socioeconomic variables in the acceleration, peak cases and deaths by in Brazilian states.
This is an ecological study with time series analysis of new cases and deaths by in Brazil and its federation units. Conrado Gini in 1912, is used to measure the distribution of income across a social group. It points out the difference between the income of the poorest and the richest in a population, numerically varies from zero, 0, perfect equality to one, 1, perfect inequality) (9), per capita income (ratio between the total income obtained and the total number of inhabitants in a given state/territory -numerical indicator), population density (ratio between the total population and a given territory (geographical area) -numerical indicator)(10), HDI (Human Development Index-developed in 1990, by economists Nahbub ul Haq (Pakistani) and Amartya Sem (Indian), it is a combination of life expectancy, average schooling and per capita income of a given population, numerically ranges from zero (0) very low HDI one (1) very high HDI) (9). The HDI of the population of Brazil and federation units was obtained from the IBGE website.
We calculated the incidence rate by the ratio between the number of cases accumulated on the last day of the series and the population multiplied by 1000.
Likewise, mortality was obtained by dividing the number of deaths accumulated at the end of the historical series and the population multiplied by 1000. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . https://doi.org/10.1101/2020.09.09.20191353 doi: medRxiv preprint
The epidemic curve was obtained by using the polynomial method in a similar way in previous work (4) .
The polynomial was automatically generated by the Matlab software, whose degree and coefficients were adjusted to the curve of daily cases and deaths, figure 1, using the degree at most 8, according to the equation an. day n + an-1. day n-1 + .... + a1. day + a0, n ∈ N In order to illustrate the applicability of the polynomial in describing the epidemic curve, we present data on new cases from Austria, a country that presented the complete curve at the end of this historical series, figure 1. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . https://doi.org/10.1101/2020.09.09.20191353 doi: medRxiv preprint
The correlations of socioeconomic data, incidence rate, mortality, maximum acceleration of cases, peak of cases and deaths were measured by the Pearson Correlation Coefficient if they presented normal or normalized distribution after logarithmic transformation. The Spearman method was used to assess the correlation between variables with non-normal distribution.
The normality analysis was performed by the Kolmogorov-Smirnov tests.
The results were considered significant if p <0.05.
Cases:
On July 11, 2020, the last day of the historical series, Brazil reached 1,839,850 cases, incidence rate = 8.94 cases/1000 inhabitants, showing a reduction, but still remaining high. As it presented a decrease in acceleration, the country was in the second stage of the acceleration phase, is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . 
On July 11, 2020, the last day of the historical series, Brazil registered 71,469 deaths, mortality equal to 0.34 deaths/1000 inhabitants. The country presented the maximum acceleration = 23.9 deaths/day 2 on May 7th, day 83 of the series.
The most recent acceleration is equal to 13.4 deaths/day 2 , after a short period in which it was negative, constituting a peak in plateau, table 1 and figure 3 . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . https://doi.org/10.1101/2020.09.09.20191353 doi: medRxiv preprint
Our results demonstrate that the peak of daily cases, acceleration of cases and deaths and peak of deaths showed a positive correlation with population density and the Gini Index. This result is in agreement with articles that demonstrate the importance of population distancing for the flattening of the epidemic curve, and reinforce the usefulness of lockdown or physical distancing to reduce peak cases and deaths (11).
Brazil presented a great acceleration of new cases, and, at the end of this series, it was approaching the peak. This curve represents the sum of various epidemics already occurring in the states, in different phases and at different severity levels. Such heterogeneity may be related to the central government's lack of coordination regarding measures to control the spread of the virus, territorial extent and the country's geographical, social, economic and cultural diversity. In addition, unlike other epidemic diseases, the Covid-19 epidemic in Brazil had its first reports of imported cases (aloctenes), brought by subjects who returned from international trips or foreigners from countries that were themselves in epidemic situation, and later extended to the periphery and smaller cities in the interior of the country (8).
The results of this study suggest that the worst Covid-19 indicators were related to demographic density and the Gini Index (indicator of income inequality), same behavior observed with social problems that are more related to income inequality than per capita income (12).
The incidence and mortality rate data should be viewed with caution, as we are still experiencing the epidemic and, at this moment, we need data that reflect the daily variation of newly reported cases and their acceleration, which are important because they reflect the strength or trend of the outbreaks taking daily data into account. It does not need to be compared with previous data, it assesses the absolute slope of the curve. Its measurement can be useful to evaluate non-pharmacological measures in response to the Covid-19 pandemic. is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . . CC-BY-NC-ND 4.0 International license It is made available under a perpetuity.
is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. . is the author/funder, who has granted medRxiv a license to display the preprint in (which was not certified by peer review) preprint
The copyright holder for this this version posted September 12, 2020. .