A hierarchical spatial modelling approach to investigate MRSA transmission in a tertiary hospital

BMC Infectious Diseases

Research Article

David L Paterson¹  Michael Whitby²  Michael Coory³  Archie CA Clements³  Fiona Kong⁴ 

[1] Center for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Queensland, Australia;Centre for Clinical Research, University of Queensland, Queensland, Australia;Greenslopes Clinical School, University of Queensland, Queensland, Australia;Infectious Disease Epidemiology Unit, School of Population Health, University of Queensland, Queensland, Australia;Infectious Disease Epidemiology Unit, School of Population Health, University of Queensland, Queensland, Australia;Center for Healthcare Related Infection Surveillance and Prevention, Queensland Health, Queensland, Australia;

关键词: MRSA;    Staphylococcus aureus;    Spatial model;    Spatial clustering;   

DOI  :  10.1186/1471-2334-13-449

 received in 2013-03-28, accepted in 2013-09-23,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundMost hospitals have a hierarchical design with beds positioned within cubicles and cubicles positioned within wards. Transmission of MRSA may be facilitated by patient proximity and thus the spatial arrangements of beds, cubicles and wards could be important in understanding MRSA transmission risk. Identifying high-risk areas of transmission may be useful in the design of more effective, targeted MRSA interventions.MethodsRetrospective data on numbers of multi-resistant and non-multiresistant MRSA acquisitions were collected for 52 weeks in 2007 in a tertiary hospital in Brisbane, Australia. A hierarchical Bayesian spatio-temporal modelling approach was used to investigate spatial correlation in the hierarchically arranged datasets. The spatial component of the model decomposes cubicle-level variation into a spatially structured component and a spatially unstructured component, thereby encapsulating the influence of unmeasured predictor variables that themselves are spatially clustered and/or random. A fixed effect for the presence of another patient with the same type of MRSA in the cubicles two weeks prior was included.ResultsThe best-fitting model for non-multiresistant MRSA had an unstructured random effect but no spatially structured random effect. The best-fitting model for multiresistant MRSA incorporated both spatially structured and unstructured random effects. While between-cubicle variability in risk of MRSA acquisition within the hospital was significant, there was only weak evidence to suggest that MRSA is spatially clustered. Presence of another patient with the same type of MRSA in the cubicles two weeks prior was a significant predictor of both types of MRSA in all models.ConclusionsWe found weak evidence of clustering of MRSA acquisition within the hospital. The presence of an infected patient in the same cubicle two weeks prior may support the importance of environmental contamination as a source of MRSA transmission.

【 授权许可】

Unknown   
© Kong et al.; licensee BioMed Central Ltd. 2013. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.