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(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using the instructions here.)

A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)

This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the University of Prince Edward Island, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.


  • Removed all functions and references that used the deprecated rsi class, which were all replaced with their sir equivalents over a year ago


  • One Health implementation
    • Function as.sir() now has extensive support for animal breakpoints from CLSI. Use breakpoint_type = "animal" and set the host argument to a variable that contains animal species names.
    • The clinical_breakpoints data set contains all these breakpoints, and can be downloaded on our download page.
    • The antibiotics data set contains all veterinary antibiotics, such as pradofloxacin and enrofloxacin. All WHOCC codes for veterinary use have been added as well.
    • ab_atc() now supports ATC codes of veterinary antibiotics (that all start with “Q”)
    • ab_url() now supports retrieving the WHOCC url of their ATCvet pages
  • Clinical breakpoints
    • EUCAST 2024 and CLSI 2024 are now supported, by adding all of their over 4,000 new clinical breakpoints to the clinical_breakpoints data set for usage in as.sir(). EUCAST 2024 is now the new default guideline for all MIC and disks diffusion interpretations.
    • as.sir() now brings additional factor levels: “NI” for non-interpretable and “SDD” for susceptible dose-dependent. Currently, the clinical_breakpoints data set contains 24 breakpoints that can return the value “SDD” instead of “I”.
  • MIC plotting and transforming
    • New function group scale_*_mic(), namely: scale_x_mic(), scale_y_mic(), scale_colour_mic() and scale_fill_mic(). They are advanced ggplot2 extensions to allow easy plotting of MIC values. They allow for manual range definition and plotting missing intermediate log2 levels.
    • New function rescale_mic(), which allows to rescale MIC values to a manually set range. This is the powerhouse behind the scale_*_mic() functions, but it can be used by users directly to e.g. compare equality in MIC distributions by rescaling them to the same range first.
  • Microbiological taxonomy (microorganisms data set) updated to June 2024, with some exciting new features:
    • Added MycoBank as the primary taxonomic source for fungi
      • The microorganisms data set now contains additional columns mycobank, mycobank_parent, and mycobank_renamed_to
      • New function mo_mycobank() to get the MycoBank record number, analogous to existing functions mo_lpsn() and mo_gbif()
    • We’ve welcomed over 2,000 records from 2023, over 900 from 2024, and many thousands of new fungi
  • Other
    • New function mo_group_members() to retrieve the member microorganisms of a microorganism group. For example, mo_group_members("Strep group C") returns a vector of all microorganisms that are in that group.


  • SIR interpretation
    • It is now possible to use column names for argument ab, mo, and uti: as.sir(..., ab = "column1", mo = "column2", uti = "column3"). This greatly improves the flexibility for users.
    • Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.
    • To get quantitative values, as.double() on a sir object will return 1 for S, 2 for SDD/I, and 3 for R (NI will become NA). Other functions using sir classes (e.g., summary()) are updated to reflect the change to contain NI and SDD.
  • antibiotics data set
    • Added “clindamycin inducible screening” as CLI1. Since clindamycin is a lincosamide, the antibiotic selector lincosamides() now contains the argument only_treatable = TRUE (similar to other antibiotic selectors that contain non-treatable drugs)
    • Added Amorolfine (AMO, D01AE16), which is now also part of the antifungals() selector
  • Antibiotic selectors
    • Added selectors nitrofurans() and rifamycins()
    • When using antibiotic selectors such as aminoglycosides() that exclude non-treatable drugs like gentamicin-high, the function now always returns a warning that these can be included using only_treatable = FALSE
  • MICs
    • Added as valid levels: 4096, 6 powers of 0.0625, and 5 powers of 192 (192, 384, 576, 768, 960)
    • Added new argument keep_operators to as.mic(). This can be "all" (default), "none", or "edges". This argument is also available in the new rescale_mic() and scale_*_mic() functions.
    • Comparisons of MIC values are now more strict. For example, >32 is higher than (and never equal to) 32. Thus, as.mic(">32") == as.mic(32) now returns FALSE, and as.mic(">32") > as.mic(32) now returns TRUE.
    • Sorting of MIC values (using sort()) was fixed in the same manner; <0.001 now gets sorted before 0.001, and >0.001 gets sorted after 0.001.
  • Updated italicise_taxonomy() to support HTML output
  • custom_eucast_rules() now supports multiple antibiotics and antibiotic groups to be affected by a single rule
  • mo_info() now contains an extra element group_members, with the contents of the new mo_group_members() function
  • Greatly improved vctrs integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as dplyr’s bind_rows(), rowwise() and c_across() are now supported for e.g. columns of class mic. Despite this, this AMR package is still zero-dependent on any other package, including dplyr and vctrs.
  • Updated all ATC codes from WHOCC
  • Updated all antibiotic DDDs from WHOCC
  • Fix for using a manual value for mo_transform in antibiogram()
  • Fix for mapping ‘high level’ antibiotics in as.ab() (amphotericin B-high, gentamicin-high, kanamycin-high, streptomycin-high, tobramycin-high)
  • Improved overall algorithm of as.ab() for better performance and accuracy
  • Improved overall algorithm of for better performance and accuracy. Specifically, more weight is given to genus and species combinations in cases where the subspecies is miswritten, so that the result will be the correct genus and species.
  • Intermediate log2 levels used for MIC plotting are now more common values instead of following a strict dilution range
  • Fixed a bug for when antibiogram() returns an empty data set


