Chart and table of population level and growth rate for the Sao Paulo, Brazil metro area from 1950 to 2025.

The study brings an analysis on how the subway system of São Paulo - Brazil is distributed according with the population distribution and income distribution.

The main goals of the study is to answer the matters below:

Is the subway system proportionally distributed when compared to the population density of the city?

Are the lower incomes neighborhoods, which would be most benefited from the subway, well served by the existing stations?

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).

The Global Human Footprint dataset of the Last of the Wild Project, version 2, 2005 (LWPv2) is the Human Influence Index (HII) normalized by biome and realm. The HII is a global dataset of 1 km grid cells, created from nine global data layers covering human population pressure (population density), human land use and infraestructure (built-up areas, nighttime lights, land use/land cover) and human access (coastlines, roads, navigable rivers).The Human Footprint Index (HF) map, expresses as a percentage the relative human influence in each terrestrial biome. HF values from 0 to 100. A value of zero represents the least influence -the "most wild" part of the biome with value of 100 representing the most influence (least wild) part of the biome.

SARS-CoV-2 spread rapidly in the Brazilian Amazon. Mortality was elevated, despite the young population, with the health services and cemeteries overwhelmed. The attack rate in this region is an estimate of the final epidemic size in an unmitigated epidemic. Here we show that by June, one month after the epidemic peak in Manaus, capital of the Amazonas state, 44% of the population had detectable IgG antibodies. This equates to a cumulative incidence of 52% after correcting for the false-negative rate of the test. Further correcting for the effect of antibody waning we estimate that the final attack rate was 66%. This is higher than seen in other settings, but lower than the predicted final size for an unmitigated epidemic in a homogeneously mixed population. This discrepancy may be accounted for by population structure as well as some limited physical distancing and non-pharmaceutical measures adopted in the city.

Methods Selection of blood samples for serology testing

Both the FPS and HEMOAM blood centers routinely store residual blood samples for six months after donation. In order to cover a period starting from the introduction of SARSCoV-2 in both cities, we retrieved stored samples covering the months of February to May in São Paulo, and February to June in Manaus, at which point testing capacity became available. In subsequent months blood samples were prospectively selected for testing. The monthly target was to test 1,000 samples at each study site. However, due to problems with purchasing the kits, supply chain issues, and the period of test validity, some months were under and others over the target (to avoid wasting kits soon to expire). We aimed to include donations starting from the second week of each month. Part of the remit of the wider project is to develop a system to prospectively select blood donation samples, based on the donor’s residential address, so as to capture a spatially representative sample of each participating city. For example, FPS receives blood donations from people living across the whole greater metropolitan region of São Paulo. The spatial distribution of donors does not follow the population density, with some areas over- and others under-represented. We used residential zip codes (recorded routinely at FPS) to select only individuals living within the city of São Paulo. We then further divided the city into 32 regions (subprefeituras) and used their projected population sizes for 2020 to define sampling weights, such that the number of donors selected in any given subprefeitura was proportional to the population size. We piloted this approach in São Paulo and have developed an information system to operationalize this process at the participating center. However, at the time of data collection the system was not implemented in HEMOAM and therefore it was not possible to use this sampling strategy. As such, we simply tested consecutive blood donations, beginning from the second week of each month until the target was reached.

Quantifying antibody waning and rate of seroreversion

We sought to quantify the rate of decline of the anti-nucleocapsid IgG antibody that is detected by the Abbott CMIA. We tested paired serum samples from our cohort of convalescent plasma donors (described above). We calculated the rate of signal decay as the difference in log2 S/C between the first and second time points divided by the number of days between the two visits. We used simple linear regression to determine the mean slope and 95% CI.

