Based on the number of deaths of despair in 2018 and projected levels of unemployment from 2020 to 2029, it is estimated that the additional number of deaths in 2023 could range from 2,017 to 21,457 depending on the rate of economic recovery after the COVID-19 recession. This statistic shows the possible additional deaths of despair following the COVID-19 recession for select economic scenarios, given a 1.6 percent increase in unemployment, in the United States from 2020 to 2029.

This table contains data on the percent of the population in the labor force who are unemployed (unemployment rate), for California, its regions, counties, county divisions, cities/towns, and census tracts. Data is from the Local Area Unemployment Statistics (LAUS), Bureau of Labor Statistics (BLS), and the U.S. Census Bureau, American Community Survey (ACS). The table is part of a series of indicators in the Healthy Communities Data and Indicators Project of the Office of Health Equity. Unemployment is associated with higher rates of self-reported poor health, long-term illnesses, higher incidence of risky health behaviors (alcoholism, smoking), and increased mortality. Various explanations have been proposed for the link between poor health and unemployment; for example, economic deprivation that results in reduced access to essential goods and services. Another explanation is that unemployment causes the loss of latent functions (social contact, social status, time structure and personal identity) which can result in stigma, isolation and loss of self-worth. More information about the data table and a data dictionary can be found in the About/Attachments section.

This scatter chart displays unemployment (% of total labor force) against death rate (per 1,000 people) and is filtered where the region is Southern Africa. The data is about countries per year.

This scatter chart displays suicide mortality rate (per 100,000 population) against unemployment (% of total labor force) and is filtered where the country is Angola. The data is about countries per year.

Column 3 reports point estimates of b in Eq 1 and its standard errors (in parenthesis) both multiplied per 100.***, **, and * mean statistical significance at the 1, 5 and 10 percent level, respectively.In column 1 and 2 are point estimates of b8089 * 100 and b9004 * 100 in Eq 2 and their standard errors (in parenthesis). % represents the percent change in the outcome for a one percentage point increase in the state unemployment rate at the time of conception. In square brackets are the P-values of the test of equality of bw and bb in Eq 3 (column 3) and P-values of the test of equality of b8089w and b8089b, and equality between b9004w and b9004b in Eq 4 (columns 1 and 2, respectively). Standard errors are clustered at the state levelPrenatal Care.

The unemployment rate in Sweden decreased steadily from 2010 after the financial crisis the previous years. However, the employment rate increased since 2018, reaching nearly nine percent in 2021 after the outbreak of COVID-19 in 2020. In 2023, it stood at 7.7 percent. The unemployment rate among women was slightly higher than among men in 2022. Unemployment benefits As unemployed in Sweden, there is a possibility to receive unemployment benefits (A-kassa). To receive these benefits, the unemployed person needs to be registered at the Swedish Public Employment Service, needs to be ready to take on a job at any time, and needs to have had a job for at least six months during the last year. In 2022, nearly 228,000 individuals in Sweden received these benefits. The COVID-19 pandemic As the novel coronavirus (COVID-19) started spreading in Sweden in February 2020, the country's health authorities chose a milder way than most other European countries, allowing most stores, including cafés and restaurants to remain open. Ultimately, the government's handling of the pandemic was criticized as the country registered an unusually high number of deaths during the first weeks of the pandemic. Moreover, the country's economy was hit hard, with economic decline and layoffs.

Source: Anderson et al., 2001 and CDC “Report on infant mortality for the United States for 1990”. Columns 4 and 5 report the ranking of the selected causes of death for years 1990 and 2000.Main Causes of Neonatal and Postneonatal Mortality 1990 and 2000.

Given the lack of potential vaccines and effective medications, non-pharmaceutical interventions are the major option to curtail the spread of COVID-19. An accurate estimate of the potential impact of different non-pharmaceutical measures on containing, and identify risk factors influencing the spread of COVID-19 is crucial for planning the most effective interventions to curb the spread of COVID-19 and to reduce the deaths. Additive model-based bivariate causal discovery for scalar factors and multivariate Granger causality tests for time series factors are applied to the surveillance data of lab-confirmed Covid-19 cases in the US, University of Maryland Data (UMD) data, and Google mobility data from March 5, 2020 to August 25, 2020 in order to evaluate the contributions of social-biological factors, economics, the Google mobility indexes, and the rate of the virus test to the number of the new cases and number of deaths from COVID-19. We found that active cases/1,000 people, workplaces, tests done/1,000 people, imported COVID-19 cases, unemployment rate and unemployment claims/1,000 people, mobility trends for places of residence (residential), retail and test capacity were the popular significant risk factor for the new cases of COVID-19, and that active cases/1,000 people, workplaces, residential, unemployment rate, imported COVID cases, unemployment claims/1,000 people, transit stations, mobility trends (transit), tests done/1,000 people, grocery, testing capacity, retail, percentage of change in consumption, percentage of working from home were the popular significant risk factor for the deaths of COVID-19. We observed that no metrics showed significant evidence in mitigating the COVID-19 epidemic in FL and only a few metrics showed evidence in reducing the number of new cases of COVID-19 in AZ, NY and TX. Our results showed that the majority of non-pharmaceutical interventions had a large effect on slowing the transmission and reducing deaths, and that health interventions were still needed to contain COVID-19.

