In 2024, approximately 11.9 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 11.9 million inhabitants, and Rio de Janeiro with around 6.7 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 88 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 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.

In 2025, approximately 23 million people lived in the São Paulo metropolitan area, making it the biggest in Latin America and the Caribbean and the sixth most populated in the world. The homonymous state of São Paulo was also the most populous federal entity in the country. The second place for the region was Mexico City with 22.75 million inhabitants. Brazil's cities Brazil is home to two large metropolises, only counting the population within the city limits, São Paulo had approximately 11.45 million inhabitants, and Rio de Janeiro 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 88 percent of inhabitants living in cities. Mexico City Mexico City's metropolitan area ranks sevenths in the ranking of most populated cities in the world. Founded over the Aztec city of Tenochtitlan in 1521 after the Spanish conquest as the capital of the Viceroyalty of New Spain, the city still stands as one of the most important in Latin America. Nevertheless, the preeminent economic, political, and cultural position of Mexico City has not prevented the metropolis from suffering the problems affecting the rest of the country, namely, inequality and violence. Only in 2023, the city registered a crime incidence of 52,723 reported cases for every 100,000 inhabitants and around 24 percent of the population lived under the poverty line.

This paper investigated population misreporting in Brazil from 1991 to 2010. We have firstly documented that there is a discontinuity in the population distribution, but only for census years. Secondly, we estimated the elasticity of population (mis)reporting regarding intergovernmental grant that ranges from 0.3 to 2.5. Lastly, we have found that not only political variables operate to help those municipalities to obtain more federal funds, but also fiscal autonomy and the proximity to local population office bureau.

Context

This dataset has information about brazilian cities.

Content

• city: the name of the city
• lat: the latitude of each city
• lng: the longitude of each city
• country: the country of each city (all Brazil in this case)
• iso2: country code (BR)
• admin: state of each city
• capital: wheter the city is a capital or not
• population: amount of inhabitants of each city
• population_proper: area contained within city limits

This dataset provides information about: Population in Brazil by Municipalities and Mortality rates in Brazil by States.

This dataset collects information on municipal expenditures, water-sewerage-and trash collection service coverage, and basic socioeconomic characteristics at municipal level, for two census waves (2000; 2010) for all municipalities of Brazil, Chile, and Mexico.

This statistic shows the ten largest cities in Italy in 2025. In 2025, around 2.75 million people lived in Rome, making it the largest city in Italy. Population of Italy Italy has high population figures and a high population density in comparison to other European countries. A vast majority of Italians lives in urban areas and in the metropolises (as can be seen in this statistic), while other areas, such as the island Sardinia, are rather sparsely inhabited. After an increase a few years ago, Italy’s fertility rate, i.e. the average amount of children born to a woman of childbearing age, is now on a slow decline; however, it is still high enough to offset any significant effect the decrease might have on the country’s number of inhabitants. The median age of Italy’s population has been increasing rapidly over the past 50 years – which mirrors a lower mortality rate – and Italy is now among the countries with the highest life expectancy worldwide, only surpassed by two Asian countries, namely Japan and Hong Kong. Currently, the average life expectancy at birth in Italy is at about 83 years. Most of Italy’s population is of Roman Catholic faith. The country actually boasts one of the largest numbers of Catholics worldwide; other such countries include Brazil, Mexico and the United States. The central government of the Roman Catholic Church, the Holy See, is located in Vatican City in the heart of Italy’s capital and ruled by the Bishop of Rome, the Pope. Officially, Vatican City does not belong to Italy, but is a sovereign state with its own legislation and jurisdiction. It has about 600 inhabitants, who are almost exclusively members of the clergy or government officials.

