Risk factor analysis and spatiotemporal CART model of cryptosporidiosis in Queensland, Australia
Background: It remains unclear whether it is possible to develop a spatiotemporal epidemic prediction model for cryptosporidiosis disease. This paper examined the impact of social economic and weather factors on cryptosporidiosis and explored the possibility of developing such a model using social economic and weather data in Queensland, Australia. ----- -----
Methods: Data on weather variables, notified cryptosporidiosis cases and social economic factors in Queensland were supplied by the Australian Bureau of Meteorology, Queensland Department of Health, and Australian Bureau of Statistics, respectively. Three-stage spatiotemporal classification and regression tree (CART) models were developed to examine the association between social economic and weather factors and monthly incidence of cryptosporidiosis in Queensland, Australia. The spatiotemporal CART model was used for predicting the outbreak of cryptosporidiosis in Queensland, Australia. ----- -----
Results: The results of the classification tree model (with incidence rates defined as binary presence/absence) showed that there was an 87% chance of an occurrence of cryptosporidiosis in a local government area (LGA) if the socio-economic index for the area (SEIFA) exceeded 1021, while the results of regression tree model (based on non-zero incidence rates) show when SEIFA was between 892 and 945, and temperature exceeded 32°C, the relative risk (RR) of cryptosporidiosis was 3.9 (mean morbidity: 390.6/100,000, standard deviation (SD): 310.5), compared to monthly average incidence of cryptosporidiosis. When SEIFA was less than 892 the RR of cryptosporidiosis was 4.3 (mean morbidity: 426.8/100,000, SD: 319.2). A prediction map for the cryptosporidiosis outbreak was made according to the outputs of spatiotemporal CART models. ----- -----
Conclusions: The results of this study suggest that spatiotemporal CART models based on social economic and weather variables can be used for predicting the outbreak of cryptosporidiosis in Queensland, Australia.
Impact and interest:
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|Item Type:||Journal Article|
|Keywords:||spatiotemporal epidemic prediction model, cryptosporidiosis disease, weather factors|
|Subjects:||Australian and New Zealand Standard Research Classification > MEDICAL AND HEALTH SCIENCES (110000) > MEDICAL BIOCHEMISTRY AND METABOLOMICS (110100)|
|Divisions:||Current > QUT Faculties and Divisions > Faculty of Health|
Current > Institutes > Institute of Health and Biomedical Innovation
Past > Schools > Mathematical Sciences
Current > Schools > School of Public Health & Social Work
|Copyright Owner:||Copyright 2010 2010 Hu et al; licensee BioMed Central Ltd.|
|Deposited On:||02 Mar 2011 11:16|
|Last Modified:||01 Mar 2012 00:31|
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