In 2021, Massachusetts, Connecticut, and Minnesota had the highest Human Development Index (HDI) score of any other states at 0.95. Many more states had a score just below this at 0.94. Mississippi had the lowest HDI score at 0.87, and the U.S. average was 0.92.

Switzerland had the highest level of the Human Development Index (HDI) worldwide in 2022 with a value of 0.967. With a score of 0.966, Norway followed closely behind Switzerland and had the second highest level of human development in that year. The rise of the Asian tigers In the decades after the Cold War, the four so-called Asian tigers, South Korea, Singapore, Taiwan, and Hong Kong (now a Special Administrative Region of China) experienced rapid economic growth and increasing human development. At number four and number nine of the HDI, respectively, Hong Kong and Singapore are the only Asian locations within the top 10 highest HDI scores. Both locations have experienced tremendous economic growth since the 1980’s and 1990’s. In 1980, the per capita GDP of Hong Kong was 5,703 U.S. dollars, increasing throughout the decades until reaching 50,029 in 2023, which is expected to continue to increase in the future. Meanwhile, in 1989, Singapore had a GDP of nearly 31 billion U.S. dollars, which has risen to nearly 501 billion U.S. dollars today and is also expected to keep increasing. Growth of the UAE The United Arab Emirates (UAE) is the only Middle Eastern country besides Israel within the highest ranking HDI scores globally. Within the Middle East and North Africa (MENA) region, the UAE has the third largest GDP behind Saudi Arabia and Israel, reaching nearly 507 billion U.S. dollars by 2022. Per capita, the UAE GDP was around 21,142 U.S. dollars in 1989, and has nearly doubled to 43,438 U.S. dollars by 2021. Moreover, this is expected to reach over 67,538 U.S. dollars by 2029. On top of being a major oil producer, the UAE has become a hub for finance and business and attracts millions of tourists annually.

Europe and Central Asia was the region with the highest Human Development Index (HDI) worldwide at 0.8. Meanwhile, the lowest HDI was found in Sub-Saharan Africa, underlining the high prevalence of poverty in the region. The difference between the regions was even stronger after adjusting for inequality.

In 2023 Zurich was both the leading smart city based on the IMD smart city index as well as the city with the highest human development index score, making it one of the premier places on earth to live in. Notable exceptions to the HDI to IMD index score were Beijing, Dubai, and Abu Dhabi. Beijing is a notable outlier because although it ranked 12th on the digital smart cities ranking it was nearly 90 points lower than Zurich on the HDI score. This is compared to Munich, Germany, which was the 20th digital city but had a HDI score of 950.

Smart tech is watching.

CCTV cameras powered by artificial intelligence have become a significant growing market in the modern city. These are predominantly residential, with half the market catering to residential applications of CCTV cameras. However, commercial and business-related CCTV cameras have also seen significant growth, with the market reaching over 800 million U.S. dollars in 2023.

Digital cities need data and data needs infrastructure.

The leading issue with AI infrastructure is data management. AI is a strong influence on how digital cities work and requires a considerable amount of infrastructure to be effective. Storage of AI software is a minor concern, accounting for less than ten percent of challenges globally in 2023.

The aim of the Human Development Report is to stimulate global, regional and national policy-relevant discussions on issues pertinent to human development. Accordingly, the data in the Report require the highest standards of data quality, consistency, international comparability and transparency. The Human Development Report Office (HDRO) fully subscribes to the Principles governing international statistical activities.

The HDI was created to emphasize that people and their capabilities should be the ultimate criteria for assessing the development of a country, not economic growth alone. The HDI can also be used to question national policy choices, asking how two countries with the same level of GNI per capita can end up with different human development outcomes. These contrasts can stimulate debate about government policy priorities. The Human Development Index (HDI) is a summary measure of average achievement in key dimensions of human development: a long and healthy life, being knowledgeable and have a decent standard of living. The HDI is the geometric mean of normalized indices for each of the three dimensions.

