The Epidemiology of Coccidioidomycosis: Correlating Rainfall, Temperature, and
Wind Speed
Angélica Álvarez, NASA Space Grant Intern
Dr. Joellen Russell, Department of Geosciences
Dr. Eyal Oren, Division of Epidemiology & Biostatistics
AZ Space Grant Symposium 11 April 2014
Coccidiodes:Valley FeverWhat is it? Where is it?
Centers for Disease Control and PreventionBy Janet loehrke and Karl Gelles, USA TODAY
Objectives To what extent do climate anomalies such as in wind
speed, temperature and rainfall correlate with Valley Fever reporting data in the state of Arizona?
Is there variability in the influence of these climate variables to specific locations of Arizona?
What is the influence of wind speed, temperature, and rainfall anomalies on Valley Fever reporting data one month later?
Methods Calculation of regression maps of statewide monthly Valley Fever reporting data
from the Arizona Department of Health Services on various climate anomalies (wind speed, temperature, rainfall) across Arizona from 2006-2013
Climate variable data taken from Climate Forecast Reanalysis System under the National Oceanic and Atmospheric Administration
Climate anomalies are defined as monthly deviations from normal months (average taken between 1979 – 2010)
Example: Normal January is the average of all Januaries whereas the anomaly in January of 2000 is the difference between the actual value in January of 2000 and the normal value
Calculation of significance of correlation coefficients calculated using student t-tests on regression maps
Correlation and significance of one month lag analysis by correlating the monthly anomaly for a specific climate variable with the following month’s reporting data (ADHS)
Cocci Timeline
change in major commerciallaboratory reporting practices
change in laboratorytesting methods
Endemic Areas
SourceArizona Department of Health Services
SourceArizona Department of Health ServicesClimate Forecast Reanalysis System
SourceArizona Department of Health ServicesClimate Forecast Reanalysis System
SourceArizona Department of Health ServicesClimate Forecast Reanalysis System
Regression Analyses & One Month Lag
SourceArizona Department of Health ServicesClimate Forecast Reanalysis System
One
Mon
th L
ag
Reg
ress
ion
Ana
lysi
sR
egre
ssio
n A
naly
sis
Conclusions Positive correlation between wind anomaly and Cocci in southeast AZ Strong positive correlation between rain anomaly and Cocci in
northwest AZ Negative correlation of rain anomaly in one month lag regression No significant difference in lagged correlation using wind anomalies Further testing with climate variables needed
Correlate meteorological factors such as precipitation, dust exposure, humidity (RH & AH) with Valley Fever looking at incidence rates, date of exposure, and per varying lagged time frames
Correlate comorbidity of Valley Fever with other respiratory diseases
Acknowledgements
Dr. Paul Goodman, Department of Geosciences
Dr. Andrew C. Comrie, School of Geography & Development
Susan Brew, UA Space Grant Consortium
Dr. Barron Orr, UA NASA Space Grant Program
Reporting Data - Arizona Department of Health Services
Climate Forecast Reanalysis System, National Oceanic and
Atmospheric Administration