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

Abstract

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 (VR E-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.