  • Added Jordan Stull, Matthew Saab, and Javier Sanchez as contributors, to thank them for their valuable input

AMR 2.1.1

CRAN release: 2023-10-21

  • Fix for selecting first isolates using the phenotype-based method
    • This included too many isolates when patients had altering antibiograms within the same bacterial species
    • See for more info our issue #122
  • Added 1,366 LOINC codes to the antibiotics data set and updated to the latest version (LOINC v2.76)
  • MICs can now be used in complex number calculations and allow scientific number format as input (e.g., as.mic("1.28e-2"))
  • Fix rounding MICs on latest R beta (‘R-devel’)
  • Removed unneeded note about the used language when option AMR_locale is set
  • Fixed non-ASCII characters in documentation, according to CRAN maintainers

AMR 2.1.0

CRAN release: 2023-07-16


  • Regarding clinical breakpoints:
    • Clinical breakpoints and intrinsic resistance of EUCAST 2023 and CLSI 2023 have been added to the clinical_breakpoints data set for usage in as.sir(). EUCAST 2023 (v13.0) is now the new default guideline for all MIC and disks diffusion interpretations
    • The EUCAST dosage guideline of v13.0 has been added to the dosage data set
    • The clinical_breakpoints data set now also contains epidemiological cut-off (ECOFF) values and CLSI animal breakpoints. These two new breakpoint types can be used for MIC/disk interpretation using as.sir(..., breakpoint_type = "ECOFF") oras.sir(..., breakpoint_type = "animal"), which is an important new addition for veterinary microbiology.
  • Added support for 30 species groups / complexes. They are gathered in a new data set microorganisms.groups and are used in clinical breakpoint interpretation. For example, CLSI 2023 contains breakpoints for the RGM group (Rapidly Growing Mycobacterium, containing over 80 species) which is now supported by our package.
  • Added oxygen tolerance from BacDive to over 25,000 bacteria in the microorganisms data set
  • Added LPSN and GBIF identifiers, and oxygen tolerance to mo_info()
  • Added SAS Transport files (file extension .xpt) to our download page to use in SAS software
  • Added microbial codes for Gram-negative/positive anaerobic bacteria


  • Updated algorithm of by giving more weight to fungi
  • Fixed clinical breakpoints errors introduced by the source we import the rules from
  • mo_rank() now returns NA for ‘unknown’ microorganisms (B_ANAER, B_ANAER-NEG, B_ANAER-POS, B_GRAMN, B_GRAMP, F_FUNGUS, F_YEAST, and UNKNOWN)
  • When printing microorganism or antibiotic codes in a tibble, a mouse-hover now shows the full name of the code
  • Plots for MIC and disk diffusion values:
    • Now have settable arguments for breakpoint type and PK/PD, like as.sir()
    • Will now contain the name of the guideline table in the subtitle of the plot
  • Fixed formatting for sir_interpretation_history()
  • Fixed some WHONET codes for microorganisms and consequently a couple of entries in clinical_breakpoints
  • Fixed a bug for that led to coercion of NA values when using custom microorganism codes
  • Fixed usage of icu_exclude in first_isolates()
  • Improved algorithm:
    • Now allows searching on only species names
    • Fix for using the keep_synonyms argument when using MO codes as input
    • Fix for using the minimum_matching_score argument
  • Updated the code table in
  • Fixed an endless loop if using reference_df in
  • Fixed bug for indicating UTIs in as.sir()
  • Greatly improved speed of as.sir()

AMR 2.0.0

CRAN release: 2023-03-12

This is a new major release of the AMR package, with great new additions but also some breaking changes for current users. These are all listed below.


