Discussion on “Real-time monitoring of events applied to syndromic surveillance”

Abstract

This article presents a discussion of Sparks et al., focusing on the application and need for control charting methodologies for real-world syndromic surveillance applications. The discussion is divided into a: (a) non-technical component, where some of the design choices and assumptions behind the research problem are reviewed; and (b) a technical component, where a closer examination of the simulation and the control charts’ performance are presented. Following the discussion, some concluding remarks are presented.

Keywords:

• control charts
• EWMA control charts
• phase II analysis
• data mining
• process monitoring

About the author

Dr. Fadel M. Megahed is an Assistant Professor of Information Systems & Analytics at Miami University. He received his Ph.D. and M.S. in Industrial and Systems Engineering from Virginia Tech, and a B.S. in Mechanical Engineering from the American University in Cairo. His current research focuses on creating new tools to store, organize, analyze, model, and visualize the large heterogeneous data sets associated with modern manufacturing, healthcare and service environments. His work in these areas have been recently been funded by Aflac, American Society for Safety Professionals (ASSP) Foundation, Proctor and Gamble (P&G) Fund of the Greater Cincinnati Foundation, Amazon Web Services (AWS), Windows Azure (Microsoft), the NIOSH Deep South Center for Occupational Safety and Ergonomics, and the National Science Foundation (NSF). Dr. Megahed has 30 published journal papers and 8 conference proceedings. He is an Editorial Board Member for the Journal of Quality Technology. He has reviewed for over 15 academic journals including: Decision Support Systems, Expert Systems with Applications, Journal of Quality Technology, Naval Research Logistics, Reliability Engineering and Systems Safety, Journal of Manufacturing Systems, and IIE Transactions. Dr. Megahed is the recipient of the Career Development Award from the NIOSH Deep South Center for Occupational Health and Safety (2013), and the Mary G. and Joseph Natrella Scholarship from the Quality and Productivity Section of the American Statistical Association (2012).

Disclosure statement

No potential conflict of interest was reported by the author.