الفهرس 
Title : An integrated approach of data mining and geographic information system
ContentsOnly 14 pages are availabe for public view
 |  | from | 168 |  |  |
| | | from | 168 | | |
Abstract
Lots of studies worldwide have been carried out to check the prevalence of hepatitis C virus (HCV) in human populations. Spatial data analysis and clustering detection is a vital process in HCV monitoring to discover the areas of high risk and to help involved decision makers to draw hypotheses about the causes and the high risk transmission factors of the disease in this geographical area. Egypt is declared as having the highest prevalence of HCV in the world; in 2008 the Egyptian Demographic Health Survey (EDHS) estimated the prevalence of HCV nationally as 14.7% with 9.8% are chronically infected. In 2015, a re-estimation was done by Egypt Health Issues survey (EHIS) reporting HCV infections as 10% of the population [E. Elghitany, 2019] [EHIS, 2015]. The anomaly of the HCV infection{u2019}s distribution in Egypt allowed several researches to identify the various reasons that contributed to such widespread of HCV in this country. Nowadays a field scanning program across the country is run to reveal the unknown infections among all Egyptians in all ages for better and faster diagnosis and recovery from HCV. Egyptian government is doing its best working in all possible ways and by all available tools such a serious effort to eliminate HCV from Egypt. One way that can help decision makers in identification of areas with highest critical infections for focusing the field effort is to obtain a detailed knowledge about the geographical distribution of HCV in Egypt