A mathematical model for the spatiotemporal epidemic spreading of COVID19

Alex Arenas; Wesley Cota; Jesus Gomez-Gardenes; Sergio Gómez; Clara Granell; Joan T. Matamalas; David Soriano-Panos; Benjamin Steinegger

As of 20 March 2020 the outbreak of the novel coronavirus, SARS-CoV-2, has infected more than 270.000 persons worldwide with COVID-19, killing more than 11.300. Epidemiological analysis of the outbreak have been used to estimate epidemiologically relevant parameters [1-10], and available mathematical models have been used to track and anticipate the spread of the epidemics [11] [12] [13] [14] [15] [16] [17] . Nevertheless, the particularities of the current epidemics calls for a rethinking of conventional models towards tailored ones. Here, we propose mathematical model particularly designed to capture the main ingredients characterising the propagation of SARS-CoV-2 and the clinical characteristics reported for the cases of COVID-19. To this aim, we rely on previous metapopulation models by the authors [18] [19] [20] [21] including the spatial demographical distribution and recurrent mobility patterns, and develop a more refined epidemic model that incorporates the stratification of population by age in order to consider the different epidemiological and clinical features associated to each group age that have been reported so far. The mathematical formulation of these models rely on the Microscopic Markov Chain Approach formulation for epidemic spreading in complex networks [22] [23] [24] [25] [26] [27] .