The 2019 Global Multidimensional Poverty Index (MPI) data shed light on the number of people experiencing poverty at regional, national and subnational levels, and reveal inequalities across countries and among the poor themselves.Jointly developed by the United Nations Development Programme (UNDP) and the Oxford Poverty and Human Development Initiative (OPHI) at the University of Oxford, the 2019 global MPI offers data for 101 countries, covering 76 percent of the global population. The MPI provides a comprehensive and in-depth picture of global poverty – in all its dimensions – and monitors progress towards Sustainable Development Goal (SDG) 1 – to end poverty in all its forms. It also provides policymakers with the data to respond to the call of Target 1.2, which is to ‘reduce at least by half the proportion of men, women, and children of all ages living in poverty in all its dimensions according to national definition'.

The average for 2022 based on 27 countries was 0.903 points. The highest value was in Denmark: 0.952 points and the lowest value was in Bulgaria: 0.799 points. The indicator is available from 1980 to 2022. Below is a chart for all countries where data are available.

Iceland had the highest level of the Human Development Index (HDI) worldwide in 2022 after adjusting for inequality, with a value of 0.91. Its Nordic neighbors Norway and Denmark followed behind. Meanwhile, Switzerland topped the HDI not adjusted for inequality.

Countries from Natural Earth 50M scale data with a Human Development Index attribute for each of the following years: 1980, 1985, 1990, 1995, 2000, 2005, 2010, 2013, 2015, & 2017. The Human Development Index measures achievement in 3 areas of human development: long life, good education and income. Specifically, the index is computed using life expectancy at birth, Mean years of schooling, expected years of schooling, and gross national income (GNI) per capita (PPP $). The United Nations categorizes the HDI values into 4 groups. In 2013 these groups were defined by the following HDI values: Very High: 0.736 and higher High: 0.615 to 0.735 Medium: 0.494 to 0.614 Low: 0.493 and lower

In 2015 & 2017 these groups were defined by the following HDI values: Very High: 0.800 and higher High: 0.700 to 0.799 Medium: 0.550 to 0.699 Low: 0.549 and lower

Human Development Index attributes are from The World Bank: HDRO calculations based on data from UNDESA (2013a), Barro and Lee (2013), UNESCO Institute for Statistics (2013), UN Statistics Division(2014), World Bank (2014) and IMF (2014). 2015 & 2017 values source: HDRO calculations based on data from UNDESA (2017a), UNESCO Institute for Statistics (2018), United Nations Statistics Division (2018b), World Bank (2018b), Barro and Lee (2016) and IMF (2018).

Population data are from (1) United Nations Population Division. World Population Prospects, (2) United Nations Statistical Division. Population and Vital Statistics Report (various years), (3) Census reports and other statistical publications from national statistical offices, (4) Eurostat: Demographic Statistics, (5) Secretariat of the Pacific Community: Statistics and Demography Programme, and (6) U.S. Census Bureau: International Database.

The human development index (HDI) score of Russia slightly decreased in 2022, having reached 0.821. The score of 0.824, which was recorded in 2018 and 2019, was the highest observation since 1990. The HDI is a statistic that combines life-expectancy, education levels and GDP per capita. Countries with scores over 0.800 are considered to have very high levels of development, compared with countries that score lower. The HDI score of Russia declined between 1990 and 1995 before recovering from 2000 onwards.

The Human Development Index (HDI) of the United Kingdom has increased from 0.804 in 1990 to 0.940 by 2022, indicating that the UK has reached very high levels of human development. HDI is a statistic that combines life-expectancy, education levels and GDP per capita. Countries with scores over 0.800 are considered to have very high levels of development, compared with countries that score lower.

Ranked bottom and top five states, HLI, 2016.

Compared to other African countries, Seychelles scored the highest in the Human Development Index (HDI) in 2022. The country also ranked 67th globally, as one of the countries with a very high human development. This was followed by Mauritius, Libya, Egypt, and Tunisia, with scores ranging from 0.80 to 0.73 points. On the other hand, Central African Republic, South Sudan, and Somalia were among the countries in the region with the lowest index scores, indicating a low level of human development.

These test data files were used to debug the code used in the following study: "Is the Gini Coefficient Enough? A Microeconomic Data Decomposition Study."

List of test data: 1. it14ih.dta - household-level dataset for Italy. 2. it14ip.dta - person-level dataset for Italy. 3. mx16ih.dta - household-level dataset for Mexico. 4. mx16ip.dta - person-level dataset for Mexico. 5. us18ih.dta - household-level dataset for the USA. 6. us18ip.dta - person-level dataset for the USA.

