Journal article
Using Sensor Networks to Study the Effect of Peripatetic Healthcare Workers on the Spread of Hospital-Associated Infections
The Journal of infectious diseases, Vol.206(10), pp.1549-1557
2012
DOI: 10.1093/infdis/jis542
PMCID: PMC3475631
PMID: 23045621
Abstract
Background: Super-spreading events, in which an individual with measurably high connectivity is responsible for infecting a large number of people, have been observed. Our goal is to determine the impact of hand hygiene noncompliance among peripatetic (eg, highly mobile or highly connected) healthcare workers compared with less-connected workers.
Methods: We used a mote-based sensor network to record contacts among healthcare workers and patients in a 20-bed intensive care unit. The data collected from this network form the basis for an agent-based simulation to model the spread of nosocomial pathogens with various transmission probabilities. We identified the most- and least-connected healthcare workers. We then compared the effects of hand hygiene noncompliance as a function of connectedness.
Results: The data confirm the presence of peripatetic healthcare workers. Also, agent-based simulations using our real contact network data confirm that the average number of infected patients was significantly higher when the most connected healthcare worker did not practice hand hygiene and significantly lower when the least connected healthcare workers were noncompliant.
Conclusions: Heterogeneity in healthcare worker contact patterns dramatically affects disease diffusion. Our findings should inform future infection control interventions and encourage the application of social network analysis to study disease transmission in healthcare settings.
Details
- Title: Subtitle
- Using Sensor Networks to Study the Effect of Peripatetic Healthcare Workers on the Spread of Hospital-Associated Infections
- Creators
- Thomas HORNBECK - Department of Computer Science, University of Iowa, Iowa City, United StatesDavid NAYLOR - Department of Computer Science, University of Iowa, Iowa City, United StatesAlberto M SEGRE - Department of Computer Science, University of Iowa, Iowa City, United StatesGeb THOMAS - Department of Industrial and Mechanical Engineering, University of Iowa, Iowa City, United StatesTed HERMAN - Department of Computer Science, University of Iowa, Iowa City, United StatesPhilip M POLGREEN - Carver College of Medicine and College of Public Health, University of Iowa, Iowa City, United States
- Resource Type
- Journal article
- Publication Details
- The Journal of infectious diseases, Vol.206(10), pp.1549-1557
- DOI
- 10.1093/infdis/jis542
- PMID
- 23045621
- PMCID
- PMC3475631
- NLM abbreviation
- J Infect Dis
- ISSN
- 0022-1899
- eISSN
- 1537-6613
- Publisher
- Oxford University Press; Oxford
- Language
- English
- Date published
- 2012
- Academic Unit
- Infectious Diseases; Epidemiology; Orthopedics and Rehabilitation; Industrial and Systems Engineering; Nursing; Injury Prevention Research Center; Computer Science; Internal Medicine
- Record Identifier
- 9984040598402771
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