Spatial Patterns and Impacts of Environmental and Climatic Factors on Canine Sinonasal Aspergillosis in Northern California

Application of Bayesian Regression for the Identification of a Catchment Area for Cancer Cases in Dogs and Cats

Research on cancer in dogs and cats, among other diseases, finds an important source of information in registry data collected from hospitals. These sources have proved to be decisive in establishing incidences and identifying temporal patterns and risk factors. However, the attendance of patients is not random, so the correct delimitation of the hospital catchment area (CA) as well as the identification of the factors influencing its shape is relevant to prevent possible biases in posterior inferences. Despite this, there is a lack of data-driven approaches in veterinary epidemiology to establish CA. Therefore, our aim here was to apply a Bayesian method to estimate the CA of a hospital. We obtained cancer (n = 27,390) and visit (n = 232,014) registries of dogs and cats attending the Veterinary Medical Teaching Hospital of the University of California, Davis from 2000 to 2019 with 2,707 census tracts (CTs) of 40 neighboring counties. We ran hierarchical Bayesian models with different likelihood distributions to define CA for cancer cases and visits based on the exceedance probabilities for CT random effects, adjusting for species and period (2000-2004, 2005-2009, 2010-2014, and 2015-2019). The identified CAs of cancer cases and visits represented 75.4 and 83.1% of the records, respectively, including only 34.6 and 39.3% of the CT in the study area. The models detected variation by species (higher number of records in dogs) and period. We also found that distance to hospital and average household income were important predictors of the inclusion of a CT in the CA. Our results show that the application of this methodology is useful for obtaining data-driven CA and evaluating the factors that influence and predict data collection. Therefore, this could be useful to improve the accuracy of analysis and inferences based on registry data.

Fungal Rhinosinusitis and Disseminated Invasive Aspergillosis in Cats

Fungal rhinosinusitis, including sinonasal aspergillosis (SNA) and sino-orbital aspergillosis (SOA), is the most common type of aspergillosis encountered in cats. Other focal forms of aspergillosis including disseminated invasive aspergillosis occur less frequently. SOA is an invasive mycosis that is increasingly recognized and is most commonly caused by Aspergillus felis, a close relative of Aspergillus fumigatus. SNA can be invasive or noninvasive and is most commonly caused by A fumigatus and Aspergillus niger. Molecular methods are required to correctly identify the fungi that cause SNA and SOA. SNA has a favorable prognosis with treatment, whereas the prognosis for SOA remains poor.