Vol.10 (2020) No. 4 ISSN: 2088-5334 Using Multivariate Analysis to Study the Spread of Transitional Diseases in Iraq Aseel Abdul Razzak Rasheed a,1 , Rawaa Salh Al-saffar a , Husam A. Rasheed a a Collage of administration and Economics / Statistics Department Mustansiriyah University, Iraq E-mail: 1 aseelstat@uomustansiriyah.edu.iq Abstract— Medical and technological development has achieved continuous successes during the last period. However, the statistics received from the World Health Organization (WHO) show the suffering that millions of people are subjected to daily as a result of their exposure to transitional diseases. The most prevalent transitional disease in the Iraqi provinces and for all age groups for both genders is water pox disease, followed by cutaneous leishmaniosis and then mumps. The most affected governorate with transitional diseases is Baghdad Governorate (Rusafa Sector), followed by Dhi Qar Governorate and Baghdad (Al Karkh Sector). The most age- groups affected with transition diseases are the categories (5-9) years for males, followed by (5-9) years for females. The highest total contribution to the first axis was for cutaneous leishmaniasis, followed by mumps, then Basil dysentery, as for the absolute contribution in the first axis, it was Dhi Qar Governorate, followed by Baghdad. There are more than 14,000,000 people who die each year because of these diseases, and most infections are concentrated in developing countries, including Iraq. Hence, this research is vital to examine the extent of transitional diseases in Iraq for different age groups, both male and female gender. The use of the multivariate method, which is the correspondence analyses, it was found through the research that Baghdad (Rusafa Sector) has a high incidence of transitional diseases and the largest age group at risk of transitional diseases is (5-9) years form male gender. Keywords— diseases; Iraq; statistical method; pandemic; WHO. I. INTRODUCTION The developments in the field of combating transitional diseases, and the availability of antibiotics to eliminate these diseases, did not prevent members of society from developing new diseases, or the return of some rare diseases. The sources of infection and methods of transmission vary from person to another. Moreover, the transmission of infectious agents from the infected person or the carrier of the disease or animals were infected with diseases common to humans and animals. The diseases may be transmitted from the environment close to humans, including food and drink contaminated with microorganisms that cause the disease. Transitional diseases are classified as serious in that they often cause death as well as permanent or temporary complications such as polio, which causes permanent disability.[1], [2] Disease can be defined as resulting from the transmission of microorganisms, like the viruses, bacteria, fungi, or parasites from an infected person to another healthy person that leads to his illness.[3] Correspondence analysis was used as a tool for analyzing disease data; given that the symmetric analysis is a classification tool from two sides, the research covers all governorates of Iraq except the Kurdistan Region and the age groups and both gender[4], [5]. In this paper, we used a simple corresponding analysis to study (data classified as multivariate and discrete) and represented by transitional diseases and knowing the most prevalent types of transitional diseases in the Iraqi governorates, according to age groups and gender [6]. II. MATERIALS AND METHOD A. Correspondence Analysis Correspondence analysis is a multivariate method that has been known for a long time. Furthermore, Correspondence analysis is a special case of correct correlation analysis that concerned with analyzing the metadata and non-meta data. There is a special kind of graphical display that rows and columns are drawn as two-dimensional points. The location of theses points indicates that they are reconciled [6]–[8]. 1) Weighted Euclidean distance: If the points B and A in this field are the sum of the squares of the weighted differences for the coordinates as follows [7]: D 2 (A, B) =(A-B) T Dq (A-B) =∑qi (AJ-BJ) (1) D_q: q: diagonal matrix with dimension J, in which the diameter elements represent weights. 1543