In 2020, global gross domestic product declined by 6.7 percent as a result of the coronavirus (COVID-19) pandemic outbreak. In Latin America, overall GDP loss amounted to 8.5 percent.

The coronavirus (COVID-19) pandemic, has had a significant impact on the global economy. In 2020, global Gross Domestic Product (GDP) decreased by *** percent, while the forecast initially was *** percent GDP growth. As the world's governments are working towards a fast economic recovery, the GDP increased again in 2021 by *** percent. Global GDP increased by over ***** percent in 2022, but it is still not clear to what extent Russia's war in Ukraine will impact the global economy. Global GDP growth is expected to slow somewhat in 2023.

The impact of the coronavirus (COVID-19) pandemic had not only brought the global economy to a standstill but set the clock backwards on the developmental progress of several nations. While the rate of infection in India did not appear to be as high as in other countries, precautionary measures adopted dealt a severe blow to the country’s major industries - with the service sector bearing the largest brunt of estimated loss. Manufacturing made a swift recovery in the following months.

Impact of key industries

The loss incurred by enforcing a lockdown in the country was estimated at 26 billion U.S. dollars and a significant decline in GDP growth is also expected in the June quarter of 2020. With the imposition of restrictions on transportation worldwide, the trade sector also took a hit. Exports and imports saw a drastic decline in the country especially in the case of essential commodities such as petroleum, food crops, and coal, among others.

Effect on business in India

The growth rate of the automotive business in India was expected to be the most adversely affected followed by the power supply and IT sectors. Furthermore, many startups, small and medium enterprises in India expected to face issues of supply disruption and a decrease in demand. The effects of aid from the Narendra Modi-led government arguably did little to help in the face of a faltering economy.

IntroductionIn early March 2020, a SARS-CoV-2 outbreak occurred in the ski resort of Ischgl, in Austria. After an initial seroprevalence study in April 2020, a follow-up study in November 2020 showed persistence of high levels of seropositivity. The impacts of SARS-CoV-2 infections and non-pharmaceutical interventions required to reduce transmission were wide-ranging, including worsened mental and physical health and economic damage.MethodsWe analysed data from the Ischgl follow-up study. Of the 1,259 adults that participated in the Ischgl-1 study (Ischgl-1), 801 were followed-up. Seropositivity was defined using presence of binding and neutralizing antibodies at Ischgl-1. At follow-up, 7 months later (Ischgl-2), participants reported changes to self-rated mental and physical health, physical activity, alcohol consumption, smoking and economic status. Changes were compared by serological status, using multivariable logistic and multinomial regression models, where appropriate, and adjusting for factors including age, sex, and morbidity.Results1 in 2 participants reported experiencing a moderate or severe impact of the pandemic. One fifth of participants reported a worsening in their mental health from November 2019 to November 2020; women and participants aged ≥35 to

To create the dataset, the top 10 countries leading in the incidence of COVID-19 in the world were selected as of October 22, 2020 (on the eve of the second full of pandemics), which are presented in the Global 500 ranking for 2020: USA, India, Brazil, Russia, Spain, France and Mexico. For each of these countries, no more than 10 of the largest transnational corporations included in the Global 500 rating for 2020 and 2019 were selected separately. The arithmetic averages were calculated and the change (increase) in indicators such as profitability and profitability of enterprises, their ranking position (competitiveness), asset value and number of employees. The arithmetic mean values of these indicators for all countries of the sample were found, characterizing the situation in international entrepreneurship as a whole in the context of the COVID-19 crisis in 2020 on the eve of the second wave of the pandemic. The data is collected in a general Microsoft Excel table. Dataset is a unique database that combines COVID-19 statistics and entrepreneurship statistics. The dataset is flexible data that can be supplemented with data from other countries and newer statistics on the COVID-19 pandemic. Due to the fact that the data in the dataset are not ready-made numbers, but formulas, when adding and / or changing the values in the original table at the beginning of the dataset, most of the subsequent tables will be automatically recalculated and the graphs will be updated. This allows the dataset to be used not just as an array of data, but as an analytical tool for automating scientific research on the impact of the COVID-19 pandemic and crisis on international entrepreneurship. The dataset includes not only tabular data, but also charts that provide data visualization. The dataset contains not only actual, but also forecast data on morbidity and mortality from COVID-19 for the period of the second wave of the pandemic in 2020. The forecasts are presented in the form of a normal distribution of predicted values and the probability of their occurrence in practice. This allows for a broad scenario analysis of the impact of the COVID-19 pandemic and crisis on international entrepreneurship, substituting various predicted morbidity and mortality rates in risk assessment tables and obtaining automatically calculated consequences (changes) on the characteristics of international entrepreneurship. It is also possible to substitute the actual values identified in the process and following the results of the second wave of the pandemic to check the reliability of pre-made forecasts and conduct a plan-fact analysis. The dataset contains not only the numerical values of the initial and predicted values of the set of studied indicators, but also their qualitative interpretation, reflecting the presence and level of risks of a pandemic and COVID-19 crisis for international entrepreneurship.

