Recent research published in Nature’s Scientific Reports and sponsored by Fetch Pet Insurance found that canine insurance data can help predict human disease outbreaks up to one year before they occur. The research highlights the importance of One Health, the concept that human, animal and environmental health are interconnected.
The researchers compared Fetch Pet Insurance’s U.S. claims for Lyme disease, Giardia and Valley Fever from 2008 to 2022 against human data from the U.S. Centers for Disease Control and Prevention. They explored the use of dogs as sentinels for human disease because people and dogs share similar environments.
“Pet insurance data could help us predict disease outbreaks earlier, impacting both dog and human health,” said Dr. Audrey Ruple, a co-author of the study, a veterinary epidemiologist and chair of the Fetch Veterinary Advisory Board. “This will allow us to warn public health officials in both human and pet fields sooner.”
Lyme disease is spread by Ixodes ticks, also known as deer ticks or black-legged ticks, and is most common in the Northeastern United States. Lyme disease patterns show that the disease incidence is 44 times greater in dogs (471 cases per 100,000 dogs) than in humans (11 cases per 100,000 people). Although canine cases tend to appear earlier in the year, with an increase in March compared to a May increase in human cases, human and canine disease patterns were found to follow similar trends. However, the change in canine case incidence preceded human incidence by one to two years.
Although giardiasis is rarely shared between dogs and humans, both species can contract the disease from contaminated water sources. The geographic incidence was similar for dogs and humans, with a higher number of cases in northern states. Canine giardiasis cases typically spike in March and then slowly decrease, whereas human cases rise in May and peak in August. Like with Lyme disease, however, years with higher canine case rates were followed by years with higher human cases.
Valley Fever is caused by inhaling spores of the fungal organism Coccidioides, which is found in the soil. The geographic distribution is similar for dogs and humans, with higher incidence focused in California and Arizona. Patterns in disease incidence were similar for dogs and humans, with years of higher and lower cases correlating between the species.
The information could potentially be used to predict human disease outbreaks, the researchers reported. Current machine learning algorithms could be retooled as surveillance databases to detect increases in canine diseases and alert public health officials and human health care workers.