Journal
GEOSPATIAL HEALTH
Volume 14, Issue 1, Pages 111-120Publisher
UNIV NAPLES FEDERICO II
DOI: 10.4081/gh.2019.750
Keywords
Lyme disease; Canine sentinel; Borrelia burgdorferi; USA
Funding
- National Science Foundation [DMS 1407480]
- National Institutes of Health [R01 AI121351]
- Boehringer Ingelheim Vetmedica-CAPC Infectious Disease Postdoctoral Fellowship
- NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [R01AI121351] Funding Source: NIH RePORTER
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Lyme disease (LD) is the most common vector-borne disease in the United States. Early confirmatory diagnosis remains a challenge, while the disease can be debilitating if left untreated. Further, the decision to test is complicated by under-reporting, low positive predictive values of testing in non-endemic areas and travel, which together exacerbate the difficulty in identification of newly endemic areas or areas of emerging concern. Spatio-temporal analyses at the national scale are critical to establishing a baseline human LD risk assessment tool that would allow for the detection of changes in these areas. A well-established surrogate for human LD incidence is canine LD seroprevalence, making it a strong candidate covariate for use in such analyses. In this paper, Bayesian statistical methods were used to fit a spatio-temporal spline regression model to estimate the relationship between human LD incidence and canine seroprevalence, treating the latter as an explanatory covariate. A strong non-linear monotonically increasing association was found. That is, this analysis suggests that mean incidence in humans increases with canine seroprevalence until the seroprevalence in dogs reaches approximately 30%. This finding reinforces the use of canines as sentinels for human LD risk, especially with respect to identifying geographic areas of concern for potential human exposure.
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