Inflation was the most worrying topic worldwide as of May 2025, with ********* of the respondents choosing that option. Crime and violence, as well as poverty and social inequality, followed behind. Moreover, following Russia's invasion of Ukraine and the war in Gaza, *** percent of the respondents were worried about military conflict between nations. Only *** percent were worried about the COVID-19 pandemic, which dominated the world after its outbreak in 2020. Global inflation and rising prices Inflation rates have spiked substantially since the beginning of the COVID-19 pandemic in 2020. From 2020 to 2021, the worldwide inflation rate increased from *** percent to *** percent, and from 2021 to 2022, the rate increased sharply from *** percent to *** percent. While rates are predicted to fall by 2025, many are continuing to struggle with price increases on basic necessities. Poverty and global development Poverty and social inequality were the third most worrying issues for respondents. While poverty and inequality are still prominent, global poverty rates have been on a steady decline over the years. In 1994, ** percent of people in low-income countries and around one percent of people in high-income countries lived on less than 2.15 U.S. dollars per day. By 2018, this had fallen to almost ** percent of people in low-income countries and 0.6 percent in high-income countries. Moreover, fewer people globally are dying of preventable diseases, and people are living longer lives. Despite these aspects, issues such as wealth inequality have global prominence.

A survey of people from 30 different countries around the world found that mental health was the biggest health problem respondents said was facing their country in 2025. Other health problems reported by respondents included cancer, stress, and obesity. The COVID-19 pandemic The COVID-19 pandemic impacted almost every country in the world and was the biggest global health crisis in recent history. It resulted in hundreds of millions of cases and millions of deaths, causing unprecedented disruption in health care systems. Lockdowns imposed in many countries to halt the spread of the virus also resulted in a rise of mental health issues as feelings of stress, isolation, and hopelessness arose. However, vaccines to combat the virus were developed at record speed, and many countries have now vaccinated large shares of their population. Nevertheless, in 2025, *** percent of respondents still stated that COVID-19 was the biggest health problem facing their country. Mental health issues One side effect of the COVID-19 pandemic has been a focus on mental health around the world. The two most common mental health issues worldwide are anxiety disorders and depression. In 2021, it was estimated that around *** percent of the global population had an anxiety disorder, while **** percent suffered from depression. Rates of depression are higher among females than males, with some *** percent of females suffering from depression, compared to *** percent of men. However, rates of suicide in most countries are higher among men than women. One positive outcome of the COVID-19 pandemic and the spotlight it shined on mental health may be a decrease in stigma surrounding mental health issues and seeking help for such issues. This would be a positive development, as many people around the world do not or cannot receive the necessary treatment they need for their mental health.

This statistic shows the answers to the following survey question "What do you think are the most pressing challenges the world is currently facing?" As of 2017, ** percent of respondents indicated terrorism is among the most pressing challenges the world is currently facing. Approximately two thirds of respondents found that climate change was also an important global pressing challenge currently. Less than half would consider caring for an ageing population, access to healthcare and economic growth and job creation being in their top five of most pressing challenges to the world.

World Health Organization's Data for Sweden

Disease, Injury and Health System Indicators

By Humanitarian Data Exchange [source]

About this dataset

The World Health Organization's data portal offers a broad scope of health indicators on Mortality, Sustainable Development Goals, Millennium Development Goals (MDGs), Health Systems and beyond from more than 190 countries worldwide. This dataset contains essential information about Sweden that aims to help people comprehend the country’s current position in relation to other nations when it comes to public health and environment-related issues.

Explore various factors such as Disease Control, Demographics & Socioeconomics Statistics, Financial Protection, Mental Health and Substance Useand many more with this comprehensive collection of Swedish indicators covering both national and global data sources from WHO's portal! The data contains relevant information related to mortality rates; start and end year when the data was collected; display values for sex, region & age group codes as well as key URLs providing reference links to GHO indices or other external websites among others - everything that you need in order to evaluate the current state of health in Sweden. And not only can you access pre-aggregated datasets here on Kaggle but also have access sections of individual indicator metadata for further exploration using our distinct resource descriptions! With this interactive source at your fingertips make sure you seize this opportunity now!

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• Access the data – The WHO Data for Sweden can be accessed by clicking on the above link in this guide or through kaggle directly. To access the data once you have decided where to get it, download and save it to a suitable place on your device that is easy to recall later. These may include folders such as desktop, documents, or downloads folder so that you can access them easily when needed.

• Explore column names – Look at what are included in each of these columns in terms of information types like string, integer or float etc., details about indicators (like coded values for gender), object codes (like GHO code), URL’s related to countries and regions as applicable as per global places and standards used by organisations like WHO etc., feature types (like ‘display value’). Once you know what types of categories are available under each column name/ header, it would help understand which areas/ aspects one needs to further explore for insights through analysis using statistics tools such pandas & numpy etc; knowledge graphs & charts using libraries like matplotlib; keep track using a dashboard using Tableau online app & links etc.; fetch meaningful insights though machine learning libraries like Scikit-learn along with relevant algorithms depending upon need & loss function optimization techniques applied!

• Organize tabulation / visualisation format: Creating visuals such tables or charts helps one better understanding between various indexing columns (x-axis/ Y-axis) vs other columns mentioned in #2 above; further exploring categorisations of variables by agegroup(s); subcategorisation by sex , region wise vs national trends along with visibilities if any relationale validations among those metrics multiple category level combination generation comapre metric performance over time period frame set based upon start year , end year possible overlay competing validations across nations establish baseline metrics from already published / shared past reports if availble look at map view alternatives for visualisations based upon population patterns demography changes evaluated over years

• Utilize other sources : Online resources available which could be explored - datasets from working organisation linked with targets answered via google datastudio connected metric analysed versus potential forecast measures supported hyperlinks queries into specific KPIs gathered from forumlands managed indexed provided hints & clues attributed additional overlays hinted outcomes reflected intitiative related indices drawn creeed conclusions evidence deduction

Research Ideas

• Visualizing health trends in Sweden over time, by region, and by gender to identify areas of improvement or concentrated areas of vulnerability.
• Tracking poverty in Sweden and observing the correlation between poverty rate and the availability of public healthcare resources.
• Evaluating the impact of public health initiatives like immunization programs, substance abuse...

The average for 2023 based on 193 countries was -0.07 points. The highest value was in Liechtenstein: 1.61 points and the lowest value was in Syria: -2.75 points. The indicator is available from 1996 to 2023. Below is a chart for all countries where data are available.

Students in statistics, data science, analytics, and related fields study the theory and methodology of data-related topics. Some, but not all, are exposed to experiential learning courses that cover essential parts of the life cycle of practical problem-solving. Experiential learning enables students to convert real-world issues into solvable technical questions and effectively communicate their findings to clients. We describe several experiential learning course designs in statistics, data science, and analytics curricula. We present findings from interviews with faculty from the U.S., Europe, and the Middle East and surveys of former students. We observe that courses featuring live projects and coaching by experienced faculty have a high career impact, as reported by former participants. However, such courses are labor-intensive for both instructors and students. We give estimates of the required effort to deliver courses with live projects and the perceived benefits and tradeoffs of such courses. Overall, we conclude that courses offering live-project experiences, despite being more time-consuming than traditional courses, offer significant benefits for students regarding career impact and skill development, making them worthwhile investments. Supplementary materials for this article are available online.

As our generation and collection of quantitative digital data increase, so do our ambitions for extracting new insights and knowledge from those data. In recent years, those ambitions have manifested themselves in so-called “Grand Challenge” projects coordinated by academic institutions. These projects are often broadly interdisciplinary and attempt to address to major issues facing the world in the present and the future through the collection and integration of diverse types of scientific data. In general, however, disciplines that focus on the past are underrepresented in this environment – in part because these grand challenges tend to look forward rather than back, and in part because historical disciplines tend to produce qualitative, incomplete data that are difficult to mesh with the more continuous quantitative data sets provided by scientific observation. Yet historical information is essential for our understanding of long-term processes, and should thus be incorporated into our efforts to solve present and future problems. Archaeology, an inherently interdisciplinary field of knowledge that bridges the gap between the quantitative and the qualitative, can act as a connector between the study of the past and data-driven attempts to address the challenges of the future. To do so, however, we must find new ways to integrate the results of archaeological research into the digital platforms used for the modeling and analysis of much bigger data.

