LEADER 03727nam 22005775 450 001 9910865281503321 005 20240709143703.0 010 $a9783031567940 010 $a3031567943 024 7 $a10.1007/978-3-031-56794-0 035 $a(MiAaPQ)EBC31369967 035 $a(Au-PeEL)EBL31369967 035 $a(CKB)32238789300041 035 $a(DE-He213)978-3-031-56794-0 035 $a(OCoLC)1438673326 035 $a(EXLCZ)9932238789300041 100 $a20240604d2024 u| 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 $eToward a Multiscale, Multidisciplinary Framework through Modeling and Simulation /$fedited by Maira Aguiar, Nicola Bellomo, Mark Chaplain 205 $a1st ed. 2024. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Birkhäuser,$d2024. 215 $a1 online resource (233 pages) 225 1 $aModeling and Simulation in Science, Engineering and Technology,$x2164-3725 311 08$a9783031567933 311 08$a3031567935 327 $aChapter. 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. 330 $aIn an increasingly globally-connected world, the ability to predict, monitor, and contain pandemics is essential to ensure the health and well-being of all. This contributed volume investigates several mathematical techniques for the modeling and simulation of viral pandemics, with a special focus on COVID-19. Modeling a pandemic requires an interdisciplinary approach with other fields such as epidemiology, virology, immunology, and biology in general. Spatial dynamics and interactions are also important features to be considered, and a multiscale framework is needed at the societal level, the level of individuals, and the level of virus particles and the immune system. Chapters in this volume explore the latest research related to these items to demonstrate the utility of a variety of mathematical methods. Perspectives for the future are also offered. 410 0$aModeling and Simulation in Science, Engineering and Technology,$x2164-3725 606 $aBiomathematics 606 $aMathematical models 606 $aMathematical and Computational Biology 606 $aMathematical Modeling and Industrial Mathematics 615 0$aBiomathematics. 615 0$aMathematical models. 615 14$aMathematical and Computational Biology. 615 24$aMathematical Modeling and Industrial Mathematics. 676 $a570,285 700 $aAguiar$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