Students will explore U.S. census data to see the spatial differences in the United States’ population. The activity uses a web-based map and is tied to the AP Human Geography benchmarks.

Learning outcomes:

·
Unit 2, A1: Geographical analysis of population (density, distribute and scale)·
Unit 2, A3: Geographical analysis of population (composition: age, sex, income, education and ethnicity)·
Unit 2, A4: Geographical analysis of population (patterns of fertility, mortality and health)

Find more advanced human geography geoinquiries and explore all geoinquiries at http://www.esri.com/geoinquiries

NBU: GA: Liabilities: Accounts of Banks data was reported at 39,994.000 UAH mn in 2017. This records a decrease from the previous number of 44,299.000 UAH mn for 2016. NBU: GA: Liabilities: Accounts of Banks data is updated yearly, averaging 23,359.000 UAH mn from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 47,432.000 UAH mn in 2013 and a record low of 2,989.000 UAH mn in 2001. NBU: GA: Liabilities: Accounts of Banks data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .

Background: The unprecedented impact of the COVID-19 pandemic on modern society has ignited a “gold rush” for effective treatment and diagnostic strategies, with a significant diversion of economic, scientific, and human resources toward dedicated clinical research. We aimed to describe trends in this rapidly changing landscape to inform adequate resource allocation.Methods: We developed an online repository (COVID Trial Monitor) to analyze in real time the growth rate, geographical distribution, and characteristics of COVID-19 related trials. We defined structured semantic ontologies with controlled vocabularies to categorize trial interventions, study endpoints, and study designs. Analyses are publicly available at https://bioinfo.ieo.it/shiny/app/CovidCT.Results: We observe a clear prevalence of monocentric trials with highly heterogeneous endpoints and a significant disconnect between geographic distribution and disease prevalence, implying that most countries would need to recruit unrealistic percentages of their total prevalent cases to fulfill enrolment.Conclusions: This geographically and methodologically incoherent growth casts doubts on the actual feasibility of locally reaching target sample sizes and the probability of most of these trials providing reliable and transferable results. We call for the harmonization of clinical trial design criteria for COVID-19 and the increased use of larger master protocols incorporating elements of adaptive designs. COVID Trial Monitor identifies critical issues in current COVID-19-related clinical research and represents a useful resource with which researchers and policymakers can improve the quality and efficiency of related trials.

This data set contains Quarterly Results and yearly Targets by Operating Unit and Sub-National Units 1-3 for Fiscal Years 2016 – 2020 for a broad array of indicators across PEPFAR’s Program Areas. Data can be downloaded as a compressed (zip) file, which contains text files in csv (comma separated values) format. For indicator definitions, please consult the latest MER Indicator Reference Guide. For additional PEPFAR data, please visit data.pepfar.gov. Unless otherwise noted, the content, data, documentation, code, and related materials on data.pepfar.gov is public domain and made available with a Creative Commons CC0 1.0 Universal dedication and license-free (per US Code 17 USC § 105). Citation of data.pepfar.gov as a source of the data is appreciated.

This dataset is made available for individuals to replicate the analysis done to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions.

Ukraine NBU: GA: Net Position data was reported at -115,988.000 UAH mn in 2017. This records a decrease from the previous number of -68,366.000 UAH mn for 2016. Ukraine NBU: GA: Net Position data is updated yearly, averaging -89,135.000 UAH mn from Dec 2002 (Median) to 2017, with 16 observations. The data reached an all-time high of 44,765.000 UAH mn in 2014 and a record low of -150,388.000 UAH mn in 2007. Ukraine NBU: GA: Net Position data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .

Additional climate information for research paper «Ecological and Geographical Analysis of Distribution of Heracleum persicum, H. mantegazzianum and H. sosnowskyi on The Northern Limit of Its Invaded Range in Europe» submitted to Russian Journal of Biological Invasions

Ukraine NBU: GA: Assets: Internal State Debt data was reported at 1,926.000 UAH mn in 2017. This records a decrease from the previous number of 2,002.000 UAH mn for 2016. Ukraine NBU: GA: Assets: Internal State Debt data is updated yearly, averaging 3,042.000 UAH mn from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 10,522.000 UAH mn in 2002 and a record low of 1,926.000 UAH mn in 2017. Ukraine NBU: GA: Assets: Internal State Debt data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .

According to Verified Market Research, North America and Europe Ad Tech Software Market were valued at USD 16011.45 Million in 2024 and are projected to reach USD 28386.51 Million by 2031, growing at a CAGR of 7.42% from 2024 to 2031.

When the first advertising technology was introduced at the dawn of digital advertising evolution, the most significant change occurred. Every year, new ad tech solutions emerge, and marketers polish their strategies by adding more complex tools to their strategies. Advertisers may utilize sophisticated tools, extensive data, and cutting-edge methods to create flawless campaigns that get their messages to the correct users, rather than posting ads at random and hoping for luck. In addition, the programmatic advertising market relies heavily on ad tech tools. Modern advertisements are sent to the most appropriate viewers at the right time and in the right context thanks to Ad tech. Moreover, increasing internet penetration and the growing adoption of smart devices have resulted in the growing demand for the Ad-tech Software Market. Ad tech methods assisted by influential data allow agencies to make smarter placements of ads at the perfect time.

