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 on Thursday 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 (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.