Planet Texas 2050 is a grand challenge project recently launched by The University of Texas at Austin. Its central goal is to understand the dynamic interactions between water supply, urbanization, energy use, and ecosystems services in Texas, a state that will be especially affected by climate change and population mobility by the middle of the 21st century. Like many such projects, one of the products of Planet Texas 2050 will be an integrated data platform that will make it possible to model various scenarios and help decision-makers project the results of resent policies or trends into the future. Unlike other such projects, however, PT2050 incorporates data collected from past societies, primarily through archaeological inquiry. We are currently designing a data integration and modeling platform that will allow us to bring together quantitative sensor data related to the present environment with “fuzzier” data collected in the course of research in the social sciences and humanities. Digital archaeological data, from LiDAR surveys to genomic information to excavation documentation, will be a central component of this platform. In this paper, I discuss the conceptual integration between scientific “big data” and “medium-sized” archaeological data in PT2050; the process that we are following to catalog data types, identify domain-specific ontologies, and understand the points of intersection between heterogeneous data sets of varying resolution and precision as we construct the data platform; and how we propose to incorporate digital data from archaeological research into integrated modeling and simulation modules.

Abstract

The World Bank Group is interested in gauging the views of clients and partners who are either involved in development in Brazil or who observe activities related to social and economic development. The World Bank Country Assessment Survey is meant to give the World Bank Group's team that works in Brazil, greater insight into how the Bank's work is perceived. This is one tool the World Bank Group uses to assess the views of its critical stakeholders. With this understanding, the World Bank Group hopes to develop more effective strategies, outreach and programs that support development in Brazil at the federal/state/municipal level. The World Bank Group commissioned an independent firm to oversee the logistics of this effort in Brazil.

This survey was designed to achieve the following objectives: - Assist the World Bank Group in gaining a better understanding of how stakeholders in Brazil perceive the Bank;

• Obtain systematic feedback from stakeholders in Brazil regarding: · Their views regarding the general environment in Brazil; · Their overall attitudes toward the World Bank Group in Brazil; · Overall impressions of the World Bank Group's effectiveness and results, knowledge work, and communication and information sharing in Brazil; · Perceptions of the recent trends and the World Bank Group's future role in Brazil.

• Use data to help inform Brazil country team's strategy.

Geographic coverage

National

Analysis unit

Stakeholder

Universe

Stakeholders of the World Bank in Brazil

Kind of data

Sample survey data [ssd]

Sampling procedure

From June to August 2013, 10,200 stakeholders of the World Bank Group in Brazil were invited to provide their opinions on the Bank's assistance to the country by participating in a country survey. Participants in the survey were drawn from the office of the President, Prime Minister/Minister, office of a parliamentarian, ministries, ministerial departments, or implementation agencies; consultants/ contractors working on World Bank Group-supported projects/programs; project management units (PMUs) overseeing implementation of a project; state Government; municipal governments; bilateral and multilateral agencies; private sector organizations; private foundations; the financial sector/private banks; NGOs; community-based organizations; the media; independent government institutions; trade unions; academia/research institutes/think tanks; faith-based groups, the judiciary branch; and other organizations.

Mode of data collection

Internet [int]

Research instrument

The Questionnaire consists of 8 Sections:

A. General Issues facing Brazil: Respondents were asked to indicate whether Brazil is headed in the right direction, what they thought were the top three development priorities in Brazil, and which areas would contribute most to reducing poverty and generating economic growth

B. Overall Attitudes toward the World Bank Group: Respondents were asked to rate their familiarity with the World Bank, Inter-American Development Bank, Latin American Development Bank, and the International Finance Corporation, their perceived effectiveness of these organizations in Brazil, and which of these organizations they work with the most in Brazil. They were asked to rate the Bank staff's preparedness to help Brazil solve its development challenges, their agreement with various statements regarding the Bank's work, and the extent to which the Bank is an effective development partner.

