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Coordination of Epidemic Control Policies: A Game Theoretic Perspective

Identifieur interne : 000128 ( Hal/Corpus ); précédent : 000127; suivant : 000129

Coordination of Epidemic Control Policies: A Game Theoretic Perspective

Auteurs : Lorenzo Maggi ; Francesco De Pellegrini ; Alexandre Reiffers ; Jean-Jacques Herings ; Eitan Altman

Source :

RBID : Hal:hal-01069087

Abstract

We consider two neighbouring countries in which a pandemic disease spreads. Countries face a trade-off between the social costs of the epidemic diffusion and the monetary costs in order to avoid the insurgence of pandemics. However, due to migration of people across countries, the treatment efforts by one country generate a positive externality for the neighbouring country. Both countries can negotiate on the healthcare cost that each has to sustain. But, they do so subject to a central authority (CA) who can impose penalties to both countries whenever they cannot reach an agreement. We analyse the outcome of such situation via the Nash bargaining concept. Next we show how the CA should design penalties to i) ensure that revealing the true migration flow data is a self-enforcing behaviour, and to ii) enforce that the NB solution adheres to certain fairness properties.


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<p>We consider two neighbouring countries in which a pandemic disease spreads. Countries face a trade-off between the social costs of the epidemic diffusion and the monetary costs in order to avoid the insurgence of pandemics. However, due to migration of people across countries, the treatment efforts by one country generate a positive externality for the neighbouring country. Both countries can negotiate on the healthcare cost that each has to sustain. But, they do so subject to a central authority (CA) who can impose penalties to both countries whenever they cannot reach an agreement. We analyse the outcome of such situation via the Nash bargaining concept. Next we show how the CA should design penalties to i) ensure that revealing the true migration flow data is a self-enforcing behaviour, and to ii) enforce that the NB solution adheres to certain fairness properties.</p>
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<ptr type="url" target="http://researchers-sbe.unimaas.nl/jeanjacquesherings/"></ptr>
<idno type="halauthorid">1078845</idno>
<affiliation ref="#struct-253509"></affiliation>
</author>
<author role="aut">
<persName>
<forename type="first">Eitan</forename>
<surname>Altman</surname>
</persName>
<email type="md5">effebdfe9210cdaa22207de13a027855</email>
<email type="domain">inria.fr</email>
<idno type="halauthorid">51805</idno>
<affiliation ref="#struct-2465"></affiliation>
</author>
</analytic>
<monogr>
<meeting>
<title>7th International Conference on NETwork Games COntrol and OPtimization (NETGCOOP 2014)</title>
<date type="start">2014-10-29</date>
<date type="end">2014-10-31</date>
<settlement>Trento</settlement>
<country key="IT">Italy</country>
</meeting>
<imprint>
<date type="datePub">2014-10-29</date>
</imprint>
</monogr>
</biblStruct>
</sourceDesc>
<profileDesc>
<langUsage>
<language ident="en">English</language>
</langUsage>
<textClass>
<classCode scheme="halDomain" n="info.info-gt">Computer Science [cs]/Computer Science and Game Theory [cs.GT]</classCode>
<classCode scheme="halTypology" n="COMM">Conference papers</classCode>
</textClass>
<abstract xml:lang="en">
<p>We consider two neighbouring countries in which a pandemic disease spreads. Countries face a trade-off between the social costs of the epidemic diffusion and the monetary costs in order to avoid the insurgence of pandemics. However, due to migration of people across countries, the treatment efforts by one country generate a positive externality for the neighbouring country. Both countries can negotiate on the healthcare cost that each has to sustain. But, they do so subject to a central authority (CA) who can impose penalties to both countries whenever they cannot reach an agreement. We analyse the outcome of such situation via the Nash bargaining concept. Next we show how the CA should design penalties to i) ensure that revealing the true migration flow data is a self-enforcing behaviour, and to ii) enforce that the NB solution adheres to certain fairness properties.</p>
</abstract>
</profileDesc>
</hal>
</record>

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