Innovative computational advances for disease outbreaks

Kidane Desta Gebreyesus, Chuan-Hsiung Chang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


SIR (susceptible, infectious, removed) epidemic models are commonly used in infectious disease study. These models use systems of differential equations to estimate epidemiological parameters. However, differential equations often suffer from numerical challenges. Here, we proposed simple, effective and robust innovative methods for estimating key infectious disease parameters. Our methods are reformed from the SIR models, by adjusting components of model compartments. We illustrated the methods using the recent large disease outbreaks, Ebola virus disease and Middle East respiratory syndrome Coronavirus.

Original languageEnglish
Title of host publicationWCE 2016 - World Congress on Engineering 2016
EditorsLen Gelman, David W.L. Hukins, S. I. Ao, S. I. Ao, Len Gelman, S. I. Ao, Alexander M. Korsunsky, Andrew Hunter
PublisherNewswood Limited
Number of pages3
ISBN (Electronic)9789881925305
StatePublished - 2016
EventWorld Congress on Engineering 2016, WCE 2016 - London, United Kingdom
Duration: 29 Jun 20161 Jul 2016

Publication series

NameLecture Notes in Engineering and Computer Science
ISSN (Print)2078-0958


ConferenceWorld Congress on Engineering 2016, WCE 2016
Country/TerritoryUnited Kingdom


  • Infectious disease
  • Innovative method
  • Parameter
  • Robust estimation


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