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.

Funnel-based antimicrobial resistance monitoring in Italy: the FUN-IT study / S. Milanesi, M. Colaneri, S.L. Ferrari, A. Baratelli, S. Villa, E.M. Tosca, P.M. Perrone, A. Gori, M. Raviglione, G. De Nicolao. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 15:1(2025 Nov 18), pp. 40477.1-40477.11. [10.1038/s41598-025-24383-z]

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

M. Colaneri
Secondo
;
S.L. Ferrari;A. Baratelli;S. Villa;P.M. Perrone;A. Gori;M. Raviglione;
2025

Abstract

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.
Settore MEDS-24/B - Igiene generale e applicata
Settore MEDS-10/B - Malattie infettive
   One Health Basic and Translational Research Actions addressing Unmet Need on Emerging Infectious Diseases (INF-ACT)
   INF-ACT
   MINISTERO DELL'UNIVERSITA' E DELLA RICERCA
   PE00000007
18-nov-2025
Article (author)
File in questo prodotto:
File Dimensione Formato  
unpaywall-bitstream-2086632595.pdf

accesso aperto

Tipologia: Publisher's version/PDF
Licenza: Creative commons
Dimensione 2.16 MB
Formato Adobe PDF
2.16 MB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/2434/1205616
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
  • OpenAlex ND
social impact