An AI deep learning model to predict the number of COVID-19 cases 14 days into the future.
By Hugo Francisco de SouzaOct 24 2023Reviewed by Lily Ramsey, LLM In a recent study published in Scientific Reports, researchers developed and trained an artificial intelligence deep learning model to predict the number of COVID-19 cases 14 days into the future.
Deep learning models such as this may help safeguard us from future pandemics by providing policymakers with the best information to utilize their available resources. Additionally, reproduction number computations, the estimate of cases stemming from a single infected individual, were used to improve these epidemiological models' predictive power and accuracy.
About the study The present study borrows from the US Centers for Disease Control and Prevention's ensembled forecasting method, which operates on the belief that mortality and prevalence of a pandemic subsides after 30 days of containment policy implementation. The preliminary LSTM model was feature-engineered to use the preceding 30 days of data as sequential inputs and a single prediction 14 days into the future as an output. Modeling was carried out individually for the 190 countries in training and validation.
The statistical evaluation metrics used included Root Mean Square Error , Mean Absolute Percentage Error , Mean Absolute Error , and total absolute percentage error. The BiLSTM algorithm additionally has the potential for further improvements to its predictive power by incorporating additional variables over the preexisting 24 and supplementary prevalence training data.
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