Universal nonlinear infection kernel from heterogeneous exposure on higher-order networks
Abstract
The collocation of individuals in different environments is an important prerequisite for exposure to infectious diseases on a social network. Standard epidemic models fail to capture the potential complexity of this scenario by neglecting higher-order contact structure and assuming a linear relationship between exposure and infection risk. This work shows that heterogeneous exposure and minimal infective dose induce a universal nonlinear relationship between infected contacts and infection risk.
Type
Publication
In Physical Review Letters