Analysis of seroprevalence data

Using the manufacturer's threshold of 1.4 S/C to define a positive result we first calculated the monthly crude prevalence of anti-SARS-CoV-2 antibodies as the number of positive samples/total samples tested. The 95% confidence intervals (CI) were calculated by the exact binomial method. We then re-weighted the estimates for age and sex to account for the different demographic make-up of blood donors compared to the underlying populations of São Paulo and Manaus (Fig. S4). Because only people aged between 16 and 70 years are eligible to donate blood, the re-weighting was based on the projected populations in the two cities in this age range only. The population projections for 2020 are available from (https://demografiaufrn.net/laboratorios/lepp/). We further adjusted these estimates for the sensitivity and specificity of the assay using the Rogan and Gladen method As a sensitivity analysis, we took two approaches to account for the effect of seroreversion through time. Firstly, the manufacturer's threshold of 1.4 optimizes specificity but misses many true-cases in which the S/C level is in the range of 0.4 – 1.4 (see ref and main text). In addition, individuals with waning antibody levels would be expected to fall initially into this range. Therefore, we present the results using an alternative threshold of 0.4 to define a positive result and adjust for the resultant loss in specificity. Secondly, we corrected the prevalence with a model-based method assuming that the probability of seroreversion for a given patient decays exponentially with time. In the model-based method for correcting the prevalence, only the months between March and August were considered. The measured prevalence used as input for this method was obtained using the manufacturer’s threshold of 1.4, and the correction based on the test specificity (99.9%) and sensitivity (84%) was applied, as well as the normalization by age and sex. Confidence intervals were calculated through bootstrapping, assuming a beta distribution for the input measured prevalence. It is worth noting that even though this model is limited by the exponential decay assumption, assuming distributions with more degrees of freedom may lead to overfitting due to the small number of samples of 9[7]. Finally, the obtained values for - and " must be interpreted as parameters for this model, and not estimates for the actual decay rate and seroreversion probability as they may absorb the effect of variables that are not taken into account by this model.

Infection fatality ratio

We calculated the global infection fatality ratio in Manaus and São Paulo. The total number of infections was estimated as the product of the population size in each city and the antibody prevalence in June (re-weighted and adjusted for sensitivity and specificity). The number of deaths were taken from the SIVEP-Gripe system, and we used both confirmed COVID-19 deaths, and deaths due to severe acute respiratory syndrome of unknown cause. The latter category likely represents COVID-19 cases in which access to diagnostic testing was limited , and more closely approximate the excess mortality. We calculated age-specific infection fatality ratios by assuming equal prevalence across all age groups.

Effective reproduction number

We calculated the effective reproduction number for São Paulo and Manaus using the renewal method9, with the serial interval as estimated by Ferguson (2020)10. Calculations were made using daily severe acute respiratory syndrome cases with PCR-confirmed COVID-19 in the SIVEP-Gripe system. Region-specific delays between the PCR result release and the date of symptom onset were accounted for using the technique proposed by Lawless (1994).

Although Aedes fluviatilis is an anthropophilic mosquito found abundantly in urban environments, its biology, epidemiological potential and genetic characteristics are poorly understood. Climate change and urbanization processes that result in environmental modifications benefit certain anthropophilic mosquito species such as Ae. fluviatilis, greatly increasing their abundance in urban areas. To gain a better understanding of whether urbanization processes modulate the genetic structure of this species in the city of São Paulo, we used eight microsatellite loci to genetically characterize Ae. fluviatilis populations collected in nine urban parks in the city of São Paulo. Our results show that there is high gene flow among the populations of this species, heterozygosity deficiency and low genetic structure and that the species may have undergone a recent population expansion. There are two main hypotheses to explain these findings: (i) Ae. fluviatilis populations have undergone a population expansion as a result of urbanization; and (ii) as urbanization of the city of São Paulo occurred recently and was quite intense, the structuring of these populations cannot be observed yet, apart from in the populations of Ibirapuera and Piqueri parks, where the first signs of structuring have appeared. We believe that the expansion found in Ae. fluviatilis populations is probably correlated with the unplanned urbanization of the city of São Paulo, which transformed green areas into urbanized areas, as well as the increasing population density in the city.

In 2025, there were approximately **** medical doctors per 1,000 people in Brazil, an increase compared to the physician density of about **** doctors per 1,000 inhabitants reported a year earlier. That same year, the number of doctors registered in the South American country totaled about ******* professionals, most of them based in São Paulo.

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.

