The population density in Brazil saw no significant changes in 2022 in comparison to the previous year 2021 and remained at around 25.16 inhabitants per square kilometer. Still, the population density reached its highest value in the observed period in 2022. Population density refers to the average number of residents per square kilometer of land across a given country or region. It is calculated by dividing the total midyear population by the total land area.

Brazil population density for 400m H3 hexagons.

Built from Kontur Population: Global Population Density for 400m H3 Hexagons Vector H3 hexagons with population counts at 400m resolution.

Fixed up fusion of GHSL, Facebook, Microsoft Buildings, Copernicus Global Land Service Land Cover, Land Information New Zealand, and OpenStreetMap data.

WorldPop produces different types of gridded population count datasets, depending on the methods used and end application. Please make sure you have read our Mapping Populations overview page before choosing and downloading a dataset.

Datasets are available to download in Geotiff and ASCII XYZ format at a resolution of 30 arc-seconds (approximately 1km at the equator)

-Unconstrained individual countries 2000-2020: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population count datasets by dividing the number of people in each pixel by the pixel surface area. These are produced using the unconstrained top-down modelling method.
-Unconstrained individual countries 2000-2020 UN adjusted: Population density datasets for all countries of the World for each year 2000-2020 – derived from the corresponding Unconstrained individual countries 2000-2020 population UN adjusted count datasets by dividing the number of people in each pixel, adjusted to match the country total from the official United Nations population estimates (UN 2019), by the pixel surface area. These are produced using the unconstrained top-down modelling method.

Data for earlier dates is available directly from WorldPop.

WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00674

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in Brazil: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

In 2024, the Southeast was the most populated region in Brazil, according to the estimations. In that year, more than 88 million people lived in the four states of this region: Espírito Santo, Minas Gerais, Rio de Janeiro and São Paulo. The Central-West region, where the country's capital, Brasília, is located, was the least populated region in the South American country in 2021, with only 17 million inhabitants. Throughout the past decade, Brazil's population has grown at slower rates than before.

The history of modern Brazil begins in the year 1500 when Pedro Álvares Cabral arrived with a small fleet and claimed the land for the Portuguese Empire. With the Treaty of Torsedillas in 1494, Spain and Portugal agreed to split the New World peacefully, thus allowing Portugal to take control of the area with little competition from other European powers. As the Portuguese did not arrive with large numbers, and the indigenous population was overwhelmed with disease, large numbers of African slaves were transported across the Atlantic and forced to harvest or mine Brazil's wealth of natural resources. These slaves were forced to work in sugar, coffee and rubber plantations and gold and diamond mines, which helped fund Portuguese expansion across the globe. In modern history, transatlantic slavery brought more Africans to Brazil than any other country in the world. This combination of European, African and indigenous peoples set the foundation for what has become one of the most ethnically diverse countries across the globe.

Independence and Monarchy By the early eighteenth century, Portugal had established control over most of modern-day Brazil, and the population more than doubled in each half of the 1800s. The capital of the Portuguese empire was moved to Rio de Janeiro in 1808 (as Napoleon's forces moved closer towards Lisbon), making this the only time in European history where a capital was moved to another continent. The United Kingdom of Portugal, Brazil and the Algarves was established in 1815, and when the Portuguese monarchy and capital returned to Lisbon in 1821, the King's son, Dom Pedro, remained in Brazil as regent. The following year, Dom Pedro declared Brazil's independence, and within three years, most other major powers (including Portugal) recognized the Empire of Brazil as an independent monarchy and formed economic relations with it; this was a much more peaceful transition to independence than many of the ex-Spanish colonies in the Americas. Under the reign of Dom Pedro II, Brazil's political stability remained relatively intact, and the economy grew through its exportation of raw materials and economic alliances with Portugal and Britain. Despite pressure from political opponents, Pedro II abolished slavery in 1850 (as part of a trade agreement with Britain), and Brazil remained a powerful, stable and progressive nation under Pedro II's leadership, in stark contrast to its South American neighbors. The booming economy also attracted millions of migrants from Europe and Asia around the turn of the twentieth century, which has had a profound impact on Brazil's demography and culture to this day.

