| 書目名稱 | Mathematical and Statistical Estimation Approaches in Epidemiology |
| 編輯 | Gerardo Chowell,James M. Hyman,Carlos Castillo-Cha |
| 視頻video | http://file.papertrans.cn/627/626711/626711.mp4 |
| 概述 | Essential resource for graduate students interested in the analysis of infectious disease outbreaks and epidemic modeling.Approaches for the estimation of the transmission potential of infectious dise |
| 圖書封面 |  |
| 描述 | Mathematical and Statistical Estimation Approaches in Epidemiology compiles t- oretical and practical contributions of experts in the analysis of infectious disease epidemics in a single volume. Recent collections have focused in the analyses and simulation of deterministic and stochastic models whose aim is to identify and rank epidemiological and social mechanisms responsible for disease transmission. The contributions in this volume focus on the connections between models and disease data with emphasis on the application of mathematical and statistical approaches that quantify model and data uncertainty. The book is aimed at public health experts, applied mathematicians and sci- tists in the life and social sciences, particularly graduate or advanced undergraduate students, who are interested not only in building and connecting models to data but also in applying and developing methods that quantify uncertainty in the context of infectious diseases. Chowell and Brauer open this volume with an overview of the classical disease transmission models of Kermack-McKendrick including extensions that account for increased levels of epidemiological heterogeneity. Their theoretical tour i |
| 出版日期 | Book 2009 |
| 關(guān)鍵詞 | Epidemiological; Epidemiology; Infectious disease epidemiology; Measure; Observable; SAS; Time series; dyna |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-90-481-2313-1 |
| isbn_softcover | 978-94-007-7990-7 |
| isbn_ebook | 978-90-481-2313-1 |
| copyright | Springer Science+Business Media B.V. 2009 |
|Archiver|手機(jī)版|小黑屋|
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