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J Infect. 2014 Nov;69(5):447-55. doi: 10.1016/j.jinf.2014.06.014. Epub 2014 Jun 28.

A population-based spatio-temporal analysis of Clostridium difficile infection in Queensland, Australia over a 10-year period.

Author information

1
School of Population Health, The University of Queensland, Herston, QLD, Australia. Electronic address: l.furuyakanamori@uq.edu.au.
2
Sullivan Nicolaides Pathology, Taringa, QLD, Australia.
3
School of Population Health, The University of Queensland, Herston, QLD, Australia.
4
The University of Queensland, UQ Centre for Clinical Research, Herston, QLD, Australia.
5
Microbiology & Immunology, The University of Western Australia and Department of Microbiology PathWest Laboratory Medicine, Queen Elizabeth II Medical Centre, Nedlands, WA, Australia.
6
Research School of Population Health, The Australian National University, Canberra, ACT, Australia.

Abstract

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.

KEYWORDS:

Australia; Clostridium difficile; Epidemiology; Infection; Spatio-temporal analysis

PMID:
24984276
DOI:
10.1016/j.jinf.2014.06.014
[Indexed for MEDLINE]
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