The New Republic

Despite his popularity, King Pedro II was overthrown in a military coup in 1889, ending his 58 year reign and initiating six decades of political instability and economic difficulties. A series of military coups, failed attempts to restore stability, and the decline of Brazil's overseas influence contributed greatly to a weakened economy in the early 1900s. The 1930s saw the emergence of Getúlio Vargas, who ruled as a fascist dictator for two decades. Despite a growing economy and Brazil's alliance with the Allied Powers in the Second World War, the end of fascism in Europe weakened Vargas' position in Brazil, and he was eventually overthrown by the military, who then re-introduced democracy to Brazil in 1945. Vargas was then elected to power in 1951, and remained popular among the general public, however political opposition to his beliefs and methods led to his suicide in 1954. Further political instability ensued and a brutal, yet prosperous, military dictatorship took control in the 1960s and 1970s, but Brazil gradually returned to a democratic nation in the 1980s. Brazil's economic and political stability fluctuated over the subsequent four decades, and a corruption scandal in the 2010s saw the impeachment of President Dilma Rousseff. Despite all of this economic instability and political turmoil, Brazil is one of the world's largest economies and is sometimes seen as a potential superpower. The World Bank classifies it as a upper-middle income country and it has the largest share of global wealth in Latin America. It is the largest Lusophone (Portuguese-speaking), and sixth most populous country in the world, with a population of more than 210 million people.

In 2023, the share of urban population in Brazil remained nearly unchanged at around 87.79 percent. Nevertheless, 2023 still represents a peak in the share in Brazil with 87.79 percent. A population may be defined as urban depending on the size (population or area) or population density of the village, town, or city. The urbanization rate then refers to the share of the total population who live in an urban setting. International comparisons may be inconsistent due to differing parameters for what constitutes an urban center.Find more statistics on other topics about Brazil with key insights such as anual population growth.

As of 2021, Ecuador had a population density of 72 people per squared kilometer, the highest in South America. Colombia ranked second, with 42 people per km2 of land area. When it comes to total population in South America, Brazil had the largest number, with over 216 million inhabitants.

Brazil administrative division with aggregated population. Built from Kontur Population: Global Population Density for 400m H3 Hexagons on top of OpenStreetMap administrative boundaries data. Enriched with HASC codes for regions taken from Wikidata.
Global version of boundaries dataset: Kontur Boundaries: Global administrative division with aggregated population

The present dataset is part of the published scientific paper entitled “The role of spatial planning in land change: An assessment of urban planning and nature conservation efficiency at the southeastern coast of Brazil” (Pierri Daunt, Inostroza and Hersperger, 2021). In this work, we evaluated the conformance of stated spatial planning goals and the outcomes in terms of urban compactness, basic services and housing provision, and nature conservation for different land-use strategies. We evaluate the 2005 Ecological-Economic Zoning (EEZ) and two municipal master plans from 2006 in a coastal region in São Paulo State, Brazil. We used Partial Least Squares Path Modelling (PLS-PM) to explain the relationship between the plan strategies and land-use change ten years after implementation in terms of urban compactness, basic services and housing increase, and nature conservation.

We acquired the data for the explanatory variables from different sources listed on Table 1. Since the model is spatially explicit, all input data were transformed to a 30 m resolution raster. Regarding the evaluated spatial plans, we acquired the zones limits from the São Paulo State Environmental Planning Division (CPLA-SP), Ilhabela and Ubatuba municipality.

1) Land use and cover data: Urban persistence, Urban axial, Urban infill, Urban Isolates, Forest cover persistence, Forest cover gain, NDVI increase

We acquired two Landsat Collection 1 Higher-Level Surface Reflectance images distributed by the U.S. Geological Survey (USGS), covering the entire study area (paths 76 and 77, row 220, WRS-2 reference system, https://earthexplorer.usgs.gov/). We classified one image acquired by the Landsat 5 Thematic Mapper (TM) sensor on 2005-05-150, and one image from the Landsat 8 Operational Land Imager (OLI) sensor from 2015-08-15. We collected 100 samples for forest cover, 100 samples for built-up cover and 100 samples for other classes. We then classified these three classes of land cover at each image date using the Support Vector Machine (SVM) supervised algorithm (Hsu et al., 2003), using ENVI 5.0 software.

Land-use and land-cover changes from 2005 to 2015 were quantified using map algebra, by mathematically adding them together in pairs (10*LULC2015 + LULC2005). We reclassified the LULC data into forest gain (conversion of any 2005 LULC to forest cover in 2015); forest persistence (2005 forested pixels that remained forested in 2015); new built-up area (conversion of any 2005 LULC to built-up in 2015); and urban maintenance (2005 built-up pixels that remained built-up in 2015).

To describe the spatial configuration of the urban expansion, we classified the new built-up areas into axial, infill and isolated, following Inostroza et al. (2013) (For details, please refer to Supplementary Material I at the original publication).

