Disease study maps horses’ social life

It’s too bad horses aren’t on Facebook.

Knowing how many friends a horse has would be useful to understand their risk of infectious diseases such as strangles.

Luckily, Kelsey Spence is building a social network for them.

The PhD student from the Ontario Veterinary College is using a horse social network to analyze contacts between horse facilities.

Determining travel patterns of horses in Ontario has important implications for understanding how infectious diseases might spread within the horse population.

The study included horses only from Ontario, but the results may be applicable to horses across Canada.

Spence, who worked with OVC epidemiologists Dr. Terri O’Sullivan and Dr. Amy Greer on the project, chose a network-based approach to consider the horse population as a whole rather than focus on individual horses.

“At a population level, the risk of infection in each horse depends on another horse, so it becomes this intertwined web of factors that you can only account for when you do a network study,” she said.

There is no master list of horses and horse owners, so the researchers got creative with their recruitment strategy. They found study participants through horse associations, social media, including Facebook, Twitter and Instagram and Kijiji.

Another successful tactic was to promote the study at horse shows, where the researchers offered participants horse treats that came with study information attached.

The study included 570 horses.

“Once we got people interested, the challenge was keeping them interested,” said Spence.

Instead of a passport, horse owners logged their horse’s travel once a month on an online form during the show season from May to November. These anonymous surveys asked about when, where and why the horse travelled.

“Any time they left their barn, we wanted to know,” said Spence.

Once she collected the surveys, Spence distilled the complicated interconnections between horse movements into a network. The visual representation of these movements consists of clustered dots and lines.

Although analysis of the network is ongoing, there are a few key findings.

The most significant is the confirmation that horses establish connections with other horses and facilities when they travel.

Also, there is a trend that highly travelled horses tend to visit the most connected facilities. A horse owner may have only a few horses that compete, but it is these travelling equines that can bring infection back to their farms and spread it among the horses that stay home.

Spence’s research is starting with equine influenza, a highly infectious respiratory disease that often affects young horses.

The next step is to run computer simulations on the network to see how disease could spread through the horse population.

The computer model can estimate whether a disease is likely to cause an outbreak.

Researchers can also use the network to simulate other disease outbreaks, including strangles and equine herpes virus 1.

“The good thing about models is they can be modified,” Spence said.

“Now that we have collected the travel pattern, we can model any disease.”

This study is one of a handful that have applied this technique to horses, even through simulations are a popular way to understand the spread of human infections such as measles.

Horse organizations across Canada could use the results to develop disease response plans.

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