Social and economic figures for 67 large West German cities. The data aggregated at city level have been collected for most topics over several years, but not necessarily over the entire reference time period.

Topics: 1. Situation of the city: surface area of the city; fringe location in the Federal Republic.

1. Residential population: total residential population; German and foreign residential population.

2. Population movement:live births; deaths; influx; departures; birth rate; death rate; population shifts; divorce rate; migration rate; illegitimate births.

3. Education figures: school degrees; occupational degrees; university degrees.

4. Wage and income: number of taxpayers in the various tax classes as well as municipality income tax revenue in the respective classes; calculated income figures, such as e.g. inequality of income distribution, mean income or mean wage of employees as well as standard deviation of these figures; GINI index.

5. Gross domestic product and gross product: gross product altogether; gross product organized according to area of business; gross domestic product; employees in the economic sectors.

6. Taxes and debts: debt per resident; income tax and business tax to which the municipality is entitled; municipality tax potential and indicators for municipality economic strength.

7. Debt repayment and management expenditures: debt repayment, interest expenditures, management expenditures and personnel expenditures.

8. From the ´BUNTE´ City Test of 1979 based on 100 respondents per city averages of satisfaction were calculated. satisfaction with: central location of the city, the number of green areas, historical buildings, the number of high-rises, the variety of the citizens, openness to the world, the dialect spoken, the sociability, the density of the traffic network, the OEPNV prices {local public passenger transport}, the supply of public transportation, provision with culture, the selection for consumers, the climate, clean air, noise pollution, the leisure selection, real estate prices, the supply of residences, one´s own payment, the job market selection, the distance from work, the number of one´s friends, contact opportunities, receptiveness of the neighbors, local recreational areas, sport opportunities and the selection of further education possibilities.

9. Traffic and economy: airport and Intercity connection; number of kilometers of subway available, kilometers of streetcar, and kilometers of bus lines per resident; car rate; index of traffic quality; commuters; property prices; prices for one´s own home; purchasing power.

10. Crime: recorded total crime and classification according to armed robbery, theft from living-rooms, of automobiles as well as from motor vehicles, robberies and purse snatching; classification according to young or adult suspects with these crimes; crime stress figures. 12. Welfare: welfare recipients and social expenditures; proportion of welfare recipients in the total population and classification according to German and foreign recipients; aid with livelihood; expenditures according to the youth welfare law; kindergarten openings; culture expenditures per resident. 13. Foreigners: proportion of foreigners in the residential population.

11. Students: number of German students and total number of students; proportion of students in the residential population.

12. Unemployed: unemployment rate; unemployed according to employment office districts and employment office departments.

13. Places of work: workers employed in companies, organized according to area of business.

14. Government employees: full-time, part-time and total government employees of federal government, states and municipalities as well as differentiated according to workers, employees, civil servants and judges.

15. Employees covered by social security according to education and branch of economy: proportion of various education levels in the individual branches of the economy.

The statistic shows the unemployment rate in Japan from 1999 to 2023. In 2023, the unemployment rate in Japan was at about 2.6 percent. Employment and the economy in Japan Japan is one of the leading countries when it comes to economic key factors; its unemployment rate, for example, is lower than that of other major industrial and emerging countries. The Japanese work ethic is well-known worldwide, it is synonymous with a strong devotion to the company and to the task at hand; competition among co-workers and loyalty to the company are common and encouraged, working hours and over-time work are said to be excessive. The Japanese language even has its own term for sudden death from being overworked – “Karoshi”. After the devastating effects of World War II, Japan managed to recover economically and even earn a prominent role among other leading economic powers – a fact which is probably partly due to this attitude towards work and employment. Today, Japan is among the leading import countries worldwide, as well as the leading export countries worldwide. Additionally, Japan is one of the 20 countries with the largest proportion of the global domestic product, and also among the 20 countries with the largest gross domestic product per capita, even though it is also ranked tenth among the leading countries with the largest population.

Graph and download economic data for Unemployment Rate in Clarke County, AL (ALCLAR5URN) from Jan 1990 to Jan 2025 about Clarke County, AL; AL; unemployment; rate; and USA.

In 2024, six percent of the Black or African-American population in the United States were unemployed, the highest unemployment rate of any ethnicity. In 2024, the national unemployment rate stood at four percent.