All files can be used for testing/debugging of the following scripts: lis_theil.R, lis_scv.R, lis_theil_functions.R, lis_scv_functions.R.

These datasets were donloaded from the following website. https://www.lisdatacenter.org/resources/self-teaching/.

In 2023, Switzerland led the ranking of countries with the highest average wealth per adult, with approximately 709,600 U.S. dollars per person. Luxembourg was ranked second with an average wealth of around 607,500 U.S. dollars per adult, followed by Hong Kong SAR. However, the figures do not show the actual distribution of wealth. The Gini index shows wealth disparities in countries worldwide. Does wealth guarantee a longer life? As the old adage goes “money can’t buy you happiness”, yet wealth and income are continuously correlated to the quality of life of individuals in different countries around the world. While greater levels of wealth may not guarantee a higher quality life, it certainly increases an individual’s chances of having a longer one. Although they do not show the whole picture, life expectancy at birth is higher in the more wealthier world regions. Does money bring happiness? A number of the world’s happiest nations also feature in the list of those countries for which average income was highest. Finland, however, which was the happiest country worldwide in 2022, is missing in the list of top twenty countries with the highest wealth per adult. As such, the explanation for this may be the fact that the larger proportion of the population has access to a high income relative to global levels. Measures of quality of life Criticism of the use of income or wealth as a proxy for quality of life led to the creation of the United Nations’ Human Development Index. Although income is included within the index, it also has other factors taken into account such as health and education. As such, the countries with the highest human development index can be correlated to those with the highest income levels. That said, none of the above measures seek to assess the physical and mental environmental impact of a high quality of life sourced through high incomes. The happy planet index demonstrates that the inclusion of experienced well-being and ecological footprint in place of income and other proxies for quality of life results in many of the world’s materially poorer nations being included in the happiest.

Introduction

This study reproduces the results of the article Relationship of gender differences in preferences to economic development and gender equality (DOI: 10.1126/science.aas9899) and partially its supplementary material.

The code for the analysis can be found at the following GitHub page: https://github.com/scerioli/Global-Preferences-Survey

Preparation of the data

Data Collection, Cleaning, and Standardization

The data used in the Falk & Hermle 2018 is not fully available because of two reasons:

1. Data paywall: Some part of the data is not available for free. It requires to pay a fee to the Gallup to access them. This is the case for the additional data set that is used in the article, for instance, the one that contains the education level and the household income quintile. Check the website of the briq - Institute on Behavior & Inequality for more information on it.

2. Data used in study is not available online: This is what happened for the LogGDP p/c calculated in 2005 US dollars (which is not directly available online). We decided to calculate the LogGDP p/c in 2010 US dollars because it was easily available, which should not change the main findings of the article.

Global Preferences Survey

This data is protected by copyright and cannot be given to third parties.

To download the GPS data set, go to the website of the Global Preferences Survey in the section "downloads". There, choose the "Dataset" form and after filling it, we can download the data set.

Hint: The organisation can be also "private".

The following two relevant papers have to be also cited in all publications that make use of or refer in any kind to GPS dataset:

• Falk, A., Becker, A., Dohmen, T., Enke, B., Huffman, D., & Sunde, U. (2018). Global evidence on economic preferences. Quarterly Journal of Economics, 133 (4), 1645–1692.

• Falk, A., Becker, A., Dohmen, T. J., Huffman, D., & Sunde, U. (2016). The preference survey module: A validated instrument for measuring risk, time, and social preferences. IZA Discussion Paper No. 9674.

GDP per capita

From the website of the World Bank, one can access the data about the GDP per capita on a certain set of years. We took the GDP per capita (constant 2010 US$), made an average of the data from 2003 until 2012 for all the available countries, and matched the names of the countries with the ones from the GPS data set.

Gender Equality Index

The Gender Equality Index is composed of four main data sets.

