New hybrid prediction model for adverse environmental health effects
2008 Research Project Grant Round
Approved for Funding by CMRF $74,801.00
For a period of 12 months
Start Date: 01 February 2009
Reseacher 1: Associate Professor Simon Kingham
University of Canterbury
Photo: Research Team from left to right Phil Hider, Simon Kingham,
Kyoko Fukuda and Mike Epton
Reseacher 2: Dr Mike Epton
University of Otago, Christchurch
Reseacher 3: Dr Phil Hider
University of Otago, Christchurch
Reseacher 4: Kyoko Fukuda
University of Canterbury
The objective of this research is to produce and test a model that will predict admission rates to Christchurch Hospital for acute cardio-respiratory conditions using a variety of factors, such as air pollution, climate and virology. The model will use a hybrid method that incorporates a unique combination of statistical, mathematical and computational algorithms, combining the advantages of each method to predict the admission rate more accurately. Previously, a few statistical analyses have been conducted on the adverse effect of air pollution on human health in Christchurch (Hales et al., 1999, and McGowan et al., 2002), but there is a significant need for updated and improved statistical analysis that incorporates recent international and local geographical and methodological criticisms. The prediction method developed in this research will be a critical part, as it will be integrated into the hospital operation system to help plan and organise the automated cost effective hospital operation (e.g., scheduling nurses, numbers of beds to meet needs) in advance.