The Brazil cold chain logistics market, valued at $2.67 billion in 2025, is poised for robust growth, exhibiting a Compound Annual Growth Rate (CAGR) of 10.02% from 2025 to 2033. This expansion is fueled by several key drivers. The burgeoning food processing industry, particularly within the horticulture (fresh fruits and vegetables), meats, fish, and poultry sectors, necessitates efficient cold chain solutions for maintaining product quality and extending shelf life. Rising consumer demand for fresh and high-quality food products further fuels market growth. Furthermore, the pharmaceutical and life sciences sectors are contributing significantly, demanding stringent temperature-controlled logistics for sensitive medications and biological samples. The expansion of e-commerce and the increasing adoption of temperature-sensitive products delivered directly to consumers are also contributing factors. Growth is concentrated in key cities like Sao Paulo, Rio de Janeiro, and Salvador, reflecting higher population density and consumption patterns. While challenges remain, such as maintaining infrastructure and addressing regulatory hurdles, the overall market outlook is positive, driven by increasing investment in modern cold storage facilities and logistics technology. The market segmentation reveals significant opportunities across various services (storage, transportation, value-added services), temperature types (chilled, frozen), and applications. Growth in the frozen segment is expected to be particularly strong, driven by the rising popularity of frozen foods and the need for efficient handling of temperature-sensitive products. Key players like Superfrio Armazens Gerais Ltda, Maersk, Logfrio SA, and others are actively investing in capacity expansion and technological advancements to cater to the rising demand. The strategic partnerships between logistics providers and food producers are paving the way for integrated and efficient cold chain solutions, improving overall supply chain resilience and reducing losses. The continuous improvement in cold chain infrastructure, including refrigerated trucking and warehousing, is vital to sustaining the market's projected growth trajectory. This in-depth report provides a comprehensive analysis of the Brazil cold chain logistics market, offering invaluable insights for businesses operating within or planning to enter this dynamic sector. With a study period spanning 2019-2033, a base year of 2025, and a forecast period of 2025-2033, this report leverages historical data (2019-2024) to project future market trends and growth opportunities. The report covers key segments, including storage, transportation, and value-added services, across various temperature types (chilled and frozen) and applications (horticulture, meats, pharmaceuticals, and more) in major cities like Sao Paulo, Rio de Janeiro, and Salvador. The market is valued in millions and analyzes the impact of regulations, competition, and technological advancements. Key drivers for this market are: The Growth of Banking and Financial Institutions in Emerging Economies, Mobile Payments are Being Increasingly Used. Potential restraints include: Increasing Usage of Payments from Mobile. Notable trends are: Increasing Meat Exports to Drive the Market.

Market Size for Brazil Toys and Games Industry on the Basis of Revenue in USD Billion, 2018-2024 In 2023, Estrela launched a new line of eco-friendly educational toys to cater to the growing demand for sustainable products, aiming to capture the environmentally conscious segment of the market. São Paulo and Rio de Janeiro are key regions, driven by high population density and higher disposable incomes, contributing significantly to the market's overall growth trajectory. The Brazil toys and games market reached a valuation of BRL 25 billion in 2023, fueled by increasing consumer expenditure on children’s entertainment, a rising young population, and growing demand for educational and interactive products. The market is dominated by key players such as Estrela, Hasbro, Mattel, and Grow. These companies are recognized for their strong brand presence, broad distribution networks, and innovative product lines designed to appeal to both children and parents.

The Southeast Region in Brazil, was the region with the highest density of surgeons in the country in 2022, with 30.9 surgeons per 100,000 people. The most populated cities in Brazil, like Rio de Janeiro and São Paulo, are located in this region. That year, São Paulo was the city with the highest number of doctors in the country.

Emerging contaminants have been considered one of the main concerns for ensuring the quality of water around the world. This work presents the results of 10 years of analyses carried out in the state of São Paulo (Brazil) that has the high population density and intense agricultural and industrial activities. In this work 58 compounds (9 hormones, 14 pharmaceuticals and personal care products, 8 industrial compounds, 17 pesticides and 10 illicit drugs) were determined from 2006 to 2015 in 708 samples including raw and treated sewage, surface and ground and drinking waters. A preliminary risk assessment for aquatic life protection identified potential risks for caffeine, paracetamol, diclofenac, 17α-ethynylestradiol, 17β-estradiol, estriol, estrone, testosterone, triclosan, 4-n-nonylphenol, bisphenol A, atrazine, azoxystrobin, carbendazim, fipronil, imidacloprid, malathion and tebuconazole. Drinking water criteria were available only for 22 compounds and for them no adverse effects were expected at the concentrations found, except for 17β-estradiol.

Brazil Vehicle Rental Market Outlook

According to our latest research, the global vehicle rental market size reached USD 98.8 billion in 2024, with Brazil accounting for a significant and expanding portion of this figure. The global market is projected to grow at a CAGR of 7.9% from 2025 to 2033, reaching approximately USD 198.2 billion by 2033. This robust growth is driven by rising urbanization, increasing tourism, and the growing preference for flexible mobility solutions. In Brazil, the vehicle rental market has witnessed accelerated momentum in recent years, supported by both domestic travel demand and a surge in business activities, positioning the country as a vital contributor to the global landscape.

