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2000 Years of Pandemics : Past, Present, and Future / / by Claudia Ferreira, Marie-Françoise J. Doursout, Joselito S. Balingit
| 2000 Years of Pandemics : Past, Present, and Future / / by Claudia Ferreira, Marie-Françoise J. Doursout, Joselito S. Balingit |
| Autore | Ferreira Claudia <1955-> |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
| Descrizione fisica | 1 online resource (416 pages) |
| Disciplina |
306.461
362.1969 |
| Soggetto topico |
Internal medicine
Public health Epidemiology Emergency medical services Family medicine Internal Medicine Public Health Emergency Services General Practice and Family Medicine Epidèmies Epidemiologia Salut pública Història |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-10035-2 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Introduction. Part-1: Pandemic in the past -- First 1000 Years -- Black Death -- Outbreaks in the new World -- Syphilis, Cholera, and Yellow Fever -- Part-2: Pandemics In The Present -- The World Since 1900: Background to Pandemics in the Present -- Influenza Pandemics -- Coronavirus Pandemics -- Human Immunodeficiency Virus (HIV) -- Vaccines -- Zoonoses -- The Next Pandemic -- The Next Pandemic: Hemorrhagic Fevers -- Part-3:The Next Pandemic: Bioterrorism -- The Next Pandemic: Climate Change -- The Next Pandemic: Antibiotic Resistance -- The Next Pandemic: Challenges and Hopes. |
| Record Nr. | UNINA-9910659484503321 |
Ferreira Claudia <1955->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Artificial Intelligence in Covid-19 / / edited by Niklas Lidströmer, Yonina C. Eldar
| Artificial Intelligence in Covid-19 / / edited by Niklas Lidströmer, Yonina C. Eldar |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (346 pages) |
| Disciplina |
362.1962414
362.19624140028563 |
| Collana | Medicine Series |
| Soggetto topico |
Medicine
Artificial intelligence Virology Immunology Epidemiology Clinical Medicine Artificial Intelligence COVID-19 Epidèmies Processament de dades Informàtica mèdica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-031-08506-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 AI and Pooling Tests for COVID-19 -- 2 AI for Drug Repurposing in the Pandemic Response -- 3 AI and Point Of Care Image Analysis For COVID-19 -- 4 Machine Learning and Laboratory Values in the Diagnosis, Prognosis and Vaccination Strategy of COVID-19 -- 5 AI and the Infectious Medicine of COVID-19 -- 6 AI and ICU Monitoring in COVID-19 -- 7 Symptom Based Detection Models of COVID-19 Infection Using AI -- 8 AI Techniques for Forecasting Epidemic Dynamics: Theory and Practice -- 9 Regulatory Aspects on AI and Pharmacovigilance for COVID-19 -- 10 AI and the Clinical Immunology / Immunoinformatics for COVID-19 -- 11 AI, Epidemiology and Public Health in the Covid Pandemic -- 12 AI and Dynamic Sepsis Prediction in Covid-19. |
| Record Nr. | UNINA-9910624309003321 |
| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Epidemics : models and data using R / / Ottar N. Bjørnstad
| Epidemics : models and data using R / / Ottar N. Bjørnstad |
| Autore | Bjørnstad Ottar N. |
| Edizione | [Second edition] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (386 pages) |
| Disciplina | 616.9 |
| Collana | Use R! |
| Soggetto topico |
Communicable diseases
Epidemics Epidemics - statistics & numerical data Communicable Diseases Software Epidèmies Malalties infeccioses Processament de dades R (Llenguatge de programació) |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031120565
9783031120558 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910634047503321 |
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Bjørnstad Ottar N.
