Table 1.
Physical environment variables screened in the study.
Table 2.
Climate variables evaluated in the study.
Table 3.
Population and housing variables evaluated in the study.
Fig 1.
Plot of reported number of cases submitted to different state health departments in the study region.
Table 4.
Results of bivariate regression analysis and candidate variables (p ≤ 0.2).
Table 5.
Model statistics for Bayesian spatio–temporal covariate models evaluating county–level RMSF prevalence in four central Midwestern states (Kansas, Missouri, Arkansas, Oklahoma), United States of America.
Table 6.
Model fit and comparison criteria.
Fig 2.
The posterior median and 95% CrI for the overall time trend in the covariate model.
Fig 3.
County–level crude rate estimates of Rocky Mountain spotted fever prevalence reported to the state health departments for the study period, 2005–2014.
Fig 4.
County–specific Bayesian smoothed estimates (posterior median) of Rocky Mountain spotted fever prevalence for the study period between years 2005–2014.
Fig 5.
Posterior median of county–specific differential trends. Counties with values closer to 0 indicate a higher risk for RMSF.