COVID-19 and COVID-related decisions are having significant impacts on children and adults vulnerable to, and already experiencing, the crime of forced marriage. This mixed-methods project aimed to chart and understand this impact, inform evaluation of the UK's response to COVID-19, and shape on-going policy regarding the UK's pandemic response. This data includes the questions for and responses to a survey of staff at a national helpline for victims of forced marriage. It also includes visualisations of the data made for the published report.COVID-19 and COVID-related decisions are having significant impacts on children and adults vulnerable to, and already experiencing, the crime of forced marriage. Our mixed-methods project will chart and understand this impact, inform evaluation of the UK's response to COVID-19, and shape on-going policy regarding the UK's pandemic response. We consider the uneven economic and social impact of the pandemic, and the ethical dimensions of unequal impacts of COVID-related decision-making, on this vulnerable group, and seek to impact how civil society and the voluntary sector support vulnerable people. The government's Forced Marriage Unit (FMU) and the charity Karma Nirvana (KN) (which provides a national forced marriage helpline) have warned about the significant impact of the pandemic on forced marriage in the UK. We designed this project with both organisations, and will work with them to analyse quantitative and qualitative data about the impact of COVID-19 on those at risk of, or experiencing, forced marriage; and to record and analyse the challenges faced in the pandemic, evaluate the efficacy of mitigation strategies, and formulate new policies and practises for protection and response. Within the first 6 months, we will have co-created an accurate account of the economic and social impact of COVID-19 and COVID-related decision-making on victims of forced marriage, and the ethical implications of unequal impacts. We will then continue to chart the changing risk environment, while co-developing policy reports and recommendations for the UK government (including FMU), NGO practice responses (including KN), and other stakeholders, to improve the on-going response to COVID-19 and build community resilience. An anonymous, online survey of staff working as call-handlers at a national helpine (7 people). We recorded this data via MS Forms, and made visualisations from some of the answers in Excel. A note about cleaning (a repeated response) is included as a comment in the deposited data file.

Équipement ou fournitures de protection individuelle que les entreprises ont besoin ou s'attendent à avoir besoin une fois les mesures de distanciation physique levées, selon le code du Système de classification des industries de l'Amérique du Nord (SCIAN), l'effectif de l'entreprise, le type d'entreprise, activités commerciales et le propriétaire majoritaire.

