Global COVID-19 Research and Modeling : A Historical Record

• Autore: Cao Longbing
• Pubblicazione: Singapore : , : Springer Singapore Pte. Limited, , 2024; ©2024
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (409 pages)
• Disciplina: 614.5924144
• Nota di contenuto: Intro -- Preface -- Acknowledgments -- Contents -- Acronyms -- Notations -- List of Figures -- List of Tables -- 1 COVID-19 Characteristics and Complexities -- 1.1 COVID-19 Pandemic -- 1.2 Coronavirus and COVID-19 Complexities -- 1.3 COVID-19 Data Complexities -- 1.4 COVID-19 Modeling Complexities -- 1.5 Concluding Remarks -- 2 Review Objectives, Questions and Methods -- 2.1 Motivation and Objectives -- 2.1.1 Objectives for Overall Research Profiling -- 2.1.2 Objectives for Modeling Research Profiling -- 2.2 Review Questions -- 2.2.1 Review Questions for Overall Research -- 2.2.2 Review Questions for Modeling Research -- 2.3 Review Methods -- 2.3.1 Review Methods for Overall Research -- 2.3.2 Review Methods for Modeling Research -- 2.3.2.1 Review Scope -- 2.3.2.2 Modeling Methods -- 2.4 Publication Analysis Methods -- 2.4.1 Publication Analysis for Overall Research -- 2.4.2 Publication Analysis for Modeling Research -- 3 Highlights of the Findings -- 3.1 Highlights of the Findings of the Overall Research -- 3.2 Highlights of the Findings on the Modeling Research -- Part I Overall Research Profile -- 4 Overall Publication Collection and Processing -- 4.1 Publication Collection -- 4.1.1 COVID-19 Open Research Data Acquisition -- 4.1.2 Supplementary Information Collection -- 4.1.3 Collection of Publication Impact Metrics -- 4.1.3.1 The Literature Selection on COVID-19 Modeling -- 4.2 Publication Processing -- 4.2.1 Extracting Modeling Keywords -- 4.2.2 Categorizing Publication Disciplines -- 4.2.3 Extracting Modeling Publications -- 4.2.4 Extracting Global GDP and Population Data -- 4.2.5 Extracting COVID-19 Case Data -- 4.3 Evaluation Measures -- 4.3.1 Publication Impact Metrics -- 4.3.2 Composite Indicator (CI) -- 4.3.3 GDP per Capita -- 4.3.4 Publication-GDP Correlation Coefficient -- 4.3.5 Publication-COVID-19 Infection Correlation Coefficient. ; 5 COVID-19 Research Profile and Impact -- 5.1 Global Research Publication Profile -- 5.1.1 Overview of Research Publications -- 5.1.1.1 Total Publications -- 5.1.1.2 Publications by Discipline -- 5.1.1.3 Publications with Publication Date and First-author's Affiliated Country -- 5.1.1.4 Statistics on Publication Impacts -- 5.1.1.5 Mean Publication Impact in Major Disciplines -- 5.1.2 COVID-19 Research Publication Distribution -- 5.1.3 Word Cloud of COVID-19 Research Publications -- 5.2 COVID-19 Research Publication Impact -- 5.2.1 COVID-19 Research Publication Impact by Country's Composite Indicator -- 5.2.2 COVID-19 Research Publication Impact by H5-Index -- 5.2.3 Overall Research Publication Impact Per Impact Factor -- 5.2.4 COVID-19 Research Publication Impact Per CiteScore -- 5.2.5 COVID-19 Research Publication Impact by SNIP -- 5.2.6 COVID-19 Research Publication Impact by SJR -- 5.2.7 Top-10 Most Published Countries' Research Impact -- 5.2.8 Top-10 Most Published Countries' Research Impact by Discipline -- 5.3 Research Collaborations -- 5.4 Global research Co-authorship -- 5.4.1 Most Published Authors -- 5.4.2 Most Published Institutions with Identifiable Author Information -- 5.4.3 Co-authorship by Discipline -- 6 G20 and OECD Research Profile and Impact -- 6.1 G20 Publication Profile -- 6.1.1 G20 Countries/Regions' Publication Impact -- 6.1.2 G20 Countries/Regions' Publication Impact in Computer Science -- 6.1.3 G20 Countries/Regions' Publication Impact in Medical Science -- 6.1.4 G20 Countries/Regions' Publication Impact in Social Science -- 6.1.5 G20 Countries/Regions' Mean Publication Impact -- 6.2 OECD Publication Profile -- 6.2.1 OECD Countries' Mean Publication Impact -- 6.3 Box Plots of G20 and OECD Countries/Regions' Composite Indicator -- 6.3.1 Box Plots of G20 and OECD Countries/Regions' Paper-Averaged Composite Indicator. ; 6.3.2 Box Plots of G20 and OECD Countries/Regions' Daily-Averaged Cumulative Composite Indicator -- 6.3.3 Box Plots of G20 and OECD Countries/Regions' Monthly Paper-Averaged Composite Indicator -- 6.4 Box Plots of US and China's Monthly Paper-Averaged Composite Indicator -- 7 Correlations Between Research, the Economy and Infection -- 7.1 Correlation Between Research and the Economy -- 7.1.1 Global Correlation Between Publications and GDP Per Capita -- 7.1.2 Correlation Between G20 Publications and GDP Per Capita -- 7.1.3 Correlation Between OECD Publications and GDP Per Capita -- 7.2 Correlation Between Number of Publications and Infections -- 7.2.1 Global Correlation Between Number of Publications and Infections -- 7.2.2 Global Correlation Between Number of Publications and Deaths -- 7.2.3 Correlation