Browsing by Author "Worku, Alemayehu(Dr.)"

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    Application of Data Mining for Predicting Adult Mortality.
    (Addis Abeba University, 2012-06) Hailemariam, Tesfahun; Meshesha, Million(Dr.); Worku, Alemayehu(Dr.)
    Background: The fast-growing, tremendous amount of data, collected and stored in large and massive data repositories, has far exceeded human ability for comprehension without powerful tools. As a result, data collected in large data repositories become seldom visited. This in turn, calls the application of data mining technology. Every year, more than 7·7 million children die before their fifth birthday. However, over three times those of nearly 24 million adults die every year. Less attention has been given to adults which are the most productive phase of life for both economic and social ramification of families and countries. Objective: The general objective of this research is to construct adult mortality predictive model using data mining techniques so as to identify and improve adult health status using BRHP open cohort database. Methods: The hybrid model that was developed for academic research was followed. Dataset is preprocessed for missing values, outliers and data transformation. Decision tree and Naïve Bayes algorithms were employed to build the predictive model by using a sample dataset of 62,869 records of both alive and died adults through three experiments and six scenarios. Result: In this study as compared to Bayes, the performance of J48 pruned decision tree reveals that 97.2% of accurate results are possible for developing classification rules that can be used for prediction. If no education in family and the person is living in rural highland and lowland, the probability of experiencing adult death is 98.4% and 97.4% respectively with concomitant attributes in the rule generated. The likely chance of adult to survive in completed primary school, completed secondary school, and further education is (98.9%, 99%, 100%) respectively. Conclusion: The study suggests that education plays a considerable role as a root cause of adult death, followed by outmigration. Further comprehensive and extensive experimentation is needed to substantially describe the loss experiences of adult mortality in Ethiopia.
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    Application of Data Mining Technique to Develop Chronic Disease Distribution Map using Drug Distribution Data in Ethiopia
    (Addis Abeba University, 2013-04) Zerihun, Marara; Worku, Alemayehu(Dr.); Jemaneh, Getachewu
    Background: Due to the great difference in population structure, geographic environment, food composition, ethnicity and lifestyle, it could be predicted that there may be significant differences of chronic disease forms and distribution in the various administrative areas. The amount of data getting generated in any sector these days is enormous. There are many data mining tools and technique to uncover hidden knowledge in the data. At the same time Ethiopian PFSA has huge and useful drug distribution data in their data base to investigate chronic disease distribution. Objective: The purpose of this study is to investigate distribution of chronic diseases in various administrative areas of the country based on chronic disease drug distribution data applying data mining techniques. Methods: Drug distribution data was collected from EPFSA. Data that are retrieved from the organization is from 2003 up to 2005 EC. Since annual data follow is high and distribution density is the same, two and half year’s data is enough to produce distribution map and identify increase in demand applying data mining technology. Any data beyond these years are redundant and over saturate the models. In order to optimize the desired outcome the researcher has followed Hybrid data mining process model. The model is selected because it is appropriate for academic research; it combines the best features of KDD and CRISP; and starts with problem domain understanding. Results: The study revealed that some drugs are more important at one hub than the other. Gullele hub received the hieghtest persontage of Athma (17.3%), Cardiac (38.5%), Diatetes (45.6%) and Hypertenion (28.99%). While Parkinson drugs are issued mostly to Mekele (15.5%)hub. The mining software revealed that some drugs are more important at one hub than the other in specified time. Conclusions: Issue date, issue number and expiry dates are selected as best attribute by the mining tool. Based on discussion with domain experts issue date is important for drug distribution while issue number and expiry date are not relevant to the drug distribution.
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    Magnitude and Trends of Road Traffic Accident and Associated Factors: from Akaki to Adama, July 2007-June 2012, Oromia, Ethiopia
    (Addis Abeba University, 2013-06) Asefa, Fekede; Assefa, Demeke(Dr.); Worku, Alemayehu(Dr.)
    Background: Road traffic accident is now becoming a public health problem in the world and resulting in human tragedy. Globally, about 1.2 million people are killed in road traffic accident every year and 20 to 50 million more are injured and/or disabled. These injuries account for 2.1% of global mortality. Low- and middle-income countries account for about 85% of the deaths and 90% of the DALYs lost annually due to road traffic accident. Without appropriate action, by 2020,road traffic injuries are predicted to be the third leading contributor to the global burden of disease. Despite having low road network density and vehicle ownership, Ethiopia has a relatively high accident records. Road accidents are concentrated in few of the regions in the country. The capital City of Addis Ababa and Oromia Region account for 58 per cent of all fatal accidents and two thirds of all injuries Objective: To assess magnitude, trends and associated factors of road traffic accident from Akaki to Adama. Method: Retrospective study was conducted from police reports between July 2007 and June 2012 retrieved from the 8 police stations in the study area. Result: A total of 2335 accidents have been registered in the study area from July 2007 to June 2012. Of those 389 (16.7%) resulted in death (fatal accident), 316 (13.5%) resulted in severe injuries, 290 (12.4%) resulted in slight injuries. The rest 1316 (56.4%) accidents resulted in property damage. During the study period, 1745 individuals were affected as a result of the accident. Of those 515 (29.5%) victims died, while 549 (31.5%) sustained severe injury and the rest slight injury. The major reason for the accidents were over speeding accounting for 836(36.1%) followed by careless driving 573 (24.8%) and failure to give priority 507 (21.9%) for other vehicles and pedestrians. Being Female driver, accident occurring at mid night, accident caused by over speeding, failure to give priority and vehicles having technical problem are strong determinants of fatality. Conclusions and recommendations Trend of road traffic accident was steadily increased in magnitude from July 2007-June 2012 in the study area which calls for urgent interventions. Enforcing drivers to obey traffic rules and strong enforcement of speed limit appear to be the most critical parts of interventions.