This statistic shows the projected top ten largest national economies in 2050. By 2050, China is forecasted to have a gross domestic product of over ** trillion U.S. dollars.

The impact of climate change has been forecasted to affect the economies of South-East Asian Nations (ASEAN) the hardest. The maximum projected loss incurred by the ASEAN in the event of a 3.2°C temperature rise is 37.4 percent. This is more than double the forecast loss of the Advanced Asia economies and 10 percent higher than the next largest forecast loss of the Middle East & Africa.

This statistic shows the top ten countries projected to have the greatest average annual growth in gross domestic product from 2016 to 2050. From 2016 to 2050, Vietnam is projected to have an average annual GDP growth rate of * percent.

Roughly ** percent of the annual GDP of lower income countries worldwide in 2050 could be at risk of loss due to exposure to climate hazards, in a slow transition scenario without adaptation measures. Extreme heat and water stress are forecast to have the biggest impact, at *** and *** percent, respectively. In contrast, in upper income countries, the same hazards would put less than one percent of the annual GDP at risk. Nevertheless, climate hazards would still put almost ***** percent of upper income countries' GDP at risk by 2050, in a no-adaptation scenario.

Since the beginning of the 21st century, the BRICS countries have been considered the five foremost developing economies in the world. Originally, the term BRIC was used by economists when talking about the emerging economies of Brazil, Russia, India, and China, however these countries have held annual summits since 2009, and the group has expanded to include South Africa since 2010. China has the largest GDP of the BRICS country, at 16.86 trillion U.S. dollars in 2021, while the others are all below three trillion. Combined, the BRICS bloc has a GDP over 25.85 trillion U.S. dollars in 2022, which is slightly more than the United States. BRICS economic development China has consistently been the largest economy of this bloc, and its rapid growth has seen it become the second largest economy in the world, behind the U.S.. China's growth has also been much faster than the other BRICS countries; for example, when compared with the second largest BRICS economy, its GDP was less than double the size of Brazil's in 2000, but is almost six times larger than India's in 2021. Since 2000, the country with the second largest GDP has fluctuated between Brazil, Russia, and India, due to a variety of factors, although India has held this position since 2015 (when the other two experienced recession), and it's growth rate is on track to surpass China's in the coming decade. South Africa has consistently had the smallest economy of the BRICS bloc, and it has just the third largest economy in Africa; its inclusion in this group is due to the fact that it is the most advanced and stable major economy in Africa, and it holds strategic importance due to the financial potential of the continent in the coming decades. Future developments It is predicted that China's GDP will overtake that of the U.S. by the end of the 2020s, to become the largest economy in the world, while some also estimate that India will also overtake the U.S. around the middle of the century. Additionally, the BRICS group is more than just an economic or trading bloc, and its New Development Bank was established in 2014 to invest in sustainable infrastructure and renewable energy across the globe. While relations between its members were often strained or of less significance in the 20th century, their current initiatives have given them a much greater international influence. The traditional great powers represented in the Group of Seven (G7) have seen their international power wane in recent decades, while BRICS countries have seen theirs grow, especially on a regional level. Today, the original BRIC countries combine with the Group of Seven (G7), to make up 11 of the world's 12 largest economies, but it is predicted that they will move further up on this list in the coming decades.