Between Monthly Publications by Discipline and Number of Infections -- 7.2.4 Correlation Between Number of G20 Publications and Infections -- 7.2.5 Correlation Between Number of G20 Publications and Deaths -- 7.2.6 Correlation Between Number of Publications and Infections in OECD Countries -- 7.2.7 Correlation Between Number of OECD Publications and Deaths -- Part II Modeling Research Profile -- 8 Modeling Publication Collection and Processing -- 8.1 Meta-Synthetic and Meta-Analytical Review -- 8.2 Objectives of COVID-19 Modeling -- 8.3 Categorization of COVID-19 Modeling -- 9 Modeling Research Profile and Impact -- 9.1 Keyword Word Cloud Distributions -- 9.1.1 Keyword Word Cloud of Modeling Publications -- 9.1.2 Keyword Word Cloud of Modeling Publications in Computer Science -- 9.1.3 Keyword Word Cloud of Modeling Publications in Medical Science -- 9.1.4 Keyword Word Cloud of Modeling Publications in Social Science -- 9.1.5 Keyword Word Cloud of Modeling Publications from the US -- 9.1.6 Keyword Word Cloud of Modeling Publications from China. ; 9.1.7 Keyword Word Cloud of Modeling Publications from the EU -- 9.2 Top-k Research Trends -- 9.2.1 Top-50 Modeling Problems and Their Publication Impact -- 9.2.2 Top-50 Problems and Their Modeling Methods -- 9.2.3 Top-50 Modeling Methods and Their Publication Impact -- 9.2.4 Top-10 Monthly Problems of Concern in Modeling COVID-19 -- 9.2.5 Top-10 Problems of Concern in the Top-10 Most Published Countries -- 9.2.6 Top-10 Modeling Methods Applied by the Top-10 Most Published Countries -- 9.2.7 Top-10 Problems and Top-10 Modeling Methods by the Top-10 Most Published Countries -- 10 Modeling Methods -- 10.1 Mathematical Modeling -- 10.1.1 Time-series Analysis -- 10.1.1.1 Time-Series Models -- 10.1.1.2 Time-series Modeling -- 10.1.2 Statistical Modeling -- 10.1.2.1 Statistical Models -- 10.1.2.2 Statistical Analysis -- 10.2 Data-Driven Learning -- 10.2.1 Shallow and Deep Learning -- 10.2.2 Shallow Learning -- 10.2.3 Deep Learning -- 10.3 Domain-driven Modeling -- 10.3.1 Epidemic Modeling -- 10.3.1.1 Epidemiological Compartmental Models -- 10.3.1.2 Epidemiological Modeling -- 10.3.2 Medical and Biomedical Analyses -- 10.3.2.1 COVID-19 Infection Diagnosis, Test and Case Identification -- 10.3.2.2 Patient Risk and Prognosis Analyses -- 10.3.2.3 Medical Imaging Analyses -- 10.3.2.4 Pathological and Treatment Analyses and Drug Development -- 10.4 Influence and Impact Modeling -- 10.4.1 Modeling Intervention and Policy Effects -- 10.4.2 Modeling Psychological and Mental Impact -- 10.4.3 Modeling Economic Impact -- 10.4.4 Modeling Social Impact -- 10.5 Simulation Modeling -- 10.6 Hybrid Modeling -- Part III Examples: Modeling Techniques -- 11 Modeling Intervention, Vaccination, Mutation and Ethnic Condition Influence on Resurgence -- 11.1 Introduction -- 11.2 Data and Processing -- 11.3 Interaction and Simulation Models -- 11.4 Simulation and Forecasting Results. ; 11.4.1 Main Results -- 11.4.2 Additional Results -- 11.4.3 Findings and Insights -- 11.4.4 Discussion -- 11.5 Conclusions and Future Work -- 11.5.1 Concluding Remarks -- 11.5.2 Gaps and Opportunities -- 12 AISDR: AI and Data Science for Crisis and Disaster Resilience -- 12.1 Emergencies, Crises and Disasters -- 12.2 The ECD Landscape -- 12.3 From ECD Management to Resilience -- 12.3.1 Classic ECD Management -- 12.3.2 Smart ECD Resilience: The SDR Landscape -- 12.4 ECD Data and Complexities -- 12.4.1 ECD Data Sources -- 12.4.2 ECD Data Characteristics and Complexities -- 12.5 AISDR Research Landscape -- 12.5.1 AISDR Research Map -- 12.5.2 AISDR Research Tasks -- 13 Making Science Ready for Future Emergencies, Crises and Disasters -- 13.1 COVID-19 Modeling Gap Analyses -- 13.1.1 Limitations in COVID-19 Modeling Research -- 13.1.2 Gaps in Understanding the Nature of the COVID-19 Problem -- 13.1.3 Gaps in Modeling COVID-19 System Complexities -- 13.1.4 Gaps in Actionable COVID-19 Modeling and Validation -- 13.2 ECD Research Gap Analyses -- 13.2.1 ECD Research Review -- 13.2.2 Gap Analyses of ECD Research -- 13.3 Preparing for Future Emergencies, Crises and Disasters -- 13.3.1 Characterizing ECD Ecosystem Complexities -- 13.3.2 Enhancing Deep ECD Analytics and Learning -- 13.3.3 Exploring New Epidemic and ECD Modeling Opportunities -- 13.4 Future of AISDR -- 13.5 Concluding Remarks -- A List of Disciplinary Categorization -- B List of Predefined Modeling Keywords -- C List of COVID-19 Publication Metadata -- D List of Publication Impact Metrics -- E List of COVID-19 Publication Analysis Results -- F List of COVID-19 Public Data -- References -- Index.
• Titolo autorizzato: Global COVID-19 Research and Modeling
• ISBN: 981-9999-15-4
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910847087103321
• Lo trovi qui: Univ. Federico II
• Serie: Data Analytics Series