000129345 001__ 129345
000129345 005__ 20240319081010.0
000129345 0247_ $$2doi$$a10.1016/j.chaos.2022.112735
000129345 0248_ $$2sideral$$a131371
000129345 037__ $$aART-2022-131371
000129345 041__ $$aeng
000129345 100__ $$aWan, Jinming
000129345 245__ $$aMultilayer networks with higher-order interaction reveal the impact of collective behavior on epidemic dynamics
000129345 260__ $$c2022
000129345 5060_ $$aAccess copy available to the general public$$fUnrestricted
000129345 5203_ $$aThe ongoing COVID-19 pandemic has inflicted tremendous economic and societal losses. In the absence of pharmaceutical interventions, the population behavioral response, including situational awareness and adherence to non-pharmaceutical intervention policies, has a significant impact on contagion dynamics. Game-theoretic models have been used to reproduce the concurrent evolution of behavioral responses and disease contagion, and social networks are critical platforms on which behavior imitation between social contacts, even dispersed in distant communities, takes place. Such joint contagion dynamics has not been sufficiently explored, which poses a challenge for policies aimed at containing the infection. In this study, we present a multi-layer network model to study contagion dynamics and behavioral adaptation. It comprises two physical layers that mimic the two solitary communities, and one social layer that encapsulates the social influence of agents from these two communities. Moreover, we adopt high-order interactions in the form of simplicial complexes on the social influence layer to delineate the behavior imitation of individual agents. This model offers a novel platform to articulate the interaction between physically isolated communities and the ensuing coevolution of behavioral change and spreading dynamics. The analytical insights harnessed therefrom provide compelling guidelines on coordinated policy design to enhance the preparedness for future pandemics.
000129345 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E36-20R$$9info:eu-repo/grantAgreement/ES/DGA-FEDER/Una manera de hacer Europa$$9info:eu-repo/grantAgreement/ES/MCIN-AEI-FEDER/PID2020-115800GB-I00
000129345 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000129345 590__ $$a7.8$$b2022
000129345 591__ $$aPHYSICS, MATHEMATICAL$$b1 / 56 = 0.018$$c2022$$dQ1$$eT1
000129345 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b3 / 107 = 0.028$$c2022$$dQ1$$eT1
000129345 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b11 / 85 = 0.129$$c2022$$dQ1$$eT1
000129345 592__ $$a1.393$$b2022
000129345 593__ $$aApplied Mathematics$$c2022$$dQ1
000129345 593__ $$aMathematical Physics$$c2022$$dQ1
000129345 593__ $$aStatistical and Nonlinear Physics$$c2022$$dQ1
000129345 593__ $$aPhysics and Astronomy (miscellaneous)$$c2022$$dQ1
000129345 593__ $$aMathematics (miscellaneous)$$c2022$$dQ1
000129345 594__ $$a11.8$$b2022
000129345 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000129345 700__ $$aIchinose, Genki
000129345 700__ $$aSmall, Michael
000129345 700__ $$aSayama, Hiroki
000129345 700__ $$0(orcid)0000-0002-0895-1893$$aMoreno, Yamir$$uUniversidad de Zaragoza
000129345 700__ $$aCheng, Changqing
000129345 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDpto. Física Teórica$$cÁrea Física Teórica
000129345 773__ $$g164 (2022), 112735$$pChaos, solitons fractals$$tChaos, Solitons and Fractals$$x0960-0779
000129345 8564_ $$s1242033$$uhttps://zaguan.unizar.es/record/129345/files/texto_completo.pdf$$yPostprint
000129345 8564_ $$s2058427$$uhttps://zaguan.unizar.es/record/129345/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000129345 909CO $$ooai:zaguan.unizar.es:129345$$particulos$$pdriver
000129345 951__ $$a2024-03-18-15:02:08
000129345 980__ $$aARTICLE