Anxiety, Hope, Trust And Slowing The Spread Of COVID-19 Conspiracy Theories

A Conversation With UW-Madison Professor Ajay Sethi About Making Sense Of The Coronavirus Crisis In A Sea Of Misinformation
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Illustration by WisContext; image via National Institute of Allergy and Infectious Diseases (CC BY 2.0)

Ajay Sethi, a professor at the University of Wisconsin-Madison School of Medicine and Public Health and director of its Master of Public Health program, studies the spread of infectious diseases such as HIV and measles. He also studies the spread of public health conspiracies, which can quickly unravel the progress achieved by researchers.

"Conspiracies in Public Health," a popular course taught by Sethi, prepares future clinicians and public health practitioners for thorny conversations with patients, like a pediatrician caring for a child whose parents are opposed to vaccines. When he teaches the course next, it will be "COVID-ized," Sethi said. The virus is ripe with fear, uncertainty, distrust, and disinformation – the ingredients for a conspiracy.

As states debate when and how to reopen their economies, disinformation and conspiracies about the virus have proliferated. On Facebook and talk radio shows, the virus is sometimes depicted as being no worse than the seasonal flu, and researchers are accused of exaggerating COVID-19 death tolls for political gain. "Plandemic," a short video rife with false conspiracies about the virus, was repeatedly removed from Facebook and YouTube for violating the platforms' community guidelines – but not before racking up tens of millions of views.

Everyone is vulnerable to conspiracism, Sethi said. With COVID-19, that's especially true.

"None of us feel a sense of control over this," he said in an interview with the Cap Times.

The interview has been edited for length and clarity.

Parker Schorr: What COVID-19 research do you do?
Ajay Sethi: Modeling is the main one. I'm working with a team of modelers from UW Health, and also Industrial and Systems Engineering and some clinicians at the hospital. They have in-house data scientists, but they wanted to invite people from the university to be part of this team to project what the effects of COVID might be on hospitalization rates, ICU room occupancy and ventilator use so they could predict and maybe prevent a surge from happening.

In the beginning, our tasks were pretty straightforward. Since shelter in place and other policies have been put forward, obviously that has had an effect on flattening the curve. And now we're sort of trying to figure out where to go forward, as some of these policies may be lifted or adherence to these policies [changes]. So we continue to work on those projections, but the models are getting more difficult.

Why is it becoming more difficult right now to project what's going to happen?
It's the easiest thing to model how the transmission might be when it's unmitigated as soon as you get some information about the infectiousness, what community you're trying to model, how long people are infectious, how many people end up in the hospital. To be able to project what's going to happen when you do nothing is relatively simple: You get exponential growth, as was observed here.

As soon as we got that exponential growth, politicians, decision-makers, people react to that. And, you know, we have everything from self-imposed isolation, to policies to impose those kinds of measures, different responses from the federal government and state governments. Once you have all of those factors to work with, ultimately the models get more complicated to figure out.

The sources of uncertainty have become bigger in a lot of ways because human behavior comes into play.

What is your view on some states reopening and the effect that could have on infection and hospitalization?
We can model it, and we are modeling it. What's very easy to predict is that if you cease physical distancing, you will return to exponential growth. People may not believe that necessarily, because we [Wisconsin] haven't experienced the kind of exponential growth that some settings have.

We've been able to benefit from the experience in Seattle, in New York City, in Wuhan, China, in other countries. And so we started adopting measures relatively sooner than places that had more exponential growth of cases before they had the chance to react and to evoke some policies and people began following them.

So as a result, we've had that benefit, but we're just as vulnerable as any of those other places, because we have people who don't have immunity. We don't have herd immunity really anywhere in the world. It's also just unclear whether herd immunity is even achievable, because those [measurable signs of immunity] are not even known. And everybody's got a set of lungs. And so the virus essentially just needs a set of lungs to infect.

So we have not had the New York City epidemic, but Milwaukee has had a pretty bad epidemic, and I think that's important to acknowledge. And there's been great disparities and that's also very important to recognize.

Ruthie Hauge/The Cap Times
Ajay Sethi, a professor at the University of Wisconsin-Madison School of Medicine and Public Health, teaches a popular course called "Conspiracies in Public Health." It prepares future clinicians and public health practitioners for thorny conversations with patients, like a pediatrician caring for a child whose parents are opposed to vaccines. He is pictured outside his home in Madison on May 8, 2020.

Can you tell me about the class you teach, "Conspiracies in Public Health," and why you teach it?
I've been teaching it now three years. This year is going to be the fourth. I developed the class several years ago around the time we were getting outbreaks for measles because of vaccine hesitancy that's been around now for a little while. I have training in infectious disease epidemiology, I trained at the School of Public Health, and I direct our Master of Public Health program, so all of my research ultimately has a public health focus.

As a researcher, I've seen how important it is for people to understand the value of research, to not misinterpret it. So much progress can be unraveled very quickly when we have distrust [and] people who make decisions that aren't fully informed based on good information.

And I felt like it was important to create a class where we can think about why conspiracism happens. Is there a basis for it? And what's the psychosocial basis for it? And, ultimately, the goal is to build skills in students so that they cannot run away from those difficult conversations but maybe make an attempt to look for ways we can help people make better decisions.

I'm going to teach it [this month], and one of my goals is to COVID-ize that class, if you will. I feel like I could teach the entire class in the context of COVID. But instead, I'll go through each module that I have online and show examples where things that apply to vaccines, fluoridation of water, HIV denialism, and all sorts of different topics we cover, how they apply to COVID as well.

