Here’s what we know about Minnesota’s model for predicting the toll of COVID-19

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On Friday, state health officials unveiled more information about the model they’re using to predict how different strategies designed to contain the spread of COVID-19 might change the course of the disease in Minnesota.

The model was built by researchers at the University of Minnesota’s School of Public Health and the Minnesota Department of Health, and officials say it’s one of many tools being used to chart policy in response to the coronavirus.

Here’s what we know about Minnesota’s model (you can watch the briefing yourself here and see slides from the presentation here).

What’s the purpose of the model?

As we all know by now, COVID-19 is a fast-spreading disease caused by a novel coronavirus that is believed to have first infected humans late last year and reached global pandemic status last month.

Unlike the viruses we regularly come into contact with, nobody has immunities to COVID-19, meaning we’re all susceptible to it. That sets it apart from strains of the flu, to which parts of the population have varying degrees of immunity.

An estimated 80 percent of COVID-19 cases are mild. But for the other 20 percent of people, the disease can be severe, even deadly, generally because of respiratory complications.

Minnesota does not have enough hospital beds or ventilators to accommodate the number of people who could need care in short order if COVID-19 hit the state’s population en masse.

The model is designed to predict, in general terms, how different policies could change the rate of infection, giving the state more time to respond. It’s limited to estimating things like the spread of the disease and mortality from it; it doesn’t model, say, how different policies would affect the economy.

What are some of the underlying assumptions about COVID-19 in the model?

Any model is only as good as the assumptions it makes: How fast is the virus spreading? How at-risk are different populations? How many resources do we have now, and how will that look in the future?

Here are some of the assumptions about COVID-19 the Minnesota model makes:

• Latent period: 5 days. This is the average amount of time between exposure and when someone has become infected.
• Infectious period: 8 days. Following the latent period, this is how long, on average, someone would be able to transmit the virus to others.
• R0 : Pronounced “R naught,” this number refers to how many others the average person with COVID-19 infects. The Minnesota model predicts an R0 of about 3.87 (That’s an estimate; researchers acknowledge that the real value could likely be from 2.5 to 4.7). That means the average person with COVID-19 infects approximately 3.9 other people. That makes COVID-19 less infectious than measles, which has an R0 between 12 and 18, but more infectious than the flu which has an R0 between 0.9 and 2.1.
• Average days in hospital: 13.3 (But ranging between 7 and 23)
• Average days in ICU: 10.3 (Ranging between 4 and 17)
• Mortality: Is higher for some than others. Depending on age, it’s between 1.5x and 16.5x higher for those who need ICU care and can’t get it. It also increases by 7.6x for people with underlying health factors that heighten the risk of death from COVID-19, such as obesity or COPD.

Here are assumptions about risk of hospitalization and mortality by age:

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Based on the number of people who have died of COVID-19, health officials believe the number of lab-confirmed COVID-19 cases represents about 1 percent of the cases in the state right now. With 1,336 positive cases as of Friday, that means the true number of cases the state has seen is probably more like 134,000.

Given those assumptions, how could different mitigation strategies change how COVID-19 hits in Minnesota? 

The model looks at six different policy scenarios and estimates the time of peak of cases and peak need for ICU beds  (unless noted, the model assumes the state has 2,200 ICU beds including ventilators available for COVID-19 patients) and the number of Minnesotans expected to die throughout the course of the epidemic. (The ranges for these estimates are noted parenthetically.)

