UC Irvine

Coccidioidomycosis (Valley Fever) incidence has been steadily increasing in the Southwest United States. In 2017, the highest record number of cases were diagnosed in the state of California, surpassing the previous record in 2016 by 34%, sparking a renewed interest in what is bringing about this increase in incident case counts. Coccidioides species of fungi grow in the soil and when the spores become aerosolized, they can be inhaled leading to infection. Previous studies have tried to understand the relationship between Valley Fever exposure and climate.

The goal of this research is to understand the relationship between climate and Valley Fever and how this information can assist local public health agencies in communicating preventive strategies to the vulnerable populations in their local communities. The main research hypothesis is that the relationship with the climate variables and incidence will not behave identically in terms of direction or timing across the study area, except for Precipitation, which is hypothesized to have a positive relationship with cases over the Fall and Winter months.

Monthly case data was obtained from the California Department of Public Health, Infectious Disease Branch, for five California Counties (Study area: Fresno, Kern, Kings, San Luis Obispo, and Tulare) for 2000-2015 totaling over 37,000 incident cases. To determine how environmental factors (precipitation, temperature, wind speed, evapotranspiration, Palmer Drought Severity Index, Particulate Matter 2.5 and 10, and El Nino Southern Oscillation Index) were related to diagnosed cases, linear and Poisson regression were used to analyze case counts and incidence rate for 2000-2015. To determine how the relationship between environmental factors and Valley Fever cases changed due to different hypothesized exposure scenarios, ten different exposure scenarios were investigated. To determine how the local public health agencies currently or would like to use climate information in Valley Fever messages, a qualitative survey and interview to representatives from the Public Health agencies in the study area were conducted.

This study verified previous findings that the more total season rainfall that occurs during the Fall and Winter season typically indicates that cases will be higher the following diagnosis season for each county in the study area. Secondly, the Palmer Drought Severity Index, found that the drier the soil was in the months before the peak diagnosis season, the more cases were likely to be diagnosed. Third, most of the cases were diagnosed during La Nina events, which usually indicates a drier weather environment over California. These patterns emerged with the different quantitative methods and the different exposure periods, where the other environmental variables did not have this same consistency. Lastly, the Public Health Agencies in the study area would like to see climate information tailored in a way to allow Behavior Adaptation messaging like bad air quality days or the risk level for the upcoming flu season.