This dataset holds annual dengue case notifications, population and dengue incidence per 100,000 population for Brazilian cities, for 2007-2024. It underlies the visualisations of annual dengue case incidence in Niterói compared with cities in Rio de Janeiro state or all of Brazil, pre and post Wolbachia implementation, reported in the submitted manuscript by Anders et al "Long-term durability and public health impact of city-wide wMel Wolbachia mosquito releases in Niterói, Brazil during a dengue epidemic surge".Dengue case data source: https://datasus.saude.gov.br/informacoes-de-saude-tabnet/Population data source: https://sidra.ibge.gov.br/pesquisa/censo-demografico

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

There is a considerable gap linking human dimensions and marine ecosystem services with Sustainable Development Goals, and one of these issues relate to differing perspectives and ideas around concepts of human development. There is also a lack of contemporary evaluations of coastal communities from developing nations under the lens of wellbeing and social vulnerability indexes. This study contributes to that discussion by presenting an analysis of Brazilian coastal municipalities, based on two indexes: The Social Vulnerability Index (SVI) and the Municipal Human Development Index (MHDI). These indicators intend to map some aspects of social well-being and development in the Brazilian territory under different perspectives. MHDI illustrates the average population conditions in a certain territory for humans to thrive, while the SVI points more specifically to the lack of assets necessary for wellbeing in a territory. The main aims are to map inequalities between coastal municipalities based on these two indexes and to provide a critical view reinforcing the importance of also considering natural capital as a key issue for wellbeing. Both indexes were developed with data from the Brazilian Institute of Geography and Statistics Census of 2010, the most recent one available for municipalities. Overall, 65.9 and 78% of a total of 387 Brazilian coastal municipalities assessed were ranked below SVI and MHDI country average values, respectively. Both indexes indicated higher human development conditions in Southern municipalities than in Northern ones, especially for income and education conditions, also showing large heterogeneity of discrepancies among and within regions. The importance of combined approaches for local socioeconomic wellbeing improvements, as measured by the MHDI and the SVI, and natural capital optimization seems essential for improvements in coastal communities’ quality-of-life conditions.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Abstract

This study is an experiment designed to compare the performance of three methodologies for sampling households with migrants:

• a stratified sample using the census to sample census tracts randomly, in which each household is then listed and screened to determine whether or not it has a migrant, with the full length questionnaire then being applied in a second phase only to the households of interest;
• a snowball survey in which households are asked to provide referrals to other households with migrant members;
• an intercept point survey (or time-and-space sampling survey), in which individuals are sampled during set time periods at a prespecified set of locations where households in the target group are likely to congregate.

Researchers from the World Bank applied these methods in the context of a survey of Brazilians of Japanese descent (Nikkei), requested by the World Bank. There are approximately 1.2-1.9 million Nikkei among Brazil’s 170 million population.

The survey was designed to provide detail on the characteristics of households with and without migrants, to estimate the proportion of households receiving remittances and with migrants in Japan, and to examine the consequences of migration and remittances on the sending households.

The same questionnaire was used for the stratified random sample and snowball surveys, and a shorter version of the questionnaire was used for the intercept surveys. Researchers can directly compare answers to the same questions across survey methodologies and determine the extent to which the intercept and snowball surveys can give similar results to the more expensive census-based survey, and test for the presence of biases.

Geographic coverage

Sao Paulo and Parana states

Analysis unit

Japanese-Brazilian (Nikkei) households and individuals

The 2000 Brazilian Census was used to classify households as Nikkei or non-Nikkei. The Brazilian Census does not ask ethnicity but instead asks questions on race, country of birth and whether an individual has lived elsewhere in the last 10 years. On the basis of these questions, a household is classified as (potentially) Nikkei if it has any of the following: 1) a member born in Japan; 2) a member who is of yellow race and who has lived in Japan in the last 10 years; 3) a member who is of yellow race, who was not born in a country other than Japan (predominantly Korea, Taiwan or China) and who did not live in a foreign country other than Japan in the last 10 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

1) Stratified random sample survey

Two states with the largest Nikkei population - Sao Paulo and Parana - were chosen for the study.

