000135901 001__ 135901
000135901 005__ 20250924073708.0
000135901 0247_ $$2doi$$a10.1016/j.chaos.2024.115119
000135901 0248_ $$2sideral$$a138936
000135901 037__ $$aART-2024-138936
000135901 041__ $$aeng
000135901 100__ $$aWang, Xiangrong
000135901 245__ $$aUnveiling the reproduction number scaling in characterizing social contagion coverage
000135901 260__ $$c2024
000135901 5060_ $$aAccess copy available to the general public$$fUnrestricted
000135901 5203_ $$aThe spreading of diseases depends critically on the reproduction number, which gives the expected number of new cases produced by infectious individuals during their lifetime. Here we reveal a widespread power-law scaling relationship between the variance and the mean of the reproduction number across simple and complex contagion mechanisms on various network structures. This scaling relation is verified on an empirical scientific collaboration network and analytically studied using generating functions. Specifically, we explore the impact of the scaling law of the reproduction number on the expected size of cascades of contagions. We find that the mean cascade size can be inferred from the mean reproduction number, albeit with limitations in capturing spreading variations. Nonetheless, insights derived from the tail of the distribution of the reproduction number contribute to explaining cascade size variation and allow the distinction between simple and complex contagion mechanisms. Our study sheds light on the intricate dynamics of spreading processes and cascade sizes in social networks, offering valuable insights for managing contagion outbreaks and optimizing responses to emerging threats.
000135901 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E36-23R-FENOL$$9info:eu-repo/grantAgreement/ES/MICINN/PID2020-115800GB-I00
000135901 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc-nd$$uhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
000135901 590__ $$a5.6$$b2024
000135901 592__ $$a1.184$$b2024
000135901 591__ $$aPHYSICS, MATHEMATICAL$$b1 / 61 = 0.016$$c2024$$dQ1$$eT1
000135901 593__ $$aApplied Mathematics$$c2024$$dQ1
000135901 591__ $$aMATHEMATICS, INTERDISCIPLINARY APPLICATIONS$$b7 / 136 = 0.051$$c2024$$dQ1$$eT1
000135901 593__ $$aMathematical Physics$$c2024$$dQ1
000135901 591__ $$aPHYSICS, MULTIDISCIPLINARY$$b17 / 114 = 0.149$$c2024$$dQ1$$eT1
000135901 593__ $$aStatistical and Nonlinear Physics$$c2024$$dQ1
000135901 593__ $$aPhysics and Astronomy (miscellaneous)$$c2024$$dQ1
000135901 593__ $$aMathematics (miscellaneous)$$c2024$$dQ1
000135901 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000135901 700__ $$aHou, Hongru
000135901 700__ $$aLu, Dan
000135901 700__ $$aWu, Zongze
000135901 700__ $$0(orcid)0000-0002-0895-1893$$aMoreno, Yamir$$uUniversidad de Zaragoza
000135901 7102_ $$12004$$2405$$aUniversidad de Zaragoza$$bDpto. Física Teórica$$cÁrea Física Teórica
000135901 773__ $$g185 (2024), 115119 [8 pp.]$$pChaos, solitons fractals$$tChaos, Solitons and Fractals$$x0960-0779
000135901 8564_ $$s4034236$$uhttps://zaguan.unizar.es/record/135901/files/texto_completo.pdf$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2025-06-18
000135901 8564_ $$s2184495$$uhttps://zaguan.unizar.es/record/135901/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint$$zinfo:eu-repo/date/embargoEnd/2025-06-18
000135901 909CO $$ooai:zaguan.unizar.es:135901$$particulos$$pdriver
000135901 951__ $$a2025-09-22-14:35:30
000135901 980__ $$aARTICLE