001441318 000__ 03281cam\a2200565\i\4500
001441318 001__ 1441318
001441318 003__ OCoLC
001441318 005__ 20230309004732.0
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001441318 019__ $$a1288556558$$a1288632057$$a1288667574$$a1289367537
001441318 020__ $$a9783658359324$$q(electronic bk.)
001441318 020__ $$a3658359323$$q(electronic bk.)
001441318 020__ $$z9783658359317
001441318 020__ $$z3658359315
001441318 0247_ $$a10.1007/978-3-658-35932-4$$2doi
001441318 035__ $$aSP(OCoLC)1288465199
001441318 040__ $$aYDX$$beng$$erda$$epn$$cYDX$$dGW5XE$$dEBLCP$$dOCLCF$$dOCLCO$$dOCLCQ
001441318 049__ $$aISEA
001441318 050_4 $$aRA644.C67$$bT74 2021
001441318 08204 $$a362.1962/41401/5118$$223
001441318 1001_ $$aTreibert, Sarah Marie,$$eauthor.
001441318 24510 $$aMathematical modelling and nonstandard schemes for the Corona virus pandemic /$$cSarah Marie Treibert.
001441318 264_1 $$aWiesbaden :$$bSpringer Spektrum,$$c[2021]
001441318 264_4 $$c©2021
001441318 300__ $$a1 online resource :$$billustrations
001441318 336__ $$atext$$btxt$$2rdacontent
001441318 337__ $$acomputer$$bc$$2rdamedia
001441318 338__ $$aonline resource$$bcr$$2rdacarrier
001441318 4901_ $$aBestMasters,$$x2625-3615
001441318 504__ $$aIncludes bibliographical references.
001441318 5050_ $$aIntroduction -- The Severe Acute Respiratory Syndrome Corona Virus Type 2 -- The SIR Model in Epidemic Modelling -- The SARS-CoV-2-fitted SEIR Model -- Model Specifications -- Parameter Estimation in MAT LAB -- Markov Chain Epidemic Models -- Rþesumþ.
001441318 506__ $$aAccess limited to authorized users.
001441318 520__ $$aThis book deals with the prediction of possible future scenarios concerning the COVID-19 pandemic. Based on the well-known SIR model by Kermack and McKendrick a compartment model is established. This model comprises its own assumptions, transition rates and transmission dynamics, as well as a corresponding system of ordinary differential equations. Making use of numerical methods and a nonstandard-finite-difference scheme, two submodels are implemented in Matlab in order to make parameter estimations and compare different scenarios with each other. About the author Sarah Marie Treibert is a research assistant at the Chair of Applied Mathematics / Numerical Analysis of the University of Wuppertal (Bergische Universität Wuppertal). Her focus is on Epidemic Modelling.
001441318 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed December 20, 2021).
001441318 647_7 $$aCOVID-19 Pandemic$$d(2020- )$$2fast$$0(OCoLC)fst02024716
001441318 650_0 $$aCOVID-19 Pandemic, 2020-$$xMathematical models.
001441318 650_0 $$aCOVID-19 Pandemic, 2020-$$xForecasting.
001441318 650_6 $$aPandémie de COVID-19, 2020-$$xModèles mathématiques.
001441318 650_6 $$aPandémie de COVID-19, 2020-$$xPrévision.
001441318 655_0 $$aElectronic books.
001441318 77608 $$iPrint version:$$aTreibert, Sarah Marie.$$tMathematical modelling and nonstandard schemes for the Corona virus pandemic.$$dWiesbaden : Springer Spektrum, [2021]$$z3658359315$$z9783658359317$$w(OCoLC)1273331431
001441318 830_0 $$aBestMasters.$$x2625-3615
001441318 852__ $$bebk
001441318 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-658-35932-4$$zOnline Access$$91397441.1
001441318 909CO $$ooai:library.usi.edu:1441318$$pGLOBAL_SET
001441318 980__ $$aBIB
001441318 980__ $$aEBOOK
001441318 982__ $$aEbook
001441318 983__ $$aOnline
001441318 994__ $$a92$$bISE