Publicly available geocoded social determinants of health and mobility datasets used in the analysis of "Chronic Acid Suppression and Social Determinants of COVID-19 Infection".These datasets are required for the analytical workflow shared on Github which demonstrates how the analysis in the manuscript was done using randomly generated samples to protect patient privacy.zcta_county_rel_10.txt - Population and housing density from the 2010 decennial census. Obtained from: https://www2.census.gov/geo/docs/maps-data/data/rel/zcta_county_rel_10.txtcre-2018-a11.csv - Community Resilience Estimates which is is the capacity of individuals and households to absorb, endure, and recover from the health, social, and economic impacts of a disaster such as a hurricane or pandemic. Data obtained from: https://www.census.gov/data/experimental-data-products/community-resilience-estimates.htmlzcta_tract_rel_10.txt - Relationship between ZCTA and US Census tracts (used to map census tracts to ZCTA). Data obtained from: https://www.census.gov/geographies/reference-files/time-series/geo/relationship-files.html#par_textimage_674173622mask-use-by-county.txt - Mask Use By County comes from a large number of interviews conducted online by the global data and survey firm Dynata at the request of The New York Times. The firm asked a question about mask use to obtain 250,000 survey responses between July 2 and July 14, enough data to provide estimates more detailed than the state level. Data obtained from: https://github.com/nytimes/covid-19-data/tree/master/mask-usemobility_report_US.txt - Google mobility report which charts movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential. Data obtained from: https://github.com/ActiveConclusion/COVID19_mobility/blob/master/google_reports/mobility_report_US.csvACS2015_zctaallvars.csv - Social Deprivation Index is a composite measure of area level deprivation based on seven demographic characteristics collected in the American Community Survey (https://www.census.gov/programs-surveys/acs/) and used to quantify the socio-economic variation in health outcomes. Factors are: Income, Education, Employment, Housing, Household Characteristics, Transportation, Demographics. Data obtained from: https://www.graham-center.org/rgc/maps-data-tools/sdi/social-deprivation-index.html

This data table covers key mental health, economic and education indicators at the provincial and territorial levels of geography to better understand the different ways that remote learning approaches and temporarily closed schools have affected children and youth during the COVID-19 pandemic.

United States Leading Economic Index: MoM data was reported at -0.300 % in Feb 2025. This records a decrease from the previous number of -0.200 % for Jan 2025. United States Leading Economic Index: MoM data is updated monthly, averaging 0.300 % from Feb 1959 (Median) to Feb 2025, with 793 observations. The data reached an all-time high of 2.200 % in Jun 2020 and a record low of -5.500 % in Apr 2020. United States Leading Economic Index: MoM data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.The Conference Board: Leading Economic Index. [COVID-19-IMPACT]

The employment and unemployment indicator shows several data points. The first figure is the number of people in the labor force, which includes the number of people who are either working or looking for work. The second two figures, the number of people who are employed and the number of people who are unemployed, are the two subcategories of the labor force. The unemployment rate is a calculation of the number of people who are in the labor force and unemployed as a percentage of the total number of people in the labor force.

The unemployment rate does not include people who are not employed and not in the labor force. This includes adults who are neither working nor looking for work. For example, full-time students may choose not to seek any employment during their college career, and are thus not considered in the unemployment rate. Stay-at-home parents and other caregivers are also considered outside of the labor force, and therefore outside the scope of the unemployment rate.

The unemployment rate is a key economic indicator, and is illustrative of economic conditions in the county at the individual scale.

There are additional considerations to the unemployment rate. Because it does not count those who are outside the labor force, it can exclude individuals who were looking for a job previously, but have since given up. The impact of this on the overall unemployment rate is difficult to quantify, but it is important to note because it shows that no statistic is perfect.

The unemployment rates for Champaign County, the City of Champaign, and the City of Urbana are extremely similar between 2000 and 2023.

All three areas saw a dramatic increase in the unemployment rate between 2006 and 2009. The unemployment rates for all three areas decreased overall between 2010 and 2019. However, the unemployment rate in all three areas rose sharply in 2020 due to the effects of the COVID-19 pandemic. The unemployment rate in all three areas dropped again in 2021 as pandemic restrictions were removed, and were almost back to 2019 rates in 2022. However, the unemployment rate in all three areas rose slightly from 2022 to 2023.

This data is sourced from the Illinois Department of Employment Security’s Local Area Unemployment Statistics (LAUS), and from the U.S. Bureau of Labor Statistics.