The NDVI was obtained from the same source used for the LULC data. With the Google Engine platform, we used an annual average for the best pixels (without clouds) for 2005 and 2015, and we calculated the changes between dates. We used increases of > 0.2 NDVI to represent an improvement in forest quality.

2) Federal Census data organization: Urban Basic Services and Housing indicator, socioeconomic and population:

The data used to infer the values of basic services provision, socioeconomic and population drivers was derived from the Brazilian National Census data (IBGE, 2000 and 2010). Population density, permanent housing unit density, mean income, basic education, and the percentage of houses receiving waste collection, sanitation and water provision services, called basic services in the context of this study, were calculated per 30 m pixel. The Human Development Index is only available at the municipality level. We attributed the HDI for the vector file with the municipality border, and we rasterized (30 m resolution) this file in QGIS. Annual rates of change were then calculated to allow comparability between LULC periods. To infer the BSH, we used only areas with an increase in permanent housing density and basic services provision (See Supplementary Material I at the original publication).

3) Topographic drivers

To infer the values of the topographic driver, we used the slope data and the Topographic Index Position (TPI) based on the digital elevation model from SRTM (30 m resolution) produced by ALOS (freely available at eorc.jaxa.jp/ALOS/en/about/about_index.htm), and both variables were considered constant from 2005 to 2015 (See Supplementary Material I at the original publication).

p = significance level (α = 0.05); a-Population; b-Settlements; c-Urban centers; d-Unpaved road; e-Paved road; f-Total roads.

Feira de Santana–Bahia, April to September, 2017.

In 2022, approximately 11.45 million people lived in São Paulo, making it the largest municipality in Brazil and one of the most populous cities in the world. The homonymous state of São Paulo was also the most populous federal entity in the country.

Brazil's cities

Brazil is home to two large metropolises: São Paulo with close to 11.45 million inhabitants, and Rio de Janeiro with around 6.21 million inhabitants. It also contains a number of smaller, but well known cities such as Brasília, Salvador, Belo Horizonte and many others, which report between 2 and 3 million inhabitants each. As a result, the country's population is primarily urban, with nearly 85 percent of inhabitants living in cities.

While smaller than some of the other cities, Brasília was chosen to be the capital because of its relatively central location. The city is also well-known for its modernist architecture and utopian city plan which is quite controversial - criticized by many and praised by others.

Sports venues capitals

A number of Brazil’s medium-sized and large cities were chosen as venues for the 2014 World Cup, and the 2015 Summer Olympics also took place in Rio de Janeiro. Both of these events required large sums of money to support infrastructure and enhance mobility within a number of different cities across the country. Billions of dollars were spent on the 2014 World Cup, which went primarily to stadium construction and renovation, but also to a number of different mobility projects. Other short-term spending on infrastructure for the World Cup and the Rio Olympic Games was estimated at around 50 billion U.S. dollars. While these events have poured a lot of money into urban infrastructure, a number of social and economic problems within the country remain unsolved.

This data set provides the results of (1) synoptic streamwater sampling and analyses from numerous sites across Rondonia and (2) corresponding watershed characteristics derived from remote sensing and historical/available data sources.

Sixty streams, in both forested and non-forested sites, were sampled once during the dry season in August of 1998 and 49 of the same streams were sampled again during the wet season in January-February of 1999. Analyses included sodium (Na), calcium (Ca), magnesium (Mg), potassium (K), silica (Si), chloride (Cl), sulfate, pH, and acid neutralizing capacity.

Watershed characteristics, including soil cation content, pH, watershed lithology, area, percent deforested, and urban watershed population density, were derived and calculated from digitized soil maps and available soil profile analyses, digitized topographic maps, land use mosaics from Landsat Thematic Mapper (TM) images, and Brazilian census data.

The objective of the study was to determine the relative influence of watershed soil exchangeable cation content, rock type, deforestation, and urban population density on stream concentrations of base cations, dissolved silicon, chloride and sulfate in both the dry and wet seasons in a humid tropical region undergoing regional land use transformation. There are three comma-delimited data files with this data set.

