Developing the Minnesota COVID model

Governor Tim Walz's stay at home order was based on modeling of what could happen with the coronavirus here in Minnesota.  

Professor Eva Enns of the University of Minnesota School of Public Health was part of the team that developed that mathematical model.

Time was critical.  

“As a modeler who is used to developing a model for years, going to a situation where you are trying to make a decision in days has been a real adjustment in my day to day,” said Professor Enns.  

The work of developing a mathematical model for the spread of infectious disease involves meticulous calculations.  The Minnesota model was based on what has happened in other countries, U.S. cities, and some specific demographic and health care data for Minnesota.  

Working with a multidisciplinary team of five faculty members and three students, with expertise in epidemiology, modeling, computer science, and biology, their calculations were used to inform unprecedented public policy decisions in a quickly moving pandemic.

The pressure was on.  It still is.  

“Someone asked me, ‘Are you working this weekend?’  There is no weekend,” she said. 

The calculations if Minnesota failed to take any social mitigation efforts were dire.  The model predicted 74,000 people could die, and more than 2.4 million could be infected by the time the pandemic peaked around May 24, although many of those infected would have only mild symptoms.    

The model predicted hospitals would reach capacity three weeks before the pandemic peaked, and there would be no available ICU beds, or ventilators to help people breathe. Health officials have said ICU care makes it 10 times more likely the most critically ill will survive.  

She also helped develop a second scenario predicting that social mitigation efforts, including a two week ‘Stay At Home’ order, would shift the peak of the pandemic back five weeks, to around June 28.  It would also shift the peak ICU capacity to June 7.

Governor Walz has declined to say how many might still die even with social mitigation efforts. Professor Enns would not give a figure, either.  

“In terms of mortality, we’re not predicting it,” said Prof. Enns.  “Just the curve and how it moves, and how much ICU capacity it’s possible to build over this period of time.”

The model predicts that 15 percent of those who are infected will require hospitalization, and 5 percent of those hospitalized would require ICU care.  

The model also assumes an incubation period of five days and an average infectious period of eight days. 

The model assumes an average reproduction rate of 2.5 (R0=2.5) without any mitigation efforts, meaning on average one infected person would infect two-and-a-half other people.  That number drops with mitigation efforts (R0=2).

There are factors that might help Minnesotans in a pandemic, including that much of the state, and even our cities, have a lower population density.  The metropolitan area also has above average access to health care.  

Professor Enns anticipates more busy weeks to come as they continue to add Minnesota specific data to the model and calculate the impact of social mitigation efforts.  

“That’s a function of the urgency of getting some information as we refine the model,” she said.

“It’s also a function that my three year old is home. And the reality is we are all living now with social distancing.  That has been quite the experience.”