key: cord-0847394-7xrjtt4d authors: Reza Mahmoudi, Mohammad; Baleanu, Dumitru; Band, Shahab S.; Mosavi, Amir title: Factor Analysis Approach to Classify COVID-19 Datasets in Several Regions date: 2021-03-22 journal: Results Phys DOI: 10.1016/j.rinp.2021.104071 sha: d72cd84bf442220f92bf0b80b4373200bd27df08 doc_id: 847394 cord_uid: 7xrjtt4d The aim of this research is to investigate the relationships between the counts of cases with Covid-19 and the deaths due to it in seven countries that are severely affected from this pandemic disease. First, the Pearson’s correlation is used to determine the relationships among these countries. Then, the factor analysis is applied to categorize these countries based on their relationships. In the winter months of 2019-2020, another type of coronavirus, Covid-19, has been reported in Wuhan [1] . This virus has severe destructive effects on the respiratory system. From January to now (April 18, 2020) , this epidemic has become epidemic all over the world and day by day the cases with Covid-19 and the deaths due to Covid-19 are extremely increasing in most of countries [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] . There are many techniques analyze the natural phenomena including artificial intelligence, mathematical and statistical methods such as optimization, deep learning, time series analysis, machine learning, regression modeling, clustering and numerical analysis . Since Covid-19 has many impacts on environment, health, society and economy, the study of the rate of spread of this disease and the comparison of its rate in different countries is essential. There are some researches about the classification of Covid-19 datasets [40] [41] [42] [43] . These researches are based on time series analysis, principal component analysis and fuzzy clustering. The aim of this research is to study the relationships between the counts of the cases with Covid-19 and the deaths due to it in seven countries that are severely affected from this pandemic disease. First, the coefficients of correlation are computed to determine the relationships between these countries. Then, the factor analysis is applied to categorize these countries using the counts of cases and deaths. This section is devoted to study the research's dataset and to and to introduce the factor analysis. In this work, the counts of the cases with Covid-19 and the deaths due to it in United States America, United Kingdom, Spain, Italy, Iran, Germany, and France from February 22 to April 18 of 2020, are considered. Table 1 summarizes the descriptive statistics of dataset containing the mean and the standard deviation. It can be observed that Iran and United States America have the minimum and the maximum counts of the cases with Covid-19. In addition, Germany and United States America have the minimum and the maximum of the deaths due to Covid-19. The plots for the counts of the cases with Covid-19 and the deaths due to it are also demonstrated in Figure 1 . The relationships between the rates of the spread of Covid-19 among these countries have been studied using Pearson's coefficient of correlation. As it can be seen in Table 2 , all of the values are more than 0.5 and significant, and consequently there are strong positive relationships between the rates of spread of Covid-19 in all of countries. This model can be rewritten by such that is named as the loading of on the factor . In orthogonal factor analysis, we have This section reports the results of FA approach to classify the countries based on research's variables. It should be noted that the number of the main factors in FA was considered as the number of the eigenvalues of the correlation's matrix with the values larger than one. Moreover, the KMO values were more than 0.8 that verify the accuracy of FA approach. The results of FA technique to categorize the research countries, in basis of the counts of the cases with Covid-19, are provided in Figure 2 . The outputs demonstrate the statistical differences between the relationships among the countries and we can categorize the countries into following classes: First class: Iran, France, Spain, Germany, Italy. Second class: United Kingdom, United States America. The results of FA technique to categorize the research countries, in basis of the counts of the deaths due to Covid-19, are provided in Figure 3 . The outputs demonstrate the statistical differences between the relationships among the countries and we can categorize the countries into following classes: First class: France, United Kingdom, Germany and United States America. Second class: Iran, Italy and Spain. The results of FA technique to categorize the research countries, in basis of the cumulative counts of the cases with Covid-19, are provided in Figure 4 . The outputs demonstrate the statistical differences between the relationships among the countries and we can categorize the countries into following classes: The results of FA technique to categorize the research countries, in basis of the cumulative counts of the deaths due to Covid-19, are provided in Figure 5 . The outputs demonstrate the statistical differences between the relationships among the countries and we can categorize the countries into following classes: First class: France, United Kingdom, Germany and United States America. Second class: Iran, Italy and Spain. Since Covid-19 has many impacts on environment, health, society and economy, the study of the rate of spread of this disease and the comparison of its rate in different countries is essential. The aim of this research was to study the cases with Covid-19 and the deaths due to this pandemic disease in seven countries that are severely affected from this pandemic disease. The cases and the deaths in United States America, United Kingdom, Spain, Italy, Iran, Germany, and France from February 22 to April 18 of 2020, were considered. First, the coefficients of correlation were computed to determine the relationships among these countries. The outputs showed that there were strong positive relationships between the rates of spread in all of countries. Then, the factor analysis was applied to categorize the countries in basis of the counts and deaths. For the cases with Covid-19, United Kingdom and United States America were similarly distributed to each other and were differently distributed from other countries. Also, for the deaths, Iran, Italy and Spain were similarly distributed to each other and were differently distributed from other countries. For future works, the authors suggest classifying the Covid-19 datasets of more regions based on FA technique, or apply this technique to classify the regions for other epidemic or pandemic diseases. The authors declare no conflict of interest. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. 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