This research selected three cities as case studies in Brazil (Pelotas, Belo Horizonte, and Brasilia) and three cities as case studies in the UK (Edinburgh, Manchester and Glasgow). The case study cities represented a broad spectrum of urban areas, in terms of demography (mixed tenures by age), inequality (health and social disparities between high and low income groups), topography (different types of urban densities and form) and urban development (varying levels of physical transformation and change). Within each of the case study cities, three neighbourhoods were selected as study sites reflecting a diversity in population density and income levels (measures guided by previous research examining neighbourhood satisfaction amongst older adults). The neighbourhoods comprised a mix of low, medium and high income and low, medium and high-density areas. Neighbourhood level analysis has been chosen because: (i) the greatest time spent by older adults in retirement is at home and in the immediate neighbourhood locality, (ii) older adults are increasingly dependent upon social relationships in the neighbourhood as they age; and (iii) older adults have important psychological and emotional bonds and association with the neighbourhood (as community). As part of the first work package of the research, a total number of 180 semi-structured interviews (30 per case study city; 10 per neighbourhood) were conducted with older adults to explore the in-depth experiences of ageing-in-place. The interviews identified how sense of place is negotiated and constructed (meaning, identity, belonging), identifying everyday behaviours within the built environment, and the importance of specific social and cultural supports.

Ageing populations in Brazil and the UK have generated new challenges in how to best design living environments that support and promote everyday social engagement for older people. The ageing-in-place agenda posits that the preferred environment to age is the community, enabling older people to retain a sense of independence, safety and belonging. Encouraging older adults to remain in their communities has contributed to planning and design concepts such as Age-Friendly Cities and Communities, Lifelong Homes and Liveable Neighbourhoods. However, current urban planning and development models have overlooked the notion of sense of place, articulated through supports for active living, social participation and meaningful involvement in the community. Integrating sense of place into the built environment is essential for supporting active ageing, ensuring that older adults can continue to make a positive contribution in their communities and potentially reducing health and social care costs. This project has three core aims: (i) to investigate how sense of place is experienced by older people from different social settings living in diverse neighbourhoods in Brazil and the UK; (ii) to translate these experiences into designs for age friendly communities that support sense of place; and (iii) to better articulate the role of older adults as active placemakers in the design process by involving the community at all stages of the research. We will undertake fieldwork in a total of 18 neighbourhoods (of varying densities and income levels) across 6 case study cities in Brazil (Pelotas, Porto Alegre, and Brasilia) and the UK (Edinburgh, Manchester and Glasgow). We will use a range of methods to achieve the project aims, including sense of place surveys and semi-structured interviews alongside experiential methods including 'go along' walks, photo and video diaries and community mapping exercises to capture the place-based needs of older adults. The new data generated will answer the following research questions: (i) How is sense of place experienced by older adults from different social classes living in diverse neighbourhoods in Brazil and the UK? (ii) What services, amenities and features are needed to create age friendly communities that promote healthy cities and active ageing in different urban and cultural contexts? (iii) How can communities be designed to better integrate the sense of place needs of older adults across different urban and cultural contexts? A community-based participatory approach will be adopted to the research, bringing together all stakeholders in a process of collaborative dialogue and co-design to challenge the hierarchical power relationships that exist when planning 'for' and not 'with' older people. The results will be used to co-create place-making tools and resources which are essential for designing age friendly environments for older adults. Findings will be disseminated to community, policymaker, practitioner and academic audiences through ongoing and end of project knowledge translation activities.

Disclosure of information with far right's ideas, negationism of science and anti-vaccine attitude x Risk of COVID-19

The electoral preference by Bolsonaro in the first round of Brazil presidential election 2018 per state, shows a relation with the amount of deaths by Covid-19 per 100000, excess death per 100,000, increased P-score and intensity in reducing Brazilian population growth in the 1st quarter 2021

Content

In the period from January to April (1st Quadrimester Q1) from 2021 and 2019 per state (UF)

Main variables for each of the 27 Brazilian states and 4 States groups

1. The main population rates: - Number deaths, excess deaths, births, birth rate, mortality rate, vegetative growth, p-score, total population, population> 70A., Demographic density

2. The main rates of Pandemic by Coronavirus - Covid-19:

   • No. Total cases, cases Q1, Nº Total deaths, Nº Q1 deaths, Total deaths / 100000 hab, mortality rate, cases / 100000 hab

3. The main metrics of the 2018 presidential election:

   • Voters, voting paragraphs, nº of votes in Bolsonararo 1st turn, nº of abstinences.

Groups of Brazilian UFS (Federation States)

1. States that Bolsonaro received more than 50% of the votes in the 1st turn
2. States that Bolsonaro received less than 50% of the votes in the 1st turn and more than 50% in the 2nd turn
3. States that Bolsonaro received less than 50% of the votes in the 1st and 2nd shifts
4. Sum of the 27 Brazilian states

PT(BR) - version

Divulgação de informações com idéias da extrema direita, negacionismo da ciência e atitude anti-vacina x risco de Covid-19

A preferência eleitoral por Bolsonaro no 1º turno de 2018 por estado, mostra-se relacionada com a quantidade de mortes por COVID-19, excesso de mortes por 100000, aumento do P-score e intensidade na redução do crescimento populacional brasileiro no 1ºquadrimestre de 2021.

