Abstract
Using the Bayesian maximum entropy (BME) method of spatiotemporal statistics, the present study examines the geographical risk pattern of influenza mortality in the state of California during the time period 1997–2001. BME risk analysis is of considerable value, since influenza is the largest contributing factor to wintertime mortality increases in the US. By incorporating age-adjusted mortality data collected at the county level, informative influenza mortality maps were generated and composite space-time influenza dependences were assessed quantitatively. On the basis this analysis, essential risk patterns and correlations were detected across the state during wintertime. It was found that significantly high risks initially occurred during December in the west-central part of the state; in the following two weeks the risk distribution extended in the south and east-central parts of the state; in late February significant influenza mortalities were detected mainly in the west-central part of the state. These findings, combined with the results of earlier works, can lead to useful conclusions regarding influenza risk assessment in a space-time context and, also, point toward promising future research directions.
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Acknowledgments
We would like to thank Dr. RA Olea of USGS for his valuable suggestions. This research was supported by grants from the Oak Ridge National Lab (OR7865-001.01), the Fred J. Hansen Institute, SDSU Foundation, California (54266A P3590), the Office of the Vice President for Research at the University of Michigan and the National Oceanographic and Atmospheric Administration (NA16GP23361).
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Choi, KM., Yu, HL. & Wilson, M.L. Spatiotemporal statistical analysis of influenza mortality risk in the State of California during the period 1997–2001. Stoch Environ Res Risk Assess 22 (Suppl 1), 15–25 (2008). https://doi.org/10.1007/s00477-007-0168-4
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DOI: https://doi.org/10.1007/s00477-007-0168-4