ArticleJournal of theoretical biology2008
Controlling nosocomial infection based on structure of hospital social networks.
Article in Journal of theoretical biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 3 of them syntheses that pooled it.
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Who cites it
28 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Simulation models for transmission of health care-associated infection: A systematic review.American journal of infection control · 2020Pooled it
- Applications of network analysis to routinely collected health care data: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2018Pooled it
- Modelling the transmission of healthcare associated infections: a systematic review.BMC infectious diseases · 2013Pooled it
- The precipitate structure of copper-based antibacterial and antiviral agents enhances their longevity for kitchen use.NPJ science of food · 2024Article
- A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.Frontiers in public health · 2022Article
- Reorganization of nurse scheduling reduces the risk of healthcare associated infections.Scientific reports · 2021Article
- Evaluation of nosocomial infections through contact patterns in a small animal hospital using social network analysis and genotyping techniques.Scientific reports · 2021Article
- Environmental Design Strategies to Decrease the Risk of Nosocomial Infection in Medical Buildings Using a Hybrid MCDM Model.Journal of healthcare engineering · 2021Article
- Network interventions for managing the COVID-19 pandemic and sustaining economy.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Tracking Nosocomial Diseases at Individual Level with a Real-Time Indoor Positioning System.Journal of medical systems · 2018Article
- Contact among healthcare workers in the hospital setting: developing the evidence base for innovative approaches to infection control.BMC infectious diseases · 2018Article
- Healthcare-associated infections: potential for prevention through vaccination.Therapeutic advances in vaccines and immunotherapy · 2018Review
- Hunter-Gatherer Social Networks and Reproductive Success.Scientific reports · 2017Article
- Network position and health care worker infections.Journal of economic interaction and coordination · 2017Article
- Fragmenting networks by targeting collective influencers at a mesoscopic level.Scientific reports · 2016Article
- Controlling infectious disease through the targeted manipulation of contact network structure.Epidemics · 2015Article
- Article
- The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- A social network of hospital acquired infection built from electronic medical record data.Journal of the American Medical Informatics Association : JAMIA · 2013Article
- Limits of patient isolation measures to control extended-spectrum beta-lactamase-producing Enterobacteriaceae: model-based analysis of clinical data in a pediatric ward.BMC infectious diseases · 2013Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Nosocomial infection (i.e. infection in healthcare facilities) raises a serious public health problem, as implied by the existence of pathogens characteristic to healthcare facilities such as methicillin-resistant Staphylococcus aureus and hospital-mediated outbreaks of influenza and severe acute respiratory syndrome. For general communities, epidemic modeling based on social networks is being recognized as a useful tool. However, disease propagation may occur in a healthcare facility in a manner different from that in a urban community setting due to different network architecture. We simulate stochastic susceptible-infected-recovered dynamics on social networks, which are based on observations in a hospital in Tokyo, to explore effective containment strategies against nosocomial infection. The observed social networks in the hospital have hierarchical and modular structure in which dense substructure such as departments, wards, and rooms, are globally but only loosely connected, and do not reveal extremely right-skewed distributions of the number of contacts per individual. We show that healthcare workers, particularly medical doctors, are main vectors (i.e. transmitters) of diseases on these networks. Intervention methods that restrict interaction between medical doctors and their visits to different wards shrink the final epidemic size more than intervention methods that directly protect patients, such as isolating patients in single rooms. By the same token, vaccinating doctors with priority rather than patients or nurses is more effective. Finally, vaccinating individuals with large betweenness centrality (frequency of mediating connection between pairs of individuals along the shortest paths) is superior to vaccinating ones with large connectedness to others or randomly chosen individuals, which was suggested by previous model studies.
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