This dataset is about countries per year and is filtered where the country includes Liberia, featuring 4 columns: country, date, death rate, and unemployment. The preview is ordered by date (descending).

This dataset is about countries in Singapore per year, featuring 4 columns: country, date, death rate, and unemployment. The preview is ordered by date (descending).

This statistic shows the unemployment rate in Malaysia from 1999 to 2023. In 2023, the unemployment rate in Malaysia was at approximately 3.87 percent. Unemployment in Malaysia Malaysia’s unemployment is relatively low and stable at around three percent which means the population is experiencing close to full employment. The country reached its lowest level of unemployment in 2014, with a rate of 2.85 percent. Malaysia’s vibrant economy is considered one of the strongest in South_East Asia. Together with years of political stability, it has been supporting such a low unemployment rate and good growth rates each year. Industry has been a strong contributor to GDP and currently provides around 30 percent of employment opportunities. But even more - about 50 percent - of GDP is generated by the services sector. Given the country’s strong and growing economy, average GDP per capita is growing at increasing rates as well. However, despite these positive statistics, news reports state that the number of job seekers and those unemployed – the three percent - are generally young people, both graduates and non-graduates, who have had trouble entering the job market. Because of this, the Malaysian government is encouraging companies to open up employment opportunities specifically to young adults. The favorable economic climate should help. Yet, there have also been some complaints about underemployment and gender discrimination within the country.

Graph and download economic data for Unemployment Rate in Hillsdale County, MI (MIHILL9URN) from Jan 1990 to Dec 2024 about Hillsdale County, MI; MI; unemployment; rate; and USA.

The Swedish income panel was originally set up in the beginning of the 90s to make studies of how immigrants assimilate in the Swedish labour market possible. It consists of large samples of foreign-born and Swedish-born persons. Income information from registers is added for nearly 40 years. In addition income information relating to spouses is also available as well as for a subset of mothers and fathers. This makes it possible to construct measures of household income based on a relatively narrow definition. However, starting in 1998 there is also more information making it possible to include children over 18 and their incomes in the family. By matching with some different additional registers information has been added for people who have been unemployed or involved in labour market programmes during the 90s, on causes of deaths for people who have deceased since 1978 and on recent arrived immigrants from various origins. It has turned out that the data-base is quite useful for analysing research-questions other than originally motivating construction of the panel. The panel has been used for cross country comparisons of immigrants in the labour market and to analyse income mobility for different breakdowns of the population, and analyses the development in cohort income. There have been analyses of social assistance receipt among immigrants as well as studies of intergeneration mobility of income, the labour market situation of young immigrants and the second generation of immigrants. On-going work includes evaluation of labour market training programmes and studies of early retirement among immigrants. Planned work includes studies of the economic transition from child to adulthood during the 80s and 90s as well as studies of how frequent immigrant children are subject to measures under the Social Service Act and the Care of Youth Persons Act. The potentials of the Swedish Income Panel can be understood if one compares it with better known income-panels in other countries. For example SWIP covers more years and has a larger sample than the German Socio-Economic Panel (GSOEP). On the other hand, the fact that information is obtained from registers only makes this Swedish panel less rich in variables. There are striking parallels between the Gothenburg Income Panel and the labour market panel at the Centre for Labour Market and Social Research in Aarhus for the Danish population.

This dataset is about countries in Somalia per year, featuring 4 columns: country, date, death rate, and unemployment. The preview is ordered by date (descending).

countries capital city Riga. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

This database contains cross-sectional data for all municipalities in the Netherlands in two separate periods 1877-1879 and 1908-1910. Per municipality a wide variety of data is given for the two short periods. It contains demographic data: population size, infant mortality, stillbirths, births, male births, illegitimate births, and migration figures. Religious data: absolute numbers of adherents per religion. Medical data: numbers per medical personnel category and various vaccination figures. Furthermore it has participation data: unemployment rate, percentage employed in agriculture, labor participation of women, and the number of eligible voters in municipal elections. Finally it contains data on the water pipe supply, economic region, and the soil type of the municipality. It is the basis for the historical-demographic research article "Regional differentials in infant mortality of the Netherlands in the late 19th and early 20th century: Evaluating the importance of demographic, sociocultural, environmental, and medical factors". It contains the original Excel Database (with all relevant data), a STATA do-file (which 'cleans' the data), spatial datasets, and associated spatial weight files.

It also includes data derived from 'Mourits, Rick J; Boonstra, Onno; Knippenberg, Hans; Hofstee, Evert W; Zijdeman, Richard L, 2016, "Historische Database Nederlandse Gemeenten", https://hdl.handle.net/10622/RPBVK4, IISH Data Collection, V5' and the (adjusted) shapefiles are from 'Boonstra, O.W.A. (2007). NLGis shapefiles. DANS. https://doi.org/10.17026/dans-xb9-t677'. Make sure to cite both when using this database!