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?:abstract
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After the spread of COVID-19 out of China, the evolution of the pandemic has shown remarkable similarities and differences between countries around the world. Such characteristics are also observed between different regions of the same country. Herewith, we introduce a general method that allows us to compare the pandemic evolution in different localities inside a large territorial country. To evaluate our method, we study the heterogeneous spreading of the COVID-19 outbreak in Brazil and its 27 states. Each one of the states may be considered a cluster of interacting people with similar habits and distributed to a highly heterogeneous demographic density over the entire country. Our first set of results regarding the time-series analysis shows that: (i) a power-law growth of the cumulative number of infected people is observed for states of the five regions of Brazil; and (ii) the Distance Correlation (DC) calculated between the time series of the most affected states and the curve that describes the evolution of the pandemic in Brazil remains about 1 over most of the time, while such quantity calculated for the states with a low incidence of newly infected people remains about 0.95. By applying the epidemiological SIRD model we estimated the Effective Reproduction Number (ERN) Reand found that: (i) the mean value of Refor the eight most affected states in Brazil is about 2, and (ii) the current value of Refor Brazil is greater than 1, which indicates that the epidemic peak is far off. Based on these findings, we projected the effects of increase/decrease of the ERN and concluded that if the value of Reincreases 20%, not only the peak might grow at least 40% but also its occurrence might be anticipated, which hastens the collapse of the public health-care system.
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