Spatiotemporal Pattern of COVID-19-Related Mortality during the First Year of the Pandemic in Brazil: A Population-based Study in a Region of High Social Vulnerability.

Currently, the world is facing a severe pandemic caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus. Although the WHO has recommended preventive measures to limit its spread, Brazil has neglected most of these recommendations, and consequently, our country has the second largest number of deaths from COVID-19 worldwide. In addition, recent studies have shown the relationship between socioeconomic inequalities and the risk of severe COVID-19 infection. Herein, we aimed to assess the spatiotemporal distribution of mortality and lethality rates of COVID-19 in a region of high social vulnerability in Brazil (Northeast region) during the first year of the pandemic. A segmented log-linear regression model was applied to assess temporal trends of mortality and case fatality rate (CFR) and according to the social vulnerability index (SVI). The Local Empirical Bayesian Estimator and Global Moran Index were used for spatial analysis. We conducted a retrospective space-time scan to map clusters at high risk of death from COVID-19. A total of 66,358 COVID-19-related deaths were reported during this period. The mortality rate was 116.2/100,000 inhabitants, and the CFR was 2.3%. Nevertheless, CFR was > 7.5% in 27 municipalities (1.5%). We observed an increasing trend of deaths in this region (AMCP = 18.2; P = 0.001). Also, increasing trends were observed in municipalities with high (N = 859) and very high SVI (N = 587). We identified two significant spatiotemporal clusters of deaths by COVID-19 in this Brazilian region (P = 0.001), and most high-risk municipalities were on the coastal strip of the region. Taken together, our analyses demonstrate that the pandemic has been responsible for several deaths in Northeast Brazil, with clusters at high risk of mortality mainly in municipalities on the coastline and those with high SVI.

Analysis of the relationship between life expectancy and social determinants in a north-eastern region of Brazil, 2010-2017.

The process of population aging is a worldwide reality becoming a global public health challenge. Although population aging is especially noticeable in more developed regions, there has also been a significant advance in the quantity of elderly people in areas with unfavourable socioeconomic indicators, and a rapid growth in countries with a low level of economic development. This article presents an analysis based on spatial autocorrelation of the relationship between life expectancy and social determinants in a north-eastern region of Brazil. An ecological study was conducted using the secondary data of social, demographic, and health indicators of elderly people collected in the Brazilian Demographic Census of the 75 municipalities of the state of Sergipe. Spatial autocorrelation was evaluated using the Moran global index and the local indicators of space association. Multiple linear regression models were used to identify the relationship between life expectancy and social determinants. The South-eastern region of the state presented clusters with all indicators pointing to acceptable lifestyles, whereas the municipalities of the north-western and far-eastern regions were characterized by values demonstrating precarious living conditions. The high dependency ratio, illiteracy rate, and unemployment rate among elderly people had a negative impact on life expectancy. The evidence confirms that there is an autocorrelation between social determinants and life expectancy, indicating that the worse the social, economic, and health indicators are, the lower the life expectancy. This finding indicates the need to redirect public policies and formulate strategies aimed at reducing social and health inequalities.

Trend and spatial analysis of prostate cancer mortality in the state of Sergipe, Brazil.

This is an ecological study with exploratory analysis of spatial and temporal data based on mortality data with respect to prostate cancer obtained from the Mortality Information System concerning residents of the state of Sergipe, Brazil between 2000 and 2015. The analysis of temporal trends was performed using the Joinpoint Regression Program through Poisson regression. Spatial analysis was performed using the empirical Bayesian model, Kernel analysis, Global Moran and Local indices. There were 1,986 deaths due to prostate cancer, most of which occurring after 60 years of age. An increasing, non-constant but significant trend in mortality rates was noted. The kernel density estimator showed hotspot densities of the highest rates of prostate cancer mortality in the north-eastern and central regions of the state. High-risk clusters were identified for prostate cancer mortality (I = 0.55, P<0.01). There was an increase in prostate cancer mortality rates and a heterogeneous geographic distribution of risk areas, with high-risk priority areas identified in certain regions of the state. These priority areas include the municipalities located in the Northeast (Amparo do São Francisco, Aquidabã, Canhoba, Cedro de São João and Telha), the West (Frei Paulo and Pedra Mole) and the south-western region of the state (Poço Verde and Simão Dias).