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024 7 $a10.1007/978-3-319-53208-0
035   $a(CKB)3710000001072460
035   $a(DE-He213)978-3-319-53208-0
035   $a(MiAaPQ)EBC4812831
035   $a(PPN)198871287
035   $a(EXLCZ)993710000001072460
100   $a20170225d2017      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aInfectious Disease Modeling $eA Hybrid System Approach /$fby Xinzhi Liu, Peter Stechlinski
205   $a1st ed. 2017.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2017.
215   $a1 online resource (XVI, 271 p. 72 illus., 67 illus. in color.)
225 1 $aNonlinear Systems and Complexity,$x2195-9994 ;$v19
311 08$a3-319-53206-5 
311 08$a3-319-53208-1 
320   $aIncludes bibliographical references.
327   $aIntroduction -- Modelling the Spread of an Infectious Disease -- Hybrid Epidemic Models -- Control Strategies for Eradication -- Discussions and Conclusions -- References -- Appendix.
330   $aThis volume presents infectious diseases modeled mathematically, taking seasonality and changes in population behavior into account, using a switched and hybrid systems framework. The scope of coverage includes background on mathematical epidemiology, including classical formulations and results; a motivation for seasonal effects and changes in population behavior, an investigation into term-time forced epidemic models with switching parameters, and a detailed account of several different control strategies. The main goal is to study these models theoretically and to establish conditions under which eradication or persistence of the disease is guaranteed. In doing so, the long-term behavior of the models is determined through mathematical techniques from switched systems theory. Numerical simulations are also given to augment and illustrate the theoretical results and to help study the efficacy of the control schemes.
410  0$aNonlinear Systems and Complexity,$x2195-9994 ;$v19
606   $aMathematical models
606   $aInfectious diseases
606   $aComputational complexity
606   $aStatistical physics
606   $aEpidemiology
606   $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068
606   $aInfectious Diseases$3https://scigraph.springernature.com/ontologies/product-market-codes/H33096
606   $aComplexity$3https://scigraph.springernature.com/ontologies/product-market-codes/T11022
606   $aApplications of Nonlinear Dynamics and Chaos Theory$3https://scigraph.springernature.com/ontologies/product-market-codes/P33020
606   $aEpidemiology$3https://scigraph.springernature.com/ontologies/product-market-codes/H63000
615  0$aMathematical models.
615  0$aInfectious diseases.
615  0$aComputational complexity.
615  0$aStatistical physics.
615  0$aEpidemiology.
615 14$aMathematical Modeling and Industrial Mathematics.
615 24$aInfectious Diseases.
615 24$aComplexity.
615 24$aApplications of Nonlinear Dynamics and Chaos Theory.
615 24$aEpidemiology.
676   $a003.3
700   $aLiu$b Xinzhi$4aut$4http://id.loc.gov/vocabulary/relators/aut$041492
702   $aStechlinski$b Peter$4aut$4http://id.loc.gov/vocabulary/relators/aut
906   $aBOOK
912   $a9910254174103321
996   $aInfectious Disease Modeling$92203574
997   $aUNINA