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Tuning into Social Networks to Prevent and Contain Disease


As the College of Veterinary Medicine’s first and only disease ecologist, Meggan Craft, Ph.D., is a pioneer in the study of how disease spreads through animal populations. She has used mathematical models to track the spread of distemper in African lions and is currently working on a five-year collaborative project to discover what types of mountain lion contacts lead to the transmission of infectious disease.

Craft is one of the early adopters of technology that looks at how social networks—prides of lions, pods of whales, or herds of cattle—contact one another within their social network and in neighboring networks. Called contact modeling, this tool is being adopted at a rapid rate worldwide, and Craft is helping researchers make the best use of the method.

“Contact models provide a good framework and informational tool for researchers who want to combine real-world data on contacts and disease modeling in order to understand the spread of the disease and how that can impact wildlife, domestic animal populations, and humans,” says Craft.

Due to the increasing use of these models, Craft decided to review how well these models have performed over the past 10 years and how scientists can make even better use of them in the future.

Her recent work, “Infectious Disease Transmission and Contact Networks in Wildlife and Livestock,” was published in April 2015 in the prestigious journal Philosophical Transactions, the world’s first journal dedicated to science. Philosophical Transactions published its first issue in 1665.

“The paper looks at some of the questions these models have addressed, what the models are good for, where they need work, and areas for future research,” notes Craft.

The models Craft reviewed were primarily used for specific case studies, one with a host and a specific pathogen. She discovered that these models are particularly good at using social structure and complex movement patterns to help inform scientists about disease transmission.

“They are a good tool when you know something about the social structure of the animal population you want to study,” she says.

Traditional models assume that everyone within a population has an equal opportunity to contact everyone else in that population, which is often not realistic, she says. For example, in 2009 and 2011, Craft devised a model that helped her determine that hyenas and jackals were likely involved in the spread of distemper in African lions by incorporating pride structure into her model of disease spread. The model provided a look at how the disease should have spread through the population, but that was not what the real outbreak looked like, which tipped Craft off that other carnivores were likely responsible for spreading the disease.

Another new technology, proximity collars, are providing researchers with good data on animal movement and contact in the wild, which is increasing interest among scientists in using contact models.

For example, Craft is using data collected from proximity collars worn by raccoons and creating a contact model to understand how rabies is being spread through the raccoon population in suburban Chicago.

One of the challenges Craft found when reviewing the models is the mismatch between the social network constructed in the model and the pathogen of interest. For instance, if a virus is only infectious for two days, the model needs to reflect that.

“In this example, the model would need to be constructed on a two-day time scale to represent every other animal the infected host comes into contact with over a two-day period, not, for example, a full year,” Craft says. “Using a full-year time scale greatly overestimates the number of animals that could become infected.”

Lack of data on either contact behavior or pathogens can also present challenges.

“It’s an exciting time to bring together mathematical modelers, veterinarians, and field biologists in an effort to understand how best to predict and contain disease spread,” says Craft. “The resulting information can also help us develop more targeted control strategies.”

Once it is known which individuals are most likely to spread disease through the most contacts, such as pride lions, for example, then scientists know which cats to vaccinate to contain the spread of the disease.

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