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.

Context

While working with geographical data in my internship, I had to analyze information regarding the cities of Brazil, using their respective latitudes and longitudes. The data was obtained from varied sources.

Content

Schema: 1. cd_ibge ("IBGE" code of the City) 2. nm_municipio (name of each City) 3. nm_uf (name of each State) 4. cd_uf (State name abbreviation) 5. bl_capital (boolean indicating if the city is the State capital or not) 6. regiao_uf (region of the State) 7. lat_municipio (latitude of the City) 8. long_municipio (longitude of the City) 9. lat_long_municipio (lat/long of the City) 10. lat_central_uf (latitude of the State - centralized) 11. long_central_uf (longitude of the State - centralized) 12. lat_long_central_uf (lat/long of the State - centralized)

In Brazil, **** percent of consumers earned at least the equivalent of the highest 40 percent of global income earners as of 2022 in purchasing power parity (PPP) terms. Those who earned at least the equivalent of the top 10 percent of global income earners stood at *** percent.

📄 Dataset Description

This dataset contains climate and air quality data collected from 10 Brazilian cities, covering a wide range of environmental variables. It aims to support data science projects related to weather analysis, air pollution monitoring, public health research, and environmental modeling.

Each row represents a single timestamped observation for a specific city.

The data was collected through web scraping from a public website using an Apache Airflow pipeline, which fetched the data hourly between May 25, 2025 and June 1, 2025.

🌍 Cities Included

• Fernandópolis
• Ribeirão Preto
• São Paulo
• Porto Alegre
• Rio de Janeiro
• Manaus
• Belo Horizonte
• Fortaleza
• Campo Grande
• Curitiba

🌡️ Columns

• city: Name of the Brazilian city where the data was collected.
• timestamp: Date and time (ISO format) of the observation.
• temperature: Ambient temperature in degrees Celsius (°C).
• wind: Wind speed in meters per second (m/s).
• humidity: Relative humidity as a percentage (%).
• dew_point: Dew point temperature in degrees Celsius (°C).
• pressure: Atmospheric pressure in hectopascals (hPa).
• uv_index: Ultraviolet radiation index (scale from 0 to 11+).

🧪 Air Quality Indicators

Each pollutant has two associated fields:

• [pollutant]_aqi: Air Quality Index value for the pollutant, following local environmental standards.
• [pollutant]_medida: Measured concentration of the pollutant (in µg/m³ or ppm, depending on the pollutant).

Pollutants included:

• O3_aqi, O3_medida: Ozone (O₃)
• CO_aqi, CO_medida: Carbon Monoxide (CO)
• NO2_aqi, NO2_medida: Nitrogen Dioxide (NO₂)
• PM10_aqi, PM10_medida: Particulate Matter ≤10 µm
• PM2_5_aqi, PM2_5_medida: Particulate Matter ≤2.5 µm
• SO2_aqi, SO2_medida: Sulfur Dioxide (SO₂)

Feel free to use this dataset for exploratory analysis, modeling, forecasting, or visualization projects related to air and climate conditions in urban Brazil.

Acrelandia, located in the northern state of Acre, was the most polluted city in Brazil in 2022, based on fine air particulate matter concentration (PM2.5). Throughout the year, the city had an average particulate matter concentration of 23.3 micrograms per cubic meter. The World Health Organization's air quality standards recommend a maximum annual average concentration of 10 μg/m³. Four of the top five most polluted cities in Brazil that year were located in the state of Acre.

Context

Brazil has a very powerful Freedom of Information law which allows any citizen to request any data from the government which is not restricted, and where these restrictions are well defined exceptions. But still, having the right to request the information does not mean it is easy to get it. Bureaucracy and ignorance of the law gets in the way many times. In order to encourage the government to put their databases in order and to inspire people to have the courage to ask the government for information, we made a massive request of information, for the complete dataset of crime data available for the last 10 years, in the biggest city of South America.

Content

This dataset contains structured data about all crime occurrences that have been acted upon by the PM, the main police force in Sao Paulo. The dataset is not consistent in its completeness, as some of the towns comprising the Greater Sao Paulo were slow in collecting full data. It also does not contain the actual historic of each crime report, as that would violate privacy.