• Time since women’s suffrage: Taken from the Inter-Parliamentary Union Website. We prepared the data in the following way. For several countries more than one date where provided (for example, the right to be elected and the right to vote). We use the last date when both vote and stand for election right were granted, with no other restrictions commented. Some counties were a colony or within union of the countries (for instance, Kazakhstan in Soviet Union). For these countries, the rights to vote and be elected might be technically granted two times within union and as independent state. In this case we kept the first date. It was difficult to decide on South Africa because its history shows the racism part very entangled with women's rights. We kept the latest date when also Black women could vote. For Nigeria, considered the distinctions between North and South, we decided to keep only the North data because, again, it was showing the completeness of the country and it was the last date. Note: USA data doesn't take into account that also up to 1964 black women couldn't vote (in general, Blacks couldn't vote up to that year). We didn’t keep this date, because it was not explicitly mentioned in the original data set. This is in contrast with other choices made, but it is important to reproduce exactly the results of the publication, and the USA is often easy to spot on the plots.

• UN Gender Inequality Index: Taken from the Human Development Report 2015. We kept only the table called "Gender Inequality Index".

• WEF Global Gender Gap: WEF Global Gender Gap Index Taken from the World Economic Forum Global Gender Gap Report 2015. For countries where data were missing, data was added from the World Economic Forum Global Gender Gap Report 2006. We modified some of the country names directly in the csv file, that is why we provide it as an input file.

• Ratio of female and male labour force participation: Average International Labour Organization estimates from 2003 to 2012 taken from the World Bank database (http://data.worldbank.org/indicator/SL.TLF.CACT.FM.ZS). Values were inverted to create an index of equality. We took the average for the period between 2004 and 2013.

In our extended analysis, we also involved the following index:

• United Nations Development Programme Gender Development Index taken from Human Development Reports 2020. Note that we have downloaded the two tables of the Human Development Index for males and females, and used the ratio of the two as a GDI index, as described in the report.

The catalog provides the information about GGP, Sustainable Development, Economic Dimension, Ecological Dimension and Social and Institutional Dimension indices of the 2006 year. Catalog compiled on the base of the data of annual report of such international organizations as the United Nations, Heritage Foundation, World Economic Forum, International Living and Yale University working group on the environment (USA), the Columbia University. The data file contains 97 lines.

In 2021, Barbados, Lithuania, and Mongolia topped the Gender Development Index (GDI) with index scores of 1.03. On the other hand, ot was only 0.5 in Yemen. The higher the value, the smaller the gap between women and men. The Gender Development Index (GDI) is basically a ratio of Human Development Index calculated seperately for women and men.