1. Temporal Coverage of Data: The data collection periods are 2010, 2030, and 2050.2. Spatial Coverage and Projection:Spatial Coverage: GlobalLongitude: -180° - 180°Latitude: -90° - 90°Projection: GCS_WGS_19843. Disciplinary Scope: The data pertains to the fields of Earth Sciences and Geography.4. Data Volume: The total data volume is approximately 31.5 MB.5. Data Type: Raster (GeoTIFF)6. Thumbnail (illustrating dataset content or observation process/scene): · 7. Field (Feature) Name Explanation:a. Name Explanation: IND: Industrial Value Addedb. Unit of Measurement: Unit: US Dollars (USD)8. Data Source Description:a. Remote Sensing Data:2010 Global Vegetation Index data (Enhanced Vegetation Index, EVI, from MODIS monthly average data) and 2010 Nighttime Light Remote Sensing data (DMSP/OLS)b. Meteorological Data:From the CMCC-CM model in the Fifth International Coupled Model Intercomparison Project (CMIP5) published by the United Nations Intergovernmental Panel on Climate Change (IPCC)c. Statistical Data:From the World Development Indicators dataset of the World Bank and various national statistical agenciesd. Gross Domestic Product Data:Sourced from the project "Study on the Harmful Processes of Population and Economic Systems under Global Change" under the National Key R&D Program "Mechanisms and Assessment of Risks in Population and Economic Systems under Global Change," led by Researcher Sun Fubao at the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciencese. Other Data:Rivers, roads, settlements, and DEM, sourced from the National Oceanic and Atmospheric Administration (NOAA), Global Risk Data Platform, and Natural Earth9. Data Processing Methods(1) Spatialization of Baseline Industrial Value Added: Using 2010 global EVI vegetation index data and nighttime light remote sensing data, we addressed the oversaturation issue in nighttime light data by constructing an adjusted nighttime light index to obtain the optimal global light data. The EANTIL model was developed using NTL, NTLn, and EVI data, with the following formula:Here, EANTLI represents the adjusted nighttime light index, NTL represents the original nighttime light intensity value, and NTLn represents the normalized nighttime light intensity value. Based on the optimal light index EANTLI and the industrial value-added data from the World Bank, we constructed a regression allocation model to derive industrial value added (I), generating the global 2010 industrial value-added data with the formula:Here, I represents the industrial value added for each grid cell, and Ii represents the industrial value added for each country, EANTLi derived from ArcGIS statistical analysis and the regression allocation model.(2) Spatial Boundaries for Future Industrial Value Added: Using the Logistic-CA-Markov simulation principle and global land use data from 2010 and 2015 (from the European Space Agency), we simulated national land use changes for 2030 and 2050 and extracted urban land data as the spatial boundaries for future industrial value added. To comprehensively characterize the influence of different factors on land use and considering the research scale, we selected elevation, slope, population, GDP, distance to rivers, and distance to roads as land use driving factors. Accuracy validation using global 2015 land use data showed an average accuracy of 91.89%.(3) Estimation of Future Industrial Value Added: Based on machine learning and using the random forest model, we constructed spatialization models for industrial value added under different climate change scenarios: Here, tem represents temperature, prep represents precipitation, GDP represents national economic output, L represents urban land, D represents slope, and P represents population. The random forest model was constructed using factors such as 2010 industrial value added, urban land distribution, elevation, slope, distances to rivers, roads, railways (considering transportation), and settlements (considering noise and environmental pollution from industrial buildings), along with temperature and precipitation as climate scenario data. Except for varying temperature and precipitation values across scenarios, other variables remained constant. The model comprised 100 decision trees, with each iteration randomly selecting 90% of the samples for model construction and using the remaining 10% as test data, achieving a training sample accuracy of 0.94 and a test sample accuracy of 0.81.By analyzing the proportion of industrial value added to GDP (average from 2000 to 2020, data from the World Bank) and projected GDP under future Shared Socioeconomic Pathways (SSPs), we derived future industrial value added for each country under different SSP scenarios. Using these projections, we constructed regression models to allocate future industrial value added proportionally, resulting in spatial distribution data for 2030 and 2050 under different SSP scenarios.10. Applications and Achievements of the Dataseta. Primary Application Areas: This dataset is mainly applied in environmental protection, ecological construction, pollution prevention and control, and the prevention and forecasting of natural disasters.b. Achievements in Application (Awards, Published Reports and Articles):Achievements: Developed a method for downscaling national-scale industrial value-added data by integrating DMSP/OLS nighttime light data, vegetation distribution, and other data. Published the global industrial value-added dataset.

From the IPCC website: The B2 world is one of increased concern for environmental and social sustainability. Education and welfare programs are widely pursued leading to reductions in mortality and, to a lesser extent, fertility. The population reaches about 10 billion people by 2100, consistent with both the United Nations and IIASA median projections. Income per capita grows at an intermediary rate to reach about US$12,000 by 2050. By 2100 the global economy might expand to reach some US$250 trillion. International income differences decrease, although not as rapidly as in scenarios of higher global convergence (A1, B1). Local inequity is reduced considerably through the development of stronger community support networks. Generally high educational levels promote both development and environmental protection. Indeed, environmental protection is one of the few remaining truly international priorities. However, strategies to address global environmental challenges are less successful than in B1, as governments have difficulty designing and implementing agreements that combine environmental protection with mutual economic benefits. The B2 storyline presents a particularly favorable climate for community initiative and social innovation, especially in view of high educational levels. Technological frontiers are pushed less than in A1 and B1 and innovations are also regionally more heterogeneous. Globally, investment in R&D continues its current declining trend, and mechanisms for international diffusion of technology and know-how remain weaker than in scenarios A1 and B1 (but higher than in scenario A2). Some regions with rapid economic development and limited natural resources place particular emphasis on technology development and bilateral co-operation. Technical change is therefore uneven. The energy intensity of GDP declines at about one percent per year, in line with the average historical experience of the last two centuries. Land-use management becomes better integrated at the local level in the B2 world. Urban and transport infrastructure is a particular focus of community innovation, contributing to a low level of car dependence and less urban sprawl. An emphasis on food self-reliance contributes to a shift in dietary patterns towards local products, with reduced meat consumption in countries with high population densities. Energy systems differ from region to region, depending on the availability of natural resources. The need to use energy and other resources more efficiently spurs the development of less carbon-intensive technology in some regions. Environment policy cooperation at the regional level leads to success in the management of some transboundary environmental problems, such as acidification due to SO2, especially to sustain regional self-reliance in agricultural production. Regional cooperation also results in lower emissions of NOx and VOCs, reducing the incidence of elevated tropospheric ozone levels. Although globally the energy system remains predominantly hydrocarbon-based to 2100, there is a gradual transition away from the current share of fossil resources in world energy supply, with a corresponding reduction in carbon intensity. Data are available for the following periods: 1961-1990, 2010-2039; 2040-2069; and 2090-2099 Mean monthly and change fields.

Potential national income loss from climate risks can be computed using simple damage functions that estimate damages based on the temperature outcomes inferred from the emissions trajectories projected by the transition scenarios. Potential national income benefit from avoided climate damages can be computed by contrasting the damages estimates based on the temperature outcomes from the transition scenarios with the policy, or mitigation, costs from climate action needed to meet a particular temperature outcome.Sources: Network for Greening the Financial System (2023), Scenarios Portal; and International Institute for Applied Systems Analysis (2023), NGFS Phase 4 Scenario Explorer; IMF Staff Calculations.Category: Transition to a Low-Carbon EconomyMetadataThe framework of the Network of Central Banks and Supervisors for Greening the Financial System (NGFS) allows to simulate, in a forward-looking fashion, the dynamics within and between the energy, land-use, economy, and climate systems. Consistent with that framework, the NGFS explores a set of seven climate scenarios, which are characterized by their overall level of physical and transition risk. The scenarios in the current Phase IV (NGFS climate scenarios data set) are Low Demand, Net Zero 2050, Below 2°C, Delayed Transition, Nationally Determined Contributions (NDCs), Current Policies, and Fragmented World. Each NGFS scenario explores a different set of assumptions for how climate policy, emissions, and temperatures evolve. To reflect the uncertainty inherent to modeling climate-related macroeconomic and financial risks, the NGFS scenarios use different models, over and above the range of scenarios. These integrated assessment models (IAMs) are, by their acronyms: GCAM, MESSAGEix-GLOBIOM, and REMIND-MAgPIE. GDP losses and benefits are derived based on the National Institute Global Econometric Model (NiGEM). NiGEM consists of individual country models for the major economies, which are linked together through trade in goods and services and integrated capital markets. Country level data (or country aggregates, whenever country level disaggregation is not present) for GDP, population, primary energy consumption by fuel type, useful energy and carbon taxes from the IAM output is used as an input into the NiGEM scenarios. Climate scenarios within NiGEM can be broadly categorized into physical and transition events. While the effects of physical and transition shocks alongside policy decisions are contemporaneous, the scenarios in NiGEM can be run in a “stacked” manner, where each scenario uses the information provided by the previous scenario as its starting point. This allows for decomposition of shocks and their effects. Results are available for three scenarios: Net Zero 2050, Delayed Transition, and Current Policies. For details please see the NGFS climate scenarios presentation, the Climate scenarios technical documentation, and the User guide for data access.MethodologyThe NGFS climate scenarios database contains information on mitigation policy costs, business confidence losses, chronic climate damages, and acute climate damages. Mitigation policy costs reflect transition risk in a narrow sense and is measured against the Current Policies scenario (for which it is zero). Business confidence losses result from unanticipated policy changes, and only in the Delayed Transition scenario. GDP losses from chronic risks arise from an increase in global mean temperature. Estimates of the macroeconomic impact of acute risks are based on physical risk modelling covering different hazards. Acute risks are modeled independent of the input IAM. Results are available at the original sources for four hazards: droughts impacting on crop yields, tropical cyclones directly damaging assets, heatwaves affecting productivity and demand, and riverine floods directly damaging assets too. Apart from floods acute risks are the result of randomized stochastic output, yielding 60th to 99th percentile GDP impacts. In accordance with the presentation of the scenario results by the NGFS, the 90th percentile has been chosen as the representative confidence bound. That way, the results are focusing on tail risk. While the choice of the percentile will lead to marked differences for the GDP losses indicator, its influence on the GDP benefits indicator is muted due to comparing like-with-like. Further, the sum of the impacts from the four hazards is taken as the acute physical risk measure; see what follows for the methodology in deriving the net benefits. Net benefits can be calculated by comparing the impact of stronger climate action to the reference scenario, the Current Policies scenario: Net Benefit = 100 * (GDP[Policy scenario] / GDP[Current Policies] – 1). GDP in either scenario can be inferred from the hypothetical baseline with no transition nor physical risk and the percentage losses due to mitigation policy (MP), business confidence (BC), chronic climate (CC), and acute climate (AC): GDP = Baseline * (1 + (MP + BC + CC + AC) / 100). Plugging this into the above equation one finds after some algebra: Net Benefit = (MP[Policy scenario] – MP[Current Policies] + BC[Policy scenario] – BC[Current Policies] + CC[Policy scenario] – CC[Current Policies] + AC[Policy scenario] – AC[Current Policies]) / (1 + (MP + BC + CC + AC)[Current Policies] / 100). Obviously, MP[Current Policies] = BC[Current Policies] = BC[Net Zero 2050] = 0. In order to achieve consistency in aggregation of the four components to the total benefit, the denominator is kept fixed, while for the individual contributions only one component at a time, MP, BC, CC, or AC, is used in the numerator. Results are presented for the 49 countries, five geographic regions covering the remainder of countries, and a global and European total. The coverage of the five remainder regions refers to the country classification of emerging market and developing economies in the IMF’s World Economic Outlook.Data series: Potential National Income Loss From Climate RisksPotential National Income Benefit From Avoided Climate Damages

We provide free TelluBase data to select public data sources.These are small, but important, subsets of the full product.To start with, we offer all Latin American countries (except Venezuela) with GDP per city and subdivision in 2023 in these PDFs.If you represent an academic institution or a reputable media outlet and think you may benefit from TelluBase data, we may be able to provide it for free. Contact us with your query at info@tellusant.com.TelluBase covers 218 countries, 2600 cities, and 2500 subdivisions, 2000-2050. It gives a completely exhaustive view of the world economy.

Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data was reported at 1.805 % in 2050. This records a decrease from the previous number of 1.807 % for 2049. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data is updated yearly, averaging 2.504 % from Dec 2021 (Median) to 2050, with 30 observations. The data reached an all-time high of 3.154 % in 2026 and a record low of 1.805 % in 2050. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Transformation data remains active status in CEIC and is reported by Ministry of Development, Industry, Trade and Services. The data is categorized under Brazil Premium Database’s Investment – Table BR.OG003: Infrastructure Investments: Forecast.

BackgroundHematologic malignancies (HM) impose substantial healthcare and productivity-related costs globally. However, disparities in economic impact across regions and countries remain insufficiently explored. This study aimed to evaluate the global, regional, and national economic burden of HM and its subtypes (leukemia, non-Hodgkin lymphoma, multiple myeloma, and Hodgkin lymphoma) from 1990 to 2021, with projections to 2050.MethodsData from the Global Burden of Disease 2021 study were utilized to estimate the economic burden of HM using the value of a statistical life year (VSLY) approach, based on disability-adjusted life years (DALYs). Decomposition analysis was conducted to identify drivers of economic burden, including population growth and aging. Future trends were modeled using the Bayesian Age-Period-Cohort (BAPC) model, and comparisons of economic burden were made across countries by income levels.ResultsIn 2021, the global economic burden of HM reached $1.516 trillion, a 52.8% increase from $992 billion in 1990. This represented approximately 1% of the global GDP, with high-income countries (HICs) bearing the largest share of 2.17% of GDP, compared to 0.58% in lower-middle-income countries (LMICs). The United States had the highest national burden at $417.42 billion (95% UI: $389.49–$435.80 billion), followed by China $133.84 billion (95% UI: $98.63–$166.21 billion), $113.03 billion (95% UI: $101.62–$122.88 billion), and Japan $88.30 billion (95% UI: $85.65–$90.24 billion). By 2050, the global burden is projected to decline to $1.249 trillion, driven by healthcare advancements in HICs, but with a rising burden in upper-middle-income countries (UMICs), which are expected to account for 48.1% of the global burden. China is projected to lead globally with $421.65 billion (95% UI: $314.68–$1,495.35 billion), followed by India ($123.8 billion), while the United States is expected to decline to $101.6 billion. Subtype-specific analysis revealed that Leukemia accounted for the largest proportion of the burden in 2021 ($651 billion, 42.9%), followed by NHL ($492 billion, 32.5%), multiple myeloma ($278.17 billion, 100.5%), and Hodgkin lymphoma ($43.84 billion, 21%).ConclusionsThe economic burden of HM has increased significantly, with marked disparities across regions and income levels. By 2050, the burden is expected to shift from high- to middle-income countries. Investments in early diagnosis, affordable treatments, and healthcare improvements are essential to reduce the burden and address inequities.

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The bone cement market is expected to grow at a CAGR of 5% during the forecast period. Increasing rate of adoption of minimally invasive techniques, drivers.2, and drivers.3 are some of the significant factors fueling bone cement market growth.

Increasing rate of adoption of minimally invasive techniques

Technavio categorizes the global bone cement market as a part of the global healthcare supplies market that primarily covers manufacturers of medical products, including all categories of supplies such as consumables and disposables like safety needles, syringes, and catheters. The parent, global healthcare supplies market, covers products and companies engaged in R&D of a variety of product categories spanned across medical consumables that are used for the diagnosis and treatment of various diseases. The global healthcare market was valued at $1.72 trillion in 2019 and is expected to grow at a moderate pace. The global healthcare supplies market, which is a part of the global healthcare market, was valued at $27.31 bn in the same year. Technavio calculates the global healthcare supplies market size based on the combined revenue generated by manufacturers of medical supplies such as syringes, drapes, gloves, and gowns. Growth in the global healthcare supplies market will be driven by the following factors: Increasing life expectancy: The proportion of the global population over the age of 60 years is forecast to increase significantly. By 2050, nearly one-fourth of the US population is projected to be over 60 years, while Europe is likely to reach a similar proportion by 2030. Moreover, some large economies in Asia, such as Japan, already has one-third of its population above 60 years of age. China is expected to have almost half of its population above 60 years by around 2050. This geriatric population requires more medical attention leading to higher spending on healthcare. Expanding access to improved healthcare in emerging economies: With good economic growth across emerging markets in Asia and Africa, since 2000, leading to higher income levels, access to healthcare has also improved. The governments are also spending more on healthcare with a focus on improving the quality of care. Most of this growth has come from emerging countries and low-income regions. Sedentary lifestyle gaining pace: Sedentary lifestyle is the consequence of urbanization, an unhealthy diet, and decreasing levels of physical activity. It is a significant global health concern, with about one-fourth of the population in large economies like the US and China leading a physically inactive lifestyle. A sedentary lifestyle is anticipated to influence and change the nature of healthcare spending. Technavio expects healthcare spending to increase and move away from communicable diseases to chronic care. Increase in cases of chronic conditions: The number of chronic disease cases has been rising globally. The majority of the US population currently lives with at least one chronic condition. In 2018, China reached a “tipping point” by recording the highest number of early deaths due to chronic diseases. Going forward, the incidence of chronic cases is expected to be much higher than that of infectious diseases. Increasing number of surgical procedures: The increase in the number of surgical procedures due to the growing prevalence of various disorders requiring surgical interventions, and the rise in chronic conditions, apart from increasing cases of accidents and injuries, is leading to a rise in demand for medical supplies. Growing focus on infection control: Globally, hospital-acquired infections are major sources of concern among people receiving healthcare. For middle- and low-income economies, the rate of infection is much higher compared with patients in developed economies who receive healthcare of better quality. One way of countering this is to improve the conditions of healthcare facilities and provide healthcare supplies of better quality. Demand for better healthcare will push sales: Rapid urbanization in developing economies in Asia has created a demand for a high standard of healthcare and is expected to drive volume sales of healthcare supplies. Growth generated by emerging segments in healthcare: Growing adoption of healthcare supplies for home-based healthcare, home medical devices, and other advanced application areas such as robotic surgery will aid in the growth of this market. Increased healthcare spend is driving healthcare budgets. It is pushing governments to create cost pressure in the sector, which is a challenge. Some of the key cost and other pressures faced by the healthcare sector are listed below. Pricing pressure by governments: To reduce per capita healthcare spending, governments are increasingly trying to reduce costs related to the various stakeholders that include insurers, healthcare institutions, and manufacturers. Reimbursement reforms: To make healthcare more affordable for

Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Reference data was reported at 1.746 % in 2050. This records an increase from the previous number of 1.736 % for 2049. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Reference data is updated yearly, averaging 2.228 % from Dec 2021 (Median) to 2050, with 30 observations. The data reached an all-time high of 2.932 % in 2024 and a record low of 1.736 % in 2049. Brazil Forecast: Infrastructure Investments to(GDP) Gross Domestic ProductRatio: Reference data remains active status in CEIC and is reported by Ministry of Development, Industry, Trade and Services. The data is categorized under Brazil Premium Database’s Investment – Table BR.OG003: Infrastructure Investments: Forecast.

