Enhancing Public Health Surveillance by Measurement of Similarity Using Rough Sets and GIS

Abstract

Public healthcare plans are essential to regions present around the world and deriving optimal strategies to combat the negative effects is one of the tasks involved in the process. Measuring similarity between two regions based on a common attribute is a popular problem, and this paper aims to find a method for the same, the common attribute being a key statistic taken from public health surveillance records. The method uses the application of rough measurement concept to determine the similarity between different regions having disease-linked death rates, which in turn can effectively be used to derive contingency plans in the case of a relevant event or before the next one takes place. We also take advantage of GIS tools to help in the processing and visualization of spatial data, and this paper discusses the role of GIS in public health surveillance as well.