The growth trajectory of the Brazil vehicle rental market is underpinned by several critical factors. One of the most prominent drivers is the rise in domestic tourism, which has rebounded strongly post-pandemic. As travel restrictions eased, Brazilians increasingly opted for car rentals to explore the diverse landscapes of their country, from the Amazon rainforest to the vibrant coastal cities. This trend is further supported by the government’s initiatives to promote regional tourism and improve road infrastructure, making vehicle rentals a convenient and attractive option for both short and long-distance travel. The expansion of the middle class and their growing disposable incomes have also played a significant role in boosting demand for rental vehicles, especially in urban centers where car ownership remains a costly proposition.

Another key factor propelling the Brazil vehicle rental market is the rapid digital transformation within the sector. The proliferation of online booking platforms and mobile applications has revolutionized the customer experience, making it easier than ever to compare prices, select vehicles, and manage reservations. This digital shift has not only enhanced convenience but also increased transparency and competition among rental providers. Additionally, the integration of advanced technologies such as telematics, GPS tracking, and contactless payment systems has improved fleet management efficiency and customer safety, further fueling market growth. The adoption of sustainability initiatives, including the introduction of electric and hybrid vehicles into rental fleets, is also emerging as a differentiator in a market increasingly attuned to environmental concerns.

The Brazil vehicle rental market is also benefitting from the rising demand for corporate mobility solutions. As businesses expand their operations across the country, there is a growing need for flexible transportation options for employees, executives, and logistics. Corporate clients are increasingly turning to rental services to manage their mobility requirements without the long-term financial commitment and maintenance costs associated with fleet ownership. This trend is particularly pronounced in sectors such as construction, oil and gas, and technology, where project-based assignments and frequent intercity travel are common. The market is also seeing increased collaboration between rental companies and corporate clients to offer tailored solutions, including long-term rentals, subscription models, and value-added services such as chauffeur-driven vehicles and insurance packages.

Regionally, the Southeast and South regions of Brazil dominate the vehicle rental market, driven by their high population density, economic activity, and well-developed infrastructure. São Paulo and Rio de Janeiro, in particular, serve as major hubs for both leisure and business travel, generating substantial demand for rental vehicles. However, the market is also witnessing significant growth in the Northeast and Central-West regions, fueled by rising tourism and government investments in infrastructure development. The North region, while smaller in market share, presents unique opportunities due to its vast and often challenging terrain, making vehicle rentals a practical choice for both residents and visitors. Overall, the regional outlook for the Brazil vehicle rental market remains positive, with each area contributing to the sector’s robust expansion.

General information related to the mark-release-recapture experiments and estimates of Lutzomyia longipalpis density, Panorama, São Paulo state, Brazil.

IntroductionThis study sets out to provide scientific evidence on the spatial risk for the formation of a superspreading environment.MethodsFocusing on six common types of urban facilities (bars, cinemas, gyms and fitness centers, places of worship, public libraries and shopping malls), it first tests whether visitors' mobility characteristics differ systematically for different types of facility and at different locations. The study collects detailed human mobility and other locational data in Chicago, Hong Kong, London, São Paulo, Seoul and Zurich. Then, considering facility agglomeration, visitors' profile and the density of the population, facilities are classified into four potential spatial risk (PSR) classes. Finally, a kernel density function is employed to derive the risk surface in each city based on the spatial risk class and nature of activities.ResultsResults of the human mobility analysis reflect the geographical and cultural context of various facilities, transport characteristics and people's lifestyle across cities. Consistent across the six global cities, geographical agglomeration is a risk factor for bars. For other urban facilities, the lack of agglomeration is a risk factor. Based on the spatial risk maps, some high-risk areas of superspreading are identified and discussed in each city.DiscussionIntegrating activity-travel patterns in risk models can help identify areas that attract highly mobile visitors and are conducive to superspreading. Based on the findings, this study proposes a place-based strategy of non-pharmaceutical interventions that balance the control of the pandemic and the daily life of the urban population.