Respondents were also asked to indicate the Bank's greatest values, greatest weaknesses, the most effective instruments in helping reduce poverty in Brazil, in which sectoral areas the Bank should focus most resources, to what extent the Bank should seek to influence the global development agenda, and to what reasons respondents attributed failed or slow reform efforts. Respondents were invited to indicate at what level (federal, state, or municipal) the World Bank Group works mostly in Brazil. They were asked if the Bank is most effective when it works in one sector or multi-sectorally. Lastly, they were asked to indicate to what extent they believe the combination of financial, knowledge, and convening services provided by the Bank meets the national development needs of Brazil.

C. World Bank Group Effectiveness and Results: Respondents were asked to rate the extent to which the Bank's work helps achieve development results, the extent to which the Bank meets Brazil's needs for knowledge services and financial instruments, and the Bank's level of effectiveness across thirty-two development areas, such as education, public sector governance/reform, health, transport, and anti-corruption. They were also asked to what extent they believe that Brazil receives value for money from the World Bank Group's fee-based services/products.

D. The World Bank Group's Knowledge: Respondents were asked to indicate the areas on which the Bank should focus its research efforts and to rate the effectiveness and quality of the Bank's knowledge work and activities, including how significant of a contribution it makes to development results and its technical quality. Respondents were also asked whether they read/consulted the most recent LAC Flagship Report and whether it provided useful information in their work.

E. Working with the World Bank Group: Respondents were asked to rate their level of agreement with a series of statements regarding working with the Bank, such as the World Bank Group's "Safeguard Policy" requirements being reasonable, the Bank imposing reasonable conditions on its lending, disbursing funds promptly, increasing Brazil's institutional capacity, and providing effective implementation support.

F. The Future Role of the World Bank Group in Brazil: Respondents were asked to rate how significant a role the World Bank Group should play in Brazil in the near future and to indicate what the Bank should do to make itself of greater value. Respondents were asked to indicate to what extent they believe the World Bank Group has moved in the right direction in terms of the focus of its work in Brazil and how significant a role international development cooperation should play in Brazil's development in the near future at the federal, state, and/or municipal level.

G. Communication and Information Sharing: Respondents were asked to indicate how they get information about economic and social development issues, how they prefer to receive information from the Bank, and their usage and evaluation of the Bank's websites. Respondents were asked about their awareness of the Bank's Access to Information policy, whether they used/had used the World Bank Group website, and whether they accessed the Bank's social media channels. Respondents were also asked about their level of agreement that they know how to find information from the Bank, and that the Bank is responsive to information requests. Respondents were also asked to indicate what kind of e-services they are currently subscribed to.

H. Background Information: Respondents were asked to indicate their current position, specialization, at what level (federal, state, or municipal) they primarily work at, whether they professionally collaborate with the World Bank Group, whether they worked with the International Finance Corporation in Brazil, their exposure to the Bank in Brazil, and their geographic location.

Response rate

A total of 200 stakeholders participated in the survey (2% response rate).

Heart Disease Deaths in Oklahoma

Current Trends and Target Rates

By Oklahoma [source]

About this dataset

This dataset contains an overview of historical heart disease death rates in Oklahoma from 2000 to 2018. The dataset consists of yearly figures and target figures for the numbers of deaths due to heart diseases, allowing a comparison between the expected rate and the actual rate over time. This data is important as it can be used to analyze trends in heart disease death rates, helping inform public health initiatives and policy decisions

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This dataset includes the number of death due to heart disease in Oklahoma. It provides a single, comprehensive data set that captures detailed information on the historical prevalence of heart disease death rates in the state. This dataset can be used for various research or analytical purposes such as epidemiological studies or health services planning.

To use this dataset, one must first understand that it contains three main pieces: the year of reported deaths, the actual number of deaths related to heart disease during each year and a target total for expected deaths from heart disease per year, which are used as reference points when analyzing other years. The years column includes all relevant dates while historical data column provides more specifics such as exact numbers and percentages related to those who perished due to heart-related conditions.

By utilizing this data set users can easily find out how many persons died due to cardiac-related diseases along with what risks were most prevalent at certain times over that period by comparing provided figures with reference targets at any given time slice in question (time point). Additionally, one can observe trends carefully within different groups such as males versus females or rural versus urban locations thus allowing them more robust insight into factors associated with mortality from cardiac conditions across different demographics

Research Ideas

• Identifying which geographic areas in Oklahoma are at highest risk for heart disease and creating targeted public health initiatives to reduce its incidence.
• Determining correlations between changes in vital health indicators (e.g., increase of physical activity) with changes in heart disease death rates to better inform policy and research direction.
• Analyzing overall mortality rates compared to other counties or states with comparable demographics to assess the effectiveness of existing public health interventions over time

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

Unknown License - Please check the dataset description for more information.

Columns

File: res_heart_disease_deaths_kdjx-hayj.csv | Column name | Description | |:--------------------|:-----------------------------------------------------------------------------------------------------------------------------------------| | Years | The year associated with the data. (Integer) | | Historical Data | The number of deaths due to heart disease in Oklahoma in that particular year from 2000-2018. (Integer) | | Target | A value generated based on Historical Data indicating what should be targeted as a baseline performance measure going forward. (Integer) |

File: res_heart_disease_deaths_-_column_chart_3a28-gndr.csv | Column name | Description | |:--------------------|:-----------------------------------------------------------------------------------------------------------------------------------------| | Years | The year associated with the data. (Integer) | | Historical Data | The number of deaths due to heart disease in Oklahoma in that particular year from 2000-2018. (Integer) | | Target | A value generated based on Historical Data indicating what should be targeted as a baseline performance measure going forward. (Integer) |

Acknowledgements

...

TH: Current Health Expenditure Per Capita: Current Price data was reported at 0.000 USD mn in 2015. This records a decrease from the previous number of 0.000 USD mn for 2014. TH: Current Health Expenditure Per Capita: Current Price data is updated yearly, averaging 0.000 USD mn from Dec 2000 (Median) to 2015, with 16 observations. The data reached an all-time high of 0.000 USD mn in 2014 and a record low of 0.000 USD mn in 2001. TH: Current Health Expenditure Per Capita: Current Price data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Thailand – Table TH.World Bank: Health Statistics. Current expenditures on health per capita in current US dollars. Estimates of current health expenditures include healthcare goods and services consumed during each year.; ; World Health Organization Global Health Expenditure database (http://apps.who.int/nha/database).; Weighted Average;

Over the last four years since the macroeconomic crisis in 1991, the Indian economy has undergone substantial changes. Almost all areas of the economy have been opened to domestic and foreign private investment. Import licensing restrictions on intermediates and capital goods have been virtually eliminated. Tariffs have been significantly reduced and full convertibility has been established for current account transactions. In the financial sector, prudential regulations that meet international standards have been introduced; banks now have significantly more discretion in their lending decisions; financial markets have been liberalized; and entry restrictions have been eliminated. The external accounts have strengthened considerably and, although still a major obstacle to higher growth, central fiscal imbalances are lower. This report highlights a large unfinished agenda. First, all reforms, which are part of the program articulated since 1991, need to be followed through to completion. In addition, agriculture, which historically has contributed extensively to poverty reduction, requires a more focused effort. Second, an urgent and appreciable improvement in public savings - embracing reduction of the fiscal deficits of the central and state governments, and improving substantially the efficiency of public enterprises - is necessary. It is critical for restoring the capacity of the public sector to invest and for accommodating higher levels of private investment. Such levels of total investment, particularly in infrastructure and social services such as primary education, are needed to achieve and sustain rates of growth and poverty reduction comparable to higher performing countries in Asia. Third, failure to correct fiscal imbalances would implicate and ultimately undermine external sector policies. Over the last two years, the challenge has been to prevent surpluses in the capital account from causing the nominal and real exchange rates to appreciate, and thereby, from reducing export growth. Careful and cautious management of these external accounts needs to continue in the foreseeable future, whether the challenge is large capital inflows or outflows. At the same time, international experience indicates that a strong fiscal position has a central role in managing effectively the capital and current accounts of the balance of payments. Fourth, in an economy which was driven for four decades by increases in public investment, maintaining dynamic growth requires a dramatic increase in private investment in infrastructure. Recent changes in the policy framework provide ample scope for this needed private sector involvement, and private investors have expressed interest in participating in the sector.

