COVID-19 Outbreak Prediction with Machine Learning

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.3390/a13100249. This is version 1 of this Preprint.

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Authors

Sina Faizollahzadeh Ardabili, Amir Mosavi, Pedram Ghamisi, Filip Ferdinand, Annamaria R. Varkonyi-Koczy, Uwe Reuter, Timon Rabczuk, Peter M. Atkinson

Abstract

Several outbreak prediction models for COVID-19 are being used by officials around the world to make informed-decisions and enforce relevant control measures. Among the standard models for COVID-19 global pandemic prediction, simple epidemiological and statistical models have received more attention by authorities, and they are popular in the media. Due to a high level of uncertainty and lack of essential data, standard models have shown low accuracy for long-term prediction. Although the literature includes several attempts to address this issue, the essential generalization and robustness abilities of existing models needs to be improved. This paper presents a comparative analysis of machine learning and soft computing models to predict the COVID-19 outbreak as an alternative to SIR and SEIR models. Among a wide range of machine learning models investigated, two models showed promising results (i.e., multi-layered perceptron, MLP, and adaptive network-based fuzzy inference system, ANFIS). Based on the results reported here, and due to the highly complex nature of the COVID-19 outbreak and variation in its behavior from nation-to-nation, this study suggests machine learning as an effective tool to model the outbreak. This paper provides an initial benchmarking to demonstrate the potential of machine learning for future research. Paper further suggests that real novelty in outbreak prediction can be realized through integrating machine learning and SEIR models.

DOI

https://doi.org/10.32942/osf.io/xq8rb

Subjects

Computational Engineering, Diseases, Engineering, Health Information Technology, Medicine and Health Sciences, Other Medicine and Health Sciences, Public Health

Keywords

coronavirus, COVID-19, Deep learning, disease, Huge data, machine learning, model, prediction, Time-series, Time series data

Dates

Published: 2020-10-10 07:34

License

CC-By Attribution-ShareAlike 4.0 International

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