Sources: Illinois Department of Employment Security, Local Area Unemployment Statistics (LAUS); U.S. Bureau of Labor Statistics.

India's quarterly GDP was estimated to grow by 8.4 percent in the second quarter of financial year 2022 compared to the same quarter in the previous fiscal year. While continuing to be a positive change, it was a significant reduction from the performance during the first quarter of fiscal year 2022 when GDP growth peaked by 20 percent.

Cost of the pandemic

As a result of the various lockdowns enforced since the onset of the coronavirus pandemic in 2020, the Indian economy has been reeling from a multibillion dollar setback. The GDP contribution as well as the employment rate among most major sectors, especially services and trade, had taken a hit. The agriculture sector was an exception, having experienced positive changes on both these fronts.

A slowly recovering economy

With the outbreak of the second wave of the pandemic in March 2021, the government redirected financial support to boost India’s vaccination campaign. As of February 2022, over a billion vaccine doses had been administered across the country. Furthermore, inflation within the country was expected to decline 2021 onwards. However, the stagnation of employment continued to remain a matter of concern with protests erupting across different states in 2022.

In the first quarter of 2020, global stock indices posted substantial losses that were triggered by the outbreak of COVID-19. The period from March 6 to 18 was particularly dramatic, with several stock indices losing more than ** percent of their value. Worldwide panic hits markets From the United States to the United Kingdom, stock market indices suffered steep falls as the coronavirus pandemic created economic uncertainty. The Nasdaq 100 and S&P 500 are two indices that track company performance in the United States, and both lost value as lockdowns were introduced in the country. European markets also recorded significant slumps, which triggered panic selling among investors. The FTSE 100 – the leading share index of companies in the UK – plunged by as much as ** percent in the opening weeks of March 2020. Is it time to invest in tech stocks? The S&P 500 is regarded as the best representation of the U.S. economy because it includes more companies from the leading industries. However, helped in no small part by its focus on tech companies, the Nasdaq 100 has risen in popularity and seen remarkable growth in recent years. Global demand for digital technologies has increased further due to the coronavirus, with remote working and online shopping becoming part of the new normal. As a result, more investors are likely to switch to the tech stocks listed on the Nasdaq 100.

As of August 2020, the S&P 500 index had lost ** percent of its value due to the COVID-19 pandemic. However, the Great Crash, which began with Black Tuesday, remains the most significant loss in value in its history. That market crash lasted for 300 months and wiped ** percent off the index value.

The unprecedented restrictions introduced by the government to contain the spread of COVID-19 over the course of 2020 had an extremely severe impact on the Italian economy. As the chart shows, there were companies in every industry that were forced to be only partially open at best. In particular, the most impacted sector was the one providing services related to arts, sports, entertainment, and leisure time. As much as ** percent of enterprises operating in this industry were closed as of the Fall 2020, waiting to be allowed to open again. About ***** percent of them were closed and did not foresee to ever open again.

As of May 2022, the unemployment rate in India was recorded at nearly ***** percent, a decrease from the previous month. While the unemployment rate had significantly declined over the course of 2021 since having peaked in **********, the breakout of new coronavirus variants coupled with recurring lockdowns resulted in a fluctuating trend of unemployment gripping the nation. The trickle-down effect Between February and April 2020, the share of households that experienced a fall in income shot up to nearly ** percent. Inflation rates on goods and services including food products and fuel were expected to rise later this year. Social distancing resulted in job losses, specifically those within Indian society’s lower economic strata. Several households terminated domestic help services – essentially an unorganized monthly-paying job. Most Indians spent a large amount of time engaging in household chores themselves, making it the most widely practiced lockdown activity. Aid from the Pradhan Mantri Garib Kalyan Yojana The most devastating impact of the virus and the lockdown had been on the economically backward classes, with limited access to proper healthcare and other resources. As a result the government launched various programs and campaigns to help sustain such households. Under the Pradhan Mantri Garib Kalyan Yojana, *** billion Indian rupees were accrued and provided to around 331 million beneficiaries that included women, construction workers, farmers, and senior citizens. More aid was announced in mid-May, to mainly support small businesses through the crisis.