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| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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The Ethical, Legal and Social Issues of Pandemics : An Analysis from the EU Perspective / / by Iñigo de Miguel Beriain
| The Ethical, Legal and Social Issues of Pandemics : An Analysis from the EU Perspective / / by Iñigo de Miguel Beriain |
| Autore | Miguel Beriain Iñigo de <1972-> |
| Edizione | [1st ed. 2022.] |
| Pubbl/distr/stampa | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 |
| Descrizione fisica | 1 online resource (160 pages) |
| Disciplina |
363.349
344.2404369 |
| Collana | Medicine Series |
| Soggetto topico |
Medical policy
Medical ethics Medical laws and legislation Health Policy Medical Ethics Medical Law Epidèmies Política governamental Condicions socials Ètica |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031038181
9783031038174 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1.Confinement, isolation and tracking -- 2.Immunity Certificates: The New Frontier -- 3.Vaccines (I). Creation and distribution -- 4.Vaccination (II). Vaccination policies -- 5.Triage: when the tsunami hits. . |
| Record Nr. | UNINA-9910574859603321 |
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Miguel Beriain Iñigo de <1972->
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| Cham : , : Springer International Publishing : , : Imprint : Springer, , 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin
| Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin |
| Autore | Boado-Penas María del Carmen |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (xx, 298 pages) : illustrations (some color) |
| Altri autori (Persone) |
Boado-PenasMaría del Carmen
EisenbergJulia ŞahinŞule |
| Collana | Springer Actuarial |
| Soggetto topico |
Epidemics
Insurance - Mathematical models Insurance - Statistical methods Social security Assegurances Models matemàtics Estadística matemática Seguretat social Epidèmies |
| Soggetto genere / forma | Llibres electrònics |
| Soggetto non controllato |
Epidemics
Risk Insurance Social protection Actuarial modelling Open Access |
| ISBN | 3-030-78334-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- 1 COVID-19: A Trigger for Innovations in Insurance? -- 1.1 Introduction -- 1.2 Discussions from the Perspective of Insurance and Social Protection -- 1.2.1 Commercial Insurance -- 1.2.2 The Role of the Governments and Social Protection -- 1.3 Listening to the Wind of Change -- References -- 2 Epidemic Compartmental Models and Their Insurance Applications -- 2.1 Introduction -- 2.2 Compartmental Models in Epidemiology -- 2.2.1 SIR Model -- 2.2.2 Other Compartmental Models -- 2.3 Epidemic Insurance
2.3.1 Annuities and Insurance Benefits -- 2.3.2 Reserves -- 2.3.3 Further Extensions -- 2.3.4 Case Studies: COVID-19 -- 2.4 Resource Management -- 2.4.1 Pillar I: Regional and Aggregate Resources Demand Forecast -- 2.4.2 Pillar II: Centralised Stockpiling and Distribution -- 2.4.3 Pillar III: Centralised Resources Allocation -- 2.5 Conclusion -- References -- 3 Some Investigations with a Simple Actuarial Model for Infections Such as COVID-19 -- 3.1 Introduction -- 3.2 Multiple State Actuarial Models -- 3.3 A Simple Daily Model for Infection -- 3.4 Comparisons with the SIR Model 3.5 Enhancements for COVID-19 and Initial Assumptions -- 3.6 Estimating Parameters Model 1 -- 3.7 Estimating Parameters Model 2 -- 3.8 Comments on Results of Models 1 and 2 -- 3.9 Further Extensions: Models 3 and 4 -- 3.10 Comments on Results of Models 3 and 4 -- 3.11 Projection Models -- 3.12 Problems and Unknowns -- 3.13 Other Countries -- 3.14 Conclusions -- References -- 4 Stochastic Mortality Models and Pandemic Shocks -- 4.1 Stochastic Mortality Models and the COVID-19 Shock -- 4.2 The Impact of COVID-19 on Mortality Rates 4.3 Stochastic Mortality Models