Acknowledgements

We would like to acknowledge the prompt assistance from the SSP (Secretaria de Seguranca Publica), for providing the data with minimal resistance.

Inspiration

Primarily we would like to see a visualisation of this data, so that the people can have an idea of how crime has evolved in their city, which crimes are more prevalent in which areas, etc. In addition, any model which can predict at what times and where the police is most needed would be helpful, as this can then be sent to the SSP to help them in planning.

BackgroundAn interferon-γ release assay, QuantiFERON-TB (QFT) test, has been introduced an alternative test for the diagnosis of latent Mycobacterium tuberculosis infection (LTBI). Here, we compared the performance of QFT with tuberculin skin test (TST) measured at two different cut-off points among primary health care work (HCW) in Brazil.MethodsA cross-sectional study was carried out among HCWs in four Brazilian cities with a known history of high incidence of TB. Results of the QFT were compared to TST results based on both ≥5 mm and ≥10 mm as cut-off points.ResultsWe enrolled 632 HCWs. When the cut-off value of ≥10 mm was used, agreement between QFT and TST was 69% (k = 0.31), and when the cut-off of ≥5 mm was chosen, the agreement was 57% (k = 0.22). We investigated possible factors of discordance of TST vs QFT. Compared to the TST−/QFT− group, risk factors for discordance in the TST+/QFT− group with TST cut-off of ≥5 mm included age between 41–45 years [OR = 2.70; CI 95%: 1.32–5.51] and 46–64 years [OR = 2.04; CI 95%: 1.05–3.93], BCG scar [OR = 2.72; CI 95%: 1.40–5.25], and having worked only in primary health care [OR = 2.30; CI 95%: 1.09–4.86]. On the other hand, for the cut-off of ≥10 mm, BCG scar [OR = 2.26; CI 95%: 1.03–4.91], being a household contact of a TB patient [OR = 1.72; CI 95%: 1.01–2.92] and having had a previous TST [OR = 1.66; CI 95%: 1.05–2.62], were significantly associated with the TST+/QFT− group. No statistically significant associations were found among the TST−/QFT+ discordant group with either TST cut-off value.ConclusionsAlthough we identified BCG vaccination to contribute to the discordance at both TST cut-off measures, the current Brazilian recommendation for the initiation of LTBI treatment, based on information gathered from medical history, TST, chest radiograph and physical examination, should not be changed.

In 2024, six of the eight Brazilian cities with the highest homicide rates were in the Northeast. Feira da Santana led the ranking of the most violent city in Brazil, with a murder rate of ***** per 100,000 inhabitants. It was followed followed by Recife, with a homicide rate of more than ** per 100,000 inhabitants. In Latin America and the Caribbean, Feira da Santana was the **** most deadly city.

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.

This statistic presents the cities that Brazilians would like to visit at least once in their lifetime, as of April 2018. On a survey, 16 percent of respondents in Brazil chose Paris as their dream city holiday destination, followed by New York, with 10 percent of respondents. When asked about countries, Brazilians chose their own country as the most welcoming destination.

The concentration of people living in small areas has increased in the last decade, with more than half of the world's population living in cities. This is particularly true for Latin America, a region with no particular high contribution to the world total population, but hosts several large cities. The increase in urbanization causes several threats to wildlife that face the loss of their habitat and novel environmental pressures. As the number of wildlife entering cities seems to have increased in the last year, we characterize the temporal and geographical events of a widely distributed carnivore, the puma, Puma concolor. We performed an exhaustive search for media news regarding the sighting, capture, and/or killing of pumas within human settlement areas, and tried to relate them with potential explanatory variables. We found a total of 162 events in Latin America in a period of the last 10 years, particularly concentrated in the year 2020. Most records came from Brazil, followed by Argentina, Chile, and Mexico. Of the total, 41% were only sightings, 58% were captures, and a minor percentage were considered as mascotism. Almost the same number of records came from highly populated areas (cities) than from low populated areas (rural) but with important differences between countries. The countries with more records in urban areas (Brazil and Mexico) showed a larger surface occupied by cities. The countries with most records in rural areas (Argentina and Chile) present the opposite pattern of occupied surface. This might indicate that different percentages of areas dedicated to cities or urban spaces might explain the differences among countries. The most important variable related to puma events in the populated areas was sky brightness, while human density and cattle density explained minor parts. The “anthropause” due to the COVID-19 pandemic might explain the larger number of records from 2020, while the absence of high-quality habitats due to fragmentation and high cattle density, might force the pumas to enter populated areas searching for food. Minor values of night lights could be related to a facilitation of efficiency of foraging behavior. Although some bias might exist in the data, the results should be taken into account as general statements for all analyzed countries.

