Yersinia pestis is a Gram-negative bacterium, primarily transmitted via flea bite, causing plague in numerous mammal species. While human cases are rare in the United States (US), consequences of infection are severe (often fatal) and motivate expanded methods for disease surveillance including monitoring of infection within animal hosts. The incidence and prevalence of zoonotic diseases are influenced by climate variables through the ecological niche of and interactions between hosts, vector, and pathogen. Canis latrans (coyotes) provide one sentinel species for plague. In order to describe geographic patterns of infection within the coyote host, we define and apply non-parametric regression and spatial point process methods to both geographic space and the space defined by the first two principal components of climate variables. More specifically, we utilize spatial ecological niche models applied to approximately 29,000 locations of coyotes tested for plague antibodies by US government agencies linked with PRISM 30-year climate averages to determine the spatial distribution of Y. pestis infection within the principle components space of climate variables (PC space). Monte Carlo assessments identify significantly different patterns of infected and non-infected sampled coyotes yielding “maps” of high and low risk climatic niches for infection within PC space. Areas in PC space with predicted with higher likelihood of plague in coyotes are then transformed to geographic space to provide inference regarding specific areas of surveillance interest in the western US. We illustrate the approach in the state of California and more broadly across the western US. Results to date allow public health officials to gather more information from existing data as well as to strategize future sampling and testing plans, particularly to identify geographic areas which are historically undersampled but fall within predicted higher-risk PC (climate) space. We outline the methodological approach, applications to date, and areas for further development and refinement.