Temporal relation between human mobility, climate, and COVID-19 disease.

Using the example of the city of São Paulo (Brazil), in this paper, we analyze the temporal relation between human mobility and meteorological variables with the number of infected individuals by the COVID-19 disease. For the temporal relation, we use the significant values of distance correlation t0(DC), which is a recently proposed quantity capable of detecting nonlinear correlations between time series. The analyzed period was from February 26, 2020 to June 28, 2020. Fewer movements in recreation and transit stations and the increase in the maximal temperature have strong correlations with the number of newly infected cases occurring 17 days after. Furthermore, more significant changes in grocery and pharmacy, parks, and recreation and sudden changes in the maximal pressure occurring 10 and 11 days before the disease begins are also correlated with it. Scanning the whole period of the data, not only the early stage of the disease, we observe that changes in human mobility also primarily affect the disease for 0-19 days after. In other words, our results demonstrate the crucial role of the municipal decree declaring an emergency in the city to influence the number of infected individuals.

Scrutinizing the heterogeneous spreading of COVID-19 outbreak in large territorial countries.

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. Eventually, such characteristics are also observed between different regions of the same country. Herewith, we introduce a general method that allows us to compare the evolution of the pandemic in different localities inside a large territorial country: in the case of the present study, Brazil. To evaluate our method, we study the heterogeneous spreading of the COVID-19 outbreak until May 30th, 2020, in Brazil and its 27 federative units, which has been seen as the current epicenter of the pandemic in South America. Each one of the federative units 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 federative units of the five regions of Brazil; and (ii) the distance correlation calculated between the time series of the most affected federative units 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 federative units with a low incidence of newly infected people remains about 0.95. In the second set of results, we focus on the heterogeneous distribution of the confirmed cases and deaths. By applying the epidemiological susceptible-infected-recovered-dead model we estimated the effective reproduction number (ERN) [Formula: see text] during the pandemic evolution and found that: (i) the mean value of [Formula: see text] for the eight most affected federative units in Brazil is about 2; (ii) the current value of [Formula: see text] for Brazil is greater than 1, which indicates that the epidemic peak is far off; and (iii) Ceará was the only federative unit for which the current [Formula: see text]. Based on these findings, we projected the effects of increase or decrease of the ERN and concluded that if the value of [Formula: see text] increases 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. In all cases, keeping the ERN 20% below the current value can save thousands of people in the long term.

Strong correlations between power-law growth of COVID-19 in four continents and the inefficiency of soft quarantine strategies.

In this work, we analyze the growth of the cumulative number of confirmed infected cases by a novel coronavirus (COVID-19) until March 27, 2020, from countries of Asia, Europe, North America, and South America. Our results show that (i) power-law growth is observed in all countries; (ii) by using the distance correlation, the power-law curves between countries are statistically highly correlated, suggesting the universality of such curves around the world; and (iii) soft quarantine strategies are inefficient to flatten the growth curves. Furthermore, we present a model and strategies that allow the government to reach the flattening of the power-law curves. We found that besides the social distancing of individuals, of well known relevance, the strategy of identifying and isolating infected individuals in a large daily rate can help to flatten the power-laws. These are the essential strategies followed in the Republic of Korea. The high correlation between the power-law curves of different countries strongly indicates that the government containment measures can be applied with success around the whole world. These measures are scathing and to be applied as soon as possible.