Spatial Clustering and Analysis on Hepatitis C Virus Infections in Egypt

ABSTRACT Lots of studies worldwide have been carried out to check out 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 area of high risk and to help involved decision makers to draw hypotheses about the cause of disease. Egypt is declared as one of the countries having the highest prevalence rate of HCV worldwide. The anomaly of the HCV infection’s distribution in Egypt allowed several researches to identify the reasons that contributed to such widespread of HCV in this country. One way that can help in identification of areas with highest diseases is to give a detailed knowledge about the geographical distribution of HCV in Egypt. To achieve that goal, Data mining analytical tools integrated with GIS can help to visualize the distribution. Thus, the main propose of this paper is to present a spatial distribution of HCV in Egypt using case data obtained from the Egyptian health institute National Hepatology Tropical Medicine Research Institute (NHTMR). The visualization of the spatial analysis distribution by means of GIS allows us to investigate statistical results that are easily interpreted by non-experts. KEYWORDS: Data mining, clustering, k-means, spatial clustering, Geographic Information System (GIS) & Hepatitis C Virus (HCV) Original Source URL : http://aircconline.com/ijdkp/V8N5/8518ijdkp01.pdf For more details : http://airccse.org/journal/ijdkp/current.htm