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dr. M.S. (Matthijs) Berends
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DESCRIPTION
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Package: AMR
Version: 3.0.1.9082
Version: 3.0.1.9083
Date: 2026-07-03
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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NEWS.md
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# AMR 3.0.1.9082
# AMR 3.0.1.9083
Planned as v3.1.0, end of June 2026.

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index.Rmd
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@@ -20,7 +20,7 @@ AMR:::reset_all_thrown_messages()
# The `AMR` Package for R <a href="https://amr-for-r.org/"><img src="./logo.svg" align="right" height="139" /></a>
* Provides an **all-in-one solution** for antimicrobial resistance (AMR) data analysis in a One Health approach
* **Peer-reviewed**, used in over 175 countries, cites over 100 times, available in `r length(AMR:::LANGUAGES_SUPPORTED)` languages
* **Peer-reviewed**, used in over 175 countries, cited over 100 times, available in `r length(AMR:::LANGUAGES_SUPPORTED)` languages
* Generates **antibiograms** - WISCA for empiric coverage estimates, or traditional/syndromic for AMR surveillance
* Provides the **full microbiological taxonomy** of `r AMR:::format_included_data_number(AMR::microorganisms)` distinct species and extensive info of `r AMR:::format_included_data_number(NROW(AMR::antimicrobials) + NROW(AMR::antivirals))` antimicrobial drugs
* Applies **CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("CLSI", guideline))$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("CLSI", guideline))$guideline)))`** and **EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("EUCAST", guideline))$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("EUCAST", guideline))$guideline)))`** clinical and veterinary breakpoints, and ECOFFs, for MIC and disk zone interpretation
@@ -41,9 +41,7 @@ AMR:::reset_all_thrown_messages()
## Introduction
The `AMR` package is a peer-reviewed, [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. We are a team of [many different researchers](./authors.html) from around the globe to make this a successful and durable project!
This work was published in the Journal of Statistical Software (Volume 104(3); [DOI 10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and formed the basis of two PhD theses ([DOI 10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and [DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
The `AMR` package is a peer-reviewed, [free and open-source](#copyright) R package with [zero dependencies](https://en.wikipedia.org/wiki/Dependency_hell) to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial data and properties, by using evidence-based methods. **Our aim is to provide a standard** for clean and reproducible AMR data analysis, that can therefore empower epidemiological analyses to continuously enable surveillance and treatment evaluation in any setting. We are a team of [many different researchers](./authors.html) from around the globe to make this a successful and durable project! The `AMR` package was already cited [over 100 times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation_for_view=sAoHvIgAAAAJ:0EnyYjriUFMC) in scientific research.
After installing this package, R knows [**`r AMR:::format_included_data_number(AMR::microorganisms)` distinct microbial species**](./reference/microorganisms.html) (updated `r format(AMR:::TAXONOMY_VERSION$GBIF$accessed_date, "%B %Y")`) and all [**`r AMR:::format_included_data_number(NROW(AMR::antimicrobials) + NROW(AMR::antivirals))` antimicrobial and antiviral drugs**](./reference/antimicrobials.html) by name and code (including ATC, EARS-Net, ASIARS-Net, PubChem, LOINC and SNOMED CT), and knows all about valid SIR and MIC values. The integral clinical breakpoint guidelines from CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("CLSI", guideline))$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("CLSI", guideline))$guideline)))` and EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("EUCAST", guideline))$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, grepl("EUCAST", guideline))$guideline)))` are included, even with epidemiological cut-off (ECOFF) values. It supports and can read any data format, including WHONET data. This package works on Windows, macOS and Linux with all versions of R since R-3.0 (April 2013). **It was designed to work in any setting, including those with very limited resources**. It was created for both routine data analysis and academic research at the Faculty of Medical Sciences of the [University of Groningen](https://www.rug.nl) and the [University Medical Center Groningen](https://www.umcg.nl).
