Machine Learning Models Predict COVID-19 Impact in Smaller Cities

According to a robust machine learning model that can predict pandemic impact even in smaller cities, with 75% of the population in the Capital Region in New York remaining at home, the COVID-19 pandemic will peak locally in the second half of May. If the rate of people staying home drops to 50%, it will peak in early June. Rensselaer Polytechnic Institute researcher Malik Magdon-Ismail tailored the models he is developing to work with sparse data points, like those available during the early phase in a pandemic or in smaller cities, which ordinarily make trend-spotting difficult. "There are no simple, robust, general tools that, for example, officials in Albany could use to make projections," said Magdon-Ismail, a professor of computer science, and expert in machine learning, data mining, and pattern recognition. "These models show that the projections vary enormously from one city to another. This knowledge could relieve some of the uncertainty that is around in developing policy."