¶¶Òõ̽̽ professor Brian Beckage wears the black t-shirt and artfully trimmed goatee commonplace in most urban environments or at any casual music venue. He comments that he dresses as he does in part to change the perception of what a scientist looks like, "I don't want anyone aspiring to become a scientist to feel they don't belong in science because of the way they look." He's smiling as he says this, but in a way that challenges expectations. This attitude of challenging convention is borne out in Beckage's career trajectory. He has published several papers in prestigious, peer-reviewed journals that have challenged how we study and understand climate change.
"Traditionally, the way climate models would be run is that experts would look at potential futures in terms of emissions. They would look at variables such as the invention of different technologies and the adoption rate of different technologies, and so there would be these external, static pathways that would then be fed into climate models to understand how the climate system would respond and also to project what temperatures and climate we could expect by the end of the century."
His work has instead looked at an added critical variable that most climate change prediction modelers have left out: human behavior.
"I was interested in this way of thinking because it's really a lot more complex than just how it's commonly perceived, particularly among physical scientists. They're just like, 'But here's the data. Why wouldn't people just do what's obviously right?' They didn't consider the impacts of social interaction. I think human behaviors are where most of the problems, and challenges, and richness come from."
His models have shown that to predict if the earth will reach temperatures untenable for human life, the critical variable is whether or not humans will act on information that science provides.
"It's becoming increasingly clear that climate change and other global problems are really a lot less about the biology or the physics, and a lot more about human behavior, and not just humans' interactions with earth systems but the way humans take in and process information. I formed a working group with connections in the behavioral sciences a long time ago to start trying to link models of human behavior with climate models."
The future of our planet may not be dictated by temperature but rather by temperament .
"It's actually a dynamical system in which humans respond as they see things changing: More wildfires and wildfire smoke, and it's getting hotter, with shorter warmer winters and hotter summers? Then, people associate these problems with climate change. Seeing personally the effects of flooding, as we've seen here in Vermont, or the wildfire smoke, particularly last summer, or the loss of crops and its impact on food security…. all these different events are going to change people's perception of the risk they ascribe to climate change. Then their response cycles back into the system and affects how much the climate changes."
This year, the NSF Division of Mathematical Sciences awarded Beckage and his collaborators a 1.3 million dollar grant to apply his prior approach to a new area of inquiry. Their new study is titled "Integrating Human Risk Perception and Social Processes into Policy Responses in an Epidemiological Model." His interdisciplinary team will explore how we think about and model disease transmission. The project will contribute to the development of mathematical epidemiological models that better represent the complexities of the human response to disease, and that can be used to evaluate the relative impacts of public health policies on disease dynamics.
An epidemic arises from interactions between pathogens and humans, where the pathogen influences human behavior, and human behavior influences the pathogen's spread. The usual models devised to predict disease spread do not include the complexity of interactions between disease and human behavior but instead focus on biological processes and policy interventions. However, disease transmission depends on people's behaviors, which are shaped by their perceptions of risk from the disease and/or from health interventions, as well as by the opinions and behaviors of the other people around them.
"In the prior papers, we published in journals like Nature and Nature: Climate Change and Nature: Human Behavior, we started to review different models for how humans behave, and there's just a huge number of different models, and so we kind of broke it down into two, different, basic processes we call: cognition and contagion.
"So, contagion is how you get information and how you interact with other humans, like your social networks that influence your belief systems. Cognition is how we process information. So, for example, you know we habituate to change as we get used to things, and we have biases in how we process information, and we're boundedly rational, and there are all these different theories of human behavior, but we just broadly conceptualized them into two categories--contagion and cognition—that basically describe how we get and process information.
"For our new study we'll take this contagion/cognition social model which we applied to climate change, and modify it to work with these standard epidemiological models. My working group includes sociologists, psychologists, and climate scientists. I'm trained as a computational or mathematical ecologist so I’m sort of a mathematician or computational scientist but with an appreciation for systems with complex interactions and feedbacks. We also have folks that are focusing on policy and economics as well on human behavior, so different people are on different parts of these papers. On this project, I'm working most closely with Katherine Lacasse from Rhode Island College, she's a psychologist; Charles Sims at the University of Tennessee, who does environmental economics; Suzanne Lenhart, she's a mathematician also at the University of Tennessee, Lou Gross, also a mathematician recently retired from the University of Tennessee, and Chadi Saad-Roy, a mathematical epidemiologist currently at UC Berkely.
"It's validating to get NSF Funding. We showed that we could do it in the climate field, and now we're taking this approach into a different field. The pandemic made a big impression, so this work doesn't feel as far off as climate change -- though climate change isn't really far off, it's already here. We're not really focusing on COVID in this study. COVID is one of the diseases we're incorporating, but we're also interested in the flu and the new emerging Avian Flu. Avian Flu has jumped to cattle and could make the jump to humans, and it seems to have a much higher mortality rate than COVID did. So, it's a good time to be looking at these systems and how social interactions and social processes influence outcomes. There's a lot of uncertainty, and so it matters a lot."
Though Beckage and his colleagues are focusing on improving the modeling capabilities in this realm, he feels his work is not relegated to mere theoretical understanding but has a timely practical application.
"The benefit when you have these models, and you look at what the system is most sensitive to, then it gives you guidance as to where to intervene in the system if you want to avoid… say dangerous climate change, or if you want to find the best way to try to reduce the impact of a pandemic or the spread of a disease. It gives you points of intervention where you have high leverage to change the direction of the system."
Timely intervention could lead to better human outcomes. The group plans to disseminate their results and foster connections with the disease modeling community through a workshop for public health professionals.
They will also engage the public through the production of educational music videos targeted at the broader community. Avian Flu Fusion? Covid Rock? Adding modeling variables isn't the only way this scientific working group will provide a fresh approach.
