title: Hierarchical Bayesian Spatio-Temporal Analysis of Climatic and Socio-Economic Determinants of Rocky Mountain Spotted Fever.
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 socio-economic factors associated with this disease. Bayesian hierarchical models were used to quantify space and time only trends and spatio-temporal interaction effect in the case reports submitted to the state health departments in the region. Various socio-economic, environmental and climatic covariates screened a priori in a bivariate procedure were added to a main-effects 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 (>35°C) in the region, and the relevance of these factors in the context of climate-change impacts on tick-borne diseases are discussed.
authors.affiliation: Kansas State Veterinary Diagnostic Laboratory, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America.|Center for Excellence in Vector Borne Diseases, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America.
authors.forename: Ram K
authors.initials: RK
authors.lastname: Raghavan
authors.affiliation: Department of Geography, Kansas State University, Manhattan, Kansas, United States of America.
authors.forename: Douglas G
authors.initials: DG
authors.lastname: Goodin
authors.affiliation: Bureau of Epidemiology and Public Health Informatics, Kansas Department of Health and Environment, Topeka, Kansas, United States of America.
authors.forename: Daniel
authors.initials: D
authors.lastname: Neises
authors.affiliation: Kansas State Veterinary Diagnostic Laboratory, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America.
authors.forename: Gary A
authors.initials: GA
authors.lastname: Anderson
authors.affiliation: Center for Excellence in Vector Borne Diseases, Department of Diagnostic Medicine and Pathobiology, Kansas State University, Manhattan, Kansas, United States of America.
authors.forename: Roman R
authors.initials: RR
authors.lastname: Ganta
mesh_terms: D001499:Bayes Theorem; D002980:Climate; D006798:Housing; D006801:Humans; D015233:Models, Statistical; D011157:Population Dynamics; D012044:Regression Analysis; D012373:Rocky Mountain Spotted Fever / Q000191:economics* / Q000453:epidemiology*; D012959:Socioeconomic Factors; D062211:Spatio-Temporal Analysis