A new computational algorithm to estimate case fatality rate

Kidane Desta Gebreyesus, Chuan Hsiung Chang

研究成果: Conference contribution同行評審

摘要

Case fatality rate, an indicator of disease severity, is one of the most important parameters in medical and epidemiological studies. Simple naive estimate method is often used to estimate case fatality rate. However, the naive method can lead to biased estimates for a number of reasons including, for example, ascertainment error and incomplete data. Here, we developed a new model called NELM (derived from Naive Estimate and Linear Model), which incorporates both the naive method and the regression models, for the regression model takes Gaussian random error into account. We illustrated the algorithm using Ebola epidemic data of three West African countries. Our algorithm is robust and effective. And it provides insight into the ongoing Ebola outbreak and other emerging infectious diseases.

原文English
主出版物標題WCE 2016 - World Congress on Engineering 2016
編輯S. I. Ao, S. I. Ao, Len Gelman, S. I. Ao, Len Gelman, David W.L. Hukins, Andrew Hunter, Alexander M. Korsunsky
發行者Newswood Limited
頁面629-631
頁數3
ISBN(電子)9789881404800
出版狀態Published - 2016
事件World Congress on Engineering 2016, WCE 2016 - London, United Kingdom
持續時間: 29 6月 20161 7月 2016

出版系列

名字Lecture Notes in Engineering and Computer Science
2224
ISSN(列印)2078-0958

Conference

ConferenceWorld Congress on Engineering 2016, WCE 2016
國家/地區United Kingdom
城市London
期間29/06/161/07/16

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