An Integrated Geographical Approach of the Spatiotemporal Distribution of COVID-19 in Minas Gerais State, Brazil (preprint)

Abstract. Background: COVID-19's first victim was announced by Chinese health authorities on the 11th of January 2020. On January 13, the first official case was reported outside China, in Thailand. On January 25, the same occurred in São Paulo and on March 8, the first case was recorded in Minas Gerais. From that point onwards until the 3rd of October 2020, a total of 370,911 cases and 9,204 deaths were recorded in the state. This study aims to investigate spatiotemporal patterns of COVID-19 with incidence from March 22 to October 3 of 2020. Methods: The database itself was obtained from Health Division of Minas Gerais state. The vulnerability index was calculated using a principal component analysis. Moran's I autocorrelation was tested, z-score and P-value < 0.05. Results: From March 22 to October 3 of 2020 the incidence level varied from 45.680/100,000 to 312.130/100,000. The most influential variables were: illiteracy, gross domestic product and breath apparel per municipality. The clusters were concentrated in the metropolitan area of Belo Horizonte, Zona da Mata and Triangulo Mineiro. Conclusion: The spatial distribution of COVID-19 from week 13 until week 40 showed that different levels of endemicity and mesoregional vulnerabilities were represented in these maps.

Epidemiological Monitoring of COVID-19 in a Brazilian City: The Interface between the Economic Policies, Commercial Behavior, and Pandemic Control

The new Coronavirus disease (COVID-19) pandemic was responsible for one of the worst public health crises in Brazil, which led to the implementation of economic policies to keep social distance. Our aim is to perform an epidemiological analysis of the COVID-19 pandemic in Uberlândia, Minas Gerais, in 2021, highlighting the impact of government commercial policies on pandemic control. This is an epidemiological, observational, and analytical study with secondary data. We constructed a regression for count data using the Poisson model. Data adherence to the regression was verified by Cameron & Trivedi and the Likelihood Ratio tests. According to the Poisson model, there was a statistically significant association (p < 0.001) between the adoption of rigid commercial interventions and the drop in deaths. Moreover, we revealed a consistency between the economic policies and the number of screening tests applied, which may have contributed to the deaths behavior. This study shows the importance of institutionalizing economic policies and their positive impacts on pandemic control;however, it raises the discussion about the serious repercussions of these measures on population vulnerability.

A vulnerability analysis for the management of and response to the COVID-19 epidemic in the second most populous state in Brazil (preprint)

The COVID-19 pandemic has the potential to affect all individuals, however in a heterogeneous way. In this sense, identifying specificities of each location is essential to minimize the damage caused by the disease. Therefore, the aim of this research was to assess the vulnerability of the 853 municipalities in the second most populous state in Brazil, Minas Gerais (MG), in order to direct public policies. Then, an epidemiological study was carried out based on Multi-Criteria Decision Analysis (MCDA) using indicators with some relation to the process of illness and death caused by COVID-19. The indicators were selected by a literature review and categorized into: demographic, social, economic, health infrastructure, population at risk and epidemiological. The variables were collected in Brazilian government databases at the municipal level and evaluated according to MCDA, through the Program to Support Decision Making based on indicators (PRADIN). Based on this approach, the study performed simulations by category of indicators and a general simulation that allowed to divide the municipalities into groups of 1 to 5, with 1 being the least vulnerable and 5 being the most vulnerable. The groupings of municipalities were exposed in their respective mesoregions of MG in a thematic map, using the software Tabwin 32. The results revealed that the mesoregion of Norte de Minas stands out with more than 40% of its municipalities belonging to group 5, according to economic, social and health infrastructure indicators. Similarly, the Jequitinhonha mesoregion exhibited almost 60% of the municipalities in this group for economic and health infrastructure indicators. For demographic and epidemiological criteria, the Metropolitana de Belo Horizonte mesoregion is the most vulnerable, with 42.9% and 26.7% of the municipalities in group 5, respectively. Considering the presence of a population at risk, Zona da Mata reported 42.3% of the municipalities in the most vulnerable group. In the joint analysis of data, the Jequitinhonha, Vale do Mucuri and Vale do Rio Doce mesoregions were the most vulnerable in the state of MG. Thus, through the outlined profile, the present study proved how socioeconomic diversity affects the vulnerability of the municipalities to face COVID-19 outbreak, highlighting the need for interventions directed to each reality.

Underreporting of death by COVID-19 in Brazil's second most populous state (preprint)

The COVID-19 pandemic brings to light the reality of the Brazilian health system. The underreporting of COVID-19 deaths in the state of Minas Gerais (MG), where is concentrated the second largest population of the country, reveals government unpreparedness, as there is a low capacity of testing in the population, which prevents the real understanding of the general panorama of Sars-Cov-2 dissemination. The goals of this research are to analyze the causes of deaths in the different Brazilian government databases (ARPEN and SINAN) and to assess whether there are sub-records shown by the unexpected increase in the frequency of deaths from causes clinically similar to COVID-19. A descriptive and quantitative analysis of the number of COVID-19 deaths and similar causes was made in different databases. Ours results demonstrate that the different official sources had a discrepancy of 209.23% between these data referring to the same period. There was also a 648.61% increase in SARS deaths in 2020, when compared to the average of previous years. Finally, it was shown that there was an increase in the rate of pneumonia and respiratory insufficiency (RI) by 5.36% and 5.72%, respectively. In conclusion, there is an underreporting of COVID-19 deaths in MG due to the unexplained excess of SARS deaths, Respiratory insufficiency and pneumonia compared to previous years.