Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduct...Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduction number(R0)have been adapted to account for the structure of social contact networks but still may be unable to capture epidemic potential relative to more recent measures based on spectral graph properties.Here,we explore the ability of R0 and the spectral radius of the social contact network to estimate epidemic susceptibility.To do so,we simulate epidemics on a series of constructed(small world,scale-free,and random networks)and a collection of over 700 empirical biological social contact networks.Further,we explore how other network properties are related to these two epidemic estimators(R0 and spectral radius)and mean infection prevalence in simulated epidemics.Overall,we find that network properties strongly influence epidemic dynamics and the subsequent utility of R0 and spectral radius as indicators of epidemic risk.展开更多
基金supported by the U.S.National Science Foundation RAPID grant(NSF-DEB-2031196).
文摘Understanding and mitigating epidemic spread in complex networks requires the measurement of structural network properties associated with epidemic risk.Classic measures of epidemic thresholds like the basic reproduction number(R0)have been adapted to account for the structure of social contact networks but still may be unable to capture epidemic potential relative to more recent measures based on spectral graph properties.Here,we explore the ability of R0 and the spectral radius of the social contact network to estimate epidemic susceptibility.To do so,we simulate epidemics on a series of constructed(small world,scale-free,and random networks)and a collection of over 700 empirical biological social contact networks.Further,we explore how other network properties are related to these two epidemic estimators(R0 and spectral radius)and mean infection prevalence in simulated epidemics.Overall,we find that network properties strongly influence epidemic dynamics and the subsequent utility of R0 and spectral radius as indicators of epidemic risk.
