A View on technology and controls for epidemic preparedness and the growth of COVID-19 disease in Saudi Arabia

Abeer Mahmoud Mohammad, Halah Ahmad Abd Almeneem, Wafa Mohammed Asiri, Ishraga Abdullah Sulieman Mohamed


This work emphasizes that the best chance of ending the pandemic lies in the Measures that can help us respond to these epidemic threats more effectively than before in the scope of protection from epidemic risks that we were not aware of before the outbreak of the disease, which is to benefit from the study of previous experiences. The work show the importance of technology about how to prepare for and handle any pandemic by discussing a successful case from the past. We examine Saudi Arabia's COVID-19 pandemic response experiences. We proposed a case evolution study from the southern region of Jazan to demonstrate the consequences of these techniques. Data on the daily Jazan COVID-19 infection curve collected from July 1st  to September 30th, 2020, was processed using multiple Python software modules, such as encoder-decoder LSTM, 1D-CNN, and Complex network analysis of time series to identify changes within the infection curve's structure. A Gaussian modeling study was performed to compare the data movement with the protection from epidemic risks computed by stratification based on the data group.The network analysis shows that hubs are stable while medium and low-degree nodes are unstable. Also, from the perspective of Gaussian modeling, the COVID-19 infection curve parts indicate that the pandemic in Saudi Arabia is about to peak and move into the second (declining) half of the bell-shaped distribution.Technology in many areas and internet access make Saudi Arabia's social separation strategies a pandemic-eradication success story

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DOI: https://doi.org/10.33865/wjb.009.02.1283


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Copyright (c) 2024 Abeer Mahmoud Mohammad, Halah Ahmad Abd Almeneem, Wafa Mohammed Asiri, Ishraga Abdullah Sulieman Mohamed Mail

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This work is licensed under a Creative Commons Attribution 4.0 International License.

Print ISSN: 2522-6746 : Online ISSN: 2522-6754
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