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Dynamics and Implications of Data-Based Disease Models in Public Health and Agriculture

Abstract The increased number of novel pathogens that potentially threaten the human population has motivated the development of mathematical and computational modeling approaches for forecasting epidemic impact and understanding key environmental characteristics that influence the spread of diseases. Yet, in the case that substantial uncertainty surrounds the transmission process during a rapidly developing infectious disease outbreak, complex mechanistic models may be too difficult to be calibrated quick enough for policy makers to make informed decisions. Simple phenomenological models that rely on a small number of parameters can provide an initial platform for assessing the epidemic trajectory, estimating the reproduction number and quantifying... (more)
Created Date 2016
Contributor Pell, Bruce (Author) / Kuang, Yang (Advisor) / Chowell-Puente, Gerardo (Committee member) / Nagy, John (Committee member) / Kostelich, Eric (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Subject Applied mathematics / Public health / Botany / Barley Yellow Dwarf Virus / Bombay Plague / Delay Differential Equations / Ebola Virus Disease / Mathematical Modeling / Patch Models
Type Doctoral Dissertation
Extent 135 pages
Language English
Reuse Permissions All Rights Reserved
Note Doctoral Dissertation Applied Mathematics 2016
Collaborating Institutions Graduate College / ASU Library
Additional Formats MODS / OAI Dublin Core / RIS

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Description Dissertation/Thesis