Paper Info
Title
Spatial aspects of MRSA epidemiology: a case study using stochastic simulation, kernel estimation and SaTScan
Abstract
The identification of disease clusters in space or space-time is of vital importance for public health policy and action. In the case of methicillin-resistant Staphylococcus aureus (MRSA), it is particularly important to distinguish between community and health care-associated infections, and to identify reservoirs of infection. 832 cases of MRSA in the West Midlands (UK) were tested for clustering and evidence of community transmission, after being geo-located to the centroids of UK unit postcodes (postal areas roughly equivalent to Zip+4 zip code areas). An age-stratified analysis was also carried out at the coarser spatial resolution of UK Census Output Areas. Stochastic simulation and kernel density estimation were combined to identify significant local clusters of MRSA (p
Year
DOI
Venue
2007
10.1080/13658810601135767
International Journal of Geographical Information Science
Keywords
Field
DocType
age-stratified analysis,disease cluster,mrsa epidemiology,public health policy,kernel estimation,case study,uk census output areas,health care-associated infection,community transmission,coarser spatial resolution,west midlands,spatial aspect,uk unit postcode,stochastic simulation,kernel density estimation,kernel density,health care,space time,spatial resolution,data collection,kernel density estimate
Econometrics,Public health,Stochastic simulation,Data mining,Data collection,Computer science,Epidemiology,Sampling (statistics),Statistics,Cluster analysis,Census,Kernel density estimation
Journal
Volume
Issue
ISSN
21
7
1365-8816
Citations 
PageRank 
References 
6
0.86
1
Authors
10
Name
Order
Citations
PageRank
Lucy Bastin116417.19
J. Rollason260.86
A. Hilton360.86
D. Pillay460.86
C. Corcoran560.86
J. Elgy660.86
P. Lambert760.86
de Vries, A.P.870774.05
T. Worthington960.86
K. Burrows1060.86