ArticlePLoS computational biology2017
Spread of hospital-acquired infections: A comparison of healthcare networks.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.
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Who cites it
26 citing papers in PubMed.
- Reconstructing healthcare networks from patient transfer data: A systematic review.PLOS digital health · 2026Article
- High-risk clonal expansion of IMP-producingAntimicrobial agents and chemotherapy · 2025Article
- Prevalence and associated factors of hospital acquired infection among surgical patients at Adama Hospital Medical College, Ethiopia.Scientific reports · 2025Article
- A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research.Medical care research and review : MCRR · 2025Article
- Healthcare as a driver, reservoir and amplifier of antimicrobial resistance: opportunities for interventions.Nature reviews. Microbiology · 2024Review
- Antimicrobial activity of cefepime-tazobactam combination against extended spectrum beta-lactamase and/or AmpC beta-lactamase- producing gram-negative bacilli.BMC infectious diseases · 2024Observational
- Regional patient transfer patterns matter for the spread of hospital-acquired pathogens.Scientific reports · 2024Article
- Transmission of drug-resistant bacteria in a hospital-community model stratified by patient risk.Scientific reports · 2023Article
- Physician Attitude toward Their Attires and Laundering Habit Changes during the COVID-19: A Cross-Sectional Survey in a Tertiary Care Center.Avicenna journal of medicine · 2023Article
- Innovation for infection prevention and control-revisiting Pasteur's vision.Lancet (London, England) · 2022Review
- Cross-site collaboration on infection prevention and control research-room for improvement? A 7-year comparative study in five European countries.Antimicrobial resistance and infection control · 2022Article
- Efficacy andFrontiers in cellular and infection microbiology · 2022Review
- Making sense of the French public hospital system: a network-based approach to hospital clustering using unsupervised learning methods.BMC health services research · 2021Article
- How does innovative technology impact nursing in infectious diseases and infection control? A scoping review.Nursing open · 2021Article
- Assessment of Hospital Characteristics and Interhospital Transfer Patterns of Adults With Emergency General Surgery Conditions.JAMA network open · 2021Article
- Effects of incomplete inter-hospital network data on the assessment of transmission dynamics of hospital-acquired infections.PLoS computational biology · 2021Article
- Relevance of intra-hospital patient movements for the spread of healthcare-associated infections within hospitals - a mathematical modeling study.PLoS computational biology · 2021Article
- Article
- Modelling pathogen spread in a healthcare network: Indirect patient movements.PLoS computational biology · 2020Article
- Assessing the role of inter-facility patient transfer in the spread of carbapenemase-producing Enterobacteriaceae: the case of France between 2012 and 2015.Scientific reports · 2020Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hospital-acquired infections (HAIs), including emerging multi-drug resistant organisms, threaten healthcare systems worldwide. Efficient containment measures of HAIs must mobilize the entire healthcare network. Thus, to best understand how to reduce the potential scale of HAI epidemic spread, we explore patient transfer patterns in the French healthcare system. Using an exhaustive database of all hospital discharge summaries in France in 2014, we construct and analyze three patient networks based on the following: transfers of patients with HAI (HAI-specific network); patients with suspected HAI (suspected-HAI network); and all patients (general network). All three networks have heterogeneous patient flow and demonstrate small-world and scale-free characteristics. Patient populations that comprise these networks are also heterogeneous in their movement patterns. Ranking of hospitals by centrality measures and comparing community clustering using community detection algorithms shows that despite the differences in patient population, the HAI-specific and suspected-HAI networks rely on the same underlying structure as that of the general network. As a result, the general network may be more reliable in studying potential spread of HAIs. Finally, we identify transfer patterns at both the French regional and departmental (county) levels that are important in the identification of key hospital centers, patient flow trajectories, and regional clusters that may serve as a basis for novel wide-scale infection control strategies.
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