A Smarter Response to Disease
How UC Davis Engineers are Building Tools to Slow the Next Outbreak
In the near future, a researcher works in a lab to receive and analyze data when an alert goes off. The data, from a network of strategically placed sensors, indicates the pandemic potential of a disease spreading between animal species. The researcher informs other teams of scientists to further investigate the issue, possibly mitigating the spread of that disease and stopping a new pandemic before it even starts.
This is the goal of the National Science Foundation’s Center for Pandemic Insights, an $18 million, seven-year, multi-institutional project led by the University of California, Davis. The center aims to harness and develop new sensing technologies to detect, investigate and mitigate pandemics at their source.
“Our center is focused on learning about the pre-emergence phase of pandemics, meaning the events that happen before humans get infected,” said David Coil, the center’s program manager. “An important part of that is developing and deploying technologies that better allow us to monitor and understand what’s happening out in the world.”
That’s where two College of Engineering professors come in. Professor Cristina Davis and Associate Professor Zhaodan Kong, both of mechanical and aerospace engineering, are applying their respective expertise — chemical sensors and robotics, respectively — to help the center achieve its goals of arming humanity in the fight against another global disease outbreak.
Sniffing Out Disease
In the security line at the airport, a TSA agent swabs a bag or someone’s hands with a cloth. Inside that cloth, there is a sensor programmed to “sniff” out explosive chemicals.
That same type of technology is what Cristina Davis and the researchers in her Bioinstrumentation and BioMEMS Laboratory are working with to detect chemical shifts in the scents of mammals — like the smell of skin or excrement — and the colonies in which they live to see if the scents can provide information about disease and its spread.
“If there is a disease spread going on at a population level, can we tell based on a shift in this chemical signature?” said Mitchell McCartney, director of the lab. “What we want to do with our sensors is flag changes in chemical emissions and say, ‘We think there's something suspicious going on here. We probably need to come in and take a closer look.’”
Their arsenal of sensors includes differential mobility spectrometry, or DMS, micro preconcentrator chips and microcondensers, as well as a variety of samplers to capture samples in the field for testing.
The sensors utilize different mechanisms to detect volatile organic compounds, or VOCs. For example, DMS separates and identifies ions in the gas phase by size, shape and chemical interactions based on how they move through an electric field. A micro preconcentrator chip, meanwhile, captures trace gases, pollutants and biomarkers by trapping the target molecules, preconcentrating them and then heating them rapidly and releasing them in short bursts to the detector.
Working closely with organizations like the Marine Mammal Center in Sausalito, Colorado State University and the San Diego Zoo Wildlife Alliance, the lab has retrieved samples from animals such as gorillas, bats and dolphins to train their sensors. (McCartney described a recent expedition to Alaska that involved skimming the ocean for dolphin excrement and flying petri dishes on drones to catch the dolphins’ blow exhalations.)
So far, the testing of these sensors has been in relatively controlled environments. The next step, which Davis is particularly looking forward to, is to bring these sensors into the wild.
“We build things in the lab, and we test them in what we think are mostly real environments, but there's a difference between being outdoors here versus taking them out somewhere really remote or somewhere with extreme weather conditions, or an austere environment,” Davis said. “I'm excited about field testing our technology at another level.”
Into the Wild with Drones and Data
The sensors that Davis’ lab is developing will provide key insights into when disease is occurring in animal colonies. Of course, they have to get there first.
Zhaodan Kong, an expert in autonomous robotic systems, particularly uncrewed aerial vehicles, or UAVs, is customizing drones to deploy these sensors and other payloads in various conditions, from adverse weather like gusty winds and fog, to locations where GPS doesn’t work, like caves and deep woods.
Kong and his team, including Baihan Chen, a Ph.D. student in mechanical and aerospace engineering, are investigating how to fly a drone in windy conditions. They use data-driven modeling and control to learn how the wind affects a drone’s dynamics. The drone’s computer uses the learned model to estimate its state — position, orientation, velocity, etc. — in real time. The appropriate motor commands to maintain stability are computed, allowing the drone to hover or fly straight despite strong gusts.
It's one step Kong and his team are taking toward their long-term goal: a 24/7, all-weather autonomous monitoring network. Other challenges the team is addressing to achieve this goal include developing autonomous recharging and cooperative scheduling between multiple drones, supporting navigation where GPS doesn’t work, and using smart data processing and communication tools so remote experts can watch and analyze live images in real time.
“Eventually, maybe we can count on this type of fully automated system to provide automated all-weather persistent surveillance without a human needing to be there,” Kong said.
Kong is also working with disease tracking teams to integrate multimodal cameras into the UAVs, enabling them to monitor different species across various environments and lighting conditions.
These modular cameras can record in color, infrared, or in a combined color–infrared mode, where both channels operate simultaneously, and each mode supports different scientific objectives.
The color camera enables detailed monitoring of the social behavior of seals and birds, including the detection of anomalies and any indications of avian flu transmission across species. In parallel, Kong and his team are developing facial-recognition algorithms to identify individual seals and track their interactions — both with one another and with birds.
The infrared camera, which measures heat radiation, allows the team to track animals such as bats in low-light environments or even at night.
When used simultaneously, the cameras provide a richer picture of animal health and behavior: the color channel supports species identification and behavioral analysis, while the infrared channel helps detect thermal patterns that may indicate infection, stress, or other early markers of disease.
To further these monitoring efforts, Kong will also field test an automated sequential air-filtration system designed to collect airborne viral particles inside bat cave environments. This system, developed in collaboration with Simon Anthony, an associate professor of pathology, microbiology and immunology at the UC Davis School of Veterinary Medicine, uses a series of filters to collect multiple air samples over extended periods of time (up to 24 hours) without human intervention, enabling Anthony’s group to study viral recombination events between different bat species occupying different zones of a cave.
“By far the most exciting aspect of this center is seeing teams work together across these different disciplines to achieve what never would have been possible otherwise,” said NSF Center for Pandemic Insights Director Christine Johnson, a professor of epidemiology and ecosystem health in the UC Davis School of Veterinary Medicine.
Protecting the World of Tomorrow
As the project concludes its first year of seven total, Davis and Kong are on the cusp of implementing the tools they are designing, creating and troubleshooting in the lab out in the world. They are taking the first few steps so that other scientists can use the tools they are creating to gain better and more informed insights.
“It’s so clear that engineering efforts are needed to create these new technologies to give us remote access into what is going on, into our environment around us, both for animal health and human health.” — McCartney
And one day, in the not-so-distant future, these technologies might be what save the world from another viral catastrophe on a global scale.
“The COVID-19 pandemic was such a horrible experience,” Kong said. “If we understand how these things emerge, we can maybe not completely prevent but reduce the chance of another COVID.”