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Deterministické a stochastické epidemické modely
dc.contributor.advisorŠtěpán, Josef
dc.creatorStaněk, Jakub
dc.date.accessioned2018-11-30T11:31:42Z
dc.date.available2018-11-30T11:31:42Z
dc.date.issued2009
dc.identifier.urihttp://hdl.handle.net/20.500.11956/23402
dc.description.abstractKermack-McKendrick model and its version with vaccination are presented. First, we introduce a model with vaccination and then a numerical study that includes comparison of di erent vaccination strategies and searching for optimal vaccination strategy is presented. We proceed to introduce a stochastic model with migration and consequently we suggest its generalization and prove the existence and uniqueness of a solution to the stochastic di erential equation (henceforth SDE) describing this model. Three stochastic versions of Kermack-McKendrick model with vaccination are suggested and compared. A procedure of nding the optimal vaccination strategy is presented. We also prove the theorem on the existence and uniqueness of a solution to the SDE that drives a model with multiple pathogens. Finally, the stochastic di erential equation describing the general model is presented. We study properties of a solution to this SDE and present sufficient conditions for the existence of a solution that is absorbed by the natural barrier of the model.en_US
dc.languageEnglishcs_CZ
dc.language.isoen_US
dc.publisherUniverzita Karlova, Matematicko-fyzikální fakultacs_CZ
dc.titleDeterministic and Stochastic Epidemic Modelsen_US
dc.typedizertační prácecs_CZ
dcterms.created2009
dcterms.dateAccepted2009-09-11
dc.description.departmentKatedra pravděpodobnosti a matematické statistikycs_CZ
dc.description.departmentDepartment of Probability and Mathematical Statisticsen_US
dc.description.facultyFaculty of Mathematics and Physicsen_US
dc.description.facultyMatematicko-fyzikální fakultacs_CZ
dc.identifier.repId43333
dc.title.translatedDeterministické a stochastické epidemické modelycs_CZ
dc.contributor.refereeHlubinka, Daniel
dc.contributor.refereeDohnal, Gejza
dc.identifier.aleph001446166
thesis.degree.namePh.D.
thesis.degree.leveldoktorskécs_CZ
thesis.degree.disciplinePravděpodobnost a matematická statistikacs_CZ
thesis.degree.disciplineProbability and Mathematical Statisticsen_US
thesis.degree.programMathematicsen_US
thesis.degree.programMatematikacs_CZ
uk.thesis.typedizertační prácecs_CZ
uk.taxonomy.organization-csMatematicko-fyzikální fakulta::Katedra pravděpodobnosti a matematické statistikycs_CZ
uk.taxonomy.organization-enFaculty of Mathematics and Physics::Department of Probability and Mathematical Statisticsen_US
uk.faculty-name.csMatematicko-fyzikální fakultacs_CZ
uk.faculty-name.enFaculty of Mathematics and Physicsen_US
uk.faculty-abbr.csMFFcs_CZ
uk.degree-discipline.csPravděpodobnost a matematická statistikacs_CZ
uk.degree-discipline.enProbability and Mathematical Statisticsen_US
uk.degree-program.csMatematikacs_CZ
uk.degree-program.enMathematicsen_US
thesis.grade.csProspěl/acs_CZ
thesis.grade.enPassen_US
uk.abstract.enKermack-McKendrick model and its version with vaccination are presented. First, we introduce a model with vaccination and then a numerical study that includes comparison of di erent vaccination strategies and searching for optimal vaccination strategy is presented. We proceed to introduce a stochastic model with migration and consequently we suggest its generalization and prove the existence and uniqueness of a solution to the stochastic di erential equation (henceforth SDE) describing this model. Three stochastic versions of Kermack-McKendrick model with vaccination are suggested and compared. A procedure of nding the optimal vaccination strategy is presented. We also prove the theorem on the existence and uniqueness of a solution to the SDE that drives a model with multiple pathogens. Finally, the stochastic di erential equation describing the general model is presented. We study properties of a solution to this SDE and present sufficient conditions for the existence of a solution that is absorbed by the natural barrier of the model.en_US
uk.file-availabilityV
uk.publication.placePrahacs_CZ
uk.grantorUniverzita Karlova, Matematicko-fyzikální fakulta, Katedra pravděpodobnosti a matematické statistikycs_CZ
thesis.grade.codeP
dc.identifier.lisID990014461660106986


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