  • All functions and arguments with ‘rsi’ were replaced with ‘sir’, such as the interpretation of MIC values (now as.sir() instead of as.rsi()) - all old functions still work for now
  • Many new interesting functions, such as antibiogram() (for generating traditional/combined/syndromic/WISCA antibiograms), sir_confidence_interval() and mean_amr_distance(), and add_custom_microorganisms() to add custom microorganisms to this package
  • Clinical breakpoints added for EUCAST 2022 and CLSI 2022
  • Microbiological taxonomy (microorganisms data set) updated to 2022 and now based on LPSN and GBIF
  • Much increased algorithms to translate user input to valid taxonomy, e.g. by using recent scientific work about per-species human pathogenicity
  • 20 new antibiotics added and updated all DDDs and ATC codes
  • Extended support for antiviral agents (antivirals data set), with many new functions
  • Now available in 20 languages
  • Many small bug fixes



For this milestone version, we replaced all mentions of RSI with SIR, to comply with what is actually being commonly used in the field of clinical microbiology when it comes to this tri-form regarding AMR.

While existing functions such as as.rsi(), rsi_df() and ggplot_rsi() still work, their replacements as.sir(), sir_df(), ggplot_sir() are now the current functions for AMR data analysis. A warning will be thrown once a session to remind users about this. The data set rsi_translation is now called clinical_breakpoints to better reflect its content.

The ‘RSI functions’ will be removed in a future version, but not before late 2023 / early 2024.

New antibiogram function

With the new antibiogram() function, users can now generate traditional, combined, syndromic, and even weighted-incidence syndromic combination antibiograms (WISCA). With this, we follow the logic in the previously described work of Klinker et al. (2021, DOI 10.1177/20499361211011373) and Barbieri et al. (2021, DOI 10.1186/s13756-021-00939-2).

The help page for antibiogram() extensively elaborates on use cases, and antibiogram() also supports printing in R Markdown and Quarto, with support for 20 languages.

Furthermore, different plotting methods were implemented to allow for graphical visualisations as well.

Interpretation of MIC and disk diffusion values

The clinical breakpoints and intrinsic resistance of EUCAST 2022 and CLSI 2022 have been added for as.sir(). EUCAST 2022 (v12.0) is now the new default guideline for all MIC and disks diffusion interpretations, and for eucast_rules() to apply EUCAST Expert Rules. The default guideline (EUCAST) can now be changed with the new AMR_guideline option, such as: options(AMR_guideline = "CLSI 2020").

With the new arguments include_PKPD (default: TRUE) and include_screening (default: FALSE), users can now specify whether breakpoints for screening and from the PK/PD table should be included when interpreting MICs and disks diffusion values. These options can be set globally, which can be read in our new manual.

Interpretation guidelines older than 10 years were removed, the oldest now included guidelines of EUCAST and CLSI are from 2013.

Supported languages

We added support for the following ten languages: Chinese (simplified), Czech, Finnish, Greek, Japanese, Norwegian (bokmål), Polish, Romanian, Turkish and Ukrainian. All antibiotic names are now available in these languages, and the AMR package will automatically determine a supported language based on the user’s system language.

We are very grateful for the valuable input by our colleagues from other countries. The AMR package is now available in 20 languages in total, and according to download stats used in almost all countries in the world!

Outbreak management

For analysis in outbreak management, we updated the get_episode() and is_new_episode() functions: they now contain an argument case_free_days. This argument can be used to quantify the duration of case-free days (the inter-epidemic interval), after which a new episode will start.

This is common requirement in outbreak management, e.g. when determining the number of norovirus outbreaks in a hospital. The case-free period could then be 14 or 28 days, so that new norovirus cases after that time will be considered a different (or new) episode.

Microbiological taxonomy

The microorganisms data set no longer relies on the Catalogue of Life, but on the List of Prokaryotic names with Standing in Nomenclature (LPSN) and is supplemented with the ‘backbone taxonomy’ from the Global Biodiversity Information Facility (GBIF). The structure of this data set has changed to include separate LPSN and GBIF identifiers. Almost all previous MO codes were retained. It contains over 1,400 taxonomic names from 2022.

We previously relied on our own experience to categorise species into pathogenic groups, but we were very happy to encounter the very recent work of Bartlett et al. (2022, DOI 10.1099/mic.0.001269) who extensively studied medical-scientific literature to categorise all bacterial species into groups. See mo_matching_score() on how their work was incorporated into the prevalence column of the microorganisms data set. Using their results, the and all mo_*() functions are now much better capable of converting user input to valid taxonomic records.

The new function add_custom_microorganisms() allows users to add custom microorganisms to the AMR package.

