A metapopulations epidemic model and its measures for potential mitigation.

Abstract

Strategies attempting to reduce the impact of Covid19 attempted harnessing available geo-spatial, demographic, and behavioural data. Such data has shown to be extremely useful for identifying drivers behind the transmission of the disease. In this article, we develop a toy model emulating the spatial and demographic features of Santiago de Chile, quantify the presence and interaction among different groups in the different spaces defined by the model, and show that effects of the infection dynamics are hidden in the infection data that is usually fitted. In partiucular, we show that the distribution of contagion rates among different sectors distributes as a power-law regardless of the pandemic situation (outbreak vs full spread), and that the power-law distribution strongly depends on a social segregation.