Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach

• Main Authors: Ullah, S., Daud, H., Dass, S.C., Khan, H.N., Khalil, A.
• Format: Article
• Published: Page Press Publications 2017
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85033239575&doi=10.4081%2fgh.2017.567&partnerID=40&md5=5948a5c8185bd6ddff13a31452df31ba; http://eprints.utp.edu.my/19820/

Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square) scanning windows to discover diseas...