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Forecasting COVID-19 Infections in Gulf Cooperation Council (GCC) Countries using Machine Learning

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arxiv 2303.07600 v1 pith:JMKBRMQC submitted 2023-03-14 cs.LG cs.AIcs.CY

Leila Ismail , Huned Materwala , Alain Hennebelle This is my paper · ORCID
classification cs.LGcs.AIcs.CY
keywords covid-19modelscountriesinfectionscooperationcouncildatasetdeveloped
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COVID-19 has infected more than 68 million people worldwide since it was first detected about a year ago. Machine learning time series models have been implemented to forecast COVID-19 infections. In this paper, we develop time series models for the Gulf Cooperation Council (GCC) countries using the public COVID-19 dataset from Johns Hopkins. The dataset set includes the one-year cumulative COVID-19 cases between 22/01/2020 to 22/01/2021. We developed different models for the countries under study based on the spatial distribution of the infection data. Our experimental results show that the developed models can forecast COVID-19 infections with high precision.

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