Work

Using Social Network Analysis to Map Infectious Risk Across Care Settings

Year: 2026

Type: article

Abstract: Background Long-term care facilities (LTCFs) and hospitals form an interconnected system in which patient mobility shapes the transmission of multidrug-resistant organisms. Facility-level approaches may fail to capture the system-level structure of infectious risk. We applied Social Network Analysis to map carbapenem-resistant Enterobacterales (CRE) circulation in Tuscany. Methods Retrospective study of 2024 regional administrative healthcare flows for residents aged ≥65 years in LTCFs in Tuscany. Three directed weighted networks linking LTCFs, hospitals and emergency departments were built: all-cause transfers, transfers of CRE-colonised and CRE-infected residents. Node-level centrality metrics (degree, weighted degree, and betweenness) were compared between networks using Spearman’s rank correlation stratified by node type, with case studies on top-ranking nodes. Results The cohort included 11,914 residents in 325 LTCFs (mean age 85, 70% female); CRE incidence was 4.1/100,000 person-days, with hospital-acquired (79.7) far exceeding LTCF-acquired (3.1) rates. The CRE-colonised network was sparser than the all-cause network (107 vs 411 nodes). Centralities in the CRE-infected network correlated strongly with all-cause centralities (weighted in-degree ρ = 0.91; betweenness ρ = 0.71; p < 0.001), whereas the CRE-colonised network showed only moderate correlations (ρ = 0.59 and ρ = 0.28; p < 0.001); betweenness showed the lowest agreement. Case studies revealed a tertiary hospital with high all-cause betweenness (0.109) but limited CRE bridging role (0.004), and an LTCF channelling 271 CRE-positive transfers exclusively to acute care. Conclusions Infectious risk is shaped not only by healthcare volume but by the structural position of facilities within patient-sharing networks. Bridging roles diverge most between all-cause and CRE networks; network-informed indicators may identify high-risk nodes invisible to traditional surveillance and support coordinated prevention. Key messages • Patient-sharing networks reveal infectious risk patterns that facility-level surveillance may miss, especially across LTCFs, hospitals and emergency departments. • Bridging roles differ markedly between all-cause and CRE networks, supporting network-informed targeting of IPC and screening strategies.

Source: European Journal of Public Health

DOI: 10.1093/eurpub/ckag169.422