Introduction
-
The AMR package is a peer-reviewed, free and open-source R package with zero dependencies 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 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) and formed the basis of two PhD theses (DOI 10.33612/diss.177417131 and DOI 10.33612/diss.192486375).
+
The AMR package is a peer-reviewed, free and open-source R package with zero dependencies 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 from around the globe to make this a successful and durable project! The AMR package was already cited over 100 times in scientific research.
After installing this package, R knows ~97 000 distinct microbial species (updated mei 2026) and all ~620 antimicrobial and antiviral drugs 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 2011-2026 and EUCAST 2011-2026 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 and the University Medical Center Groningen.
Used in over 175 countries, available in 28 languages
@@ -120,7 +119,6 @@
Since its first public release in early 2018, this R package has been used in almost all countries in the world. Click the map to enlarge and to see the country names.
With the help of contributors from all corners of the world, the AMR package is available in 
English, 
Arabic, 
Bengali, 
Chinese, 
Czech, 
Danish, 
Dutch, 
Finnish, 
French, 
German, 
Greek, 
Hindi, 
Indonesian, 
Italian, 
Japanese, 
Korean, 
Norwegian, 
Polish, 
Portuguese, 
Romanian, 
Russian, 
Spanish, 
Swahili, 
Swedish, 
Turkish, 
Ukrainian, 
Urdu, and 
Vietnamese. Antimicrobial drug (group) names and colloquial microorganism names are provided in these languages.
-
The AMR package was cited over 100 times in scientific research.
@@ -192,9 +190,9 @@
Piperacillin/tazobactam + Tobramycin |
-| 69.9% (64.9-75.3%) |
+70.1% (65.1-75.4%) |
93.6% (92.1-95%) |
-89.9% (87-92.4%) |
+89.8% (87.3-92.4%) |
WISCA supports stratification by any clinical variable, so you can generate syndrome-specific or ward-specific coverage estimates:
@@ -220,21 +218,21 @@
| Clinical |
-74.5% (68.6-80.5%) |
-93.7% (91.7-95.1%) |
-90.4% (87.1-93.1%) |
+74.4% (68.2-79.9%) |
+93.6% (91.9-95.1%) |
+90.4% (86.9-93.3%) |
| ICU |
-57% (48.6-65.6%) |
-86.7% (83.3-89.9%) |
-83% (78.1-87.5%) |
+57% (48.6-65.9%) |
+86.8% (83.4-89.8%) |
+82.9% (77.5-87.1%) |
| Outpatient |
-57.4% (46-69.1%) |
-76.7% (70.5-82.7%) |
-67.7% (57.3-77.4%) |
+57.5% (45.9-69.3%) |
+76.6% (70.6-82.3%) |
+67.9% (57.6-77.2%) |
diff --git a/index.md b/index.md
index ef163eaff..bcf3b1419 100644
--- a/index.md
+++ b/index.md
@@ -2,7 +2,7 @@
- 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
@@ -41,14 +41,10 @@ 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](https://amr-for-r.org/authors.md) 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)).
+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 [**~97 000 distinct microbial
species**](https://amr-for-r.org/reference/microorganisms.md) (updated
@@ -89,10 +85,6 @@ Swahili,  Swedish,  Turkish,
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
@@ -187,7 +179,7 @@ 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:
@@ -203,9 +195,9 @@ 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:
diff --git a/llms.txt b/llms.txt
index fa9958d46..ec9fad6af 100644
--- a/llms.txt
+++ b/llms.txt
@@ -2,7 +2,7 @@
- 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
@@ -41,14 +41,10 @@ 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](https://amr-for-r.org/authors.md) 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)).
+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 [**~97 000 distinct microbial
species**](https://amr-for-r.org/reference/microorganisms.md) (updated
@@ -89,10 +85,6 @@ Swahili,  Swedish,  Turkish,
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
@@ -187,7 +179,7 @@ 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:
@@ -203,9 +195,9 @@ 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:
diff --git a/news/index.html b/news/index.html
index 797852ed1..bf91f5259 100644
--- a/news/index.html
+++ b/news/index.html
@@ -7,7 +7,7 @@
AMR (for R)
-
3.0.1.9082
+
3.0.1.9083