The transmission of nosocomial pathogens in an intensive care unit: a space–time clustering and structural equation modelling approach

Rushton, Steven, Shirley, Mark, Sheridan, E. A., Lanyon, Clare and O'Donnell, Anthony (2010) The transmission of nosocomial pathogens in an intensive care unit: a space–time clustering and structural equation modelling approach. Epidemiology and Infection, 138 (06). pp. 915-926. ISSN 0950-2688

[img]
Preview
PDF (Article)
S095026880999094Xa.pdf - Published Version

Download (186kB) | Preview
Official URL: http://dx.doi.org/10.1017/S095026880999094X

Abstract

We investigated the incidence of cases of nosocomial pathogens and risk factors in an intensive treatment unit ward to determine if the number of cases is dependent on location of patients and the colonization/infection history of the ward. A clustering approach method was developed to investigate the patterns of spread of cases through time for five microorganisms [methicillin-resistant Staphylococcus aureus (MRSA), Acinetobacter spp., Klebsiella spp., Candida spp., and Pseudomonas aeruginosa] using hospital microbiological monitoring data and ward records of patient-bed use. Cases of colonization/infection by MRSA, Candida and Pseudomonas were clustered in beds and through time while cases of Klebsiella and Acinetobacter were not. We used structural equation modelling to analyse interacting risk factors and the potential pathways of transmission in the ward. Prior nurse contact with colonized/infected patients, mediated by the number of patient-bed movements, were important predictors for all cases, except for those of Pseudomonas. General health and invasive surgery were significant predictors of cases of Candida and Klebsiella. We suggest that isolation and bed movement as a strategy to manage MRSA infections is likely to impact upon the incidence of cases of other opportunist pathogens

Item Type: Article
Uncontrolled Keywords: intensive treatment unit, nosocomial pathogens, space–time clustering, structural equation modelling
Subjects: A100 Pre-clinical Medicine
C900 Others in Biological Sciences
Department: Faculties > Health and Life Sciences > Applied Sciences
Depositing User: Ay Okpokam
Date Deposited: 18 Jan 2012 10:50
Last Modified: 17 Dec 2023 14:48
URI: https://nrl.northumbria.ac.uk/id/eprint/4560

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics