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        Pandemics: Insurance and Social Protection

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        Contributor(s)
        Boado-Penas, María del Carmen (editor)
        Eisenberg, Julia (editor)
        Şahin‬‬‬, Şule (editor)
        Collection
        Austrian Science Fund (FWF)
        Language
        English
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        Abstract
        This 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.
        URI
        https://library.oapen.org/handle/20.500.12657/51459
        Keywords
        Epidemics; Risk; Insurance; Social protection; Actuarial modelling; Open Access
        DOI
        10.1007/978-3-030-78334-1
        ISBN
        9783030783341, 9783030783341
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        2022
        Grantor
        • Austrian Science Fund - [grantnumber unknown]
        • University of Liverpool - [grantnumber unknown]
        Imprint
        Springer International Publishing
        Series
        Springer Actuarial,
        Classification
        Applied mathematics
        Probability and statistics
        Education
        Public international law: economic and trade
        Pages
        298
        Rights
        https://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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