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Titlebook: Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases; Gerardo Chowell,James M. Hyman Book 2016 Springer

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發(fā)表于 2025-3-21 16:12:26 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱(chēng)Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases
編輯Gerardo Chowell,James M. Hyman
視頻videohttp://file.papertrans.cn/627/626725/626725.mp4
概述Provides contributions by epidemic modeling experts describing a broad range of approaches to address contemporary questions related to the spread and control of infectious diseases.Demonstrates examp
圖書(shū)封面Titlebook: Mathematical and Statistical Modeling for Emerging and Re-emerging Infectious Diseases;  Gerardo Chowell,James M. Hyman Book 2016 Springer
描述.The contributions by epidemic modeling experts describe how mathematical models and statistical forecasting are created to capture the most important aspects of an emerging epidemic.Readers will discover a broad range of approaches to address questions, such as.Can we control Ebola via ring vaccination strategies?.How quickly should we detect Ebola cases to ensure epidemic control?.?What is the likelihood that an Ebola epidemic in West Africa leads to secondary outbreaks in other parts of the world? ?.When does it matter to incorporate the role of disease-induced mortality on epidemic models?.?What is the role of behavior changes on Ebola dynamics??.How can we better understand the control of cholera or Ebola using optimal control theory?.How should a population be structured in order to mimic the transmission dynamics of diseases such as chlamydia, Ebola, or cholera?.How can weobjectively determine the end of an epidemic?.How can we use metapopulation models to understand the role of movement restrictions and migration patterns on the spread of infectious diseases?.How can we capture the impact of household transmission using compartmental epidemic models?.How could behavior-depe
出版日期Book 2016
關(guān)鍵詞Emerging infectious diseases; Epidemic; Epidemic forecasting; Infectious disease dynamics; Mathematical
版次1
doihttps://doi.org/10.1007/978-3-319-40413-4
isbn_softcover978-3-319-82094-1
isbn_ebook978-3-319-40413-4
copyrightSpringer International Publishing Switzerland 2016
The information of publication is updating

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Inverse Problems and Ebola Virus Disease Using an Age of Infection Model,of iterative regularization along with a special algorithm for computing initial values. The numerical study is illustrated by data fitting and forward projections for the most recent EVD outbreak in Sierra Leone and Liberia.
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Designing Public Health Policies to Mitigate the Adverse Consequences of Rural-Urban Migration via probabilities. Results suggest that when sub-populations differ in density (which may affect contact rates), heterogeneous vaccination coverage among migrants is most effective according to measures such as final epidemic size, peak size, number of vaccine doses needed to prevent outbreaks, and lik
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Methods to Determine the End of an Infectious Disease Epidemic: A Short Review,ory testing has been commonly adapted to substantiate a freedom from disease, but such study has only accounted for binomial sampling process in estimating the error probability of elimination. Surveillance and mathematical modeling are two complementary instruments in the toolbox of epidemiologists
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Epidemic Models With and Without Mortality: When Does It Matter?,clude disease-related mortality in a model should, however, take into account the fact that diseases such as influenza, that sicken a high proportion of a population, may nonetheless lead to high numbers of deaths. These deaths can affect a real population’s perception of and response to an epidemic
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Book 2016ely determine the end of an epidemic?.How can we use metapopulation models to understand the role of movement restrictions and migration patterns on the spread of infectious diseases?.How can we capture the impact of household transmission using compartmental epidemic models?.How could behavior-depe
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