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Record Nr. |
UNINA9910254174103321 |
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Autore |
Liu Xinzhi |
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Titolo |
Infectious Disease Modeling : A Hybrid System Approach / / by Xinzhi Liu, Peter Stechlinski |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2017 |
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Edizione |
[1st ed. 2017.] |
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Descrizione fisica |
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1 online resource (XVI, 271 p. 72 illus., 67 illus. in color.) |
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Collana |
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Nonlinear Systems and Complexity, , 2195-9994 ; ; 19 |
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Disciplina |
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Soggetti |
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Mathematical models |
Infectious diseases |
Computational complexity |
Statistical physics |
Epidemiology |
Mathematical Modeling and Industrial Mathematics |
Infectious Diseases |
Complexity |
Applications of Nonlinear Dynamics and Chaos Theory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references. |
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Nota di contenuto |
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Introduction -- Modelling the Spread of an Infectious Disease -- Hybrid Epidemic Models -- Control Strategies for Eradication -- Discussions and Conclusions -- References -- Appendix. |
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Sommario/riassunto |
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This volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques |
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