This paper examines the spatial pattern of ill-defined causes of death across Brazilian regions, and its relationship with the evolution of completeness of the deaths registry and changes in the mortality age profile. We make use of the Brazilian Health Informatics Department mortality database and population censuses from 1980 to 2010. We applied demographic methods to evaluate the quality of mortality data for 137 small areas and correct for under-registration of death counts when necessary. The second part of the analysis uses linear regression models to investigate the relationship between, on the one hand, changes in death counts coverage and age profile of mortality, and on the other, changes in the reporting of ill-defined causes of death. The completeness of death counts coverage increases from about 80% in 1980-1991 to over 95% in 2000-2010 at the same time the percentage of ill-defined causes of deaths reduced about 53% in the country. The analysis suggests that the government’s efforts to improve data quality are proving successful, and they will allow for a better understanding of the dynamics of health and the mortality transition.
In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2–10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems.
As of mid-August 2020, Brazil was the country with the second-highest number of cases and deaths by the COVID-19 pandemic, but with large regional and social differences. In this study, using data from the Brazilian Ministry of Health, we analyze the spatial patterns of infection and mortality from Covid-19 across small areas of Brazil. We apply spatial autoregressive Bayesian models and estimate the risks of infection and mortality, taking into account age, sex composition of the population and other variables that describe the health situation of the spatial units. We also perform a decomposition analysis to study how age composition impacts the differences in mortality and infection rates across regions. Our results indicate that death and infections are spatially distributed, forming clusters and hotspots, especially in the Northern Amazon, Northeast coast and Southeast of the country. The high mortality risk in the Southeast part of the country, where the major cities are located, can be explained by the high proportion of the elderly in the population. In the less developed areas of the North and Northeast, there are high rates of infection among young adults, people of lower socioeconomic status, and people without access to health care, resulting in more deaths.
We focus here on deforestation and human development dynamics among 211 small and medium-sized municipalities (in terms of population) in the Amazonian arc of deforestation, Brazil. First, we construct a typology of municipalities through principal component analysis and cluster analysis. Using this typology, we seek to identify changing deforestation frontiers in the study area based not only on forest loss levels, but also on sets of socioeconomic and demographic elements associated with human development. We find four well-defined macro-deforestation frontiers that exhibit distinct interactions between forest loss and human development levels. Our results show different levels of demographic and economic pressures in these frontiers while revealing some important trends such as the internalization of investments and demographic growth in the arc of deforestation. In addition, population growth and inmigration and out-migration patterns in the explored municipalities suggest a demographic complementarity among frontiers. Finally, we explore implications for public policies seeking to advance forest recovery and long-term conservation through sustainable development growth at the local and regional levels.
To determine the variations and spatial patterns of adult mortality across regions, over time, and by sex for 137 small areas in Brazil, we first apply TOPALS to estimate and smooth mortality rates and then use death distribution methods to evaluate the quality of the mortality data. Lastly, we employ spatial autocorrelation statistics and cluster analysis to identify the adult mortality trends and variations in these areas between 1980 and 2010. We find not only that regions in Brazil’s South and Southeast already had complete death registration systems prior to the study period, but that the completeness of death count coverage improved over time across the entire nation—most especially in lesser developed regions—probably because of public investment in health data collection. By also comparing adult mortality by sex and by region, we document a mortality sex differential in favor of women that remains high over the entire study period, most probably as a result of increased morbidity from external causes, especially among males. This increase also explains the concentration of high male mortality levels in some areas.
BACKGROUNDThe covid-19 pandemic has considerably affected the mortality numbers of many countries in the world, and Latin America is now the epicenter of the diseases. There is a great demand on analyzing the impact of this new disease in the amount of deaths, but available information of deaths by cause is still lacking in most of the countries in the region. OBJECTIVEWe aimed to measure the effects of the disease on mortality, using excess mortality, in two Latin America countries that were most affected by the covid-19 pandemic in the region: Brazil, Chile, Ecuador and Peru. METHODSWe measured the effects of the pandemic by looking at the excess mortality, and comparing estimates of differences in the average number of deaths, variation coefficients and percentages of deaths between the months of March to May for 2019 and 2020. RESULTSOur findings indicated an excess of deaths initially in major cities, but then is spreading towards the least urbanized areas. In the next phase, pandemic will probably affect countries’ cities in worse socioeconomic and sanitary conditions. In Ecuador, we saw that the most affected locations were the less socioeconomic areas of the country. CONCLUSIONDespite the lack of information on causes of death, the excess of deaths is a good indicator for measuring the effects of the coronavirus pandemic, especially in the context Latin America countries. We find strong evidence of the pandemic’s impact and interiorization, especially in Brazilian cases. CONTRIBUTIONThis study provides an initial discussion of the effects of pandemic in small and less urbanized areas of Brazil and Ecuador.
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