We also made the following changes regarding the included taxonomy or microorganisms functions:

  • Updated full microbiological taxonomy according to the latest daily LPSN data set (December 2022) and latest yearly GBIF taxonomy backbone (November 2022)
  • Added function mo_current() to get the currently valid taxonomic name of a microorganism
  • Support for all 1,516 city-like serovars of Salmonella, such as Salmonella Goldcoast. Formally, these are serovars belonging to the S. enterica species, but they are reported with only the name of the genus and the city. For this reason, the serovars are in the subspecies column of the microorganisms data set and “enterica” is in the species column, but the full name does not contain the species name (enterica).
  • All new algorithm for (and thus all mo_*() functions) while still following our original set-up as described in our recently published JSS paper (DOI 10.18637/jss.v104.i03).
    • A new argument keep_synonyms allows to not correct for updated taxonomy, in favour of the now deleted argument allow_uncertain
    • It has increased tremendously in speed and returns generally more consequent results
    • Sequential coercion is now extremely fast as results are stored to the package environment, although coercion of unknown values must be run once per session. Previous results can be reset/removed with the new mo_reset_session() function.
    • Support for microorganism codes of the ASIan Antimicrobial Resistance Surveillance Network (ASIARS-Net)
    • The MO matching score algorithm (mo_matching_score()) now counts deletions and substitutions as 2 instead of 1, which impacts the outcome of and any mo_*() function
  • Removed all species of the taxonomic kingdom Chromista from the package. This was done for multiple reasons:
    • CRAN allows packages to be around 5 MB maximum, some packages are exempted but this package is not one of them
    • Chromista are not relevant when it comes to antimicrobial resistance, thus lacking the primary scope of this package
    • Chromista are almost never clinically relevant, thus lacking the secondary scope of this package
  • The microorganisms.old data set was removed, and all previously accepted names are now included in the microorganisms data set. A new column status contains "accepted" for currently accepted names and "synonym" for taxonomic synonyms; currently invalid names. All previously accepted names now have a microorganisms ID and - if available - an LPSN, GBIF and SNOMED CT identifier.

Antibiotic agents and selectors

The new function add_custom_antimicrobials() allows users to add custom antimicrobial codes and names to the AMR package.

The antibiotics data set was greatly updated:

  • The following 20 antibiotics have been added (also includes the new J01RA ATC group): azithromycin/fluconazole/secnidazole (AFC), cefepime/amikacin (CFA), cefixime/ornidazole (CEO), ceftriaxone/beta-lactamase inhibitor (CEB), ciprofloxacin/metronidazole (CIM), ciprofloxacin/ornidazole (CIO), ciprofloxacin/tinidazole (CIT), furazidin (FUR), isoniazid/sulfamethoxazole/trimethoprim/pyridoxine (IST), lascufloxacin (LSC), levofloxacin/ornidazole (LEO), nemonoxacin (NEM), norfloxacin/metronidazole (NME), norfloxacin/tinidazole (NTI), ofloxacin/ornidazole (OOR), oteseconazole (OTE), rifampicin/ethambutol/isoniazid (REI), sarecycline (SRC), tetracycline/oleandomycin (TOL), and thioacetazone (TAT)
  • Added some missing ATC codes
  • Updated DDDs and PubChem Compound IDs
  • Updated some antibiotic name spelling, now used by WHOCC (such as cephalexin -> cefalexin, and phenethicillin -> pheneticillin)
  • Antibiotic code “CEI” for ceftolozane/tazobactam has been replaced with “CZT” to comply with EARS-Net and WHONET 2022. The old code will still work in all cases when using as.ab() or any of the ab_*() functions.
  • Support for antimicrobial interpretation of anaerobic bacteria, by adding a ‘placeholder’ code B_ANAER to the microorganisms data set and adding the breakpoints of anaerobics to the clinical_breakpoints data set, which is used by as.sir() for interpretion of MIC and disk diffusion values

Also, we added support for using antibiotic selectors in scoped dplyr verbs (with or without using vars()), such as in: ... %>% summarise_at(aminoglycosides(), resistance), please see resistance() for examples.

Antiviral agents

We now added extensive support for antiviral agents! For the first time, the AMR package has extensive support for antiviral drugs and to work with their names, codes and other data in any way.

  • The antivirals data set has been extended with 18 new drugs (also from the new J05AJ ATC group) and now also contains antiviral identifiers and LOINC codes
  • A new data type av (antivirals) has been added, which is functionally similar to ab for antibiotics
  • Functions as.av(), av_name(), av_atc(), av_synonyms(), av_from_text() have all been added as siblings to their ab_*() equivalents

Other new functions

  • Function sir_confidence_interval() to add confidence intervals in AMR calculation. This is now also included in sir_df() and proportion_df().
  • Function mean_amr_distance() to calculate the mean AMR distance. The mean AMR distance is a normalised numeric value to compare AMR test results and can help to identify similar isolates, without comparing antibiograms by hand.
  • Function sir_interpretation_history() to view the history of previous runs of as.sir() (previously as.rsi()). This returns a ‘logbook’ with the selected guideline, reference table and specific interpretation of each row in a data set on which as.sir() was run.