@@ -61,8 +59,6 @@ lang_txt <- AMR:::vector_and(paste(img, langs), sort = FALSE, quotes = FALSE)
With the help of contributors from all corners of the world, the `AMR` package is available in `r lang_txt`. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
The `AMR` package was cited [over 100 times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation_for_view=sAoHvIgAAAAJ:0EnyYjriUFMC) in scientific research.
## Practical examples
### Filtering and selecting data

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index.md
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- Provides an **all-in-one solution** for antimicrobial resistance (AMR)
data analysis in a One Health approach
- **Peer-reviewed**, used in over 175 countries, cites over 100 times,
- **Peer-reviewed**, used in over 175 countries, cited over 100 times,
available in 28 languages
- Generates **antibiograms** - WISCA for empiric coverage estimates, or
traditional/syndromic for AMR surveillance
@@ -51,14 +51,10 @@ and reproducible AMR data analysis, that can therefore empower
epidemiological analyses to continuously enable surveillance and
treatment evaluation in any setting. We are a team of [many different
researchers](./authors.html) from around the globe to make this a
successful and durable project!
This work was published in the Journal of Statistical Software (Volume
104(3); [DOI
10.18637/jss.v104.i03](https://doi.org/10.18637/jss.v104.i03)) and
formed the basis of two PhD theses ([DOI
10.33612/diss.177417131](https://doi.org/10.33612/diss.177417131) and
[DOI 10.33612/diss.192486375](https://doi.org/10.33612/diss.192486375)).
successful and durable project! The `AMR` package was already cited
[over 100
times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation_for_view=sAoHvIgAAAAJ:0EnyYjriUFMC)
in scientific research.
After installing this package, R knows [**~97 000 distinct microbial
species**](./reference/microorganisms.html) (updated mei 2026) and all
@@ -144,10 +140,6 @@ Urdu, and
Vietnamese. Antimicrobial drug (group) names and colloquial
microorganism names are provided in these languages.
The `AMR` package was cited [over 100
times](https://scholar.google.com/citations?view_op=view_citation&hl=en&citation_for_view=sAoHvIgAAAAJ:0EnyYjriUFMC)
in scientific research.
## Practical examples
### Filtering and selecting data
@@ -233,7 +225,7 @@ wisca(example_isolates,
| Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:------------------------|:-------------------------------------|:-------------------------------------|
| 69.9% (64.9-75.3%) | 93.6% (92.1-95%) | 89.9% (87-92.4%) |
| 70.1% (65.1-75.4%) | 93.6% (92.1-95%) | 89.8% (87.3-92.4%) |
WISCA supports stratification by any clinical variable, so you can
generate syndrome-specific or ward-specific coverage estimates:
@@ -248,9 +240,9 @@ wisca(example_isolates,
| Syndromic Group | Piperacillin/tazobactam | Piperacillin/tazobactam + Gentamicin | Piperacillin/tazobactam + Tobramycin |
|:----------------|:------------------------|:-------------------------------------|:-------------------------------------|
| Clinical | 74.5% (68.6-80.5%) | 93.7% (91.7-95.1%) | 90.4% (87.1-93.1%) |
| ICU | 57% (48.6-65.6%) | 86.7% (83.3-89.9%) | 83% (78.1-87.5%) |
| Outpatient | 57.4% (46-69.1%) | 76.7% (70.5-82.7%) | 67.7% (57.3-77.4%) |
| Clinical | 74.4% (68.2-79.9%) | 93.6% (91.9-95.1%) | 90.4% (86.9-93.3%) |
| ICU | 57% (48.6-65.9%) | 86.8% (83.4-89.8%) | 82.9% (77.5-87.1%) |
| Outpatient | 57.5% (45.9-69.3%) | 76.6% (70.6-82.3%) | 67.9% (57.6-77.2%) |
**For AMR surveillance**, traditional antibiograms remain the right tool
for tracking resistance per species over time: