Goiás

Monthly production index and growth rate by industry sectors from the Brazilian Institute of Geography and Statistics (IBGE)

Brazil: Household Internet Access by Classes of Household, 2015

Brazil : Household Internet Access by Household Situation

Brazil: Internet Use by Classes of Household Income per Capita, 2015

Brazil : Internet Use by Employment Status and Situation

Brazil : Internet Use by Household Situation, 2015

Brazil : Internet Use by Occupational Group, 2015

Brazil : Internet Use by Sex and Education Level, 2015

Brazil : Internet Use by Student Status and Educational Network, 2015

Brazil: Cellular Mobile Phone Ownership for Personal Use by Sudent Status and Educational Network, 2015

Annual outcomes of crop area and production by product in Brazil from Brazilian Institute of Geography and Statistics (IBGE)

This dataset presents the Consumer Price Index of Brazil, monthly variation and accumulated variation in the price index in the last 12 months. In this dataset IPCA-15 series is captured. The data is obtained from Brazilian Institute of Geography and Statistics (IBGE). The IPCA-15 measures the inflation of a set of products and services sold at retail, referring to the personal consumption of families, whose income varies between 1 and 40 minimum wages, whatever the source of income. This income bracket was created with the aim of ensuring coverage of 90% of families belonging to the urban areas covered by the National System of Consumer Price Indexes (SNIPC). This measure differs from the Extended National Consumer Price Index – IPCA, in geographic coverage and data collection period, which, for the former, starts on the 16th of the preceding month. Thus IPCA 15 is a type of IPCA preview.

The Consumer Price Index (IPCA)  measures the inflation of a set of products and services marketed in retail. The dataset presents the monthly variation, accumulated in the year and monthly weight for general price index and groups of products and services. 

These Community Mobility Reports aim to provide insights into what has changed in response to policies aimed at combating COVID-19. The reports chart movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

Electricity Consumption by Class (regions and subsystems) The Energy Research Company - EPE makes available in the attached file the monthly history, from 2004 to 2018, of electricity consumption at national, regional and subsystem levels, segmented by residential, industrial, commercial and other classes (rural, utility public lighting and street lighting). The data are updated by the Superintendency of Economic and Energy Studies - SEE of the Directorate of Economic-Energy and Environmental Studies - DEA.

The Global Consumption Database is a one-stop source of data on household consumption patterns in developing countries. It is designed to serve a wide range of users—from researchers seeking data for analytical studies to businesses seeking a better understanding of the markets into which they are expanding or those they are already serving.   The data are based on national household surveys, which collect information for a group of households representative of the entire country. For each of the countries covered, the resulting datasets have been used to calculate the share of the population at different levels of consumption.   Four levels of consumption are used to segment the market in each country: lowest, low, middle, and higher. They are based on global income distribution data, which rank the global population by income per capita. The lowest consumption segment corresponds to the bottom half of the global distribution, or the 50th percentile and below; the low consumption segment to the 51th–75th percentiles; the middle consumption segment to the 76th–90th percentiles; and the higher consumption segment to the 91st percentile and above.   The Global Consumption Database is the most comprehensive data source to date on consumer spending patterns in developing countries. It builds on the 2007 report The Next 4 Billion, published by IFC (a member of the World Bank Group) and the World Resources Institute.

Global Burden of Disease Study 2016 (GBD 2016) Healthcare Access and Quality Index Based on Amenable Mortality 1990–2016. Global Burden of Disease Study 2016 (GBD 2016) estimates were used in an analysis of personal healthcare access and quality for 195 countries and territories, as well as selected subnational locations, over time. This dataset includes the following global, regional, national, and selected subnational estimates for 1990-2016: age-standardized risk-standardized death rates from 24 non-cancer causes considered amenable to healthcare; age-standardized mortality-to-incidence ratios for 8 cancers considered amenable to healthcare; and the Healthcare Access and Quality (HAQ) Index and individual scores for each of the 32 causes on a scale of 0 to 100. Code used to produce the estimates is also included. Results were published in The Lancet in May 2018 in "Measuring performance on the Healthcare Access and Quality Index for 195 countries and territories and selected subnational locations: a systematic analysis from the Global Burden of Disease Study 2016

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In December 2022, IHME paused its COVID-19 modeling. IHME has developed projections for total and daily deaths, daily infections and testing, hospital resource use, and social distancing due to COVID-19 for a number of countries. Forecasts at the subnational level are included for select countries. The projections for total deaths, daily deaths, and daily infections and testing each include a reference scenario: Current projection, which assumes social distancing mandates are re-imposed for 6 weeks whenever daily deaths reach 8 per million (0.8 per 100k). They also include two additional scenarios: Mandates easing, which reflects continued easing of social distancing mandates, and mandates are not re-imposed; and Universal Masks, which reflects 95% mask usage in public in every location. Hospital resource use forecasts are based on the Current projection scenario. Social distancing forecasts are based on the Mandates easing scenario. These projections are produced with a model that incorporates data on observed COVID-19 deaths, hospitalizations, and cases, information about social distancing and other protective measures, mobility, and other factors. They include uncertainty intervals and are being updated daily with new data. These forecasts were developed in order to provide hospitals, policy makers, and the public with crucial information about how expected need aligns with existing resources, so that cities and countries can best prepare. Dataset contains Observed and Projected data

