Full Citation
Title: Hierarchical Bayesian SpatioTemporal Analysis of Climatic and SocioEconomic Determinants of Rocky Mountain Spotted Fever
Citation Type: Miscellaneous
Publication Year: 2016
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Abstract: This study aims to examine the spatio-temporal dynamics of Rocky Mountain spotted fever (RMSF) prevalence in four contiguous states of Midwestern United States, and to determine the impact of environmental and socioeconomic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatiotemporal interaction effect in the case reports submitted to the state health departments in the region. Various socioeconomic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a maineffects Bayesian model in progressive steps to evaluate important drivers of RMSF space-time patterns in the region. Our results show a steady increase in RMSF incidence over the study period to newer geographic areas, and the posterior probabilities of county-specific trends indicate clustering of high risk counties in the central and southern parts of the study region. At the spatial scale of a county, the prevalence levels of RMSF is influenced by poverty status, average relative humidity, and average land surface temperature (>35C) in the region, and the relevance of these factors in the context of climatechange impacts on tickborne diseases are discussed.
Url: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0150180
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Authors: Raghavan, Ram K; Goodin, Douglas G; Neises, Daniel; Anderson, Gary A; Ganta, Roman R
Publisher: PLoS ONE
Data Collections: IPUMS USA
Topics: Health, Other
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