and Pandemics: Single-Population Models -- 4.3.1 Discrete-Time Single Population Models -- 4.3.2 Continuous-Time Single-Population Models -- 4.4 Stochastic Mortality Models and Pandemics: Multi-population -- 4.4.1 Discrete-Time Models -- 4.4.2 Continuous-Time Models -- 4.5 A Continuous-Time Multi-population Model with Jumps -- 4.6 Conclusions -- References -- 5 A Mortality Model for Pandemics and Other Contagion Events -- 5.1 Introduction -- 5.2 Highlights of Methodology and Findings -- 5.2.1 Summary of Methodology -- 5.2.2 Summary of Findings 5.3 Semiparametric Regression in MCMC -- 5.3.1 MCMC Parameter Shrinkage -- 5.3.2 Spline Regressions -- 5.3.3 Why Shrinkage? -- 5.3.4 Cross Validation in MCMC -- 5.4 Model Details -- 5.4.1 Formulas -- 5.4.2 Fitting Process -- 5.5 Results -- 5.5.1 Extensions: Generalisation, Projections and R Coding -- 5.6 Conclusions -- References -- 6 Risk-Sharing and Contingent Premia in the Presence of Systematic Risk: The Case Study of the UK COVID-19 Economic Losses -- 6.1 Introduction -- 6.2 Risk Levels and Systematic Risk in Insurance -- 6.3 Mathematical Setup -- 6.3.1 Probability Space 6.3.2 Insurance Preliminaries |
| Altri titoli varianti | Pandemics |
| Record Nr. | UNISA-996466419903316 |
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Boado-Penas María del Carmen
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| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin
| Pandemics : insurance and social protection / / editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin |
| Autore | Boado-Penas María del Carmen |
| Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
| Descrizione fisica | 1 online resource (xx, 298 pages) : illustrations (some color) |
| Altri autori (Persone) |
Boado-PenasMaría del Carmen
EisenbergJulia ŞahinŞule |
| Collana | Springer Actuarial |
| Soggetto topico |
Epidemics
Insurance - Mathematical models Insurance - Statistical methods Social security Assegurances Models matemàtics Estadística matemàtica Seguretat social Epidèmies |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-78334-0 |
| Classificazione | EDU000000LAW014000MAT003000MAT029000 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Contributors -- 1 COVID-19: A Trigger for Innovations in Insurance? -- 1.1 Introduction -- 1.2 Discussions from the Perspective of Insurance and Social Protection -- 1.2.1 Commercial Insurance -- 1.2.2 The Role of the Governments and Social Protection -- 1.3 Listening to the Wind of Change -- References -- 2 Epidemic Compartmental Models and Their Insurance Applications -- 2.1 Introduction -- 2.2 Compartmental Models in Epidemiology -- 2.2.1 SIR Model -- 2.2.2 Other Compartmental Models -- 2.3 Epidemic Insurance
2.3.1 Annuities and Insurance Benefits -- 2.3.2 Reserves -- 2.3.3 Further Extensions -- 2.3.4 Case Studies: COVID-19 -- 2.4 Resource Management -- 2.4.1 Pillar I: Regional and Aggregate Resources Demand Forecast -- 2.4.2 Pillar II: Centralised Stockpiling and Distribution -- 2.4.3 Pillar III: Centralised Resources Allocation -- 2.5 Conclusion -- References -- 3 Some Investigations with a Simple Actuarial Model for Infections Such as COVID-19 -- 3.1 Introduction -- 3.2 Multiple State Actuarial Models -- 3.3 A Simple Daily Model for Infection -- 3.4 Comparisons with the SIR Model 3.5 Enhancements for COVID-19 and Initial Assumptions -- 3.6 Estimating Parameters Model 1 -- 3.7 Estimating Parameters Model 2 -- 3.8 Comments on Results of Models 1 and 2 -- 3.9 Further Extensions: Models 3 and 4 -- 3.10 Comments on Results of Models 3 and 4 -- 3.11 Projection Models -- 3.12 Problems and Unknowns -- 3.13 Other Countries -- 3.14 Conclusions -- References -- 4 Stochastic Mortality Models and Pandemic Shocks -- 4.1 Stochastic Mortality Models and the COVID-19 Shock -- 4.2 The Impact of COVID-19 on Mortality Rates 4.3 Stochastic Mortality Models and Pandemics: