University of Tennessee at Chattanooga Department of Mathematics Assistant Professor Dr. Xiunan Wang has gained international recognition for her work in mathematical modeling to forecast the spread of infectious diseases.¶
According to a university news release, Wang’s mathematical biology research was recently highlighted in an article by the Society for Industrial and Applied Mathematics (SIAM), one of the three major U.S. math organizations with international memberships. The announcement said Wang served as lead author for a recent paper published in the SIAM Journal on Applied Mathematics, where she proposed a novel method for estimating the transmission rates of infectious diseases.¶
“Her research is getting a good deal of press coverage, including outlets like the CBC in Canada and BioSpace in the United States,” Dr. Chris Cox, head of the UTC Department of Mathematics, said. “To get an article published in one of the SIAM journals is a big deal.”¶
Wang said in the news release that she developed her passion for applied mathematics during her undergraduate studies at Southwest University in Chongqing, China, where she earned a bachelor’s degree in mathematics and applied mathematics and a master’s degree in applied mathematics.¶
“In my second year, I attended a mathematical modeling contest and won a prize,” she said in the news release. “I collaborated with a team of my classmates and found it very interesting.”¶
From there, Wang traveled to Canada to continue her education and received her Ph.D. in applied mathematics from Memorial University of Newfoundland in 2017. She then spent one year as a postdoctoral researcher at the University of Western Ontario before beginning her postdoc fellowship at the University of Alberta in September 2018.¶
“At the University of Alberta, I broadened my research area, including not only epidemiology but also ecology because there are some deeper connections between epidemiology and ecology,” she said.¶
Her research took on new importance in 2020 with the onset of the COVID-19 pandemic, when her team developed the “discrete inverse method” to estimate the daily number of infections.¶
“We had an urgent need to forecast how many people are infected each day in the United States or Canada,” she said. “We developed a hybrid method combining the strengths of differential equations and machine learning to forecast how many people were infected each day.”¶
According to the news release, Wang collaborated with University of Alberta Professor Hao Wang, the Canada Research Chair in Mathematical Biosciences and director of the Interdisciplinary Lab for Mathematical Ecology and Epidemiology. They applied the method to forecast transmission rates of various infectious diseases, including COVID-19, influenza, and measles.¶
“Usually the data on the website, given by the CDC or some health department, is about how many people are infected each day, but they never tell the value of the transmission rates,” Wang said. “The value of transmission rates are not observable and cannot be recorded—and that is where we, as mathematicians, can help.”¶
Cox said Wang quickly made her mark since arriving on campus in 2021. ¶
“Her contributions have been recognized both locally and internationally and she has published 24 peer-reviewed papers,” Cox said in a public statement. “To have 24 papers published in refereed journals … referee journals have very high standards. For many faculty, that’s a lifetime of work.”¶
