Daniel Galati

Applying Spatial Analysis Tools to Predict Valley Fever in California, USA ©2014

Valley Fever is a potentially fatal fungal infection native to California, Arizona & Mexico which is spread through the inhalation of C. Immitis spores. Increasing Valley Fever rates have put increasing pressure on health agencies and decision makers, however, little research has been conducted adopting the spatial analysis perspective. This study used temperature, precipitation and wind variables as predictors for the recently increasing rates in California over 2006 to 2012. Spatial techniques were employed to identify clusters. In addition, negative binomial regression was conducted. Analysis concluded that statistically significant spatial clustering of counties with high Valley Fever rates were centred in the southwest portion of California. Geographically weighted regression saw an average R2 value of .396. Negative binomial regression identified a positive relationship between temperature and precipitation. This research has demonstrated the ability of GIS tools to identify spatial clustering patterns and the use of climate variables as predictors.