{
  "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.\n\nMethods: 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.\n\nResults: 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.\n\nConclusions: 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.\n\nKey messages: • Patient-sharing networks reveal infectious risk patterns that facility-level surveillance may miss, especially across LTCFs, hospitals and emergency departments.\n\n• Bridging roles differ markedly between all-cause and CRE networks, supporting network-informed targeting of IPC and screening strategies.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": "abstract",
  "arxiv": null,
  "author_total": 10,
  "authors": [
    {
      "name": "V Casigliani"
    },
    {
      "name": "S Forni"
    },
    {
      "name": "F Collini"
    },
    {
      "name": "F Gemmi"
    },
    {
      "name": "A Bedini"
    },
    {
      "name": "F Ruffini"
    },
    {
      "name": "A Bechini"
    },
    {
      "name": "F Marcelloni"
    },
    {
      "name": "C Rizzo"
    },
    {
      "name": "M Falcone"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/bsc2dwhpf83rw.bib",
  "cited_by": 0,
  "doi": "10.1093/eurpub/ckag169.422",
  "fulltext_url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC13697715/",
  "id": "bsc2dwhpf83rw",
  "issns": [
    "1101-1262",
    "1464-360X"
  ],
  "landing_url": "https://doi.org/10.1093/eurpub/ckag169.422",
  "language": "en",
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "heading",
      "3. PARALLEL PROGRAMME"
    ],
    [
      "heading",
      "AcademicSubjects/MED00860"
    ],
    [
      "heading",
      "AcademicSubjects/SOC01210"
    ],
    [
      "heading",
      "AcademicSubjects/SOC02610"
    ],
    [
      "openalex",
      "2725|Infection Control in Healthcare"
    ]
  ],
  "openalex": "W7223688143",
  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13697715/pdf/?tool=EBI",
  "pmcid": "PMC13697715",
  "pmid": null,
  "published": "2026-10-01",
  "publisher": "Oxford University Press",
  "ris": "https://research.draconitic.com/paper/bsc2dwhpf83rw.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:18:43Z",
      "native_id": "PMC13697715",
      "source": "pmc",
      "url": "https://doi.org/10.1093/eurpub/ckag169.422"
    },
    {
      "first_seen": "2026-10-30T12:21:25Z",
      "native_id": "PMC:PMC13697715",
      "source": "europepmc",
      "url": "https://europepmc.org/article/PMC/PMC13697715"
    }
  ],
  "subjects": [
    {
      "field": "medicine",
      "origin": "openalex:2725|Infection Control in Healthcare",
      "subfield": "infectious-disease"
    }
  ],
  "title": "Using Social Network Analysis to Map Infectious Risk Across Care Settings",
  "title_text": "Using Social Network Analysis to Map Infectious Risk Across Care Settings",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T12:34:42Z",
  "url": "https://research.draconitic.com/paper/bsc2dwhpf83rw",
  "venue": "The European Journal of Public Health",
  "versions": []
}