Valley Fever, or Coccidioidomycosis, a fungal respiratory disease, is prevalent with increasing incidence in the Southwestern United States, especially in the central region of California. Public health agencies in the region do not have a consistent strategy for communication and health promotion targeting vulnerable communities about this climate-sensitive disease. We used the behavior adaptation communication model to design and conduct semi-structured interviews with representatives of public health agencies in five California counties: Fresno, Kern, Kings, San Luis Obispo, and Tulare County. While none of the agencies currently include climate change information into their Valley Fever risk messaging, the agencies discuss future communication methods similar to other health risk factors such as poor air quality days and influenza virus season. For political reasons, some public health agencies deliberately avoided the use of climate change language in communicating health risk factors to farmers who are particularly vulnerable to soil and dust-borne fungal spores. The effectiveness of health communication activities of the public health agencies has not been measured in reducing the prevalence of Valley Fever in impacted communities. Given the transboundary nature of climate influence on Valley Fever risk, a concerted and consistent health communication strategy is expected to be more effective than current practices.

We compiled a coccidioidomycosis (Valley fever) case database for three states in the southwestern United States (US). Currently, county-level, monthly case counts are available from 2000–2015 for Arizona, California, and Nevada. We collected these data from each respective state public health agency. The Valley fever case database is available on GitHub, at https://github.com/valleyfever/valleyfevercasedata. This database may be used to examine relationships between the number of Valley fever cases and hypothesized explanatory variables such as environmental conditions, social determinants, human behavior, occupational activities, public policies, or other risk factors. We aim to provide regular updates to this database and include more states as data become available. Funding statement: M. E. Gorris received support from a Department of Defense (DoD), National Defense Science & Engineering Graduate Fellowship (32 CFR 168a). M. E. Gorris, L. A. Cat, and M. Matlock thank the UC Irvine Data Science Initiative for their funding and support. L. A. Cat acknowledges funding and support from the UC-Mexico Initiative. M. Matlock is also supported by Water UCI and the UCI Graduate Division. K. K. Treseder is supported by US NSF (EAR-1411942 and DEB-1457160) and the US Department of Energy, Office of Science, Office of Biological and Environmental Research (BER), under Award Numbers DE-PS02-09ER09-25 and DE-SC001641. J. T. Randerson received support from the Gordon and Betty Moore Foundation (GBMF#3269), NASA Soil Moisture and Interdisciplinary Science Program, and the U.S. Dept. of Energy Office of Science RUBISCO Science Focus Area. C. S. Zender acknowledges support from the Borrego Valley Endowment Fund and DOE ACME DE-SC0012998.