Data cited at: Prof.Prof. Lauren Gardner; Center for Systems Science and Engineering at John Hopkins University, blog Post -  https://systems.jhu.edu/research/public-health/ncov/   On December 31, 2019, the World Health Organization (WHO) was informed of an outbreak of “pneumonia of unknown cause” detected in Wuhan City, Hubei Province, China – the seventh-largest city in China with 11 million residents. As of February 04, 2020, there are over 24,502 cases confirmed globally, including cases in at least 30 regions in China and 30 countries.  Interests: In-Market Segments Knoema All Users   Knoema modified the original dataset to include calculations per million.   https://knoema.com/WBPEP2018Oct https://knoema.com/USICUBDS2020 https://knoema.com/NBSCN_P_A_A0301 https://knoema.com/IMFIFSS2017Nov https://knoema.com/AUDSS2019 https://knoema.com/UNAIDSS2017 https://knoema.com/UNCTADPOPOCT2019Nov https://knoema.com/WHOWSS2018 https://knoema.com/KPMGDHC2019

We define our day as midnight-to-midnight, Pacific time. Cities represent usage in greater metropolitan areas and are stably defined during this period. In many countries/regions and cities, relative volume has increased since January 13th, consistent with normal, seasonal usage of Apple Maps. Day of week effects are important to normalize as you use this data. Data that is sent from users’ devices to the Maps service is associated with random, rotating identifiers so Apple doesn’t have a profile of your movements and searches. Apple Maps has no demographic information about our users, so we can’t make any statements about the representativeness of our usage against the overall population. This information will be available for a limited time during the COVID‑19 pandemic.

This dataset contains the epidemiological information related to microcephaly and / or changes in the CNS, provided for in the existing definitions in the "Surveillance Protocol and Response microcephaly occurred and / or changes in the Central Nervous System (CNS) - Version 2.1 / 2016," available in www.saude.gov.br/svs site. The overall objective of this monitoring is to describe the epidemiological pattern of occurrence of microcefalias related to congenital infections in the country.   Data has been retrieved from below mentioned tables. Table1: Cumulative Distribution of Reported Cases of Microcephaly and Changes in the CNS, Second Protocol Settings Surveillance Brazil Table2: Distribution of Municipalities with Reported and Confirmed Cases of Microcephaly and abnormal CNS Suggestive of Congenital Infection, Surveillance Federated Unit Table3: Cumulative Distribution of Reported Death Cases of Microcephaly and Abnormal CNS Progressing to Stillbirth or Neonatal

The Regional database contains annual data from 1995 to the most recent available year (generally 2022 for demographic and labor market data, 2021 for regional accounts, innovation and social statistics). 

The Regional database contains annual data from 1995 to the most recent available year (generally 2018 for demographic and labor market data, 2017 for regional accounts, innovation and social statistics). The data collection is undertaken by the Center for Entrepreneurship, SMEs, Regions and Cities (CFE). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and via downloads from the web-sites of National Statistical Offices and Eurostat

The Regional Database contains annual data from 1995 to the most recent available year. The data collection is undertaken by the Directorate of Public Governance and Territorial Development, within the Regional Development Policy division (GOV/RDP). Statistics are collected through an annual questionnaire sent to the delegates of the Working Party on Territorial Indicators (WPTI), and through access to the web-sites of National Statistical Offices and Eurostat. The WPTI is responsible for developing regional (subnational) and urban statistics and providing analysis to support policy evaluations. The Regional Database includes statistics on the regional distribution of resources, regional disparities, and how regions contribute to national growth and the well-being of society. Under this framework, the Regional Database is one of the pillars for providing indicators to the publication OECD Regions at a Glance (link).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2016 for demographic, 2015 for labor market data and 2014 for regional accounts, innovation and social statistics).

The Regional Database contains annual data from 1995 to the most recent available year (generally 2014 for demographic and labour market data, 2013 for regional accounts, innovation and social statistics).   In any analytical study conducted at sub-national levels, the choice of the territorial unit is of prime importance. The territorial grids (TL2 and TL3) used in this database are officially established and relatively stable in all member countries, and are used by many as a framework for implementing regional policies. This classification - which, for European countries, is largely consistent with the Eurostat classification - facilitates greater comparability of regions at the same territorial level. The differences with the Eurostat NUTS classification concern Belgium, Greece and the Netherlands where the NUTS 2 level correspond to the OECD TL3 and Germany where the NUTS1 corresponds to the OECD TL2 and the OECD TL3 corresponds to 97 spatial planning regions (Groups of Kreise). For the United Kingdom the Eurostat NUTS1 corresponds to the OECD TL2. Due to limited data availability, labour market indicators in Canada are presented for a different grid (groups of TL3 regions). Since these breakdowns are not part of the OECD official territorial grids, for the sake of simplicity they are labelled as Non Official Grids (NOG).

Monthly Survey of Trade, Brazil

Data cited at: Global Burden of Disease Collaborative Network. Global Burden of Disease Study 2019 (GBD 2019) Socio-Demographic Index (SDI) 1950–2019. Seattle, United States of America: Institute for Health Metrics and Evaluation (IHME), 2020.

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/    

Data cited at: The Water Footprint Network https://waterfootprint.org/en/ Topic: Product water footprint statistics Publication: https://waterfootprint.org/en/resources/waterstat/product-water-footprint-statistics/ Reference: Mekonnen, M.M. & Hoekstra, A.Y. (2011) The green, blue and grey water footprint of crops and derived crop products, Hydrology and Earth System Sciences, 15(5): 1577-1600. License: https://creativecommons.org/licenses/by-sa/3.0/