Computational epidemiology : data-driven modeling of COVID-19

• Material Type: 図書
• ISBN: 3030828891; 9783030828899
• Title: Computational epidemiology : data-driven modeling of COVID-19
• Author/Editor: Ellen Kuhl
• Author Heading: Kuhl, Ellen
• Publication, Distribution, etc.: Cham, Switzerland : Springer (出版)
• Publication Date: [2021]; 著作権日付 : ©2021
• Publication Date (W3CDTF): 2021
• Extent: xvi, 312 pages
• Other physical details: illustrations
• Size: 24 cm
• Place of Publication (Country Code): CH
• Text Language Code: eng
• Content Type: text
• Media Type: unmediated
• Carrier Type: volume
• Subject Heading: COVID-19 (Disease)--Epidemiology--Mathematical models; COVID-19--Épidémiologie--Modèles mathématiques
• LCC: RA644.C67
• NDLC: EG244
• Target Audience: 一般
• Note (Bibliography): Includes bibliographical references and index
• Holding library: 国立国会図書館
• Call No.: EG244-D162
• Data Provider (Database): 国立国会図書館 : 国立国会図書館蔵書; https://ndlsearch.ndl.go.jp
• Bibliographic ID (NDL): 031729819; http://id.ndl.go.jp/bib/031729819
• OCLC No.: 1259050347; https://www.worldcat.org/oclc/1259050347
• Cataloging Rule: RDA
• Bibliographic Record Category (NDL): 211

• Summary, etc.: This innovative textbook brings together modern concepts in mathematical epidemiology, computational modeling, physics-based simulation, data science,...