AMR 2.0.0

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.




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:

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:

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.

Other new functions



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