The sampling process consisted of three stages. First, a stratified random sample of 75 census tracts was selected based on 2000 Brazilian census. Second, interviewers carried out a door-to-door listing within each census tract to determine which households had a Nikkei member. Third, the survey questionnaire was then administered to households that were identified as Nikkei. A door-to-door listing exercise of the 75 census tracts was then carried out between October 13th, 2006, and October 29th, 2006. The fieldwork began on November 19, 2006, and all dwellings were visited at least once by December 22, 2006. The second wave of surveying took place from January 18th, 2007, to February 2nd, 2007, which was intended to increase the number of households responding.

2) Intercept survey

The intercept survey was designed to carry out interviews at a range of locations that were frequented by the Nikkei population. It was originally designed to be done in Sao Paulo city only, but a second intercept point survey was later carried out in Curitiba, Parana. Intercept survey took place between December 9th, 2006, and December 20th, 2006, whereas the Curitiba intercept survey took place between March 3rd and March 12th, 2007.

Consultations with Nikkei community organizations, local researchers and officers of the bank Sudameris, which provides remittance services to this community, were used to select a broad range of locations. Interviewers were assigned to visit each location during prespecified blocks of time. Two fieldworkers were assigned to each location. One fieldworker carried out the interviews, while the other carried out a count of the number of people with Nikkei appearance who appeared to be 18 years old or older who passed by each location. For the fixed places, this count was made throughout the prespecified time block. For example, between 2.30 p.m. and 3.30 p.m. at the sports club, the interviewer counted 57 adult Nikkeis. Refusal rates were carefully recorded, along with the sex and approximate age of the person refusing.

In all, 516 intercept interviews were collected.

3) Snowball sampling survey

The questionnaire that was used was the same as used for the stratified random sample. The plan was to begin with a seed list of 75 households, and to aim to reach a total sample of 300 households through referrals from the initial seed households. Each household surveyed was asked to supply the names of three contacts: (a) a Nikkei household with a member currently in Japan; (b) a Nikkei household with a member who has returned from Japan; (c) a Nikkei household without members in Japan and where individuals had not returned from Japan.

The snowball survey took place from December 5th to 20th, 2006. The second phase of the snowballing survey ran from January 22nd, 2007, to March 23rd, 2007. More associations were contacted to provide additional seed names (69 more names were obtained) and, as with the stratified sample, an adaptation of the intercept survey was used when individuals refused to answer the longer questionnaire. A decision was made to continue the snowball process until a target sample size of 100 had been achieved.

The final sample consists of 60 households who came as seed households from Japanese associations, and 40 households who were chain referrals. The longest chain achieved was three links.

Mode of data collection

Face-to-face [f2f]

Research instrument

1) Stratified sampling and snowball survey questionnaire

This questionnaire has 36 pages with over 1,000 variables, taking over an hour to complete.

If subjects refused to answer the questionnaire, interviewers would leave a much shorter version of the questionnaire to be completed by the household by themselves, and later picked up. This shorter questionnaire was the same as used in the intercept point survey, taking seven minutes on average. The intention with the shorter survey was to provide some data on households that would not answer the full survey because of time constraints, or because respondents were reluctant to have an interviewer in their house.

2) Intercept questionnaire

The questionnaire is four pages in length, consisting of 62 questions and taking a mean time of seven minutes to answer. Respondents had to be 18 years old or older to be interviewed.

Response rate

1) Stratified random sampling 403 out of the 710 Nikkei households were surveyed, an interview rate of 57%. The refusal rate was 25%, whereas the remaining households were either absent on three attempts or were not surveyed because building managers refused permission to enter the apartment buildings. Refusal rates were higher in Sao Paulo than in Parana, reflecting greater concerns about crime and a busier urban environment.

