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

To assess the impact of containment policies, we now theoretically study the effects of tuning the isolation rate κ 0 controlling the fraction of population staying at home. Figure 3 shows the temporal evolution of the individuals requiring intensive care units while applying the isolation policy by March 20, 2020. Interestingly, it becomes clear that there are two different regimes. For small κ 0 values, the observed behavior corresponds to the flattening of the epidemic curve while promoting social distancing. This way, increasing κ 0 leads to longer epidemic periods with much less impact within society in terms of hospitalized agents. In contrast, for large enough κ 0 values, the effective isolation of households allows for reducing at the same time the epidemic size and the duration of the epidemic wave. This is mainly caused by the depletion [41] of susceptible individuals which prevents the infectious individuals from sustaining the outbreak by infecting healthy peers.