A mathematical model developed by researchers at the University of Michigan is helping public health officials battle COVID-19 by providing important insights on how various levels of lockdown affect both the economy and the mortality rate of the virus.
April Nellis, a doctoral candidate in the U-M Department of Mathematics, worked on the research team developing the model. She explains that they wanted to capture how best to “resolve the tension between wanting a high level of lockdown to slow the spread of COVID-19 and the lower level of lockdown to maintain economic activity.”
The model includes two levels of lockdown—lockdowns for those ages 65 and older and those who are ages 20 to 64—and their impact on the economy. It also includes several other factors, including rate of ICU admittance, interaction level between groups, and base mortality rate of COVID-19.
Nellis describes how varying levels of lockdown for different groups can protect high-risk individuals while allowing those identified as low-risk to resume or continue working.
“Overall, there are a lot of insights that can be gained from using these mathematical tools, to model the spread of COVID-19, and the effects of the pandemic, as well as using these tools to investigate things like optimal lockdown strategies,” Nellis says.
Learn more in this episode of Michigan Minds.