The Federal Reserve's balance sheet has undergone significant changes since 2007, reflecting its response to major economic crises. From a modest *** trillion U.S. dollars at the end of 2007, it ballooned to approximately *** trillion U.S. dollars by August 2025. This dramatic expansion, particularly during the 2008 financial crisis and the COVID-19 pandemic - both of which resulted in negative annual GDP growth in the U.S. - showcases the Fed's crucial role in stabilizing the economy through expansionary monetary policies. Impact on inflation and interest rates The Fed's expansionary measures, while aimed at stimulating economic growth, have had notable effects on inflation and interest rates. Following the quantitative easing in 2020, inflation in the United States reached ***** percent in 2022, the highest since 1991. However, by July 2025, inflation had declined to *** percent. Concurrently, the Federal Reserve implemented a series of interest rate hikes, with the rate peaking at **** percent in August 2023, before the first rate cut since September 2021 occurred in September 2024. Financial implications for the Federal Reserve The expansion of the Fed's balance sheet and subsequent interest rate hikes have had significant financial implications. In 2023, the Fed reported a negative net income of ***** billion U.S. dollars, a stark contrast to the ***** billion U.S. dollars profit in 2022. This unprecedented shift was primarily due to rapidly rising interest rates, which caused the Fed's interest expenses to soar to over *** billion U.S. dollars in 2023. Despite this, the Fed's net interest income on securities acquired through open market operations reached a record high of ****** billion U.S. dollars in the same year.

The Standard & Poor’s (S&P) 500 Index is an index of 500 leading publicly traded companies in the United States. In 2021, the index value closed at ******** points, which was the second highest value on record despite the economic effects of the global coronavirus (COVID-19) pandemic. In 2023, the index values closed at ********, the highest value ever recorded. What is the S&P 500? The S&P 500 was established in 1860 and expanded to its present form of 500 stocks in 1957. It tracks the price of stocks on the major stock exchanges in the United States, distilling their performance down to a single number that investors can use as a snapshot of the economy’s performance at a given moment. This snapshot can be explored further. For example, the index can be examined by industry sector, which gives a more detailed illustration of the economy. Other measures Being a stock market index, the S&P 500 only measures equities performance. In addition to other stock market indices, analysts will look to other indicators such as GDP growth, unemployment rates, and projected inflation. Similarly, since these indicators say something about the economic future, stock market investors will use these indicators to speculate on the stocks in the S&P 500.

United States Coincident Economic Index: MoM data was reported at 0.300 % in Feb 2025. This records an increase from the previous number of 0.200 % for Jan 2025. United States Coincident Economic Index: MoM data is updated monthly, averaging 0.200 % from Feb 1959 (Median) to Feb 2025, with 793 observations. The data reached an all-time high of 4.400 % in Jun 2020 and a record low of -10.800 % in Apr 2020. United States Coincident Economic Index: MoM data remains active status in CEIC and is reported by The Conference Board. The data is categorized under Global Database’s United States – Table US.The Conference Board: Leading Economic Index. [COVID-19-IMPACT]

Business Survey: COVID-19 Effect: SO: Services: RE: High Risk data was reported at 0.000 % in 11 Aug 2021. This stayed constant from the previous number of 0.000 % for 09 Jun 2021. Business Survey: COVID-19 Effect: SO: Services: RE: High Risk data is updated daily, averaging 0.000 % from May 2020 to 11 Aug 2021, with 17 observations. The data reached an all-time high of 4.000 % in 24 Jun 2020 and a record low of 0.000 % in 11 Aug 2021. Business Survey: COVID-19 Effect: SO: Services: RE: High Risk data remains active status in CEIC and is reported by National Institute of Economic Research. The data is categorized under Global Database’s Sweden – Table SE.S009: Business Survey: COVID-19 Effect: Seizing Operations (Discontinued).