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\title{Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine}
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             \author[1]{DR. Mohammad Abu  Omar}

             \author[2]{Dr. Imad Abed Elateef  Ishtayyah}

             \author[3]{Dr. Osama Amin  Marie}

             \affil[1]{  Al- Quds Open University.}

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\date{\small \em Received: 7 December 2019 Accepted: 2 January 2020 Published: 15 January 2020}

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\begin{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].

\end{abstract}


\keywords{COVID-19 pandemic, palestine radar model, PRM, linear prediction, forecast function}

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\let\tabcellsep& 	 	 		 \par
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],  {\ref [5]}. This pandemic has put countries in a great predicament; they never expected to face a pandemic of this size By applying the previous actions and decisions from the Palestine government and leadership, the safety of people and society will be increased as far as the more commitment and discipline from them.  
\section[{Study Methodology}]{Study Methodology}\par
This study is theoretical and experimental research; it uses the linear prediction technique in the Microsoft Office Excel program by using the (Forecast Function) that is included in the statistical category of Microsoft Office Excel program library \hyperref[b3]{[9]}, \hyperref[b5]{[11]}. In the Microsoft Office Excel Program, there are two familiar methods to implement the linear prediction, which are \hyperref[b3]{[9]}, \hyperref[b5]{[11]}, \hyperref[b6]{[12]}: a) Using the (Forecast) statistical function\par
Here, the linear prediction will be implemented directly. Since the (Forecast) statistical function is readily available in the Microsoft Office Excel program library. It can be used directly when all historical data are enough and ready. 
\section[{b) Using the regression line equation}]{b) Using the regression line equation}\par
Here, the linear prediction will be implemented after finding the regression line equation, which is:Y = a. X + b ??????? eqn (1)\par
Where:\par
Y: The dependent variable. a: Regression coefficient.\par
X: The independent variable. b: The constant parameter.\par
So, the implementing of the linear predication in this method requires the following procedure: Firstly, the finding of both parameters: the regression coefficient (a) and the constant (b) as follows:\par
statistical category of Microsoft Office Excel program library.\par
Secondly, writing the previous regression line equation.\par
Thirdly, divide all historical data to be either independent variables or dependent variables and determine them. Now, the prediction of the (Y) value can be obtained when the corresponding(X) value is entered.\par
This study uses the forecast statistical function method to implement the linear prediction, which will increase the efficiency of the study model, since it will save time and effort in using this model, by avoiding the use of regression line equation in the Microsoft Office Excel program which requires more time and effort due to its long procedure.\par
IV. 
\section[{How Does the Model Work?}]{How Does the Model Work?}\par
The Palestine Radar Model (PRM) uses the linear predication by using the (Forecast Function) that is categorized under Excel statistical functions. The regression coefficient (a) can be obtained directly by using (Slope Function) that is included in the statistical category of Microsoft Office Excel program library. Also, the constant (b) can be obtained directly by using (Intercept Function) that is included in the V. 
\section[{Results Accuracy}]{Results Accuracy}\par
The accuracy of the model results which are the expected numbers of the infected cases of COVID-19 virus in Palestine for the coming dates depends on the accuracy of input data of the model.\par
The input data of the model which are the historical numbers of the infected cases from the beginning of the (5 th March 2020) to the end of (31 th March 2020) and their corresponding dates are being recorded accurately according to the daily reports of the Palestine Ministry of Health  {\ref [4]}.\par
So, this study expects accurate results with a surely normal percentage of error which comes from prediction.\par
VI. 
\section[{Designing the Model}]{Designing the Model}\par
The Palestine Radar Model (PRM) is designed by using Microsoft Office Excel Program. The model includes two main sections, as follows:\par
The first section is the (Input Section) which includes the following parameters: a) The historical dates from the beginning of the (5 th March 2020) to the end of (31 th March 2020). b) The corresponding sequential numbers of the previous dates. c) The historical numbers of the infected cases from the beginning of the (5 th March 2020) to the end of (31 th March 2020).   Now, for the dates that the model looking to predict for them, the entered data of the Forecast function will be as follows: VIII. 
\section[{The following figure shows the input section of the model design [1], [2], [4]:}]{The following figure shows the input section of the model design [1], [2], [4]:} 
\section[{The Results}]{The Results}\par
After running the model, the results that are related to the expected numbers of the infected cases of COVID-19 virus in Palestine are as follows:  
\section[{Results Analysis}]{Results Analysis}\par
According to the model results which are shown in the previous figure (5), there is a negative side and also a positive side, as follows: 
\section[{a) The Negative Side of the Results}]{a) The Negative Side of the Results}\par
As it is shown to the results in the figure (5), there is an increase for the expected numbers of the infected cases of COVID-19 virus in Palestine during the coming April. The expected number of the infected cases of COVID-19 virus in Palestine till to the end of 30 th April 2020 is expected to reach to (216) infected case. 
\section[{b) The Positive Side of the Results}]{b) The Positive Side of the Results}\par
As it is shown in whole study, from the beginning of 5 th March 2020 to the end of 30 th April 2020, there is a decrease for the (Growth Rate) of spreading the COVID-19 virus in Palestine by more than (15\%) .  And this means that the Growth Rate of spreading COVID-19 virus in Palestine for the coming (4) weeks will decrease by more than (15\%). 
\section[{X. Conclusion and Recommendations a) Conclusion}]{X. Conclusion and Recommendations a) Conclusion}\par
Palestine Radar Model (RPM) predicts the spreading of COVID-19 virus in Palestine for the coming April 2020 that is ended in the following dates respectively:\par
(4/4/2020, 12/4/2020, 19/4/2020, 30/4/2020), with two contradictory results as follows:\par
The bad results: there is an increase in the expected numbers of the infected cases of COVID-19 virus in Palestine during the coming April 2020. The expected number of the infected cases of COVID-19 virus in Palestine till to the end of 30 th April 2020 is expected to reach to (216) infected case.\par
The good results: there is a decrease for the (Growth Rate) of spreading the COVID-19 virus in Palestine by more than (15\%) till to the end of 30th April 2020. The study refers that for the awesome emergency case that the Palestinian government and leadership have applied on Palestine, which adopts the preventing strategy before treatment strategy, by applying the theory of social spacing through closing the schools and universities, limiting motion, asking people strongly for home-stay, Isolating the cities and towns, stopping the tourism activities, and closing the borders. In addition to the ongoing awareness activities for people and society about COVID-19 virus through the various media and also and the social media. 
\section[{b) Recommendations}]{b) Recommendations}\par
This study presents the following recommendations for Palestinian government and leadership and also for the society and people:\par
-The study strongly asks from the Palestinian government and leadership to continue in applying the case of emergency in Palestine for the coming April 2020. -Ensuring from the ready of Palestine medical infrastructure to deal with the expected numbers of infected cases that this study predicts for the coming April 2020, especially, that the expected number of infected cases that is predicted by the study model is: (216) infected cases. -Activate and develop more awareness activities about preventing COVID-19 virus for society and people from the specialized sides of the government, especially after the success of the emergency case that has launched by Palestine government which may reduce the growth rate of spreading the COVID-19 virus by more than (15\%) according to the results of this study, and which means the receding of the virus instead of the spreading it more. -The development of the emergency case to be stronger is better. -Asking society and people for more commitment towards Palestine leadership instructions and advises.\par
-Asking God to Save our Home-\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}Palestine}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-3.png}
\caption{\label{fig_1}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-4.png}
\caption{\label{fig_3}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-5.png}
\caption{\label{fig_4}Figure 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{3}\includegraphics[]{image-6.png}
\caption{\label{fig_5}Figure 3 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{4}\includegraphics[]{image-7.png}
\caption{\label{fig_6}Figure 4 :}\end{figure}
    \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{P{0.38026315789473686\textwidth}P{0.06710526315789474\textwidth}P{0.2013157894736842\textwidth}P{0.2013157894736842\textwidth}}
Dates to Predict\tabcellsep X\tabcellsep Y's\tabcellsep X's\\
4/4/2020\tabcellsep 31\tabcellsep C4:C30\tabcellsep B4:B30\\
12/4/2020\tabcellsep 39\tabcellsep C4:C30\tabcellsep B4:B30\\
19/4/2020\tabcellsep 46\tabcellsep C4:C30\tabcellsep B4:B30\\
30/4/2020\tabcellsep 57\tabcellsep C4:C30\tabcellsep B4:B30\end{longtable} \par
 
