Leveraging Network Science to Help Decision Makers and the Public Understand the Effects of Implementation and Relaxation of Social Distancing Measures on COVID-19 Viral Spread


illustration of distanced marks forming X pattern

Meggan Craft, PhD, associate professor in the Department of Veterinary Population Medicine, and Eva Enns, PhD, associate professor in the Division of Health Policy and Management, will lead the development of an individual-level network model to help decision makers address the following problem: how can we relax household isolation in a way that minimizes a rebound in transmission and consequent deaths?

The team will work with decision makers and leverage insights from network science to develop clear visualizations of different social distancing scenarios that illustrate the household-to-household interactions that decrease the rate of COVID-19 spread. Modeling contact networks at the individual level provides decision makers with a succinct example that makes planning for the extrapolated, widespread phenomenon easier to understand.

This approach can also help equip decision makers with the language and context they need to make informed recommendations to their constituencies as social distancing measures begin to loosen in the months to come.
“We will not only provide science-based guidance to decision makers, but our interactive visualizations can also assist decision makers in communicating the ‘why’ to the public,” said Craft.

The goal is to develop a network model to simulate the spread of COVID-19 virus through communities and to test the effectiveness of relaxing social distancing control strategies under different scenarios. University of Minnesota researchers Matt Michalska-Smith, PhD, and Marie Gilbertson, DVM, along with Lauren White, PhD, from the National Socio-Environmental Synthesis Center, will help to create the models. Results from this project will provide guidance to decision makers regarding the timing, implementation, and communication of reducing social distancing measures.

This project is supported by the UMN Campus Public Health Officer's CO:VID (Collaborative Outcomes: Visionary Innovation & Discovery) grants program, which support University of Minnesota faculty to catalyze and energize small-scale research projects designed to address and mitigate the COVID-19 virus and its associated risks.