Games of social distancing during an epidemic: Local vs statistical information
The choices of a population to apply social distancing are modeled as a Nash game, where the agents determine their social interactions. The interconnections among the agents are modeled by a network. The main contribution of this work is the study of an agent-based epidemic model coupled with a soc...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-01-01
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| Series: | Computer Methods and Programs in Biomedicine Update |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666990022000192 |
| _version_ | 1828116153612894208 |
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| author | A.-R. Lagos I. Kordonis G.P. Papavassilopoulos |
| author_facet | A.-R. Lagos I. Kordonis G.P. Papavassilopoulos |
| author_sort | A.-R. Lagos |
| collection | DOAJ |
| description | The choices of a population to apply social distancing are modeled as a Nash game, where the agents determine their social interactions. The interconnections among the agents are modeled by a network. The main contribution of this work is the study of an agent-based epidemic model coupled with a social distancing game, which are both determined by the networked structure of human interconnections. The information available to the agents plays a crucial role. We examine the case that the agents know exactly the health states of their neighbors and the case they have only statistical information for the global prevalence of the epidemic. The agents are considered to be myopic, and thus, the Nash equilibria of static games for each day are studied. Through theoretical analysis, we characterize these Nash equilibria and we propose algorithms to compute them. Interestingly, in the case of statistical information the equilibrium strategies for an agent, at each day, are either full isolation or no social distancing at all. Through experimental studies, we observe that in the case of local information, the agents can significantly affect the prevalence of the epidemic with low social distancing, while in the other case, they can also affect the prevalence of the epidemic, but they have to pay the burden of not being well informed by applying strict social distancing. Moreover, the effects of the network structure, the virus transmissibility, the number of vulnerable agents, the health care system capacity and the information quality (fake news) are discussed and relevant simulations are provided. |
| first_indexed | 2024-04-11T12:52:25Z |
| format | Article |
| id | doaj.art-0123eb1d46b1405e815abecc271228ba |
| institution | Directory Open Access Journal |
| issn | 2666-9900 |
| language | English |
| last_indexed | 2024-04-11T12:52:25Z |
| publishDate | 2022-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Computer Methods and Programs in Biomedicine Update |
| spelling | doaj.art-0123eb1d46b1405e815abecc271228ba2022-12-22T04:23:10ZengElsevierComputer Methods and Programs in Biomedicine Update2666-99002022-01-012100068Games of social distancing during an epidemic: Local vs statistical informationA.-R. Lagos0I. Kordonis1G.P. Papavassilopoulos2National Technical University of Athens, School of Electrical and Computer Engineering, Greece; Corresponding author.National Technical University of Athens, School of Electrical and Computer Engineering, GreeceNational Technical University of Athens, School of Electrical and Computer Engineering, Greece; USC Viterbi, Ming Hsieh Department of Electrical and Computer Engineering - Systems, United States of AmericaThe choices of a population to apply social distancing are modeled as a Nash game, where the agents determine their social interactions. The interconnections among the agents are modeled by a network. The main contribution of this work is the study of an agent-based epidemic model coupled with a social distancing game, which are both determined by the networked structure of human interconnections. The information available to the agents plays a crucial role. We examine the case that the agents know exactly the health states of their neighbors and the case they have only statistical information for the global prevalence of the epidemic. The agents are considered to be myopic, and thus, the Nash equilibria of static games for each day are studied. Through theoretical analysis, we characterize these Nash equilibria and we propose algorithms to compute them. Interestingly, in the case of statistical information the equilibrium strategies for an agent, at each day, are either full isolation or no social distancing at all. Through experimental studies, we observe that in the case of local information, the agents can significantly affect the prevalence of the epidemic with low social distancing, while in the other case, they can also affect the prevalence of the epidemic, but they have to pay the burden of not being well informed by applying strict social distancing. Moreover, the effects of the network structure, the virus transmissibility, the number of vulnerable agents, the health care system capacity and the information quality (fake news) are discussed and relevant simulations are provided.http://www.sciencedirect.com/science/article/pii/S2666990022000192Social distancingGames on networksEpidemics on networksNash gameInformation patterns |
| spellingShingle | A.-R. Lagos I. Kordonis G.P. Papavassilopoulos Games of social distancing during an epidemic: Local vs statistical information Computer Methods and Programs in Biomedicine Update Social distancing Games on networks Epidemics on networks Nash game Information patterns |
| title | Games of social distancing during an epidemic: Local vs statistical information |
| title_full | Games of social distancing during an epidemic: Local vs statistical information |
| title_fullStr | Games of social distancing during an epidemic: Local vs statistical information |
| title_full_unstemmed | Games of social distancing during an epidemic: Local vs statistical information |
| title_short | Games of social distancing during an epidemic: Local vs statistical information |
| title_sort | games of social distancing during an epidemic local vs statistical information |
| topic | Social distancing Games on networks Epidemics on networks Nash game Information patterns |
| url | http://www.sciencedirect.com/science/article/pii/S2666990022000192 |
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