Song, Insu, Hayes, Dominic, Mandal, Purnendu, and Vong, John (2017) Global health surveillance approaches. In: Mandal, Purnendu, and Vong, John, (eds.) Entrepreneurship in Technology for ASEAN. Managing the Asian Century . Springer, Singapore, pp. 59-71.

PDF (Published Version) - Published Version Restricted to Repository staff only

 

8

Abstract

Rapid penetration of Internet in the world has provided a significant amount of data on people and societies. The data captured has increased exponentially. This poses great opportunity as well as challenges. In this paper, global health surveillance and epidemic predictions of potentially life threatening diseases are considered. There is a vast amount of available data to be analyzed. The clustering methodology applied to geospatial data shows great potential for epidemic detections. However, the current methodologies mainly focus on clustering given datasets, but not their dynamics on how the size of clusters changes overtime. The existing approaches of health surveillance and data mining algorithms are reviewed. This discourse has two-fold objectives. Firstly, the disadvantages of existing approaches are identified and reported. Secondly the improved methods for detecting epidemics are proposed. A preliminary study of clustering of diseases in the US is used as an illustration.

Actions (Repository Staff Only)

Item Control Page