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Modern biology and epidemiology have become more and more driven by the need of mathematical models and theory to elucidate general phenomena arising from the complexity of interactions on the numerous spatial, temporal, and hierarchical scales at which biological systems

Modern biology and epidemiology have become more and more driven by the need of mathematical models and theory to elucidate general phenomena arising from the complexity of interactions on the numerous spatial, temporal, and hierarchical scales at which biological systems operate and diseases spread. Epidemic modeling and study of disease spread such as gonorrhea, HIV/AIDS, BSE, foot and mouth disease, measles, and rubella have had an impact on public health policy around the world which includes the United Kingdom, The Netherlands, Canada, and the United States. A wide variety of modeling approaches are involved in building up suitable models. Ordinary differential equation models, partial differential equation models, delay differential equation models, stochastic differential equation models, difference equation models, and nonautonomous models are examples of modeling approaches that are useful and capable of providing applicable strategies for the coexistence and conservation of endangered species, to prevent the overexploitation of natural resources, to control disease’s outbreak, and to make optimal dosing polices for the drug administration, and so forth.

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    Title
    • Advanced Nonlinear Dynamics of Population Biology and Epidemiology
    Contributors
    Date Created
    2014-12-22
    Resource Type
  • Text
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    Identifier
    • Digital object identifier: 10.1155/2014/214514
    • Identifier Type
      International standard serial number
      Identifier Value
      1085-3375
    • Identifier Type
      International standard serial number
      Identifier Value
      1687-0409

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    This is a suggested citation. Consult the appropriate style guide for specific citation guidelines.

    Wang, W., Kang, Y., Banerjee, M., & Wang, K. (2014). Advanced Nonlinear Dynamics of Population Biology and Epidemiology. Abstract and Applied Analysis, 2014, 1-3. doi:10.1155/2014/214514

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