Optimistic Prediction Model For the COVID-19 Coronavirus Pandemic based on the Reported Data Analysis

The world is facing new challenges every day; however, with the spread of the pandemic around the world, this new challenge is different. The pandemic is increasing and concentrating various challenges simultaneously. Although different sectors are facing consequences, the most important sectors, that is, health and economy are the most affected. When the pandemic began, it was not known how long it would last, which complicated health and economic planning. Therefore, it is important for decision makers and the public to know the predictions and expectations of the future of these challenges. In this work, the current situation is analyzed. Then, an expectation model is developed based on the statistics of the pandemic using a growth rate model based on an exponential and logarithmic rate of increase. Based on the available open data about the pandemic spread, the model can successfully predict future expectations, including the duration and maximum number of cases of the pandemic. The model uses the equilibrium point as the day the cases decrease. The model can be used for planning and the development of strategies to overcome these challenges.


Introduction
In different times in history, humanity has faced great health challenges that affect life in general. Different pandemics have spread around the world in history, such as smallpox, the Spanish flu,tuberculosis and plague [1] [2][3] [4] [5] [6]. The effects of pandemics on the health sector are a major challenge that, consequently, affect economy and social life. Humans have daily activities that change substantially during a pandemic. 5 The daily life tasks are thus done with caution until the pandemic ends. However, that can only be done when it is known when the pandemic will end. At that time, people will be able to return to normal daily activities. However, it is convenient to predict the time when life will return to normal. In late 2019, the corona virus, named COVID-19, spread around the world. All aspects of life have suddenly become difficult.
Travel between countries have suddenly stopped. Governments around the world are experiencing challenges 10 in providing the daily requirements of food and other consumed goods. Also, governments are having difficulty in stabilizing the economy by paying part of the salaries of employees of the private sector. Some travelers with transit flight are stuck living in an airport because the country they are flying through requires a visa and their continuing flight was canceled. Some people have gone to grocery stores and been unable to obtain required food. 15 Therefore, planning for the requirements of people in such circumstances is very important. The pandemic requires an expectation model to plan trade and travel activity to decrease the amount of challenges people are facing. Moreover, governments and private sectors require an expectation model to determine the actions that must be taken. For example, a factory needs to know how long it is expected that the factory must work in pandemic conditions. Also, a medicine company will need to predict the production level required 20 for a specific medicine. Coronavirus statistics are gathered from around the world and announced publicity.
The world, for the first time, is collecting the data daily, which is helping the world to work together to face the pandemic [7] [8] [9]. The power of open data has been demonstrated during this pandemic [10]. This work obtains the daily statistics and develops a prediction model of the COVID-19 pandemic. Then, the predictions can be used by decision makers to follow and develop plans to address the pandemic. An example 25 trajectory of cases based on daily records of an example territory is shown in figure 1. The green line is the actual current cases, and potential future cases are shown in red. The figure shows different numbers of cases over time with different increase ratios. Also, the figure shows different maximum numbers of cases. Each expected scenario has a different peak number of cases and a different time to reach that peak. Therefore, a model is required to measure the expected peak and the number of days to reach that peak. In this work, 30 based on the actual statistics of each country, a model is developed to predict the number of cases any country will have and the number of days to reach that number.

COVID-19 and Open Data
Different organizations around the world are reporting daily or even instant data about COVID-19. The statistics of coronavirus gathered from around the world are announced publicity. The world for the first 35 time is collecting data daily, which is helping the world to work together to face the pandemic [7] Open data is one of the initiatives of the world wide web consortium. Open data is the publication of data from different sectors, governments or private firms that is made public for general use, which increases the services provided [10].

Proposed model
In this work, a model is developed using the open data published about COVID-19. After retrieving 50 the data, the data is subject to computational processing. For this reason, the data are available in a format available for direct processing [12]. The main source file is in MS XLSX format. Java is used to process the data. Different packages are available with Java to process data [13] [14]. The data are then transformed to a text file, where the data can be processed to obtain plots using the PDF-LATEX engine.
Other methods are possible depending on the requirements. In the collected data, the currently known 55 information about the cases in any country is the number of daily cases and reporting day. Also, the number of death cases is reported, as well as number of recovery cases. From this information, the developed model can predict the situation of the cases in a country and the expected day a steady situation will occur, given the assumption that the cases have started to decrease based on the recovery ratios reported from around the world. Consequently, a mathematical prediction model is presented to predict the short-range and long-range 60 scenarios of the COVID-19 coronavirus pandemic. Then, the predicted data are saved in a text file, where the data can be processed again using the same methods. The model is used to generate a visualization of the data in text format, where the data can then be processed and presented in any required format. The model is developed using a logistic function as a process that starts with an exponential growth followed The situation of the pandemic is either stable, increasing, highly increasing, decreasing or highly decreasing. Data: [12] Result: The COVID-19 prediction data of a country initialization; obtain the list of reported data. the sample is the last sampleSize of the data in the list.    For COVID-19 around the world, the total number of cases is decreasing, with a mean of 79314.57 daily reported cases. The first case was reported on 31-12-2019. Figure ?? shows the trajectory of cases and the expectation of when the maximum number of cases will be reach. The expectation is that the total number of cases will reach 6000000 approximately 250 days after the first case was reported. However, the pandemic will continue for as long as 400 days according to the model. Figure 9 shows the daily reported cases from 95 around the world. The figure shows that the range of daily cases is between 60000 and 100000. Figure 7 shows the plots of all countries from around the world. The blue line shows the reported data.

Results and analysis
Each country has a different reporting date since the pandemic expected reached countries on different dates.
The red line shows the growth in expected cases. Figure 5 shows the maximum and mean number of cases reported per day in increasing order. Figure 6 shows the expected steady day of each country. The model parameters, the model can predict the growth rate of cases. For example, for a country where the expected number of cases will reach 50000 and the steady day midpoint is 100, the trajectory is shown in figure 10. Figure 12 shows the initial dates that countries first reported cases. Most countries reported their first case between 29-2-2020 and 9-4-2020, approximately three month after the pandemic started. Figure 13 shows the 105 percentage of countries with decreasing or increasing numbers of cases according to the reported statistics. ·10 4 x f (x)

Recommendations
This research recommends using the expectation in planning associated with the pandemic. The model 110 can be used to predict the expected number of cases and in how many days the maximum will be reached.
The model can also be used to predict the maximum and minimum numbers of cases and in how many days those numbers will be reached. processed and analyzed to show the percentage of countries with decreasing or increasing numbers of cases.
Additionally, the mean, variance, covariance and correlation of the data are used to illustrate the pandemic scenario in different countries. Then, the data are used to predict the future state. The data have shown that the growth rate scenario is the best mathematical model to represent the data. Finally, the developed model 125 can successfully represent the pandemic trajectory in a territory.