourth-generation cephalosporins has steadily increased since 2004.
Like E. coli, Klebsiella pneumoniae belong to the family of Enterobacteriales and are potentially causing urinary tract infections. They are also known to cause pneumonia, particularly in the hospital setting. The resistance rate in K. pneumoniae to third- and fourth-generation cephalosporins increased from 1% in 2004 to 13% in 2025, comparable to the increase observed in E. coli.
Patients with a K. pneumoniae infection in the hospital setting are generally isolated, due to an increased risk of transmission.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart, a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Neisseria gonorrhoeae has become a multiresistant microorganism.
The number of gonococcal infections is steadily increasing. These infections are often observed alongside other sexually transmitted diseases, such as chlamydia, HIV, hepatitis B and syphilis. Resistance proportions to oral cephalosporines, quinolones and azithromycin are increasing continuously, and ceftriaxone remains the only first-line therapy. It should be used in higher doses in order to prevent the development of new resistances (see SSI guidelines). For surveillance purposes, it is important to use culture techniques for diagnosis and not only rely on polymerase chain reaction (PCR) techniques. Conducting susceptibility testing only in cases of therapeutic failure may lead to an overestimation of resistance.
Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis isolates from all sites tested against the corresponding antibiotic (category) were considered. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The level of antibiotic resistance in P. aeruginosa is increasing slowly.
P. aeruginosa is intrinsically resistant to numerous antibiotics. Particularly from the inpatient setting it is known that P. aeruginosa can cause lung, urinary tract, and blood infections. Further, severe infections can occur after skin burns. In recent years, both incidence and resistance proportions have increased steadily.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used. It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Human salmonellosis usually does not require antimicrobial treatment.
However, in some patients, Salmonella infection can cause serious illness and sepsis. Over the past few years, resistance rates have decreased for aminopenicillins but increased for fluoroquinolones.
Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis isolates from all sites tested against the corresponding antibiotic (category) were considered. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Methicillin-resistance in S. aureus (MRSA) is declining.
Staphylococci, together with E. coli, are the most frequent cause of infection in humans. Besides wound and soft tissue infections, they can also cause sepsis, joint, bone and cardiac valve infections. In Switzerland, MRSA rates decreased from 13% in 2004 to around 4–5% in 2015 and have since stabilised. Simultaneously, a shift of MRSA from the inpatient to the outpatient setting was observed, and the overall incidence of (susceptible) S. aureus infections has increased over time, particularly in German-speaking Switzerland.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or days of care are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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Due to vaccination, penicillin resistance in pneumococci has stabilised at a low level.
Pneumococci mainly cause infections of the lungs (pneumonia) and blood (sepsis). The resistance rate to penicillin stabilised at 4% in 2021. One reason for this trend is probably the pneumococcal vaccine. Since its introduction both the morbidity and the resistance rates have decreased considerably.
Select a region of interest from the map, or an antibiotic or a year of choice from the other selection menus. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over a line chart a toolbar appears, which allows zooming or showing data on hover.
95% CI: 95% confidence interval
For this analysis, invasive isolates (blood and cerebrospinal fluid) tested against the corresponding antibiotic (category) were considered only. If multiple antibiotics within the same antibiotic category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Results are reported as delivered by laboratories. Isolates are linked to the regions via hospital identifiers. Since isolates that are not assigned to a hospital covered by ANRESIS (‘NA’) are also taken into account when calculating the nationwide N, it is possible that the nationwide N is greater than the sum of the individual regions. The following extrapolation procedure was used to calculate incidences: Each hospital was classified as covered or not covered in the ANRESIS database in each year. Using this data, a coverage rate based on hospital patient days was calculated for each linguistic region (Latin vs. German-speaking) and hospital type (university vs. non-university) and year. These coverage rates were then applied to count data obtained from the hospitals participating in ANRESIS to obtain a national count. It may be possible that population data or patient days are not yet available for the most recent years (see the note on the graph). In such cases, coverage rates from the most recent complete year are used. For population data, linear extrapolation is used.
It is further possible that the resistance data of the most recent years have not yet been fully submitted to ANRESIS. The population data used in the denominator was obtained from the Swiss Federal Statistical Office. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The clinical manifestations of infection with Candida species and other yeasts can range from local mucous membrane infections to candidemia and widespread dissemination resulting in multisystem organ failure.
Although Candida albicans is still considered the main causative pathogen, there has been a global shift towards non-albicans Candida species. Candidemia is among the leading causes of hospital-acquired bloodstream infections, representing one of the most prevalent nosocomial invasive fungal infections worldwide. Furthermore, the emergence of drug-resistant Candida species is a major concern.
Select a species of interest from the drop-down menu. Use the checkboxes to activate or deactivate time series and confidence intervals. When the mouse is moved over the graph a toolbar appears, which allows zooming or showing data on hover. Species distributions can be shown as percentages or as absolute numbers (the latter may increase over time as the ANRESIS network grows).
95% CI: 95% confidence interval
For this analysis all isolates tested against the corresponding antifungal (category) were considered. If multiple antifungal within the same antifungal category were tested, the most resistant result was selected. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Concerning the stacked bar chart: When deduplicating, only the antifungal-microorganism combination with the highest N was considered. Results are reported as delivered by laboratories. Statistics may be influenced by the changing number of laboratories participating. Data are provided for surveillance purposes and are not intended to be used for therapeutic decisions solely.
