Application of artificial neural networks to predict the COVID-19 outbreak
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(2020) 5:50
Global Health Research and Policy
METHODOLOGY
Open Access
Application of artificial neural networks to predict the COVID-19 outbreak Hamid Reza Niazkar1
and Majid Niazkar2*
Abstract Background: Millions of people have been infected worldwide in the COVID-19 pandemic. In this study, we aim to propose fourteen prediction models based on artificial neural networks (ANN) to predict the COVID-19 outbreak for policy makers. Methods: The ANN-based models were utilized to estimate the confirmed cases of COVID-19 in China, Japan, Singapore, Iran, Italy, South Africa and United States of America. These models exploit historical records of confirmed cases, while their main difference is the number of days that they assume to have impact on the estimation process. The COVID-19 data were divided into a train part and a test part. The former was used to train the ANN models, while the latter was utilized to compare the purposes. The data analysis shows not only significant fluctuations in the daily confirmed cases but also different ranges of total confirmed cases observed in the time interval considered. Results: Based on the obtained results, the ANN-based model that takes into account the previous 14 days outperforms the other ones. This comparison reveals the importance of considering the maximum incubation period in predicting the COVID-19 outbreak. Comparing the ranges of determination coefficients indicates that the estimated results for Italy are the best one. Moreover, the predicted results for Iran achieved the ranges of [0.09, 0.15] and [0.21, 0.36] for the mean absolute relative errors and normalized root mean square errors, respectively, which were the best ranges obtained for these criteria among different countries. Conclusion: Based on the achieved results, the ANN-based model that takes into account the previous fourteen days for prediction is suggested to predict daily confirmed cases, particularly in countries that have experienced the first peak of the COVID-19 outbreak. This study has not only proved the applicability of ANN-based model for prediction of the COVID-19 outbreak, but also showed that considering incubation period of SARS-COV-2 in prediction models may generate more accurate estimations. Keywords: COVID-19 outbreak, SARS-COV-2, Prediction model, Artificial neural network, Artificial intelligence, Estimation model
Introduction The novel coronavirus (COVID-19 or SARS-COV-2) epidemic has involved into a global pandemic. More than 17 million individuals have been infected globally, yielding to more than 667,000 death cases from 20 January to 30 July 2020 [1–3]. Rapid human-to-human transmission accompanied by unrevealed nature of the virus has led to a * Correspondence: [email protected] 2 Department of Civil and Environmental Engineering, Shiraz University, Shiraz, Iran Full list of author information is available at the end of the article
tremendous outbreak. To defeat the COVID-19 outbreak, appropriate and evidence-based actions must be taken worldwide. For this purpose,
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