The World Development Indicators (WDI) is the primary World Bank collection of development indicators, compiled from officially-recognized international sources. It presents the most current and accurate global development data available, and includes national, regional and global estimates.

For further details, please refer to https://datatopics.worldbank.org/world-development-indicators/

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

This dataset comes from a Zindi competition and was created in Kaggle so my team can work on it with our favourite website.

You may have seen recent news articles stating that air quality has improved due to COVID-19. This is true for some locations, but as always the truth is a little more complicated. In parts of many African cities, air quality seems to be getting worse as more people stay at home. For this challenge we’ll be digging deeper into the data, finding ways to track air quality and how it is changing, even in places without ground-based sensors. This information will be especially useful in the face of the current crisis, since poor air quality makes a respiratory disease like COVID-19 more dangerous.

We’ve collected weather data and daily observations from the Sentinel 5P satellite tracking various pollutants in the atmosphere. Your goal is to use this information to predict PM2.5 particulate matter concentration (a common measure of air quality that normally requires ground-based sensors to measure) every day for each city. The data covers the last three months, spanning hundreds of cities across the globe.

About World Air Quality Index

The World Air Quality Index project is a non-profit project started in 2007. Its mission is to promote air pollution awareness for citizens and provide a unified and world-wide air quality information. The project is providing transparent air quality information for more than 100 countries, covering more than 12,000 stations in 1000 major cities, via those two websites: aqicn.org and waqi.info

Please cite the following paper when using this dataset: N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization just declared monkeypox a global health emergency. As a result, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description The dataset consists of a total of 255,363 Tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7th May 2022 to 23rd July 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 6 different .txt files based on the timelines of the associated tweets. The following provides the details of these dataset files. • Filename: TweetIDs_Part1.txt (No. of Tweet IDs: 13926, Date Range of the Tweet IDs: May 7, 2022 to May 21, 2022) • Filename: TweetIDs_Part2.txt (No. of Tweet IDs: 17705, Date Range of the Tweet IDs: May 21, 2022 to May 27, 2022) • Filename: TweetIDs_Part3.txt (No. of Tweet IDs: 17585, Date Range of the Tweet IDs: May 27, 2022 to June 5, 2022) • Filename: TweetIDs_Part4.txt (No. of Tweet IDs: 19718, Date Range of the Tweet IDs: June 5, 2022 to June 11, 2022) • Filename: TweetIDs_Part5.txt (No. of Tweet IDs: 47718, Date Range of the Tweet IDs: June 12, 2022 to June 30, 2022) • Filename: TweetIDs_Part6.txt (No. of Tweet IDs: 138711, Date Range of the Tweet IDs: July 1, 2022 to July 23, 2022)

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used.

DPMS = Darwin Prospective Melioidosis Study. (XLSX)

Current problems with global health research and scholarship.

On behalf of the National Advanced Institute of Industrial Science and Technology (AIST), Japan, this paper gives concluding remarks to the Seventh Asian Geothermal Symposium and acknowledgements to all the supporting organizations and participants. Whether preferable or not, we Asian countries inevitably share the same global environmental issue and the same energy security problem in the current borderless world. Attention is here drawn to two urgent aspects in relation to the necessity of geothermal developments. One is that the global warming is already advancing as serious expressions such as unusual climate, desertification and sea level rise. The other is that a serious threat of the final oil crisis is closing within the earlier half of the 21-century. These trends inevitably accelerate geothermal development all over Asia. Efforts like the Seventh Asian Geothermal Symposium could be believed foresight to the future Asia.

Every public company publishes a financial report to declare the financial activities and position of a business. This financial statement contains many tables to present the information. We classify these tables into predefined categories, such as below.

1) Income Statements 2) Balance Sheets 3) Cash Flows 4) Notes 5) Others

Datasets: Within the given dataset you will find 5 folders with the above category names. Every folder contains .html files with respective tabular data.

Expecting the grouping of documents in such a way that the files appear distinguished as per their category. The categories can only be used as a benchmark for evaluation later.

Data extracted: The data has been taken from the Publically available Hexaware Technologies financial annual reports. You can find here on link https://hexaware.com/investors/

Thank you for your Patience, Enjoy the dataset and Explore and learn more. Peace out✌️

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.