\caption{\label{tab_0}Table 1 :}\end{figure}
 			\footnote{© 2020 Global Journals Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine} 			\footnote{© 2020 Global Journals} 			\footnote{Palestine Radar Model (PRM) for Predicting the Number of Infected Cases of COVID-19 Virus in Palestine} 		 		\backmatter  			  				\begin{bibitemlist}{1}
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\bibitem[Omar ()]{b4}\label{b4} 	 		‘A New Approach to Increase the Efficiency of Classical Approach In Designing Management Information Systems (MIS'S)’.  		 			M M Omar 		.  	 	 		\textit{IJRCCT}  		2014. 3 p. .  	 
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\bibitem[Omar and Abdullah ()]{b7}\label{b7} 	 		‘Developing a New Integrated Model to improve the using of Classical Approach in Designing Management Information Systems’.  		 			M M A Omar 		,  		 			K A Abdullah 		.  	 	 		\textit{International Journal of Advanced Computer Science \& Applications}  		2015. 1 p. .  	 
\bibitem[Omar ()]{b5}\label{b5} 	 		‘Developing New Methods in designing Management Information Systems to solve Management Problems by using Classical Approach’.  		 			M M Omar 		.  	 	 		\textit{International Journal of Computer Applications}  		2014. 101.  	 
\bibitem[Omar and Abdullah ()]{b6}\label{b6} 	 		‘Testing the Use of the Integrated Model in Designing the Management Information Systems by Using the Mathematical Probability Theories’.  		 			M M A Omar 		,  		 			K A Abdullah 		.  	 	 		\textit{International Journal of Advanced Computer Science \& Applications}  		2015. 1 p. .  	 
\bibitem[Stuerzlinger et al. ()]{b9}\label{b9} 	 		\textit{The design and realization of CoViD: A system for collaborative virtual 3D design. Virtual Reality},  		 			Wolfgang \& Stuerzlinger 		,  		 			Zaman 		,  		 			\& Loutfouz 		,  		 			Pavlovych 		,  		 			\& Andriy 		,  		 			Ji-Young Oh 		.  		 \xref{http://dx.doi.org/147.10.1007/s10055-006-0048-0}{147.10.1007/s10055-006-0048-0}.  		2006. 10.  	 
\bibitem[Omar and Abdullah ()]{b8}\label{b8} 	 		‘USING OF NET PRESENT VALUE (NPV) TO TEST THE INTEGRATED MODEL IN BUILDING MANAGEMENT INFORMATION SYSTEMS’.  		 			M M A Omar 		,  		 			K A Abdullah 		.  	 	 		\textit{Journal of Economics Finance and Accounting}  		2016. 3.  	 
\end{bibitemlist}
 			 		 	 
\end{document}