2) Intercept Interviews 516 intercept interviews were collected, along with 325 refusals. The average refusal rate is 39%, with location-specific refusal rates ranging from only 3% at the food festival to almost 66% at one of the two grocery stores.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

Abstract

The National Household Survey - PNAD investigates annuall and permanently, general characteristics of the population, education , labor, income and housing, and others with varying regularity, according to the information needs for the country. Topics include characteristics on migration, fertility , marriage, health, food security, among other topics. The survey of these statistics is an important instrument for the formulation, validation and evaluation of policies to socio-economic development and the improvement of living conditions in Brazil.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey is conducted by a random sample of households. The information is provided by person resident or non-resident, considered capable of providing information for the whole neighborhood and the home. The interviewer is instructed not to accept a person under 14 years of age as an informant. The sampling plan uses cluster sampling, self-weighted in three stages (respectively municipalities, census tracts and households) with geographical stratification of the units of the first stage set for each state. The large municipalities in terms of population and those belonging to the metropolitan areas were each treated as a stratum and therefore included in the sample with certainty, being called autorrepresentativos. The other municipalities within the same geographic microregion were grouped into strata of approximately equal size, and designated non autorrepresentativos. Strata in these municipalities were selected systematically with probability proportional to size (ppt).

Sectors are the unit of selection in the second stage and also are selected systematically and ppt, in which case the size is measured by the number of households. The sectors were stratified according to the situation of urban and rural states of the northern region, except for Tocantins, to allow comparison of indicators from PNADs after 2004 with those performed before insertion of the rural area of the northern states. In other regions this stratification is only implicit, ie, there is an ordering for the situation of the sector before the systematic selection. Municipalities and selected sectors are kept in the sample until they are available new Census data, when they are selected new units for the sample.

Each year, in each sector selected for the sample is prepared (or updated) in the field a listing of households, producing an updated register for selection. An important characteristic of this listing operation refers to the Register of New Buildings, which is prepared to contain the buildings account for large changes in the sizes of sectors. The inventory of new construction is done in the municipalities of the sample, both in the sectors selected for the sample as those not selected. An area of new construction is excluded from the area of the original sector and is dealt with separately at the time of selection of households in this case is performed according to the sample fraction of the area. Households, which are units of the third selection stage, are formed by private households and the housing units in collective households occupied during the listing operation. The initial number of households per sector in the sample was set at 16. The sampling fraction indicates the proportion of the population constituting the sample. Currently fractions ranging from 1/50 (rural area of Roraima) to 1/800 (Sao Paulo). How the selection of households in each selected sector for the sample is done systematically to ensure self-weighting sample, the selection range of households remains fixed from year to year. This procedure entails an annual increase in the number of households in the sample, it depends on the number of households upgraded the sector by listing operation. In PNAD 2008, approximately 151,000 households were selected. The final size of the sample of PNAD 2009 was approximately 851 municipalities, 7818 153837 sectors and households. In 2007 PNAD introduced the use of electronic collector ( Personal Digital Assistant - PDA) for carrying out data collection, making it possible to improve the research operating system. Also during PNAD 2007 the DIA system was used, which is an imputation system that automatically detects qualitative data errors. Developed by the National Institute of Statistics - INE of Spain, the software aims to facilitate debugging censuses and large statistical research. In this first year of use of the application, all steps of criticism usually applied to data from the National Household Survey core questionnaire were performed, followed by a process of simultaneous validation of the data collected. In 2008 PNAD used only the Canadian Census Edit and Imputation System - CANCEIS already including the procedures usually applied to critical data from the questionnaires. Starting from PNAD 2011 sample selection of Rondônia, Acre, Amazonas, Roraima, Pará and Amapá followed the same methodology in other units of the Federation.