Single-Population Models -- 4.3.1 Discrete-Time Single Population Models -- 4.3.2 Continuous-Time Single-Population Models -- 4.4 Stochastic Mortality Models and Pandemics: Multi-population -- 4.4.1 Discrete-Time Models -- 4.4.2 Continuous-Time Models -- 4.5 A Continuous-Time Multi-population Model with Jumps -- 4.6 Conclusions -- References -- 5 A Mortality Model for Pandemics and Other Contagion Events -- 5.1 Introduction -- 5.2 Highlights of Methodology and Findings -- 5.2.1 Summary of Methodology -- 5.2.2 Summary of Findings 5.3 Semiparametric Regression in MCMC -- 5.3.1 MCMC Parameter Shrinkage -- 5.3.2 Spline Regressions -- 5.3.3 Why Shrinkage? -- 5.3.4 Cross Validation in MCMC -- 5.4 Model Details -- 5.4.1 Formulas -- 5.4.2 Fitting Process -- 5.5 Results -- 5.5.1 Extensions: Generalisation, Projections and R Coding -- 5.6 Conclusions -- References -- 6 Risk-Sharing and Contingent Premia in the Presence of Systematic Risk: The Case Study of the UK COVID-19 Economic Losses -- 6.1 Introduction -- 6.2 Risk Levels and Systematic Risk in Insurance -- 6.3 Mathematical Setup -- 6.3.1 Probability Space 6.3.2 Insurance Preliminaries |
| Altri titoli varianti | Pandemics |
| Record Nr. | UNINA-9910504284203321 |
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Boado-Penas María del Carmen
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| Cham, : Springer International Publishing AG, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain
| Predicting pandemics in a globally connected world . Volume 1 : toward a multiscale, multidisciplinary framework through modeling and simulation / / edited by Nicola Bellomo and Mark A. J. Chaplain |
| Pubbl/distr/stampa | Cham, Switzerland : , : Birkhäuser, , [2022] |
| Descrizione fisica | 1 online resource (314 pages) |
| Disciplina | 016.36229 |
| Collana | Modeling and Simulation in Science, Engineering and Technology |
| Soggetto topico |
Epidemiology - Mathematical models
Epidèmies COVID-19 Models matemàtics |
| Soggetto genere / forma | Llibres electrònics |
| ISBN | 3-030-96562-7 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Modelling, Simulations, and Social Impact of Evolutionary Virus Pandemics -- 1 Aims and Plan of the Chapter -- 2 On the Contents of the Edited Book -- 3 Reasonings on Research Perspectives -- References -- Understanding COVID-19 Epidemics: A Multi-Scale ModelingApproach -- 1 Introduction -- 2 Mathematical Modeling Applied to Infectious Diseases: COVID-19 as a Case Study -- 2.1 The SIR and SHAR Models -- 2.2 The SHARUCD Modeling Framework -- 2.3 Modeling the Implementation of Control Measures -- 2.4 The Refined SHARUCD Model -- 2.4.1 Further Refinements: Detection Rate and Import -- 3 KTAP Modeling Framework -- 3.1 Modeling Contagion, Progression, and Recovery -- 3.2 Application of the KTAP Model to Selected Case Studies -- 3.2.1 Effect of Lockdown Measures and Restrictions Lifting -- 3.2.2 Effect of Heterogeneity -- 4 Discussion -- References -- Kinetic Modelling of Epidemic Dynamics: Social Contacts, Control with Uncertain Data, and Multiscale Spatial Dynamics -- 1 Introduction -- 2 Kinetic Modelling of Social Heterogeneity in Epidemic Dynamics -- 2.1 Modelling Contact Heterogeneity -- 2.1.1 Kinetic Model for Contact Formation -- 2.1.2 Quasi-Invariant Scaling and Steady States -- 2.1.3 The Macroscopic Social-SIR Dynamics -- 2.1.4 A Social-SIR Model with Saturated Incidence Rate -- 2.1.5 Extrapolation of the Shape of the Incidence Rate from Data -- 2.2 The Interplay Between Economy and the Pandemic -- 2.2.1 Wealth Exchanges in Epidemic Modelling -- 2.2.2 Fokker-Planck Scaling and Steady States -- 2.2.3 The Formation of Bimodal Wealth Distributions -- 2.2.4 The Increase of Wealth Inequalities -- 3 Social Control and Data Uncertainty -- 3.1 Control of Socially Structured Models -- 3.1.1 Optimal Control Formulation -- 3.1.2 Feedback Controlled Compartmental Models.