  • get_episode() (and its wrapper is_new_episode()):
    • Fix for working with NA values
    • Fix for unsorted dates of length 2
    • Now returns class integer instead of numeric since they are always whole numbers
  • Argument combine_IR has been removed from this package (affecting functions count_df(), proportion_df(), and sir_df() and some plotting functions), since it was replaced with combine_SI three years ago
  • Using units in ab_ddd(..., units = "...") had been deprecated for some time and is now not supported anymore. Use ab_ddd_units() instead.
  • Support for data.frame-enhancing R packages, more specifically: data.table::data.table, janitor::tabyl, tibble::tibble, and tsibble::tsibble. AMR package functions that have a data set as output (such as sir_df() and bug_drug_combinations()), will now return the same data type as the input.
  • All data sets in this package are now a tibble, instead of base R data.frames. Older R versions are still supported, even if they do not support tibbles.
  • Our data sets are now also continually exported to Apache Feather and Apache Parquet formats. You can find more info in this article on our website.
  • For as.sir():
    • Fixed certain EUCAST breakpoints for MIC values
    • Allow NA values (e.g. as.sir(as.disk(NA), ...))
    • Fix for bug-drug combinations with multiple breakpoints for different body sites
    • Interpretation from MIC and disk zones is now more informative about availability of breakpoints and more robust
  • Removed the as.integer() method for MIC values, since MIC are not integer values and running table() on MIC values consequently failed for not being able to retrieve the level position (as that’s how normally as.integer() on factors work)
  • Fixed determination of Gram stains (mo_gramstain()), since the taxonomic phyla Actinobacteria, Chloroflexi, Firmicutes, and Tenericutes have been renamed to respectively Actinomycetota, Chloroflexota, Bacillota, and Mycoplasmatota in 2021
  • droplevels() on MIC will now return a common factor at default and will lose the mic class. Use droplevels(..., as.mic = TRUE) to keep the mic class.
  • Small fix for using ab_from_text()
  • Fixes for reading in text files using set_mo_source(), which now also allows the source file to contain valid taxonomic names instead of only valid microorganism ID of this package
  • Fixed a bug for mdro() when using similar column names with the Magiorakos guideline
  • Using any random_*() function (such as random_mic()) is now possible by directly calling the package without loading it first: AMR::random_mic(10)
  • Extended support for the vctrs package, used internally by the tidyverse. This allows to change values of class mic, disk, sir, mo and ab in tibbles, and to use antibiotic selectors for selecting/filtering, e.g. df[carbapenems() == "R", ]
  • Fix for using info = FALSE in mdro()
  • For all interpretation guidelines using as.sir() on amoxicillin, the rules for ampicillin will be used if amoxicillin rules are not available
  • Fix for using ab_atc() on non-existing ATC codes
  • Black and white message texts are now reversed in colour if using an RStudio dark theme
  • mo_snomed() now returns class character, not numeric anymore (to make long SNOMED codes readable)
  • Fix for using as.ab() on NA values
  • Updated support for all WHONET 2022 microorganism codes
  • Antimicrobial interpretation ‘SDD’ (susceptible dose-dependent, coined by CLSI) will be interpreted as ‘I’ to comply with EUCAST’s ‘I’ in as.sir()
  • Fix for mo_shortname() in case of higher taxonomic ranks (order, class, phylum)
  • Cleaning columns with as.sir(), as.mic(), or as.disk() will now show the column name in the warning for invalid results
  • Fix for using g.test() with zeroes in a 2x2 table
  • mo_synonyns() now contains the scientific reference as names


  • Added Peter Dutey-Magni, Dmytro Mykhailenko, Anton Mymrikov, Andrew Norgan, Jonas Salm, and Anita Williams as contributors, to thank them for their valuable input
  • New website to make use of the new Bootstrap 5 and pkgdown 2.0. The website now contains results for all examples and will be automatically regenerated with every change to our repository, using GitHub Actions
  • All R and Rmd files in this project are now styled using the styler package
  • Set scalar conditional expressions (&& and ||) where possible to comply with the upcoming R 4.3
  • An enormous lot of code cleaning, fixing some small bugs along the way

This changelog only contains changes from AMR v2.0 (January 2023) and later. For prior versions, please see our archive.