The datasets are split by census block, cities, counties, districts, provinces, and states. The typical dataset includes the below fields.

Column numbers, Data attribute, Description 1, device_id, hashed anonymized unique id per moving device 2, origin_geoid, geohash id of the origin grid cell 3, destination_geoid, geohash id of the destination grid cell 4, origin_lat, origin latitude with 4-to-5 decimal precision 5, origin_long, origin longitude with 4-to-5 decimal precision 6, destination_lat, destination latitude with 5-to-6 decimal precision 7, destination_lon, destination longitude with 5-to-6 decimal precision 8, start_timestamp, start timestamp / local time 9, end_timestamp, end timestamp / local time 10, origin_shape_zone, customer provided origin shape id, zone or census block id 11, destination_shape_zone, customer provided destination shape id, zone or census block id 12, trip_distance, inferred distance traveled in meters, as the crow flies 13, trip_duration, inferred duration of the trip in seconds 14, trip_speed, inferred speed of the trip in meters per second 15, hour_of_day, hour of day of trip start (0-23) 16, time_period, time period of trip start (morning, afternoon, evening, night) 17, day_of_week, day of week of trip start(mon, tue, wed, thu, fri, sat, sun) 18, year, year of trip start 19, iso_week, iso week of the trip 20, iso_week_start_date, start date of the iso week 21, iso_week_end_date, end date of the iso week 22, travel_mode, mode of travel (walking, driving, bicycling, etc) 23, trip_event, trip or segment events (start, route, end, start-end) 24, trip_id, trip identifier (unique for each batch of results) 25, origin_city_block_id, census block id for the trip origin point 26, destination_city_block_id, census block id for the trip destination point 27, origin_city_block_name, census block name for the trip origin point 28, destination_city_block_name, census block name for the trip destination point 29, trip_scaled_ratio, ratio used to scale up each trip, for example, a trip_scaled_ratio value of 10 means that 1 original trip was scaled up to 10 trips 30, route_geojson, geojson line representing trip route trajectory or geometry

The datasets can be processed and enhanced to also include places, POI visitation patterns, hour-of-day patterns, weekday patterns, weekend patterns, dwell time inferences, and macro movement trends.

The dataset is delivered as gzipped CSV archive files that are uploaded to your AWS s3 bucket upon request.

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.

Abstract Background: Hypertension is the main risk factor for cardiovascular diseases. Technical quality of sphygmomanometers is a prerequisite for the correct measurement of arterial pressure. Objectives: To evaluate sphygmomanometers available in emergency services in the city of Belo Horizonte, Brazil. Methods: We performed a cross-sectional, observational, non-interventional study to evaluate characteristics of the sphygmomanometers available in adult emergency services of public and private hospitals in the city of Belo Horizonte, Brazil. We evaluated 337 sphygmomanometers of 25 hospitals - 15 (of 16) public hospitals and 10 (of 12) private hospitals. Results: Twenty-six percent (88/337) of devices were considered inadequate regarding the INMETRO (National Institute of Metrology, Quality and Technology) standards, 39.2% (132/337) for calibration dates, and 54% (188/337) for the mismatching between cuff's and device's brands. In 13 of 25 hospitals (52%), there were no spare cuffs in different sizes for different arm circumferences. Higher adequacy was found for aneroid and mercury sphygmomanometers used in private hospitals (p = 0.038 and p < 0.001, respectively) and electronic devices used in public hospitals (p < 0.001) compared with others. Conclusion: Seventy-eight percent of sphygmomanometers available in emergency services had technical inadequacies, and half of these services had no spare cuffs in different sizes available. These findings serve as a warning of the conditions of the equipment used in healthcare services provided to the general population in Brazil.

