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020 _a9783030783341
_9978-3-030-78334-1
024 7 _a10.1007/978-3-030-78334-1
_2doi
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072 7 _aKFFN
_2bicssc
072 7 _aMAT003000
_2bisacsh
072 7 _aKFFN
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082 0 4 _a368.01
_223
245 1 0 _aPandemics: Insurance and Social Protection
_h[electronic resource] /
_cedited by María del Carmen Boado-Penas, Julia Eisenberg, Şule Şahin‬‬‬.
250 _a1st ed. 2022.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2022.
300 _aXX, 298 p. 51 illus., 45 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Actuarial,
_x2523-3270
505 0 _aM.C. Boado-Penas, J. Eisenberg, Ş. Şahin: Covid-19: a trigger for innovations in insurance?.-Jose Garrido: Compartment models.-David Wilkie: On a dynamic epidemiological actuarial model -- Andrew Cairns: Changes in mortality during a pandemic -- Gary Venter: Mortality models with contagion -- Diagnostic tests and procedures during a pandemic -- Matthew Aldridge: Group tests -- Gustavo Demarco and Fiona Stewart: On World Bank’s pandemic emergency financial facilities -- Hirbod Assa & Tim Boonen: Mathematical modelling of catastrophe bonds -- Nuria Badenes Pla: Behaviouristic aspects, obedience to the introduced measures in different countries.-Alexia Fürnkranz-Prskawetz:The optimal length and severity of a lockdown.-Peter Filzmoser: The optimal length and severity of a lockdown -- Rachel Hillier:Pandemic related legal problems.-Frank Schiller:Anactuary's opinion. ,.
506 0 _aOpen Access
520 _aThis 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.
650 0 _aActuarial science.
650 0 _aMathematical statistics.
650 0 _aProbabilities.
650 0 _aWelfare economics.
650 0 _aLaw and economics.
650 1 4 _aActuarial Mathematics.
650 2 4 _aMathematical Statistics.
650 2 4 _aProbability Theory.
650 2 4 _aSocial Economy.
650 2 4 _aLaw and Economics.
700 1 _aBoado-Penas, María del Carmen.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aEisenberg, Julia.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aŞahin‬‬‬, Şule.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030783334
776 0 8 _iPrinted edition:
_z9783030783358
776 0 8 _iPrinted edition:
_z9783030783365
830 0 _aSpringer Actuarial,
_x2523-3270
856 4 0 _uhttps://doi.org/10.1007/978-3-030-78334-1
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
912 _aZDB-2-SOB
999 _c37749
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