The examination of the characteristic law of traditional village transformation over time represents a vital nexus in cultural heritage preservation and the transmission of vernacular culture. Historical event points were used to augment village development information, facilitating the restoration of the village’s historical pattern. Geographical analysis methods, including Standard Deviation Ellipse Analysis (SDSEA), Nearest Neighbor Analysis (NNA), and Source-Destination Analysis (SDA), were employed to explore the characteristics of the village’s geographical center of gravity, changes in concentration and dispersion, and functional transfer. The stepwise progression of the village’s evolution was investigated, as well as the mechanism of residents’ behavior during the evolution process. The results reveal: 1) The spatial evolution of the settlement shows a trend of agglomeration. As time passes, the center of gravity of each functional space gradually converges, and the average distance between elements decreases, resulting in a shift from a dispersed to a clustered distribution. 2) The village space changes from simple to complex due to the conduct of the villagers. Residential behaviors promote the establishment of residential space and the development of public and commercial space. The usage, abandonment, and functional transitions that occur inside the space cause functional zones to nest with each other, resulting in a more intricate spatial structure. 3) Both the degree of change and the preservation of the village’s functional space show an increasing trend, indicating that the protection of the built space and the expansion of the unbuilt space occur simultaneously. This represents a developmental trend that is consistent with the social surroundings and the villagers’ ambitions.

Ukraine NBU: GA: Assets: Others data was reported at 137.000 UAH mn in 2017. This records a decrease from the previous number of 184.000 UAH mn for 2016. Ukraine NBU: GA: Assets: Others data is updated yearly, averaging 295.000 UAH mn from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 1,070.000 UAH mn in 2001 and a record low of 114.000 UAH mn in 2007. Ukraine NBU: GA: Assets: Others data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .

One challenge to achieving Millennium Development Goals was inequitable access to quality health services. In order to achieve the Sustainable Development Goals, interventions need to reach underserved populations. Analyzing health indicators in small geographic units aids the identification of hotspots where coverage lags behind neighboring areas. The purpose of these analyses is to identify areas of low coverage or high need in order to inform effective resource allocation to reduce child health inequity between and within countries. Using data from The Demographic and Health Survey Program surveys conducted in 27 selected African countries between 2010 and 2014, we computed estimates for six child health indicators for subnational regions. We calculated Global Moran’s I statistics and used Local Indicator of Spatial Association analysis to produce a spatial layer showing spatial associations. We created maps to visualize sub-national autocorrelation and spatial clusters. The Global Moran’s I statistic was positive for each indicator (range: 0.41 to 0.68), and statistically significant (p

Annual average Child and Working tax credits statistics of finalised awards for each year. Geographical analysis down to local authority level. Supplement on over and under payments. Supplement on over and under payments. Geographical analysis down to local authority level.

BackgroundArea deprivation has been shown to be associated with various adverse health outcomes including communicable as well as non-communicable diseases. Our objective was to assess potential associations between area deprivation and COVID-19 standardized incidence and mortality ratios in Bavaria over a period of nearly 2 years. Bavaria is the federal state with the highest infection dynamics in Germany and demographically comparable to several other European countries.MethodsIn this retrospective, observational ecological study, we estimated the strength of associations between area deprivation and standardized COVID-19 incidence and mortality ratios (SIR and SMR) in Bavaria, Germany. We used official SARS-CoV-2 reporting data aggregated in monthly periods between March 1, 2020 and December 31, 2021. Area deprivation was assessed using the quintiles of the 2015 version of the Bavarian Index of Multiple Deprivation (BIMD 2015) at district level, analyzing the overall index as well as its single domains.ResultsDeprived districts showed higher SIR and SMR than less deprived districts. Aggregated over the whole period, the SIR increased by 1.04 (95% confidence interval (95% CI): 1.01 to 1.07, p = 0.002), and the SMR by 1.11 (95% CI: 1.07 to 1.16, p < 0.001) per BIMD quintile. This represents a maximum difference of 41% between districts in the most and least deprived quintiles in the SIR and 110% in the SMR. Looking at individual months revealed clear linear association between the BIMD quintiles and the SIR and SMR in the first, second and last quarter of 2021. In the summers of 2020 and 2021, infection activity was low.ConclusionsIn more deprived areas in Bavaria, Germany, higher incidence and mortality ratios were observed during the COVID-19 pandemic with particularly strong associations during infection waves 3 and 4 in 2020/2021. Only high infection levels reveal the effect of risk factors and socioeconomic inequalities. There may be confounding between the highly deprived areas and border regions in the north and east of Bavaria, making the relationship between area deprivation and infection burden more complex. Vaccination appeared to balance incidence and mortality rates between the most and least deprived districts. Vaccination makes an important contribution to health equality.

Ukraine NBU: GA: Liabilities: Accounts of Government and Other Clients data was reported at 56,123.000 UAH mn in 2017. This records an increase from the previous number of 48,541.000 UAH mn for 2016. Ukraine NBU: GA: Liabilities: Accounts of Government and Other Clients data is updated yearly, averaging 13,016.000 UAH mn from Dec 2001 (Median) to 2017, with 17 observations. The data reached an all-time high of 56,123.000 UAH mn in 2017 and a record low of 1,501.000 UAH mn in 2001. Ukraine NBU: GA: Liabilities: Accounts of Government and Other Clients data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .

Ukraine NBU: GA: Liabilities: Deposit Certificates Issued by NBU data was reported at 67,024.000 UAH mn in 2017. This records a decrease from the previous number of 68,073.000 UAH mn for 2016. Ukraine NBU: GA: Liabilities: Deposit Certificates Issued by NBU data is updated yearly, averaging 3,273.500 UAH mn from Dec 2004 (Median) to 2017, with 14 observations. The data reached an all-time high of 89,747.000 UAH mn in 2015 and a record low of 173.000 UAH mn in 2004. Ukraine NBU: GA: Liabilities: Deposit Certificates Issued by NBU data remains active status in CEIC and is reported by National Bank of Ukraine. The data is categorized under Global Database’s Ukraine – Table UA.KB028: Balance Sheet: National Bank of Ukraine: Geographical Analysis .