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A Six-Step Protocol for Monitoring Antimicrobial Resistance Trends Using WHONET and R: Real-World Application and R Code Integration

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Title: A Six-Step Protocol for Monitoring Antimicrobial Resistance Trends Using WHONET and R: Real-World Application and R Code Integration
Authors: Fabio Ingravalle, Antonio Vinci, Marco Ciotti, Carla Fontana, Francesca Pica, Emanuele Sebastiani, Clara Donnoli, Martino Guido Rizzo, Dario Tedesco, Silvia D’Arezzo, Stefania Cicalini, Michele Tancredi Loiudice, Massimo Maurici
Source: Methods and Protocols, Vol 8, Iss 5, p 115 (2025)
Publisher Information: MDPI AG, 2025.
Publication Year: 2025
Collection: LCC:Biology (General)
Subject Terms: antimicrobial resistance, surveillance, R programming, microbiology laboratory data, open-source tools, Biology (General), QH301-705.5
Description: Antimicrobial resistance is a global health issue, and the WHO has made significant efforts in the development of tools for its monitoring. However, such tools are underutilized, due to limited knowledge, technical capacity, and scarcity of economic resources. AMR surveillance can be conducted using WHOnet and R, two free-of-charge software tools widely adopted in both clinical practice and scientific research. WHOnet is designed for managing laboratory data and antimicrobial susceptibility test results, while R is a programming language dedicated to statistical computing and data visualization. The combined use of these tools enables a reproducible workflow for retrospective AMR trend analysis. This paper provides step-by-step instructions on how to perform such analysis and also provides the respective R code. The described code and software results are shown using real-world data from an Italian hospital as an example. The standardization of the analysis process and the rapid availability of data on antimicrobial resistance are critical for both clinicians and public health professionals. They would allow for empirical decisions on antimicrobial treatment based on the specific epidemiological characteristics of the hospital or community setting.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2409-9279
Relation: https://www.mdpi.com/2409-9279/8/5/115; https://doaj.org/toc/2409-9279
DOI: 10.3390/mps8050115
Access URL: https://doaj.org/article/e4b7b218745342ad92355fd1d9cb20ff
Accession Number: edsdoj.4b7b218745342ad92355fd1d9cb20ff
Database: Directory of Open Access Journals
Description
Abstract:Antimicrobial resistance is a global health issue, and the WHO has made significant efforts in the development of tools for its monitoring. However, such tools are underutilized, due to limited knowledge, technical capacity, and scarcity of economic resources. AMR surveillance can be conducted using WHOnet and R, two free-of-charge software tools widely adopted in both clinical practice and scientific research. WHOnet is designed for managing laboratory data and antimicrobial susceptibility test results, while R is a programming language dedicated to statistical computing and data visualization. The combined use of these tools enables a reproducible workflow for retrospective AMR trend analysis. This paper provides step-by-step instructions on how to perform such analysis and also provides the respective R code. The described code and software results are shown using real-world data from an Italian hospital as an example. The standardization of the analysis process and the rapid availability of data on antimicrobial resistance are critical for both clinicians and public health professionals. They would allow for empirical decisions on antimicrobial treatment based on the specific epidemiological characteristics of the hospital or community setting.
ISSN:24099279
DOI:10.3390/mps8050115