Researchers examined multiple factors related to canine and human Lyme disease infection in the Northeast United States.
Lyme disease is considered endemic in dogs and humans in the Northeast United States. In a recent article in Parasites and Vectors, investigators examined whether a variety of social and environmental factors can accurately predict Lyme disease prevalence.
The study focused on the New York City Metropolitan Statistical Area (NYCMSA), consisting of 30 counties with a wide range of urban, transitional, and rural areas. The NYCMSA human population is estimated at approximately 20 million, or 6% to 7% of the US population.
SNAP3Dx and SNAP4Dx canine test results were provided by Idexx Laboratories for analysis. Both tests detect canine antibodies to Borrelia burgdorferi and have an estimated 99.6% specificity and 94.4% sensitivity compared with immunofluorescence assay and Western blot.
The investigators used categorical analysis to analyze multiple factors, including SNAP test results, population density, percent forested area, and CDC-reported human Lyme disease cases. Regression analysis was also performed for detailed variables, such as precipitation, fall temperatures and vegetation, and level of urbanization in each county. Finally, the investigators performed a backward-stepwise regression to determine if the above-mentioned variables could accurately predict the prevalence of Lyme disease in dogs or humans.
A total of 234,633 SNAP test results from 2001 to 2010 were included in the study. Positive canine tests for B burgdorferi ranged from 1.2% to 27.3% by county, while human Lyme disease cases ranged from 0.5 to 438.7 cases per 100,000 people by county.
Categorical analysis showed that the percentage of positive canine tests was significantly higher in counties with low population density (18%) than in those with moderate (8%) or high (5%) populations. Positive tests were also more likely in counties with high amounts of forested area (21%) than in those with medium (15%) or low (6%) forestation.
Similarly, human Lyme disease prevalence was significantly higher in counties with low (113 cases per 100,000 people) and medium (10 cases per 100,000) population densities than in counties with high (3 cases per 100,000) population densities. Also, more cases were reported in counties with high (165/105) or medium (66/105) forestation than in counties with low (11/105) forestation. Human and canine cases correlated strongly with each other on both categorical and regression analyses.
Regression analysis also revealed that several environmental factors known to influence tick populations, including forest cover and November temperatures, significantly correlated with positive canine SNAP tests and human Lyme disease cases.
Backward-stepwise regression revealed that the following factors could be used to accurately predict the percentage of positive canine tests:
Likewise, the percentage of positive canine tests can also accurately predict the prevalence of human Lyme disease.
Canine seroprevalence for antibodies to B burgdorferi accurately predicted the risk of Lyme disease infection in humans in the NYC metropolitan area. The authors cautioned that these results may not apply to other regions of the United States, however, given the unique, endemic nature of Lyme disease in the Northeast.
Dr. Stilwell received her DVM from Auburn University, followed by an MS in Fisheries and Aquatic Sciences and a PhD in Veterinary Medical Sciences from the University of Florida. She provides freelance medical writing and aquatic veterinary consulting services through her business, Seastar Communications and Consulting.