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Funnel-based antimicrobial resistance monitoring in Italy: the FUN-IT study

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Publicado en:Scientific Reports (Nature Publisher Group) vol. 15, no. 1 (2025), p. 40477-40488
Autor principal: Milanesi, Simone
Otros Autores: Colaneri, Marta, Ferrari, Sara Laura, Baratelli, Alice, Villa, Simone, Tosca, Elena Maria, Perrone, Pier Mario, Gori, Andrea, Raviglione, Mario, De Nicolao, Giuseppe
Publicado:
Nature Publishing Group
Materias:
Italy
Pandemics
Health promotion
Antibiotic resistance
Pathogens
Public health
Random variables
Drug resistance
Control charts
Staphylococcus infections
Antimicrobial resistance
Vancomycin
Standard scores
Methicillin
COVID-19
Process control
Statistical process control
Antibiotics
Antimicrobial agents
Carbapenems
E coli
Surveillance
Expected values
Parameter estimation
Social
Economic
Acceso en línea:Citation/Abstract
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Resumen:Italy reports some of the highest antimicrobial resistance (AMR) rates in Europe. This necessitates multiple interventions among which improved surveillance is a key to solutions. Statistical Process Control (SPC) methods may help distinguishing between natural variability and significant regional trends. We applied specifically tailored SPC methods, namely funnel plots, Z-score charts, and chi-squared control charts to the AMR data from the AR-ISS surveillance system (2015–2023), focusing on bloodstream infections. Specifically, we analysed regional and temporal trends of carbapenem-resistant Klebsiella pneumoniae (CRKP), third-generation cephalosporin-resistant Escherichia coli (3GCephRE), carbapenem-resistant Acinetobacter spp. (CRAS), carbapenem-resistant Pseudomonas aeruginosa (CRPA), vancomycin-resistant Enterococcus faecium (VRE-faecium), and Staphylococcus aureus methicillin-resistant (MRSA). VRE- faecium showed a persistent increase at the national level, while other pathogens exhibited marked regional variability. Funnel plots identified significant outliers, particularly for CRAS and CRKP, with peaks in 2020–2021. These trends align with increased antibiotic use during the COVID-19 pandemic. The chi-squared control chart highlighted widening interregional disparities, possibly indicating an uneven distribution of AMR containment efforts across Italy. SPC methods can help highlighting significant deviations and interregional disparities in AMR trends across Italy. The identification of specific outliers suggests these tools can complement traditional surveillance approaches by flagging patterns that may warrant further investigation, supporting targeted public health interventions, especially where regional differences are pronounced.
ISSN:2045-2322
DOI:10.1038/s41598-025-24383-z
Fuente:Science Database