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The COVID-19 pandemic has made clear the importance of understanding precisely how diseases spread throughout networks of transportation. However, rigorously determining the connection between disease risk and changing networks — which either humans or the environment may alter — is challenging due to the complexity of these systems. In a paper publishing today (Thursday, June 10, 2021) in the SIAM Journal on Applied Mathematics, Stephen Kirkland (University of Manitoba), Zhisheng Shuai (University of Central Florida), P. van den Driessche (University of Victoria), and Xueying Wang, associate professor of mathematics (Washington State University) study the way in which changes in a network of multiple interconnected communities impact the ensuing spread of disease. The four researchers were hosted as a Structured Quartet Research Ensemble by the American Institute of Mathematics.

The authors utilized their results to explore possible strategies for controlling disease outbreaks by introducing new connections on a network or changing the strength of existing connections. “Our findings from both the star and the path networks highlight that the placement of the hot spot and the connections among patches are crucial in determining the optimal strategy for reducing the risk of an infection,” Wang said. The researchers’ techniques quantified the effectiveness of different approaches in controlling invasibility and found the mathematical conditions under which it is best to change the amount of movement between certain locations.

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