Predictive model could reveal risk for Lyme disease in dogs, humans
A new predictive model suggests that data can provide accurate predictions for the prevalence of Lyme disease in dogs. This information can not only help veterinarians get an idea of the risk dogs they treat are subject to, but give an idea of the risk of Lyme disease to the human population as well.
Researchers with the Companion Animal Parasite Council (CAPC) published an open access article in May 2017 in PLOS One that describes the methods taken to create the predictive maps and their effectiveness.
Lyme disease is the most common zoonotic tick-borne disease in the United State and Europe, and is caused by bacterial spirochetes from the Borrelia burgdorferi sensu lato complex and transmitted by ticks from the genus Ixodes. In the United States, B. burgdorferi is transmitted by Ixodes scapularis on the East coast and Midwest and Ixodes pacificus on the West Coast. Of the cases of Lyme disease reported by the Centers for Disease Control and Protection (CDC), 96% of cases come from 14 states: Connecticut, Delaware, Maine, Massachusetts, Maryland, Minnesota, New Hampshire, New Jersey, New York, Pennsylvania, Rhode Island, Vermont, Virginia, and Wisconsin.
The range of ticks carrying Lyme continues to expand, making it important to be able to forecast patterns of risk to exposure in order to target those areas for vaccines, preventives measure, and educational campaigns.
For this study, researchers looked at data from 11,937,925 B. burgdorferi serologic test results from 2011–2015, which were collected at the county level in the 48 contiguous United States. To test the forecasting technique, researchers first took results from 2011–2014 to create a prediction for 2015, which they then compared to observed numbers. The weighted correlation between the observed and forecasted prevalence for 2015 was 0.978. From there, they then produced a prediction for 2016 numbers.
The data collected was from a test that looks at antibodies produced during an infection from B. burgdorferi and did not indicate an active infection, but rather indicated the prevalence of dogs who had been exposed to B. burgdorferi. Figure 1, shown above, shows the county level prevalence of B. burgdorferi antibodies from the 2011–2015 data. Higher concentrations are in the 14 states that report the most cases of Lyme disease. Furthermore, they noted that the endemic range seems to have expanded into Northern California, Southeastern Oregon, Southwestern Idaho, Eastern Colorado and Northern New Mexico. In addition, there is an expansion of seropositive dogs along the Canadian border. The researchers note that this expansion “mirrors recent reports that Lyme disease is poised to be a significant human public health concern in North Dakota.”
The study suggests that in addition to annual testing, areas showing a risk for Lyme disease should also promote year-round use of acaracides in dogs and vaccinate dogs against Lyme disease before they are exposed to infected ticks.
By preventing Lyme disease in dogs, the human population is also at less of a risk. The researchers cited a CDC study from 2011 that suggested a prevalence of dogs with antibodies for B. burgdorferi at greater than 5% at the county level puts humans at risk for Lyme disease. Therefore, these predictive models can help veterinarians predict the risk of Lyme disease for patients, but also reduce the risk for pet owners as well.
Photo courtesy of Companion Animal Parasite Council