Statistical modeling of valley fever data in Kern County, California

被引:0
作者
Jorge Talamantes
Sam Behseta
Charles S. Zender
机构
[1] California State University,Department of Physics and Geology
[2] California State University,Department of Mathematics
[3] University of California,Department of Earth System Science
来源
International Journal of Biometeorology | 2007年 / 51卷
关键词
GARMA modeling; Time-series analysis; Valley fever prediction; Coccidioidomycosis;
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学科分类号
摘要
Coccidioidomycosis (valley fever) is a fungal infection found in the southwestern US, northern Mexico, and some places in Central and South America. The fungus that causes it (Coccidioides immitis) is normally soil-dwelling but, if disturbed, becomes air-borne and infects the host when its spores are inhaled. It is thus natural to surmise that weather conditions that foster the growth and dispersal of the fungus must have an effect on the number of cases in the endemic areas. We present here an attempt at the modeling of valley fever incidence in Kern County, California, by the implementation of a generalized auto regressive moving average (GARMA) model. We show that the number of valley fever cases can be predicted mainly by considering only the previous history of incidence rates in the county. The inclusion of weather-related time sequences improves the model only to a relatively minor extent. This suggests that fluctuations of incidence rates (about a seasonally varying background value) are related to biological and/or anthropogenic reasons, and not so much to weather anomalies.
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