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We’re all struggling to make sense of the surreal unfolding of the coronavirus pandemic and all of the news and numbers and nifty charts of curves and spikes we get bombarded with on an hourly basis.

In the process, we end up getting in over our head — I’d be the first to admit that I’ve done this — trying to draw conclusions we’re not qualified to make. Slate recently published a pretty good criticism of the epidemic of “armchair epidemiology.”

So I decided to talk to an actual epidemiologist — Lindsay Keegan, a professor at the University of Utah who studies and models the spread of infectious disease.

We discussed the frequently referenced public models — in particular state-level projections from the University of Washington Institute for Health Metrics and Evaluation (IHME) — that she says can cause unnecessary panic, her forecast on how long the outbreak will last, and whether Gov. Gary Herbert should issue a statewide shelter-in-place order. Here are some excerpts of our conversation.

Gehrke: My understanding is that you have helped the state put together some models for what we can expect from the coronavirus. What do they show?

Keegan: What I’m doing, in collaboration with a team at the Johns Hopkins Bloomberg School of Public Health, is creating scenario-based projections. … These attempt to model the disease course assuming we undertake certain interventions, rather than forecast the course we’re on based on the available data. Currently we’ve been modeling the impact of different lengths of lockdowns, voluntary social distancing measures, and comprehensive test-and-isolate. We base all of these interventions on published literature that looks at the impact either for COVID-19 in China or South Korea, where the epidemic is more complete, or from influenza pandemics.

(Trent Nelson | Tribune file photo) Gov. Gary Herbert speaks at a news conference in the state's Emergency Operations Center on Thursday, March 12, 2020, addressing the current state of COVID-19 in Utah. Representatives from the Utah System of Higher Education, the Utah Board of Education, Utah Jazz, local health authorities and Utah Department of Health were also present.

… While I am not comfortable issuing a projection of when I expect Utah [cases] to peak, I will say that I expect it to be months away and the better we are at social distancing, the later it will peak and the lower it will peak (i.e., there will be much fewer infections at the peak), which is what we are hoping for.

Gehrke: Is there anything the public should know about [these models], what to prepare for and how you approach this?

Keegan: So the thing I really want to caution people about with models is that a model is really only as good as the data and the assumptions on which it is grounded.

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I am concerned about the public facing models not clearly expressing in lay terms what data and what the assumptions that they’re using are. And so I would caution readers that if they don’t understand the assumptions that a model is making or worse, if the assumptions are not clearly laid out, that they should be cautious of the results.

What concerns me about these public-facing models, including the one you mentioned from IHME, is that they can do more harm than good. It’s not a case of some information is better than no information. On the one hand, they can cause panic, and on the other, they can cause distrust of science.

The IHME model is projecting that the peak is happening in April and when the peak doesn’t happen in April, I worry that readers will start to think that scientists don’t know what they’re talking about, that these models are wrong, that they’re not useful, that we shouldn’t use them to guide an epidemic. Or that people will say, “Oh, we’re past April, so now I can go back outside again. Now I don’t have to shelter in place or I don’t have to follow the guidelines that the state has put forward.”

It really concerns me that groups are putting out these models without potentially considering the impact of what the models might do when they’re taken by people who don’t understand the nuances of them. And so I just want people to be cautious when looking at these models, try to evaluate if they make sense with what we’re actually seeing, and try not to extrapolate too much if they don’t seem to jive with what we’re actually seeing.

Gehrke: Would it have been preferable for Utah to do a statewide lockdown? Or do you think the social distancing and some the closures that we’ve seen are adequate?

Keegan: Shelter-in-place orders or lockdowns can be incredibly effective at stopping a disease in its tracks. By reducing everyone’s number of contacts down to just household members, the number of secondary infections is incredibly limited. However, this is a global pandemic. Once someone from outside of Utah brings COVID into the state, as was the case in late February, early March, we’re back in the same place we are now.

What lockdowns are very useful for are buying time to build up hospital capacity, to increase hospital personal protective equipment stocks, and to scale up testing. So while lockdowns are incredibly effective, I’m supportive of our state leadership who seem to be saving a more broad shelter-in-place order for when it’s really needed, if or when the outbreak starts to spread out of control, as seen in other states.

Until then, I hope people continue to minimize their number of contacts voluntarily, and continue to listen to state and local government officials, who I believe are doing a really good job so far.

Gehrke: Thanks for talking with me. I learned a lot.

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I had a few takeaways from my conversation with Keegan that hopefully give us all a little peace of mind. First, like she said, don’t put too much stock in the models. They’re only a snapshot that is as good as the data and assumptions behind them, and what we know about this disease is constantly changing. Without question, this outbreak is lethal, but even the best models can only give you a range of possibilities.

Second, it’s comforting to know that there are experts — Keegan is just one of them — providing policymakers with the best data we have in real time to inform their decisions. What they do with that is obviously another story.

Third, the measures we are taking make a difference. Keep doing them.