Nova Scotia COVID-19 Health

This research aimed to develop machine learning models to predict daily COVID-19 cases using weather and mobility data and classify whether the next day would have more or fewer cases than the previous day. Due to data unavailability from Nova Scotia, the study utilized a larger dataset from 50 Ontario counties. Various machine learning techniques, including Inductive Decision Trees (IDTs), Convolutional Neural Networks (CNNs), and Long Short-Term Memory Recurrent Neural Networks (LSTMs), were employed. The models showed varying degrees of accuracy in predicting daily case counts and 7-day averages, with LSTMs demonstrating superior performance.

Daniel L Silver, Rinda Digamarthi