University of Alberta professor says the data could help public health officials prepare
Oct 10, 2024
A team of Canadian and American researchers says their method of forecasting the rate of transmission of infectious diseases is predicting an earlier spike in influenza cases this year.
Using mathematics and machine learning, the researchers analyzed data from late 2015 to September 2024, incorporating weather conditions, policy choices and movement patterns (drawn from cell phones) to predict how diseases like influenza and COVID-19 might spread.
The team expects there will be more than 1,600 new flu cases confirmed each day in U.S. laboratories by the end of November, nearly double the number of cases during the same time period last year.
“For the prediction in this report, we applied U.S. data, but I think we would state that if we used Canadian data, similar conclusions would be drawn,” said Hao Wang, director of the Interdisciplinary Lab for Mathematical Ecology and Epidemiology at the University of Alberta.
Read more: https://www.cbc.ca/news/canada/edmonton/math-machine-learning-influenza-alberta-1.7347963