03405nam a22005295i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001400153072001600167072002300183072001500206100007600221245019400297250001800491264007200509300006400581336002600645337002600671338003600697347002400733490005600757505026400813520102301077650001702100650001902117650002002136650001802156650002002174650003302194650002902227650001802256650004402274700008402318700008202402700007802484700007902562710003402641773002602675776003602701776003602737830005602773856004602829978-981-97-2539-7DE-He21320251030112612.0cr nn 008mamaa240703s2024    si |    s    |||| 0|eng d  a97898197253977 a10.1007/978-981-97-2539-72doi 4aT57-57.97 7aPBW2bicssc 7aMAT0030002bisacsh 7aPBW2thema1 aCunniffe, Nik.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut10aIdentifiability and Observability in Epidemiological Modelsh[electronic resource] :bA Primer /cby Nik Cunniffe, Frédéric Hamelin, Abderrahman Iggidr, Alain Rapaport, Gauthier Sallet.  a1st ed. 2024. 1aSingapore :bSpringer Nature Singapore :bImprint: Springer,c2024.  aXII, 108 p. 15 illus., 1 illus. in color.bonline resource.  atextbtxt2rdacontent  acomputerbc2rdamedia  aonline resourcebcr2rdacarrier  atext filebPDF2rda1 aSpringerBriefs on PDEs and Data Science,x2731-76090 aChapter 1 Introduction -- Chapter 2 Mathematical foundations -- Chapter 3 Analysis of the Kermack -- Chapter 4 McKendrick model -- Chapter 5 Observers synthesis -- Chapter 6 Practical and numerical considerations -- Chapter 7 Appendix -- Chapter 8 References.  aThis book introduces the concepts of identifiability and observability in mathematical epidemiology, as well as those of observers’ constructions. It first exposes and illustrates on several examples the mathematical definitions and properties of observability and identifiability. A chapter is dedicated to the well-known Kermack McKendrick model, for which the complete analysis of identifiability and observability is not available in the literature. Then, several techniques of observer constructions, in view of online estimation of state and parameters, are presented and deployed on several models. New developments relevant for applications in epidemiology are also given. Finally, practical considerations are discussed with data and numerical simulations related to models previously analysed in the book. The book will be appealing to epidemiological modellers and mathematicians working on models in epidemiology.This book contributes to Sustainable Development Goal 3 (SDG3): Good Health and Well Being. 0aMathematics. 0aSystem theory. 0aControl theory. 0aEpidemiology. 0aBiomathematics.14aApplications of Mathematics.24aSystems Theory, Control.24aEpidemiology.24aMathematical and Computational Biology.1 aHamelin, Frédéric.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aIggidr, Abderrahman.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aRapaport, Alain.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut1 aSallet, Gauthier.eauthor.4aut4http://id.loc.gov/vocabulary/relators/aut2 aSpringerLink (Online service)0 tSpringer Nature eBook08iPrinted edition:z978981972538008iPrinted edition:z9789819725403 0aSpringerBriefs on PDEs and Data Science,x2731-760940uhttps://doi.org/10.1007/978-981-97-2539-7