Mode of data collection

Face-to-face [f2f]

In 2023, it was estimated that more than ********* Brazilians were living outside Brazil. The United States had the largest community, with over ********* Brazilian citizens. Portugal was the second country with the largest Brazilian community, namely ******* citizens. Brazilians abroad The Brazilian community sought economic opportunities in the United States in the 1980s, leading to the establishment of communities in New York and Boston. Facilitated by the common language and Portugal's favorable laws for the Community of Portuguese-speaking countries, Lisbon became the most popular destination in Europe. This city harbors more than ****** Brazilians, with women making up the majority of these. Immigration in Brazil Although more than ********* Brazilians live outside of Brazil, the country has had a positive migration rate since 2010, meaning that more people are arriving than leaving. One factor contributing to this is the current humanitarian crisis in Venezuela, which has increased the number of refugees arriving in Brazil each year.

According to a 2024 survey, around 35 percent of WhatsApp users in Brazil lived in large cities with populations between 100 thousand and one million inhabitants. Another 25 percent of the social platform users lived in megacities with over 5 million inhabitants, while medium-sized municipalities concentrated around 15 percent of the app user base in the country. Overall, around 14 percent of respondents lived in cities with populations over 1 million.

This dataset is intended for researchers, students, and policy makers for reference and mapping purposes, and may be used for basic applications such as viewing, querying, and map output production, or to provide a basemap to support graphical overlays and analysis with other spatial data.

AbstractUrbanization often substantially influences animal movement and gene flow. However, few studies to date have examined gene flow of the same species across multiple cities. In this study, we examine brown rats (Rattus norvegicus) to test hypotheses about the repeatability of neutral evolution across four cities: Salvador, Brazil; New Orleans, USA; Vancouver, Canada; New York City, USA. At least 150 rats were sampled from each city and genotyped for a minimum of 15,000 genome-wide SNPs. Levels of genome-wide diversity were similar across cities, but varied across neighborhoods within cities. All four populations exhibited high spatial autocorrelation at the shortest distance classes (< 500 m) due to limited dispersal. Coancestry and evolutionary clustering analyses identified genetic discontinuities within each city that coincided with a resource desert in New York City, major waterways in New Orleans, and roads in Salvador and Vancouver. Such replicated studies are crucial to assessing the generality of predictions from urban evolution, and have practical applications for pest management and public health. Future studies should include a range of global cities in different biomes, incorporate multiple species, and examine the impact of specific characteristics of the built environment and human socioeconomics on gene flow. Usage notesPLINK .map file for New Orleans rat SNP GenotypesPLINK .map file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.mapPLINK .ped file for New Orleans rat SNP GenotypesPLINK .ped file for New Orleans SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NOL.plink.pedPLINK .map file for New York City rat SNP GenotypesPLINK .map file for New York City SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.mapPLINK .ped file for New York City rat SNP GenotypesPLINK .ped file for New York City SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.NYC.plink.pedPLINK .map file for Salvador, Brazil rat SNP GenotypesPLINK .map file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.mapPLINK .ped file for Salvador, Brazil rat SNP GenotypesPLINK .ped file for Salvador, Brazil SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.SAL.plink.pedPLINK .map file for Vancouver rat SNP GenotypesPLINK .map file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file of the same name, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.mapPLINK .ped file for Vancouver rat SNP GenotypesPLINK .ped file for Vancouver SNP genotypes. The genotypes themselves are in the .ped file, and the .map file contains the chromosomal coordinates for each SNP.VAN.plink.ped

The statistic shows the 30 largest countries in the world by area. Russia is the largest country by far, with a total area of about 17 million square kilometers.

Population of Russia

Despite its large area, Russia - nowadays the largest country in the world - has a relatively small total population. However, its population is still rather large in numbers in comparison to those of other countries. In mid-2014, it was ranked ninth on a list of countries with the largest population, a ranking led by China with a population of over 1.37 billion people. In 2015, the estimated total population of Russia amounted to around 146 million people. The aforementioned low population density in Russia is a result of its vast landmass; in 2014, there were only around 8.78 inhabitants per square kilometer living in the country. Most of the Russian population lives in the nation’s capital and largest city, Moscow: In 2015, over 12 million people lived in the metropolis.