Potential dissemination of epidemics based on Brazilian mobile geolocation data. Part I: Population dynamics and future spreading of infection in the states of Sao Paulo and Rio de Janeiro during the pandemic of COVID-19.

Pedro S. Peixoto; Diego R. Marcondes; Cláudia M Peixoto; Lucas Queiroz; Rafael Gouveia; Afonso Delgado; Sérgio M Oliva

The copyright holder for this preprint . https://doi.org/10.1101/2020.04.07.20056739 doi: medRxiv preprint Table 3 : Descriptive statistics of the rank of the proportion of movement out of Rio de Janeiro capital city in the days of March 2019 and March 2020. We see that the effect of is on the time, in number of days, that the disease takes to attain some location, rather than on the evolution of the spread itself. For , we observe in Figures 6 and 8 that the number of infected individuals spread from the capital cities, to the their metropolitan region and then selected cities on the countryside, which are geographically far from the capital, specially in the state of São Paulo. We see on Figures 7 and 9 that, for different values of , the evolution of the disease is the same, but the cities with focus of infections at the end of the simulation, i.e., April 30th, depend on : as greater the value of , more cities are infected at the end. Also, we can clearly see a non-local diffusion process, as described by [8] .