Why are there conspiracies about public health and now COVID-19?
I have a laundry list of things that I cover in the class. Let me just go through some one-word items here.

Fear. Fear is a source of conspiracism. Uncertainty. Not feeling control. I distinguish mistrust from distrust – mistrust just meaning not being trustful, but distrust perhaps based on the experience you've had in the past. Binary thinking — we tend to have fight or flight reactions to things and when we look at a study and say this either supports or refutes whatever you are hoping is supported or refuted, you may not do that critical thinking or that more nuanced thinking that's needed.

All those things I just listed, all human beings are susceptible to that. I think there's maybe one segment of society that has distrust of government, maybe authority. There is another group of society that doesn't trust business or the private sector or other forces. I would argue that we all exhibit some sense of conspiracism. The best examples I usually come up with are related to sports. You know, if the Patriots win the Super Bowl or Duke wins the national championship in basketball, the refs are paid off.

And I would argue that it exists all the time. Ultimately, how many of us really have the time to thoroughly research something with high quality evidence before making a decision? Often we go to our most favorite new sources, we have opinion leaders we rely on, and we have to do that because there just literally isn't enough time to go through a proper research approach to everything we want to learn.

What is your advice to someone when they're reading research or reading a story about COVID-19, especially now when we’re in uncharted territory debating whether we should reopen the state and how to do that?
What I teach students and what I try to do myself as much as possible is recognize we all have shared interests. I don't think there's anybody in the country who's happy with the economy, the direction of the economy right now. I think everybody's unhappy that we have to have these stay-at-home orders, that the economy has completely come to a halt, that people are losing their jobs. So I think once when we understand we all have the shared interest of resuming our economy, I think you can look at information a little differently. Maybe that mistrust can dissipate a little bit.

I don't think there's a single person who wants to see a lot of deaths occur in this country. You asked about the comparisons to the flu, and even if COVID operated exactly like the flu — and I'm not at all saying that, I think it's quite the opposite — who wants to double flu deaths in a given year? It doesn't make really a lot of sense that anybody would want that. So I think if we recognize our shared interest of minimizing deaths and not having these detrimental effects on the economy, I think we can approach this together and think about, based on those shared interests, what does this research mean?

And are there any misconceptions about the virus, models or herd immunity that you think are important to clear up?
The models generally point to the same things. I think it's important that we look at them kind of qualitatively. And if we focus too much on the actual numbers, then we're putting too much stock in the models and the parameters that are used to forecast this infection going forward. There's a lot of uncertainty inherent in all the models, and that's why we have so many people performing these models. They're using lots of different approaches in hopes that eventually everybody, collectively, can triangulate to what may happen. From a qualitative perspective, there's some clear certainties that if the epidemic goes unmitigated, you'll have exponential growth as long as you have people in a community who are largely not immune.

We started off this epidemic with the entire planet being not immune, because it's a novel virus. It's only been three months. I've never known of an infectious disease where in three months the entire country can develop herd immunity. Even before the measles vaccine was developed, we had hundreds of thousands of children die every year in this country. Nobody ever achieved herd immunity to measles.

As an epidemiologist and someone that studies mistrust of science, what do you think these next steps will look like?
As far as where we go from here, stay-at-home inevitably will have to be dialed back because of the economic consequences of all of this. It'll be dialed back, but it'll be dialed forward. I think as soon as we put ourselves in a situation where there's a return to exponential growth, we'll have to make a choice of how we're going to react to that. Up to this point, we've reacted by having policies like stay-at-home, closing schools, promoting physical distancing. Those things may have to return, maybe in full force, if a rebound in cases occurs at that exponential growth level or even if it gets worse. We'll have to recognize that this is potentially a possibility.

We have to define what our new normal is. It's important that we recognize we don't have a vaccine right now. The timeline for a vaccine that gets quoted is really based on, if everything goes right, we can have one sometime in 2021. I know that we are, as a country, investing heavily in that. But the science has to fall perfectly. The biology has to fall in place perfectly in order for a vaccine to work and to have the manufacturing capability to scale it up very rapidly.

That's a tall order. I would not want to see us be in denial: that the changes we have to make are temporary, that the vaccine is on the horizon. When a vaccine occurs, that's great. But in the absence of one, I think we need to assume that it's not going to be necessarily soon.

On a personal note, one of my best friends from middle school, his father passed away from COVID a couple of weeks ago. Older individual, 93. And while one can accept somebody at the age of 93 facing mortality … it was very sad to learn that he was someone who cannot hear, unable to wear hearing aids to correct his hearing. Was in the hospital alone. No family. Died. And then the funeral afterwards, he had eight children surviving and only five children could visit, and two of his children had symptoms of COVID, so they couldn't leave the home anyway.

Just thinking about that reality and thinking about all the narratives that we're hearing in the news as being part of the new normal … that’s just something that we're just going to have to accept or acknowledge moving forward, to not be there for our family members and friends at their most vulnerable time.

This story comes from a partnership of Wisconsin Watch and the Cap Times. Parker Schorr is a Cap Times public affairs reporting fellow embedded in the newsroom of Wisconsin Watch, which collaborates with WPR, PBS Wisconsin, other news media and the University of Wisconsin-Madison School of Journalism and Mass Communication. All works created, published, posted or disseminated by Wisconsin Watch do not necessarily reflect the views or opinions of UW-Madison or any of its affiliates.

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