A new type of machine learning model has been developed to predict the spread of disease in short-term epidemics. The model was developed by a team of researchers led by Dr. Sebastian Kappler from the University of Cambridge and is the first of its kind. The model is designed to provide rapid predictions of the speed and spread of an epidemic in a matter of days, rather than the weeks or months it usually takes for public health agencies to assess the situation. By using data from past epidemics, the model can quickly identify which areas are most at risk and help health authorities to take swift action to contain the spread of the disease.

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source: Phys.org