3.1.3 Containment in Homogeneous Social Mixing Dynamics -- 3.2 Dealing with Data Uncertainty -- 3.2.1 Feedback Controlled and Socially Structured Models with Uncertain Inputs -- 3.2.2 Application to the COVID-19 Outbreak -- 4 Multiscale Transport Models -- 4.1 Spatial Dynamics on Networks -- 4.1.1 1D Hyperbolic Compartmental Model -- 4.1.2 Macroscopic Formulation and Diffusion Limit -- 4.1.3 Extension to Multi-Compartmental Modelling -- 4.1.4 Network Modelling -- 4.1.5 Effect of Spatially Heterogeneous Environments in Hyperbolic and Parabolic Configuration -- 4.1.6 Application to the Emergence of COVID-19 in Italy -- 4.2 Realistic Geographical Settings -- 4.2.1 2D Kinetic Transport Model -- 4.2.2 Macroscopic Formulation and Diffusion Limit -- 4.2.3 Extension to Multi-Compartmental Modelling -- 4.2.4 Application to the Spatial Spread of COVID-19 in Italy in Emilia-Romagna and Lombardy Region -- 5 Concluding Remarks and Research Perspectives -- 5.1 Data sources -- References -- The COVID-19 Pandemic Evolution in Hawai`i and New Jersey: A Lesson on Infection Transmissibility and the Role of HumanBehavior -- 1 Introduction -- 2 Mathematical Models -- 2.1 Agent-Based Models -- 2.1.1 COVID-19 Agent-Based Simulator (Covasim) -- 2.2 Compartmental SEIR Models and Variants -- 2.3 Comparison of Agent-Based and Compartmental Models -- 3 Archipelagos and Islands -- 3.1 March 2020-June 2021 -- 3.1.1 CM Model Fit from March 06, 2020 to January 15, 2021 -- 3.1.2 Comparing CM and ABM Models -- 3.2 July 2021-September 2021 -- 3.3 Discussion -- 4 The Pandemic Waves in New Jersey -- 4.1 Comparing New Jersey to the US -- 4.2 Spatial and Temporal Patterns in COVID-19 Cases in New Jersey -- 4.3 Sociodemographic Variables -- 4.4 Discussion -- 5 The Use of Compartmental Models in New Jersey -- 5.1 Time-Evolution of the Basic Reproduction Number. 5.2 Infected Confirmed Cases, Hospitalizations, and Deaths -- 5.3 Discussion -- 6 Conclusion -- References -- A Novel Point Process Model for COVID-19: Multivariate Recursive Hawkes Process -- 1 Introduction -- 1.1 Hawkes Point Process Modeling of Infectious Diseases -- 1.2 Multivariate Hawkes Processes -- 1.3 Recursive Hawkes Processes -- 1.4 Outline -- 2 Theoretical Properties of Temporal Multivariate Recursive Hawkes Models -- 2.1 Existence -- 2.2 Mean -- 2.3 Variance -- 3 Parameter Fitting and Simulation Algorithms -- 3.1 Parameter Fitting Algorithms -- 3.1.1 Parametric (or Semi-parametric) Estimation -- 3.1.2 Temporal Version of Parameter Fitting Algorithms -- 3.2 Simulation Algorithm -- 4 Reconstruct Multivariate Point Process from Data with Imprecise Time -- 4.1 Time Reconstruction -- 4.2 Category Index Reconstruction -- 5 Numerical Experiments and Results -- 5.1 Synthetic Data Sets -- 5.1.1 Comparison Between Parametric Fitting and Non-parametric Fitting -- 5.1.2 Verification of the Parameter Fitting Algorithm -- 5.1.3 Experiments About Data Sets with Imprecise Time -- 5.2 Experiments on Real COVID-19 Data -- 5.2.1 Model Validation -- 5.2.2 Prediction Based on MRHP and Historical Information -- 6 Conclusion -- References -- Multiscale Aspects of Virus Dynamics -- 1 Introduction -- 1.1 On the Biology of the Virus -- 1.2 Modeling the Complexity of COVID-19 -- 2 Epistemic and Empirical Uncertainties in Compartmental and Individual-Based Models -- 2.1 SIR Model -- 2.2 Individual-Based Interpretation of λ -- 2.3 An Example of Modified SIR Model -- 2.4 Individuals Behind the Modified SIR Model -- 2.5 Time-Discretization -- 3 The Individual-Based Model of FlaLaFauciRiva -- 3.1 A Formula for the Parameter λ of Compartmental Models -- 3.2 Analysis of the Fluctuations -- 3.3 Simulations -- 3.4 Presence of Immunized Population and Virus Variants. Appendix -- References -- Productivity in Times of Covid-19: An Agent-Based Model Approach -- 1 Introduction -- 2 Model -- 3 Mean Field Approximation -- 4 Setting the Model Functions -- 5 Simulations -- 6 Conclusion -- References -- Transmission Dynamics and Quarantine Control of COVID-19 in Cluster Community -- 1 Introduction -- 2 Mathematical Modeling -- 2.1 Stage 1: SEIR-Type Model Without Quarantine -- 2.2 Stage 2: Transmission-Quarantine (TQ) Model -- 3 Analytic Results and Case Study for Emerging Stage -- 3.1 Analytic Results -- 3.2 A Real World Case Study for Stage 1 -- 4 Case Study and Sensitivity Analysis for Quarantine Stage -- 4.1 A Real World Study for Stage 2 -- 4.2 Sensitivity Analysis -- 5 Discussion -- Appendix: Proofs of Theorems -- References -- A 2D Kinetic Model for Crowd Dynamics with Disease Contagion -- 1 Introduction -- 2 A Simplified Two-Dimensional Kinetic Model -- 3 Discretization in Space and Time -- 4 Numerical Results -- 4.1 Tests with v = 0 -- 4.2 Tests with Prescribed Walking Velocity -- 5 A More Complex 2D Kinetic Model -- 6 Conclusions -- References -- Multiscale Derivation of a Time-Dependent SEIRD Reaction-Diffusion System for COVID-19 -- 1 Introduction -- 2 Phenomenological Modeling of Diffusion Population Dynamics -- 3 From Kinetic Theory Model to SEIRD Reaction-Diffusion System -- 3.1 Kinetic Theory Model -- 3.2 Micro-Macro Formulation -- 4 Numerical Method -- 4.1 Semi-Implicit Time Discretization -- 4.2 Fully Discrete Asymptotic Preserving Numerical Scheme in 1D -- 4.3 Boundary Conditions -- 5 Numerical Results -- 5.1 Test 1: Asymptotic Preserving Numerical Scheme Property -- 5.2 Test 2: Diffusion Effect -- 5.3 Test 3: Role of the Transmission Function -- 6 Conclusion and Perspectives -- References. |
| Record Nr. | UNISA-996490344003316 |
| Cham, Switzerland : , : Birkhäuser, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
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Predicting Pandemics in a Globally Connected World, Volume 2 : Toward a Multiscale, Multidisciplinary Framework through Modeling and Simulation / / edited by Maira Aguiar, Nicola Bellomo, Mark Chaplain
| Predicting Pandemics in a Globally Connected World, Volume 2 : Toward a Multiscale, Multidisciplinary Framework through Modeling and Simulation / / edited by Maira Aguiar, Nicola Bellomo, Mark Chaplain |
| Autore | Aguiar Maira |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Birkhäuser, , 2024 |
| Descrizione fisica | 1 online resource (233 pages) |
| Disciplina | 570,285 |
| Altri autori (Persone) |
BellomoN
ChaplainMark |
| Collana | Modeling and Simulation in Science, Engineering and Technology |
| Soggetto topico |
Biomathematics
Mathematical models Mathematical and Computational Biology Mathematical Modeling and Industrial Mathematics COVID-19 Models matemàtics Epidèmies |
| Soggetto genere / forma | Llibres electrònics |
| ISBN |
9783031567940
3031567943 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter. 1. Evolutionary Virus Pandemics: From modeling and Simulations to Society -- Chapter. 2. Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations -- Chapter. 3. The use of crowd models for risk analysis during the Covid-19 pandemic -- Chapter. 4. Modeling household effects in epidemics -- Chapter. 5. An analytic look at the last pandemic’s spread and its control by decision-makers -- Chapter. 6. A time-dependent SIRD nonlinear cross-diffusion dpidemic model: Multiscale derivation and computational analysis -- Chapter. 7. Optimal control of an epidemic using compartmental models and measure differential equations -- Chapter. 8. Complex network approaches for epidemic modeling: a case study of COVID-19 -- Chapter. 9. How vaccination helps to relax the population mobility: an agent-based model approach. |
| Record Nr. | UNINA-9910865281503321 |
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Aguiar Maira
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| Cham : , : Springer Nature Switzerland : , : Imprint : Birkhäuser, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Soggetto topico
-
Epidèmies
(8)
- Models matemàtics (4)
- COVID-19 (3)
- Epidemics (3)
- Assegurances (2)