Brazil Forecast: Infrastructure Investments: Stock: Investment to(GDP) Gross Domestic ProductRatio of 3% data was reported at 7,810,073.892 BRL mn in 2050. This records an increase from the previous number of 7,597,733.008 BRL mn for 2049. Brazil Forecast: Infrastructure Investments: Stock: Investment to(GDP) Gross Domestic ProductRatio of 3% data is updated yearly, averaging 6,083,982.919 BRL mn from Dec 2033 (Median) to 2050, with 18 observations. The data reached an all-time high of 7,810,073.892 BRL mn in 2050 and a record low of 4,553,790.949 BRL mn in 2033. Brazil Forecast: Infrastructure Investments: Stock: Investment to(GDP) Gross Domestic ProductRatio of 3% data remains active status in CEIC and is reported by Ministry of Development, Industry, Trade and Services. The data is categorized under Brazil Premium Database’s Investment – Table BR.OG003: Infrastructure Investments: Forecast.

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The bone cement market is expected to grow at a CAGR of 5% during the forecast period. Increasing rate of adoption of minimally invasive techniques, drivers.2, and drivers.3 are some of the significant factors fueling bone cement market growth.

Increasing rate of adoption of minimally invasive techniques

Technavio categorizes the global bone cement market as a part of the global healthcare supplies market that primarily covers manufacturers of medical products, including all categories of supplies such as consumables and disposables like safety needles, syringes, and catheters. The parent, global healthcare supplies market, covers products and companies engaged in R&D of a variety of product categories spanned across medical consumables that are used for the diagnosis and treatment of various diseases. The global healthcare market was valued at $1.72 trillion in 2019 and is expected to grow at a moderate pace. The global healthcare supplies market, which is a part of the global healthcare market, was valued at $27.31 bn in the same year. Technavio calculates the global healthcare supplies market size based on the combined revenue generated by manufacturers of medical supplies such as syringes, drapes, gloves, and gowns. Growth in the global healthcare supplies market will be driven by the following factors: Increasing life expectancy: The proportion of the global population over the age of 60 years is forecast to increase significantly. By 2050, nearly one-fourth of the US population is projected to be over 60 years, while Europe is likely to reach a similar proportion by 2030. Moreover, some large economies in Asia, such as Japan, already has one-third of its population above 60 years of age. China is expected to have almost half of its population above 60 years by around 2050. This geriatric population requires more medical attention leading to higher spending on healthcare. Expanding access to improved healthcare in emerging economies: With good economic growth across emerging markets in Asia and Africa, since 2000, leading to higher income levels, access to healthcare has also improved. The governments are also spending more on healthcare with a focus on improving the quality of care. Most of this growth has come from emerging countries and low-income regions. Sedentary lifestyle gaining pace: Sedentary lifestyle is the consequence of urbanization, an unhealthy diet, and decreasing levels of physical activity. It is a significant global health concern, with about one-fourth of the population in large economies like the US and China leading a physically inactive lifestyle. A sedentary lifestyle is anticipated to influence and change the nature of healthcare spending. Technavio expects healthcare spending to increase and move away from communicable diseases to chronic care. Increase in cases of chronic conditions: The number of chronic disease cases has been rising globally. The majority of the US population currently lives with at least one chronic condition. In 2018, China reached a “tipping point” by recording the highest number of early deaths due to chronic diseases. Going forward, the incidence of chronic cases is expected to be much higher than that of infectious diseases. Increasing number of surgical procedures: The increase in the number of surgical procedures due to the growing prevalence of various disorders requiring surgical interventions, and the rise in chronic conditions, apart from increasing cases of accidents and injuries, is leading to a rise in demand for medical supplies. Growing focus on infection control: Globally, hospital-acquired infections are major sources of concern among people receiving healthcare. For middle- and low-income economies, the rate of infection is much higher compared with patients in developed economies who receive healthcare of better quality. One way of countering this is to improve the conditions of healthcare facilities and provide healthcare supplies of better quality. Demand for better healthcare will push sales: Rapid urbanization in developing economies in Asia has created a demand for a high standard of healthcare and is expected to drive volume sales of healthcare supplies. Growth generated by emerging segments in healthcare: Growing adoption of healthcare supplies for home-based healthcare, home medical devices, and other advanced application areas such as robotic surgery will aid in the growth of this market. Increased healthcare spend is driving healthcare budgets. It is pushing governments to create cost pressure in the sector, which is a challenge. Some of the key cost and other pressures faced by the healthcare sector are listed below. Pricing pressure by governments: To reduce per capita healthcare spending, governments are increasingly trying to reduce costs related to the various stakeholders that include insurers, healthcare institutions, and manufacturers. Reimbursement reforms: To make healthcare more affordable for