Since 2016, the global edition of the Sustainable Development Report (SDR) has provided the most up-to-date data to track and rank the performance of all UN member states on the SDGs. This year’s edition was written by a group of independent experts at the SDG Transformation Center, an initiative of the SDSN. It focuses on the UN Summit of the Future, with an opening chapter endorsed by 100+ global scientists and practitioners. The report also includes two thematic chapters, related to SDG 17 (Strengthen the means of implementation and revitalize the Global Partnership for Sustainable Development) and SDG 2 (End hunger, achieve food security and improved nutrition and promote sustainable agriculture).This year’s SDR highlights five key findings:On average, globally, only 16% of the SDG targets are on track to be achieved by 2030, with the remaining 84% demonstrating limited or a reversal of progress. At the global level, SDG progress has been stagnant since 2020, with SDG 2 (Zero Hunger), SDG11 (Sustainable Cities and Communities), SDG14 (Life Below Water), SDG15 (Life on Land) and SDG16 (Peace, Justice, and Strong Institutions) particularly off-track. Globally, the five SDG targets on which the highest proportion of countries show a reversal of progress since 2015 include: obesity rate (under SDG 2), press freedom (under SDG 16), the red list index (under SDG 15), sustainable nitrogen management (under SDG 2), and – due in a large part to the COVID-19 pandemic and other factors that may vary across countries – life expectancy at birth (under SDG 3). Goals and targets related to basic access to infrastructure and services, including SDG9 (Industry, Innovation, and Infrastructure), show slightly more positive trends, although progress remains too slow and uneven across countries.The pace of SDG progress varies significantly across country groups. Nordic countries continue to lead on SDG achievement, with BRICS demonstrating strong progress and poor and vulnerable nations lagging far behind. Similar to past years, European countries – notably Nordic countries – top the 2024 SDG Index. Finland ranks number 1 on the SDG Index, followed by Sweden (#2), Denmark (#3), Germany (#4), and France (#5). Yet, even these countries face significant challenges in achieving several SDGs. Average SDG progress in BRICS (Brazil, the Russian Federation, India, China, and South Africa) and BRICS+ (Egypt, Ethiopia, Iran, Saudi Arabia, and the United Arab Emirates) since 2015 has been faster than the world average. In addition, East and South Asia has emerged as the region that has made the most SDG progress since 2015. By contrast, the gap between the world average SDG Index and the performance of the poorest and most vulnerable countries, including Small Island Developing States (SIDS), has widened since 2015.Sustainable development remains a long-term investment challenge. Reforming the Global Financial Architecture is more urgent than ever. The world requires many essential public goods that far transcend the nation-state. Low-income countries (LICs) and lower-middle-income countries (LMICs) urgently need to gain access to affordable long-term capital so that they can invest at scale to achieve their sustainable development objectives. Mobilizing the necessary levels of finance will require new institutions, new forms of global financing — including global taxation —, and new priorities for global financing, such as investing in quality education for all. The report presents five complementary strategies to reform the Global Financial Architecture.Global challenges require global cooperation. Barbados ranks the highest in its commitment to UN-based multilateralism; the United States ranks last. As with the challenge of SDGs, strengthening multilateralism requires metrics and monitoring. The report’s new Index of countries’ support to UN-based multilateralism (UN-Mi) ranks countries based on their engagement with the UN system including treaty ratification, votes at the UN General Assembly, membership in UN organizations, participation in conflicts and militarization, use of unilateral sanctions and financial contributions to the UN. The five countries most committed to UN-based multilateralism are: Barbados (#1), Antigua and Barbuda (#2), Uruguay (#3), Mauritius (#4), and the Maldives (#5). By contrast, the United States (#193), Somalia (#192), South Sudan (#191), Israel (#190), and the Democratic Republic of Korea (#189) rank the lowest on the UN-Mi.SDG targets related to food and land systems are particularly off-track. The SDR presents new FABLE pathways to support sustainable food and land systems. Globally, 600 million people will still suffer from hunger by 2030, obesity is increasing globally, and greenhouse gas emissions from Agriculture, Forestry, and Other Land Use (AFOLU) represent almost a quarter of annual global GHG emissions. The new FABLE pathways brought together more than 80 local researchers across 22 countries to assess how 16 targets related to food security, climate mitigation, biodiversity conservation, and water quality could be achieved by 2030 and 2050. The continuation of current trends widens the gap with targets related to climate mitigation, biodiversity, and water quality. Pursuing commitments that have been already taken by countries would improve the situation, but they are still largely insufficient. Significant progress is possible but requires several dramatic changes: 1) avoid overconsumption beyond recommended levels and limit animal-based protein consumption with dietary shifts compatible with cultural preferences; 2) invest to foster productivity, particularly for products and areas with strong demand growth; and 3) implement inclusive, robust, and transparent monitoring systems to halt deforestation. Our sustainable pathway avoids up to 100 million hectares of deforestation by 2030 and 100 Gt CO2 emissions by 2050. Additional measures would be needed to avoid trade-offs with on-farm employment and water pollution due to excessive fertilizer application and ensure that no one is left behind, particularly to end hunger.About the AuthorsProf. Jeffrey SachsDirector, SDSN; Project Director of the SDG IndexJeffrey D. Sachs is a world-renowned professor of economics, leader in sustainable development, senior UN advisor, bestselling author, and syndicated columnist whose monthly newspaper columns appear in more than 100 countries. He is the co-recipient of the 2015 Blue Planet Prize, the leading global prize for environmental leadership, and many other international awards and honors. He has twice been named among Time magazine’s 100 most influential world leaders. He was called by the New York Times, “probably the most important economist in the world,” and by Time magazine, “the world’s best known economist.” A survey by The Economist in 2011 ranked Professor Sachs as amongst the world’s three most influential living economists of the first decade of the 21st century.Professor Sachs serves as the Director of the Center for Sustainable Development at Columbia University. He is University Professor at Columbia University, the university’s highest academic rank. During 2002 to 2016 he served as the Director of the Earth Institute. Sachs is Special Advisor to United Nations Secretary-General António Guterres on the Sustainable Development Goals, and previously advised UN Secretary-General Ban Ki-moon on both the Sustainable Development Goals and Millennium Development Goals and UN Secretary-General Kofi Annan on the Millennium Development Goals.Guillaume LafortuneDirector, SDSN Paris; Scientific Co-Director of the SDG IndexGuillaume Lafortune took up his duties as Director of SDSN Paris in January 2021. He joined SDSN in 2017 to coordinate the production of the Sustainable Development Report and other projects on SDG data and statistics.Previously, he has served as an economist at the Organisation for Economic Co-operation and Development (OECD) working on public governance reforms and statistics. He was one of the lead advisors for the production of the 2015 and 2017 flagship statistical report Government at a Glance. He also contributed to analytical work related to public sector efficiency, open government data and citizens’ satisfaction with public services. Earlier, Guillaume worked as an economist at the Ministry of Economic Development in the Government of Quebec (Canada). Guillaume holds a M.Sc in public administration from the National School of Public Administration (ENAP) in Montreal and a B.Sc in international economics from the University of Montreal.Contact: EmailGrayson FullerManager, SDG Index & Data team, SDSNGrayson Fuller is the manager of the SDG Index and of the team working on SDG data and statistics at SDSN. He is co-author of the Sustainable Development Report, for which he manages the data, coding, and statistical analyses. He also coordinates the production of regional and subnational editions of the SDG Index, in addition to other statistical reports, in collaboration with national governments, NGOs and international organizations such as the WHO, UNDP and the European Commission. Grayson received his Masters degree in Economic Development at Sciences Po Paris. He holds a Bachelors in Romance Languages and Latin American Studies from Harvard University, where he graduated cum laude. Grayson has lived in several Latin American countries and speaks English, Spanish, French, Portuguese and Italian. He enjoys playing the violin, rock-climbing and taking care of his numerous plants in his free time.Contact: EmailAbout the PublishersDublin University PressDublin University Press is Ireland’s oldest printing and publishing house with its origins in Trinity College Dublin in 1734. The mission of Dublin University Press is to benefit society through scholarly communication, education, research and discourse. To further this goal, the Press

