TY - JOUR
T1 - A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period
AU - Furuya-Kanamori, Luis
AU - Robson, Jenny
AU - Soares Magalhães, Ricardo J.
AU - Yakob, Laith
AU - McKenzie, Samantha J.
AU - Paterson, David L.
AU - Riley, Thomas V.
AU - Clements, Archie C.A.
N1 - Publisher Copyright:
© 2014 The British Infection Association.
PY - 2014/11/1
Y1 - 2014/11/1
N2 - Objectives: To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia. Methods: Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level. Results: C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model. Conclusions: There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation.
AB - Objectives: To identify the spatio-temporal patterns and environmental factors associated with Clostridium difficile infection (CDI) in Queensland, Australia. Methods: Data from patients tested for CDI were collected from 392 postcodes across Queensland between May 2003 and December 2012. A binomial logistic regression model, with CDI status as the outcome, was built in a Bayesian framework, incorporating fixed effects for sex, age, source of the sample (healthcare facility or community), elevation, rainfall, land surface temperature, seasons of the year, time in months and spatially unstructured random effects at the postcode level. Results: C. difficile was identified in 13.1% of the samples, the proportion significantly increased over the study period from 5.9% in 2003 to 18.8% in 2012. CDI peaked in summer (14.6%) and was at its lowest in autumn (10.1%). Other factors significantly associated with CDI included female sex (OR: 1.08; 95%CI: 1.01-1.14), community source samples (OR: 1.12; 95%CI: 1.05-1.20), and higher rainfall (OR: 1.09; 95%CI: 1.02-1.17). There was no significant spatial variation in CDI after accounting for the fixed effects in the model. Conclusions: There was an increasing annual trend in CDI in Queensland from 2003 to 2012. Peaks of CDI were found in summer (December-February), which is at odds with the current epidemiological pattern described for northern hemisphere countries. Epidemiologically plausible explanations for this disparity require further investigation.
KW - Australia
KW - Clostridium difficile
KW - Epidemiology
KW - Infection
KW - Spatio-temporal analysis
UR - http://www.scopus.com/inward/record.url?scp=84908510566&partnerID=8YFLogxK
U2 - 10.1016/j.jinf.2014.06.014
DO - 10.1016/j.jinf.2014.06.014
M3 - Article
SN - 0163-4453
VL - 69
SP - 447
EP - 455
JO - Journal of Infection
JF - Journal of Infection
IS - 5
ER -