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At the University of Minnesota College of Veterinary Medicine (CVM), researchers pursue leading-edge practices and breakthroughs. Sometimes innovation lies in re-tooling tried-and-true methods. Recently, Tiffany Wolf questioned the application of one such method, syndromic surveillance, to free-ranging wildlife.
Syndromic surveillance utilizes data—in both human and animal health—on behavioral or clinical symptoms before diagnosis, which helps public health experts identify, track, and mitigate infectious disease. “This type of surveillance can lead to an earlier detection of an outbreak,” says Wolf, DVM, PhD, assistant professor in the Department of Veterinary Population Medicine (VPM), “sometimes well before laboratory-tested data is available to confirm an outbreak is happening.”
But how does one challenge a long-standing staple in public health?
Wolf collaborated with researchers from the University of Saskatchewan, Franklin & Marshall College, Emory University, Duke University, and Arizona State University on a project—funded by the National Institutes of Health, the Lincoln Park Zoo in Chicago, Ill., the Arcus Foundation, Morris Animal Foundation, and the Leo S. Guthman Fund—studying chimpanzee health in Tanzania’s Gombe National Park. There, they found syndromic surveillance is better for detecting chimpanzee respiratory outbreaks during certain times of the year than others.
Asking the right questions
Dominic Travis, DVM, MS, associate professor in VPM and adjunct professor in the U’s School of Public Health, helped recruit Wolf for the project. His team needed a researcher capable of analyzing their method’s efficacy—and they had plenty of data to work with.
"How do we know how well this system is working in telling us when they are sick or when an outbreak is happening?”
Tiffany Wolf, PhD
Travis sees syndromic surveillance as a win-win. With training, people already monitoring a wildlife population can acquire and assess health data for warning signs. “We’d have early, non-invasive outbreak detection to help park and research managers make decisions on the prevention and control of risks,” he says. Applying syndromic surveillance to wildlife also means researchers can gather diagnostic samples without capturing or touching wild animals.
According to Travis, Wolf was essential in optimizing the program. Their syndromic surveillance was revealing illness patterns in Gombe’s chimpanzees, but Wolf had questions: “I started asking, ‘How do we know how well this system is working in telling us when they are sick or when an outbreak is happening?’” No one had formally addressed these questions in nine years.
New applications
Syndromic surveillance is often applied to large populations, which produce copious health data. These cases have thorough methods to examine system performance. “Our chimpanzee population is small, though,” says Wolf. “I had to think about what other methods I could use in a situation where the number of individuals contributing to the data set is small and their behavior is important to both disease transmission and detection.”
Wolf turned to agent-based disease transmission modeling—a method often used in human hospitals or other settings where variations in human behavior influence how disease might spread. “At the population level, individual variation might be less important to understanding transmission patterns,” says Wolf. “But it’s critical to capture when modeling disease in small or highly social populations like Gombe chimpanzees. Their social groups change so frequently that it was important to include in the model.”
Gombe’s chimpanzee dispersion varies throughout the year. “From July to September, there are relatively few outbreaks in the park,” Wolf says, “but when they occur, they tend to be larger. To make things more complicated, this is also a time of year when our system doesn’t perform as well in detecting outbreaks.” Her team’s analysis brought this information to light.
Answers revealed
In epidemiology, surveillance system evaluation is a crucial process. The novelty of the work Wolf’s team did was quantifying the performance of syndromic surveillance in a wildlife population—a setting where the method is new.
Wolf’s research paper—written with fellow scientists, including Travis and Randy Singer, DVM, PhD, professor in the Department of Veterinary and Biomedical Sciences—was recently featured as Editor’s Choice in the Journal of Applied Ecology. To Wolf, the accomplishment carries extra weight. “I am an epidemiologist by training and not an ecologist,” she says, “but to have this article accepted into the Journal of Applied Ecology—having combined methods from both disciplines—is really exciting.”