No período de Janeiro a Abril(1º Quadrimestre Q1) de 2021 e 2019 por estado (UF)

Principais variáveis

1. As principais taxas populacionais: - nº mortes, excesso de mortes, nº nascimentos, taxa de natalidade, taxa de mortalidade, crescimento vegetativo, P-score, população total, população > 70a., densidade demográfica

2. As principais taxas da pandemia por Coronavirus - COVID-19:

   • nº casos totais, nº casos Q1, nº mortes totais, nº mortes Q1, mortes totais/100000 hab, taxa de Mortalidade, casos/100000 hab

3. As principais métricas da eleição presidencial de 2018:

   • nº eleitores, nº votantes, nº de votos em Bolsonaro 1º turno, nº de abstinências.

Grupos de UFs (Estados da Federação)

1.Estados que Bolsonaro recebeu mais de 50% dos votos no 1º turno 2.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º turno e mais de 50% no 2º turno 3.Estados que Bolsonaro recebeu menos que 50% dos votos no 1º e 2º turnos 4.Soma dos 27 Estados Brasileiros

Mendes F.M., Marenzi A.W.C., Di Domenico M. 2006. Population patterns and seasonal observations on density and distribution of Holothuria grisea (Holothuroidea: Aspidochirotida) on the Santa Catarina Coast, Brazil. SPC Beche-de-mer Information Bulletin 23:5-10.

Individual encounter history data with information of trap names, occasions, sessions and sex in eaxh area where margays were detected. (CSV)

Non-invasive genetic analysis has been frequently employed to estimate ecological and population parameters for many secretive and/or threatened species. However, Neotropical carnivores have so far been scarcely targeted by such studies. The Neotropical otter (Lontra longicaudis) is a poorly-known species for which local levels of genetic diversity and demographic parameters are virtually absent. We employed non-invasive sampling and amplification of microsatellite loci to investigate population size and density, spatial organization, and relatedness of a wild Neotropical otter population in an Atlantic forest area in southern Brazil. We directly identified 28 individuals and estimate a rather high population density at the study site. Spatial organization analysis indicated that male cumulative displacement was higher than that of females, with the latter sex showing evidence of philopatric behaviour. Also, the reconstruction of genealogical relationships suggests that spatial organization in this otter appears to be influenced by relatedness. By allowing the testing of specific hypothesis targeting these issues, our results provided important glimpses into the Neotropical otter's population biology. Moreover, the findings of the present study reaffirm the power of non-invasive genetics to investigate the biology of this elusive species, and open up new avenues for ecological and demographic studies of other Neotropical carnivores.

Background: Improper antibiotic use is one of the main drivers of bacterial resistance to antibiotics, increasing infectious diseases morbidity and mortality and raising costs of healthcare. The level of antibiotic consumption has been shown to vary according to socioeconomic determinants (SED) such as income and access to education. In many Latin American countries, antibiotics could be easily purchased without a medical prescription in private pharmacies before enforcement of restrictions on over-the-counter (OTC) sales in recent years. Brazil issued a law abolishing OTC sales in October 2010. This study seeks to find SED of antibiotic consumption in the Brazilian state of São Paulo (SSP) and to estimate the impact of the 2010 law. Methods: Data on all oral antibiotic sales having occurred in the private sector in SSP from 2008 to 2012 were pooled into the 645 municipalities of SSP. Linear regression was performed to estimate consumption levels that would have occurred in 2011 and 2012 if no law regulating OTC sales had been issued in 2010. These values were compared to actual observed levels, estimating the effect of this law. Linear regression was performed to find association of antibiotic consumption levels and of a greater effect of the law with municipality level data on SED obtained from a nationwide census. Results: Oral antibiotic consumption in SSP rose from 8.44 defined daily doses per 1,000 inhabitants per day (DID) in 2008 to 9.95 in 2010, and fell to 8.06 DID in 2012. Determinants of a higher consumption were higher human development index, percentage of urban population, density of private health establishments, life expectancy and percentage of females; lower illiteracy levels and lower percentage of population between 5 and 15 years old. A higher percentage of females was associated with a stronger effect of the law. Conclusions: SSP had similar antibiotic consumption levels as the whole country of Brazil, and they were effectively reduced by the policy.