Brazil Forecast: GDP: Reference Scenario: 2019 Prices data was reported at 15,163,158.126 BRL mn in 2050. This records an increase from the previous number of 14,861,959.297 BRL mn for 2049. Brazil Forecast: GDP: Reference Scenario: 2019 Prices data is updated yearly, averaging 10,908,436.138 BRL mn from Dec 2021 (Median) to 2050, with 30 observations. The data reached an all-time high of 15,163,158.126 BRL mn in 2050 and a record low of 7,098,443.900 BRL mn in 2021. Brazil Forecast: GDP: Reference Scenario: 2019 Prices data remains active status in CEIC and is reported by Ministry of Development, Industry, Trade and Services. The data is categorized under Brazil Premium Database’s Investment – Table BR.OG003: Infrastructure Investments: Forecast.

Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform their choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for the exploration of such scenarios. At IMPACT's core is a partial equilibrium, the multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research center through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP). This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and trade of major food commodity groups, by regions and country. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).

In 2024, the total gross domestic product (GDP) of all ASEAN states amounted to approximately 3.95 trillion U.S. dollars, a significant increase from the previous years. In fact, the GDP of the ASEAN region has been skyrocketing for a few years now, reflecting the region’s thriving economy. Power in the EastThe Association of Southeast Asian Nations (ASEAN) comprises Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, the Philippines, Singapore, Thailand, and Vietnam. It was established in 1967 among five of these countries (Indonesia, Malaysia, Thailand, Singapore, and the Philippines) to facilitate trade and economic growth, as well as promote cultural development and social structures in the region. To date, they have been joined by another five nations. The ASEAN marketThe founding of the ASEAN organization provides the collaborating nations with more autonomy and influence on the global economy than they would have had by themselves. Additionally, struggling participating countries, such as Laos, are given an opportunity to grow on an ASEAN single market.

Tellusant provides free TelluBase data to select public data sources.These are small, but important, subsets of the full product.We are currently expanding the availability of Middle East & North Africa. We currently cover Algeria, Egypt, Morocco, Saudi Arabia, Tunisia, and United Arab Emirates city and subdivision data for 2024.If you represent an academic institution or a reputable media outlet and think you may benefit from TelluBase data, we may be able to provide it for free. Contact us with your query at info@tellusant.com.TelluBase covers 218 countries, 2600 cities, and 2500 subdivisions; 2000-2050. It gives a completely exhaustive view of the world economy.

Policy makers, analysts, and civil society face increasing challenges to reducing hunger and improving food security in a sustainable way. Modeling alternative future scenarios and assessing their outcomes can help inform their choices. The International Food Policy Research Institute's IMPACT model is an integrated system of linked economic, climate, water, and crop models that allows for exploration such scenarios. At IMPACT's core is a partial equilibrium, multimarket economic model that simulates national and international agricultural markets. Links to climate, water, and crop models support the integrated study of changing environmental, biophysical, and socioeconomic trends, allowing for in-depth analysis of a variety of critical issues of interest to policy makers at national, regional, and global levels. IMPACT benefits from close interactions with scientists at all 15 CGIAR research centers through the Global Futures and Strategic Foresight (GFSF) program, and with other leading global economic modeling efforts around the world through Agricultural Model Intercomparison and Improvement Project (AgMIP). This dataset summarizes results from the latest IMPACT projections to 2030 and 2050. Results are included for production, consumption, and trade of major food commodity groups, by regions and country. The projections are for two "baseline scenarios"-one considers the impacts of climate change, while the assumes no climate change (for comparison).