Socio-economic related properties of a city grow faster than a linear relationship with the population, in a log–log plot, the so-called superlinear scaling. Conversely, the larger a city, the more efficient it is in the use of its infrastructure, leading to a sublinear scaling on these variables. In this work, we addressed a simple explanation for those scaling laws in cities based on the interaction range between the citizens and on the fractal properties of the cities. To this purpose, we introduced a measure of social potential which captured the influence of social interaction on the economic performance and the benefits of amenities in the case of infrastructure offered by the city. We assumed that the population density depends on the fractal dimension and on the distance-dependent interactions between individuals. The model suggests that when the city interacts as a whole, and not just as a set of isolated parts, there is improvement of the socio-economic indicators. Moreover, the bigger the interaction range between citizens and amenities, the bigger the improvement of the socio-economic indicators and the lower the infrastructure costs of the city. We addressed how public policies could take advantage of these properties to improve cities development, minimizing negative effects. Furthermore, the model predicts that the sum of the scaling exponents of social-economic and infrastructure variables are 2, as observed in the literature. Simulations with an agent-based model are confronted with the theoretical approach and they are compatible with the empirical evidences.

Carbonaceous particulate matter on the lung surface from adults living in São Paulo, Brazil - Table 1

Posterior mean and posterior 95% Credible Intervals (on natural scale) for the (fixed) regression parameters associated with the Ae. aegypti larval index.

Abstract Araçá Bay, located in the city of São Sebastião, São Paulo, Brazil, is a protected area of substantial complexity. It represents the last remaining mangrove swamp preserve between the cities of Bertioga and Ubatuba on the northern coast of São Paulo State. This mangrove swamp has specific physical and chemical properties, and it shelters a wide variety of life, including fungi. These microorganisms are present in a variety of species with different morphophysiological features, and they have the ability to produce enzymes of biotechnological importance. The goal of this study was to quantify, isolate, and identify filamentous fungi in water and sediment samples from the Araçá Bay mangrove swamp in São Sebastião. Two samplings were performed in the summer and two were performed in the winter. The samples were collected from intertidal zones, and dissolved oxygen (DO), temperature, salinity, and pH were measured in situ. The spread plate technique was used to inoculate the samples collected on plates with a potato dextrose agar (PDA) medium. A total of 208 colonies (68 from water samples and 140 from sediment samples) were isolated, and they were identified based on their morphological characteristics. Filamentous fungus density was higher in the sediment than in the water, and the samplings performed in the winter revealed a higher density than those performed in the summer. Though some of the environmental parameters were not ideal for fungal development, a high quantity of growth was nevertheless observed. When the isolated colonies were analyzed, the greatest diversity and species richness were found in the summer samples. The genera identified in all of the samples were Aspergillus, Penicillium, Cladosporium, and Fusarium. The pathogenic species found from these genera were Aspergillus fumigatus, A. terreus, Penicillium citrinum, and P. chrysogenum. These species are also able to produce enzymes that offer a variety of applications. The fungal community described herein represents the diversity found in this mangrove swamp during the period studied. Many of the fungus species found are pathogenic and may be useful due to their ability to produce specific enzymes applicable in the biotechnological and pharmaceutical industries.

Abstract Object: to examine the characteristics to the last fall of Brazilian elderly persons who experienced falls in 2008 and 2009, and to identify if there is a relationship with sociodemographic characteristics, physical health, comorbidities, clinical conditions and the circumstances of the falls. Methods: a cross-sectional, population based study was carried out with participants aged 65 and older from Barueri in the state of São Paulo and Cuiabá in the state of Mato Grosso, Brazil. Households were enrolled within each census region according to population density and the number of elderly persons living in each region. A multidimensional questionnaire composed of sociodemographic factors and data regarding falls was used. Associations were analyzed using contingency tables, and Fisher's Exact or Pearson's Chi-square test was used. Results: 774 elderly people were included in the study, 299 of whom reported falling in the previous year. Of these, 176 (58.9%) had fallen once and 123 (41.1%) reported having fallen twice or more. Among fallers the mean age was 72.53 (±6.12) years and 214 (71.6%) were female. About 107 (35.8%) of the elderly reported having fallen forwards, 79 (26.4%) fell to the side and 42(14%) fell backwards. Regarding the circumstances of the falls, 107 (35.8%) reported having lost their balance, 79 (26.4%) said they had stumbled and 42 (14%) said they had slipped. There was an association between the mechanism and circumstances of the falls and having fallen once or twice or more. There was an association between the circumstances of falls and the number of medications taken. Conclusion: The characteristics of falls were different among elderly persons who had fallen once or twice or more, which may guide health professionals, the elderly and their families in relation to specific fall prevention strategies.