The University of Wyoming was recently selected as one of just a few research institutions nationwide to receive approximately one million dollars in grant funding for research into pandemic modeling. Wyoming Public Radio's Hugh Cook spoke with economics faculty Dr. David Finoff and Dr. Linda Thunstrom on how the money will help them research future pandemics.
David Finoff: The grants give us the time to be able to conduct the research. They allow us to hire graduate students, and we actually will be hiring a postdoc as well. But they also allow us to pay for the data [that] doesn't exist. We might need to conduct experiments to gather "how would people respond in the face of a future pandemic," or the kinds of risks [and] the mix of risks and policies that we might see, if you will. We've been doing a lot of economic and epidemiological and behavioral modeling for quite a while. And at the start of the pandemic, we jumped in with a bunch of work looking at a cost-benefit analysis of pandemic policies. And then when we started thinking about how weird people were be[ing] in this deal, Linda jumped into really going after the consequences of vaccine hesitancy, so we had a bunch of work going on. And then last year, when Steve Newbold, Todd Cherry, and [Jason] Shogren, a bunch of us in the Department of Economics, got together and started building a team with other people at UW in mathematics and psychology, and then working with other collaborators in Sweden and other institutions across the U.S. So, we wrote a proposal and submitted it to the National Science Foundation, the NSF, and it was a really competitive process. Ours was one of eight projects that were awarded. [There were] submitted proposals [from] loads of institutions and teams did this, and we were one of only eight to get funding for it and we actually beat out a lot of really prestigious institutions.
Linda Thunstrom: We're doing this in collaboration with colleagues at George Mason University, [the] University of Tennessee, also the Norwegian Health Institute, and a research institute in Sweden. And I forgot to mention Denison University. We realized, just like the NSF that the models that existed did not do a very good job of predicting the disease developments, because people didn't behave in a manner that the models assume, standard epidemiological models would assume.
Hugh Cook: Were you involved in research during the pandemic, in regard to disease models or anything like that? Or is this something that is purely looking forward that you're involved in?
DF: Both actually. We were involved with using existing modeling to think about the costs and benefits of the social distancing policies that were imposed at the start of the epidemic. We actually wrote a paper really early on that got a lot of publicity and some of the greatest things we did with that paper, we did wide. We did a massive sensitivity analysis across all these key parameters, and the forecasted outcomes really depended keenly upon the assumptions that were built in. And some of those assumptions were based upon good data. And some of them were [when] things were moving so quickly, you had to take what was the best available, and turns out the best available wasn't as rich as what we see now.
LT: It really gives us a unique opportunity to study the behavior or behavioral responses to both the disease and the policies, like Dave said, because there is such a wide variety of policies that we could observe both in the U.S., of course, but and not least, in Scandinavia and across countries that are very similar, but took very different approaches politically to these diseases. So, Sweden, for instance, had more of a laissez-faire policy, whereas Norway was very strict and also adjusted their policies very frequently, depending on the disease situation, or the health outcomes at the time, down to a municipality level. By combining all three countries, the U.S., Norway, Sweden, we get a very large variety of policies, we get a very large variety of health outcomes during the current pandemic. And we can analyze unique policy questions because of this large variety, both across time and space, that we wouldn't have been able to do if we would have focused on one single one of these countries. We had a very efficient team that worked both on disease models and behavioral aspects. So, we combine[d] those early on. And then a small university with good relations really helps in terms of that we could build this team that Dave was talking about with mathematicians and psychologists as well. And so, there are benefits to being small and well connected so that we very quickly build these teams.
HC: Modeling was one of the things that either was kind of on point with COVID or it seemed to be kind of wildly off base when you're looking at post-pandemic modeling. What are some of the factors that you're looking to take into account that pre-pandemic or pandemic era models did not have?
DF: That's actually exactly the impetus for this work and namely, the fact that how people respond to the risk and how people respond to the difference in the risk that public policies cause really does lead you to have a set of different outcomes than what you would expect. Our work is to try to provide a more realistic characterization of behavior in these models. So the forecasts are better, or at least can be used to generate some scenarios that are kind of like, 'Well, what if people respond in a certain way to some of this? And then another certain way to, let's say, the policies?' And if so, will our public policy be efficient and a good use of money? Or will it fail?
HC: What were some of those things that you learned about Wyoming through some of your prior research?
LT: Particularly with regards to vaccine hesitancy, we learned quite a bit. And we learned that Wyoming is different. It is quite unique in terms of the stickiness of the vaccine hesitancy that we could observe here versus nationally. So we did one study, for instance, where we examined how vaccine hesitancy responded to different types of information. And we could see fairly sizable effects for the nation as a whole from some of those information messages and we saw no impact whatsoever in Wyoming. So we realize that the initial vaccine hesitancy might have been similar, or more similar at least, in Wyoming to across the nation, but it was just stickier, harder to address with policies.
