@inproceedings{f39ca68712004f0a83424433e6874449,
title = "Innovative computational advances for disease outbreaks",
abstract = "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.",
keywords = "Infectious disease, Innovative method, Parameter, Robust estimation",
author = "Gebreyesus, {Kidane Desta} and Chuan-Hsiung Chang",
year = "2016",
language = "English",
series = "Lecture Notes in Engineering and Computer Science",
publisher = "Newswood Limited",
pages = "523--525",
editor = "Len Gelman and Hukins, {David W.L.} and Ao, {S. I.} and Ao, {S. I.} and Len Gelman and Ao, {S. I.} and Korsunsky, {Alexander M.} and Andrew Hunter",
booktitle = "WCE 2016 - World Congress on Engineering 2016",
note = "null ; Conference date: 29-06-2016 Through 01-07-2016",
}
