Challenges and Opportunities in One Health: Google Trends Search Data.

Google Trends data can be informative for zoonotic disease incidences, including Lyme disease. However, the use of Google Trends for predictive purposes is underutilized. In this study, we demonstrate the potential to use Google Trends for zoonotic disease prediction by predicting monthly state-level Lyme disease case counts in the United States. We requested Lyme disease data for the years 2010-2021. We downloaded Google Trends search data on terms for Lyme disease, symptoms of Lyme disease, and diseases with similar symptoms to Lyme disease. For each search term, we built an expanding window negative binomial model that adjusted for seasonal differences using a lag term. Performance was measured by Root Mean Squared Errors (RMSEs) and the visual associations between observed and predicted case counts. The highest performing model had excellent predictive ability in some states, but performance varied across states. The highest performing models were for Lyme disease search terms, which indicates the high specificity of search terms. We outline challenges of using Google Trends data, including data availability and a mismatch between geographic units. We discuss opportunities for Google Trends data for One Health research, including prediction of additional zoonotic diseases and incorporating environmental and companion animal data. Lastly, we recommend that Google Trends be explored as an option for predicting other zoonotic diseases and incorporate other data streams that may improve predictive performance.

Factors associated with heartworm preventative use in the golden retriever lifetime study.

Introduction: Heartworm disease is preventable with use of heartworm preventatives, but the reported prevalence of heartworm preventative use in the United States is low, some estimates falling around 50% of dogs. However, there are very few estimates of prevalence and its associated factors. Methods: We aimed to estimate prevalence and evaluate factors, including vaccination status, demographics, lifestyle, physical conditions, medications and supplements, and environment and living conditions, for their association with heartworm preventative use in a large dataset from the Golden Retriever Lifetime Study (N = 2,998). Due to the large number of predictors evaluated, we built a bootstrapped elastic net logistic regression model, which is robust to overfitting and multicollinearity. Variables were evaluated by calculating covariate stability (>80%) and statistical significance (p<0.02). Results: In our sample, the prevalence of heartworm use was 39.5%. In our elastic net model, receiving vaccinations (rabies, Bordetella, or any other vaccine), being located in the Southern U.S., being altered, having an infectious disease or ear/ nose/throat system disease diagnosis, being on heartworm preventatives in the past, currently being on tick preventative, having sun exposure in an area with concrete flooring, living in a house with more rooms with carpeted floors, and spending time on hardwood flooring inside were associated with greater odds of heartworm preventative use. Supplementation use and being in the top quartile of height were associated with lower odds of heartworm preventative use. Discussion: The explanatory factors we identified can be used to improve client communication. In addition, target populations for educational interventions and outreach can be identified. Future studies can validate the findings in a more diverse population of dogs.

Serosurvey of arthropod-borne diseases among shelter dogs in the Cumberland Gap Region of the United States.

BACKGROUND: The Cumberland Gap Region (CGR) of the United States is a natural corridor between the southeastern, northeastern, and midwestern regions of the country. CGR has also many species of ticks and mosquitos that serve as competent vectors for important animal and human pathogens. In this study, we tested dogs from six different animal shelters in the CGR for Rocky Mountain spotted fever (RMSF), anaplasmosis, Lyme disease, canine ehrlichiosis and canine heartworm disease. RESULTS: Sera from 157 shelter dogs were tested for antibodies to RMSF agent, Rickettsia rickettsii, using an indirect immunofluorescence assay. Sixty-six dogs (42.0%) were positive for either IgM or IgG, or both IgM and IgG antibodies to R. rickettsii. Moreover, the same set of sera (n = 157) plus an and additional sera (n = 75) from resident dogs at the same shelters were tested using the SNAP 4Dx Plus. Of 232 dogs tested, two (0.9%) were positive for antibodies to Anaplasma phagocytophilum/A. platys, nine (3.9%) were positive for antibodies to Borrelia burgdorferi, 23 (9.9%) for positive for antibodies to Ehrlichia canis/E. ewingii, and 13 (5.6%) were positive for Dirofilaria immitis antigen. Co-infection with two or more etiologic agents was detected in five animals. Three dogs had antibodies to both B. burgdorferi and E. canis/E. ewingii, and two dogs were positive for D. immitis antigen and antibodies to B. burgdorferi and E. canis/E. ewingii. CONCLUSIONS: Shelter dogs in the CGR are exposed to a number of important vector-borne pathogens. Further studies are required to ascertain the roles these animals play in maintenance and transmission of these pathogens.