LEADER 06001nam 22004333 450 001 9910865281503321 005 20240607080433.0 010 $a3-031-56794-3 035 $a(MiAaPQ)EBC31369967 035 $a(Au-PeEL)EBL31369967 035 $a(CKB)32238789300041 035 $a(EXLCZ)9932238789300041 100 $a20240607d2024 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPredicting Pandemics in a Globally Connected World, Volume 2 $eToward a Multiscale, Multidisciplinary Framework Through Modeling and Simulation 205 $a1st ed. 210 1$aCham :$cSpringer International Publishing AG,$d2024. 210 4$dİ2024. 215 $a1 online resource (233 pages) 225 1 $aModeling and Simulation in Science, Engineering and Technology Series 311 $a3-031-56793-5 327 $aIntro -- Contents -- Evolutionary Virus Pandemics: From Modeling and Simulations to Society -- 1 Aims and Plan of the Chapter -- 2 On the Contents of the Edited Book -- 3 Reasonings on Research Perspectives -- References -- Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations -- 1 Introduction -- 2 Building Multiscale Models -- 2.1 Formulating Models of Tuberculosis and Linking Scales -- 2.2 Parameter Space Sampling for Model Simulation -- 2.3 Calibrating to Datasets Using Our CaliPro Method -- 3 Analyzing Multiscale Models -- 3.1 Uncertainty and Sensitivity -- 3.2 Tunable Resolution -- 3.3 Ten Rules for Model Credibility -- 4 Applying Multiscale Models: Generating Novel Outputs and Insights -- 4.1 Granuloma Dissemination -- 4.2 Drug Regimen Pharmacokinetics and Pharmacodynamics -- 4.3 Vaccination -- 4.4 Multiscale Intervention Design for Disease -- 5 Future Directions -- References -- The Use of Crowd Models for Risk Analysis During the Covid-19 Pandemic -- 1 Introduction -- 2 Proximity Analysis and Exposure Assessment -- 3 EXPOSED: A Model for Exposure Assessment -- 4 A Risk Analysis Methodology for the Use of Crowd Models -- 5 Case Study of Risk Analysis Methodology Application -- 5.1 The Stadium Layout -- 5.2 Application of the Methodology -- 6 Discussion -- 7 Conclusions -- References -- Modeling Household Effects in Epidemics -- 1 Introduction -- 2 Extended SIR Household Model -- 3 Basic Reproduction Number -- 4 Computing the Prevalence -- 5 A Graph Theoretic Approach to Household Infections -- 5.1 Household Graphs and Phase Transition -- 5.2 The Prevalence of the Graph Model -- 6 Computing the Peak of Infection -- 7 Simulations and Comparison with an Agent-Based Model -- 8 Effect of Household Quarantine -- References. 327 $aAn Analytic Look at the Last Pandemic's Spread and Its Control by Decision-Makers -- 1 Introduction -- 2 Agent-Based Modeling -- 3 COVID-19 Modeling -- 4 Results -- 4.1 Years of Life Lost -- 5 Discussion -- References -- A Time-Dependent SIRD Nonlinear Cross-Diffusion Epidemic Model: Multiscale Derivation and Computational Analysis -- 1 Introduction -- 2 Phenomenological Modeling of Nonlinear Cross-Diffusion Population Dynamics -- 3 From Micro-Scale to Macro-Scale Models -- 3.1 Kinetic Theory Model -- 3.2 The Equivalent Micro-Macro Formulation -- 4 Numerical Study in One-Dimensional Space -- 4.1 Semi-Implicit Time Discretization -- 4.2 Fully Discrete Asymptotic Preserving (AP) Scheme in 1D -- 4.3 Boundary Conditions -- 4.4 Numerical Simulations -- 4.4.1 Test 1: Asymptotic Preserving Property -- 4.4.2 Test 2: Time-Dependent Effect -- 4.4.3 Test 3: Self-Diffusion Effect -- 4.4.4 Test 4: Cross-Diffusion Effect -- 5 Numerical Study in Two-Dimensional Space -- 5.1 An Implicit Finite-Volume Scheme -- 5.2 Numerical Simulations -- 5.2.1 Example 1 -- 5.2.2 Example 2 -- 5.2.3 Example 3 -- 6 Conclusion and Perspectives -- References -- Managing an Epidemic Using Compartmental Models and Measure Differential Equations -- 1 Introduction -- 2 Coupled Systems of Controlled ODEs and MDE -- 2.1 Optimal Control for Coupled ODE-MDE Systems -- 3 MDE-ODE Adapted SIR-Type Model for Virus Mutations -- 3.1 Reinfection -- 4 Optimal Control -- 4.1 Numerics for Optimization -- 5 Simulations -- 5.1 Optimizing a Lockdown Schedule -- 5.2 Reinfection -- 6 Conclusion -- Appendix 1: Measure Differential Equations -- MDE for Finite Speed Diffusion -- Appendix 2: Proof of Theorem 5 -- References -- Complex Network Approaches for Epidemic Modeling: A Case Study of COVID-19 -- 1 Introduction -- 2 Formulation of the Complex Network Model -- 3 Analysis of the Network Model. 327 $a3.1 Positivity of the Solutions -- 3.2 The Basic Reproduction Number -- 3.3 Stability Analysis of the Model -- 4 Network Model Dynamics -- 4.1 A WS Network -- 4.2 A BA Scale-Free Network -- 4.3 Comparison of the Two Network Structures -- 5 Control and Immunization -- 5.1 Uniform Immunization Strategy -- 5.2 Optimized Immunization Strategies -- 5.3 Impact of Recovery Rates on Disease Prevalence -- 6 Discussion and Conclusion -- References -- How Vaccination Helps to Relax the Population Mobility: An Agent-Based Model Approach -- 1 Introduction -- 2 Methods -- 2.1 Model Description -- 2.2 Mobility of Agents -- 2.3 Vaccination Strategies -- 2.4 Basic Reproduction Number and Prevalence -- 2.5 Sensitivity Analysis -- 2.6 Optimization Method -- 3 Results -- 3.1 Different Age and Population Distributions -- 3.2 Sensitivity Analysis -- 3.3 Local Mobility Control -- 3.4 Different Mobility Levels -- 3.5 Optimization Outcomes -- 4 Discussion -- References. 410 0$aModeling and Simulation in Science, Engineering and Technology Series 700 $aAguiar$b Maira$01742462 701 $aBellomo$b Nicola$031305 701 $aChaplain$b Mark$0508835 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910865281503321 996 $aPredicting Pandemics in a Globally Connected World, Volume 2$94169232 997 $aUNINA