Scenario 1: No mitigation (no longer applicable since mitigation started mid-March). Assumes only 235 ICU beds, which was the number available in early March:

• Date of peak cases: May 11, or 7 weeks (5-10 weeks)
• Date of peak ICU need: April 20, or 4 weeks (2-5 weeks)
• Number of beds needed at peak ICU: 3,300 (2,000-4,800)
• Mortality: 50,000 (34,000-68,000)

Scenario 2: Two weeks of stay-at-home (i.e. what was called for in Walz’s original stay-at-home order, which has since been extended) followed by physical distancing similar to what was asked of Minnesotans before the stay-at-home order, lasting until May 1:

• Date of peak cases: June 8, or 11 weeks (9-15 weeks)
• Date of peak ICU need: or June 8, or 11 weeks (8-14 weeks)
• Number of beds needed at peak ICU: 4,500 (3,200-6,000)
• Mortality: 41,000 (22,000-59,000)

Scenario 3: Two weeks of stay-at-home followed by physical distancing until May 1, followed by a requirement that the vulnerable (such as people who are older), stay home until about July 10:

• Date of peak cases:or June 8, or 11 weeks (9-15 weeks)
• Date of peak ICU need: June 8, or 11 weeks (9-15 weeks)
• Number of beds needed at peak ICU: 3,700 (2,700-4,900)
• Mortality: 22,000 (9,000-36,000)

Scenario 3.1: Two weeks of stay-at-home followed by physical distancing until June 12, followed by requirement that the vulnerable stay home until about Aug. 14:

• Date of peak cases: July 6, or 15 weeks (10-20 weeks)
• Date of peak ICU need: June 29, or 14 weeks (9-19 weeks)
• Number of beds needed at peak ICU: 3,300 (2,600-4,000)
• Mortality: 20,000 (9,000-33,000)

Scenario 3.2: Two weeks of stay-at-home followed by physical distancing until May 1, followed by a low form of social distancing, such as requiring businesses to create conditions where people can be spaced apart, until the end of the epidemic, plus a requirement that the vulnerable stay home until about July 31.

• Date of peak cases: June 15, or 12 weeks (9-18 weeks)
• Date of peak ICU need: June 15, or 12 weeks (9-17 weeks)
• Number of beds needed at peak ICU: 3,400 (2,400-4,600)
• Mortality: 22,000 (6,000-35,000)

Scenario 4: Six weeks of stay-at-home (until May 8), physical distancing until June 6, plus stay-at-home for vulnerable populations until approximately Aug. 28. This is the scenario closest to what Gov. Tim Walz ordered, with the extension of the stay-at-home, although it assumes stay-at-home goes on for a few days longer than Walz has ordered it.

• Date of peak cases: July 13, or 16 weeks (13-21 weeks)
• Date of peak ICU need: July 13, or 16 weeks (12-21 weeks)
• Number of beds needed at peak ICU: 3,700 (2,700-4,800)
• Mortality: 22,000 (9,000-36,000)

How is this different from other models?

Minnesota health officials have stressed that the Minnesota model is one of many inputs being used to make decisions about the state’s response to COVID-19. It’s also looking at other states’ responses and other models, such as modeling by health systems in Minnesota, which tend to be more pessimistic than this one.

MDH officials have said they believe the oft-cited University of Washington model, which predicts fewer than 500 deaths for Minnesota, makes unrealistically optimistic assumptions about how well Americans’ success at social distancing and about the accuracy of death data from China.

The University of Washington model also only goes out four months, which means it doesn’t account for peaks MDH officials expect to see past that time period. The Minnesota model follows the course of the epidemic, which could be a year.

“We have to help people understand that this is not a one-time event,” Health Commissioner Jan Malcolm said Friday. “It isn’t you hit the peak and then everything goes back to normal. This is going to be with us in a really challenging way and multiple waves until there are treatments and a vaccine and that is just the hard reality that we also need to factor into this into this planning.”

What else do I need to know?

Pay attention to the ranges of the estimates. Health officials have said over and over that this model is designed to help predict a range of possible outcomes — not exact numbers. They are not designed to tell you that on x day, y people are expected to die.

And the model will change, becoming more refined as more data become available.

“I fully expect that our understanding of the disease will change every week,” said State Health Economist Stefan Gildemeister. “It will change every week, and as we incorporate that new understanding in the data, our data will change.”