The identification and characterisation of Cryptosporidiumgenotypes and subtypes are fundamental to the study of cryptosporidiosis epidemiology, aiding in prevention and control strategies. The objective was to determine the genetic diversity ofCryptosporidium in samples obtained from hospitals of Rio de Janeiro, Brazil, and Buenos Aires, Argentina. Samples were analysed by microscopy and TaqMan polymerase chain reaction (PCR) assays forCryptosporidium detection, genotyped by nested-PCR-restriction fragment length polymorphism (RFLP) analysis of the 18S rRNA gene and subtyped by DNA sequencing of the gp60 gene. Among the 89 samples from Rio de Janeiro, Cryptosporidium spp were detected in 26 by microscopy/TaqMan PCR. In samples from Buenos Aires,Cryptosporidium was diagnosed in 15 patients of the 132 studied. The TaqMan PCR and the nested-PCR-RFLP detected Cryptosporidium parvum, Cryptosporidium hominis, and co-infections of both species. In Brazilian samples, the subtypes IbA10G2 and IIcA5G3 were observed. The subtypes found in Argentinean samples were IbA10G2, IaA10G1R4, IaA11G1R4, and IeA11G3T3, and mixed subtypes of Ia and IIa families were detected in the co-infections. C. hominis was the species more frequently detected, and subtype family Ib was reported in both countries. Subtype diversity was higher in Buenos Aires than in Rio de Janeiro and two new subtypes were described for the first time.

Different fuels are used in Brazil and there is little knowledge about the presence of organic and inorganic acids in the atmosphere of the Brazilian cities. HNO3, HCl, HCOOH and CH3COOH were sampled in the gas phase using passive samplers and thermodiffusion system, in which the H2SO4 particulate was also sampled, in five sites of Salvador. Ion chromatography analyses showed that the organic and inorganic acids measured contributed on average with 89 and 11%, respectively, to the acidity of the city’s atmosphere. The strong correlations between HCOOH, CH3COOH and HCl with CO and NO2 indicated a common source for these compounds, predominantly from vehicular emissions. H2SO4 showed strong correlations with PM10 (particulate matter 10 µm or less in diameter) and with its precursor SO2; and HNO3 with NO2 and NO precursors. Most of the compounds presented negative correlations with meteorological parameters. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) confirmed these observations. The ratios [HCOOH] / [CH3COOH] varied between 0.69-1.9, typical of urban areas.

The share of urban population in Brazil amounted to 87.79 percent in 2023. In a steady upward trend, the share rose by 41.65 percentage points from 1960.

ABSTRACT BACKGROUND: The World Health Organization (WHO) 2017 Global Conference in Montevideo, Uruguay, was dedicated to promoting successful cases and best practices in fighting and preventing noncommunicable disease (NCDs). The global effort undertaken by WHO aims to reduce road traffic deaths in order to meet goal number 3.4 of the sustainable development goals. OBJECTIVES: To describe two Brazilian road safety prevention programs, presented at the WHO 2017 Global Conference: São Paulo Traffic Safety Movement (Movimento Paulista de Segurança no Trânsito) and Safe Life Program of Brasília (Programa Brasília Vida Segura), along with their governance structures, models and results. DESIGN AND SETTING: This was a descriptive case study conducted in São Paulo and Brasilia from 2015 to 2018. These programs aimed to reduce the number of deaths caused by road accidents to 8.3 deaths per 100,000 inhabitants in São Paulo by 2020 and in Brasília by 2016; and to reduce harmful use of alcohol by 10% by 2020. METHODS: These two initiatives were designed, managed and operated to bring together government and civil society, i.e. industry, academia, non-governmental organizations (NGOs), etc., around the common goal of saving lives. They were collaborative and guided by sharing of best practices, learning and information, thereby making it possible to attain more and better results. Their format enables reproduction in cities across all Brazilian regions. RESULTS: The results attest to the efficacy of the programs implemented in these two cities. In Brasília, the initiative helped reduce the number of traffic-related deaths by 35% (2017). In the same year in the state of São Paulo, 7,600 deaths were avoided. CONCLUSION: Both programs are innovative public policies that deal with health issues caused by the external agents that ultimately account for the rapid increase in days lost to disability. Prevention of external causes of deaths and injuries, such as traffic violence, strongly correlates with changes in habits and actions, especially excessive consumption of alcohol, and with NCDs in Brazil.

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.