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The ANRESIS-guide is an interactive web application which is directed particularly towards health professionals. It gives a fast and intuitive access to ANRESIS resistance data and connects them with the latest national treatment guidelines. The ANRESIS-guide project has been developed with support from the Federal Office of Public Health and the Institute for Infectious Diseases Bern. Fact sheets for microorganisms and antibiotics were developed in collaboration with the Institute for Infectious Diseases and PharmaSuisse.
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View the most relevant Swiss resistance data in table format and customise the query according to your preferences.
The selection of microorganism–antimicrobial combinations is based on the ANRESIS guide. For combinations with a suspected resistance phenotype, the results are overwritten to indicate a resistance proportion of 100%.
Data should be interpreted with caution and should not be used as uncritical treatment recommendations, as the likelihood of resistance depends on individual patient characteristics. Treatment decisions should be based not only on resistance rates, but also on other factors such as adverse effects, toxicity, availability, and selective pressure. For some microorganism–antibiotic combinations, increased dosing regimens or combination therapy may be required.
Data may be used in presentations or publications provided that they are correctly cited as data from “Swiss Centre for Antibiotic Resistance, anresis.ch, last accessed [date]”.
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Methods: A detailled description may be found here. Results from microorganisms with identical resistance profiles, obtained from the same patient and sample source within a 365-day period, are deduplicated. Results are reported as qualitative interpretations - susceptible (s), susceptible increased exposure (i), resistant (r) - as provided by the laboratories . Where multiple results are reported for the same antibiotic, the most resistant result is used.
Results: Proportion (%) of tested isolates, n is the number of tested isolates.
Selection criteria: Data may be stratified according to
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Although prevalence remains relatively low, the number of carbapenem-resistant Enterobacterales cases has steadily increased in recent years.
Carbapenems are a class of broad-spectrum antibiotics used to treat severe infections caused by multidrug-resistant microorganisms, particularly those that produce extended-spectrum beta-lactamases (ESBLs). Therefore, resistance to this class of antibiotics is crucial to survey. ANRESIS continuously analyses carbapenem resistance in Enterobacterales and publishes the results on this website.
Carbapenem resistance can be mediated by different mechanisms, such as permeability defects or efflux pumps, or by the production of carbapenemase enzymes. However, the resistance mechanism cannot be predicted from the resistance test alone; genomic analyses are also required. Due to their multidrug resistance and rapid spread, carbapenemase-producing Enterobacterales are the focus of a separate section (see below).
The number of CRE isolates increased steadily over time, even in invasive isolates.
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CRE is defined as resistant to at least one out of the antibiotics imipenem and meropenem. For Morganellaceae (Morganella spp, Proteus spp. and Providencia spp.), only full resistance to meropenem is considered. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Be aware that the number of isolates may be dependent on the changing number of participating laboratories. Results are reported as delivered by the laboratories.
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Klebsiella pneumonieae is the most frequent CRE species, followed by Escherichia coli.
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CRE is defined as resistant to at least one of the antibiotics imipenem and meropenem. For Morganellaceae (Morganella spp, Proteus spp. and Providencia spp.), only full resistance to meropenem is considered. In case of multiple isolates, the first isolate per patient, microorganism and calendar year was included only. Be aware that the number of isolates may be dependent on the changing number of participating laboratories. Results are reported as delivered by the laboratories.
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Enterobacterales that possess carbapenemase enzymes (known as carbapenemase-producing Enterobacterales, or CPE) are resistant to many other antibiotic classes besides carbapenems. Due to this multidrug resistance and their rapid spread, they pose a particular threat. The Swiss government therefore declared the reporting of CPE mandatory in January 2016, and since January 2019, all CPE isolates must be sent to the National Reference Centre for Emerging Antibiotic Resistance (NARA) for detailed analysis of the resistance mechanisms and early outbreak detection. An overview on CPE was published in EUROSURVEILLANCE in 2021.
Carbapenemases produced by CPE are classified into molecular classes according to their amino acid sequence similarities. ANRESIS publishes the latest CPE data on this website every quarter. Please note that these data cannot be compared directly with data from before 2019 due to a change in the reporting system. Deduplication is performed at the year, patient, bacterial species, and genotype level.
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IMP: Imipenemase
KPC: Klebsiella pneumoniae carbapenemase
NDM: New Delhi metallo-β-lactamase
OXA-48: Oxacillinase-48
OXA-other: Other oxacillinase variants
VIM: Verona integron-encoded metallo-β-lactamase
In 2013, the Swiss Antibiogram Committee (SAC) of the Swiss Society for Microbiology defined nine Swiss expert laboratories, accredited for characterising CPE on a molecular level and connected to the Swiss Centre for Antibiotic Resistance ANRESIS. From 2013 to 2015, all Swiss primary laboratories from the eight regions of Switzerland used in ANRESIS were asked to send all suspected human CPE isolates, irrespective of their origin, to one of the expert laboratories for confirmation and molecular characterisation. For suspicion of CPE, primary laboratories used the guidelines and breakpoints of the given years from the European Committee on Antimicrobial Susceptibility Testing (EUCAST) or the Clinical and Laboratory Standards Institute (CLSI). The expert laboratories provided information on genotype based on PCR or sequencing. From 1 January 2016, reporting of all CPE isolates to the Swiss Federal Office of Public Health (SFOPH) became mandatory and since January 2019, all CPE isolates must be sent to the National Reference Centre for Emerging Antibiotic Resistance (NARA) for a detailed analysis of the resistance mechanisms and for early detection of outbreaks. ANRESIS collects data from various sources and processes it. Deduplication is performed at the year, patient, bacterial species, and genotype level.
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