The Human Well-being Index (HWBI) for U.S. counties is a set of nationally consistent demonstration results that may be used to characterize community well-being. This composite index was developed by U.S. EPA Office of Research and Development in support of its Sustainable and Healthy Communities (SHC) Research. It serves as an endpoint measure for use in the creation of community decision-support tools. The HWBI characterizes community conditions in the context of the flow of economic, social and ecological services. The index calculation approach used a nested-indicator design. A decade (2000-2010) of cultural, economic, and social data were drawn from publicly available sources (e.g., US Census, Bureau of Economic Analysis, American Community Survey, General Social Survey, Centers for Disease Control) to provide the foundation for well-being related indicators. Indicators are integrated into one of eight domains or sub-indices of well-being. These domains were synthesized to represent different aspects of well-being characteristics common across communities of all sizes. Service indicators reflect the availability of select socio-ecological services that influence well-being. Community decisions often result in changes in the flow of community services. Collectively, well-being and service measures provide a means to evaluate relationships between the availability of certain community services and overall well-being. Data used to generate service indicators were also collected from existing data sources. Detailed information about the attributes of the HWBI, its components and related service indicators are described in Indicators and Methods for Constructing a U.S. Human Well-being Index (HWBI) for Ecosystem Services Research (EPA/600/R-12/023. pp. 121) and Indicators and Methods for Evaluating Economic, Ecosystem and Social Services Provisioning (EPA/600/R-14/184. pp. 174), respectively.

Analysis of ‘Suicide Rates Overview 1985 to 2016 ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/russellyates88/suicide-rates-overview-1985-to-2016 on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Content

This compiled dataset pulled from four other datasets linked by time and place, and was built to find signals correlated to increased suicide rates among different cohorts globally, across the socio-economic spectrum.

References

United Nations Development Program. (2018). Human development index (HDI). Retrieved from http://hdr.undp.org/en/indicators/137506

World Bank. (2018). World development indicators: GDP (current US$) by country:1985 to 2016. Retrieved from http://databank.worldbank.org/data/source/world-development-indicators#

[Szamil]. (2017). Suicide in the Twenty-First Century [dataset]. Retrieved from https://www.kaggle.com/szamil/suicide-in-the-twenty-first-century/notebook

World Health Organization. (2018). Suicide prevention. Retrieved from http://www.who.int/mental_health/suicide-prevention/en/

Inspiration

Suicide Prevention.

--- Original source retains full ownership of the source dataset ---