Thalassemia is a major health problem in Iraq, and despites a prevention programme. There has been no decrease in the prevalence of the disease, due to a lack of awareness, implying that genetic counseling was a failure. This failure has been attributed to a lack of recognition of problems related to Thalassemia, unorganised teamwork and services, lack of knowledge and insufficient numbers of extension workers, lack of Thalassemia support groups, and inadequate research in Thalassemia prevention and control. Autoregressive Integrated Moving Average (ARIMA) model and forecasting has become a major tool in different applications. The ARIMA model introduced by Box and Jenkins (1971) is among the most effective approaches for analysing time-series data. In this study, we used Box and Jenkins methodology to build an ARIMA model to forecast the number of people with Thalassemia, for the period from 2016-2018, from the data base from Maysan Health Center specific for Thalassemia the Maysan Provence, Iraq. After the model selection, the best model for forecasting was ARIMA (0, 1, 1) and of models were used for forecasting Thalassemia.

Iron overload is the major cause of morbidity for thalassemia patients. Even non-transfused patients develop secondary iron overload, due to increased intestinal absorption of dietary iron. Iron overload is a leading cause of mortality 1090 AL-Sudani Rana Sabeeh et al. and organ failure. It occurs very rapidly in patients who are on chronic transfusion programs. Since humans have no mechanism other than sloughing of the mucosa of their gastrointestinal tracts or menstruation to excrete excess iron, patients who are being transfused every three or four weeks gain 0.5 mg/kg per day of iron in excess of natural losses. Patients who are not on a transfusion regimen are also prone to iron overload due to significantly increased intestinal absorption of iron secondary to ineffective erythropoiesis. Thalassemia is considered one of the diseases that represents a big challenge for Iraqi people because of high morbidity, with an increasing rate every year, therefore, this study focused on the relationship between times of blood transfusion and iron overload in thalassemia patients as well as studying the effect of some physiological factors, such as age, gender, blood type and the type of thalassemia. This study used, a Co-integration (Engle-granger) model and traditional statistical analysis methods to analyse data obtained from the thalassemia centre in-Maysan province, Iraq, for 100 patients over 12 months(year 2015) by recording age group, gender, blood type, type of thalassemia, number of blood transfusions and blood iron levels. Our results demonstrated that there was a positive relationship between both the number of blood transfusions and blood iron levels, the more the number of blood transfusion increased, the more blood iron level and the males was mostly infected than females and children between 1-4 years were the age category with the highest level of infection. The group with blood type O + was the most infected group and, finally, thalassemia major beta was the highest registered type. We strongly recommend more precise investigation on this subject, focusing on secondary complications that accompany this disease.