06253nam 22008413u 450 991050428420332120231110213009.03-030-78334-0(CKB)5340000000068536EBL6790721(OCoLC)1313887644(AU-PeEL)EBL6790721(MiAaPQ)EBC6790721(oapen)https://directory.doabooks.org/handle/20.500.12854/72814(PPN)258299983(EXLCZ)99534000000006853620220617d2021|||| uy 0engur|n|---|||||txtrdacontentcrdamediacrrdacarrierPandemics insurance and social protection /editors, María del Carmen Boado-Penas, Julia Eisenberg, Şule ŞahinCham Springer International Publishing AG20211 online resource (xx, 298 pages) illustrations (some color)Springer Actuarial Description based upon print version of record.3-030-78333-2 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 Insurance2.3.1 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 Model3.5 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 Rates4.3 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 Findings5.3 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 Space6.3.2 Insurance PreliminariesThis open access book collects expert contributions on actuarial modelling and related topics, from machine learning to legal aspects, and reflects on possible insurance designs during an epidemic/pandemic. Starting by considering the impulse given by COVID-19 to the insurance industry and to actuarial research, the text covers compartment models, mortality changes during a pandemic, risk-sharing in the presence of low probability events, group testing, compositional data analysis for detecting data inconsistencies, behaviouristic aspects in fighting a pandemic, and insurers' legal problems, amongst others. Concluding with an essay by a practicing actuary on the applicability of the methods proposed, this interdisciplinary book is aimed at actuaries as well as readers with a background in mathematics, economics, statistics, finance, epidemiology, or sociology.Springer Actuarial PandemicsEpidemicsInsuranceMathematical modelsInsuranceStatistical methodsSocial securityAssegurancesthubModels matemàticsthubEstadística matemáticathubSeguretat socialthubEpidèmiesthubLlibres electrònicsthubEpidemicsRiskInsuranceSocial protectionActuarial modellingOpen AccessEpidemics.InsuranceMathematical models.InsuranceStatistical methods.Social security.AssegurancesModels matemàticsEstadística matemáticaSeguretat socialEpidèmiesBoado-Penas María del Carmenedt1235584Boado-Penas María del Carmen1235584Eisenberg Julia1235585Şahin‬‬‬ Şule1235586AU-PeELAU-PeELAU-PeELBOOK9910504284203321Pandemics2869611UNINA