Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine

Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine

DR. Mohammad Abu Omar

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Dr. Imad Abed Elateef Ishtayyah

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Dr. Osama Amin Marie

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Al-Quds Open University

Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine

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Abstract

In the light of the COVID-19 virus pandemic that has attacked the earth planet, all nations in the world are becoming suffered more and more from the increasing number of infected cases. The medical infrastructure in most countries aren’t fit to deal with such pandemic, hospitals in these countries are unable to accommodate a such number of the infected cases that have recently been recorded [1], [5]. This pandemic has put countries in a great predicament; they never expected to face a pandemic of this size [1], [5]. Palestine is one of these pandemic victims, COVID-19 virus has started spreading in Palestine on fifth March of 2020 [4]. Palestinian government and leadership have announced immediately by its Prime Minister Dr Mohammad Shtayyeh the case of emergency in Palestine to prevent this dangerous pandemic from spreading, by closing all schools and universities, crowding prevention, limiting motion and asking people strongly for home-stay [1], [2], [4].

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

DR. Mohammad Abu Omar. 2020. \u201cPalestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine\u201d. Global Journal of Computer Science and Technology - G: Interdisciplinary GJCST-G Volume 20 (GJCST Volume 20 Issue G3).

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GJCST Volume 20 Issue G3

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Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-G Classification D.4.8

Submission ReceivedDecember 7, 2019
Peer Review Double Blind
Handling Editor
Accepted January 2, 2020
Published January 15, 2020

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v1.2

Issue date

April 27, 2020

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