The number of small and medium-sized enterprises in the United States was forecast to continuously decrease between 2024 and 2029 by in total 6.7 thousand enterprises (-2.24 percent). After the fourteenth consecutive decreasing year, the number is estimated to reach 291.94 thousand enterprises and therefore a new minimum in 2029. According to the OECD an enterprise is defined as the smallest combination of legal units, which is an organisational unit producing services or goods, that benefits from a degree of autonomy with regards to the allocation of resources and decision making. Shown here are small and medium-sized enterprises, which are defined as companies with 1-249 employees.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in more than 150 countries and regions worldwide. All input data are sourced from international institutions, national statistical offices, and trade associations. All data has been are processed to generate comparable datasets (see supplementary notes under details for more information).

COVID-19 hit firms by surprise. In a high frequency, representative panel of German firms, the business outlook declined and business uncertainty increased only at the time when the spread of the COVID-19 pandemic led to domestic policy changes: The announcement of nation-wide school closures on March 13 was followed by the largest change in business perceptions by far. In contrast, the data provides no evidence for the relevance of other potential sources of information on business perceptions: Firms did not learn from foreign policy measures, even if they relied on inputs from China or Italy. The local, county-level spread of COVID-19 cases affected expectations and uncertainty, albeit to a much lesser extent than the domestic policy changes.

The Research and Development Survey (RANDS) is a platform designed for conducting survey question evaluation and statistical research. RANDS is an ongoing series of surveys from probability-sampled commercial survey panels used for methodological research at the National Center for Health Statistics (NCHS). RANDS estimates are generated using an experimental approach that differs from the survey design approaches generally used by NCHS, including possible biases from different response patterns and sampling frames as well as increased variability from lower sample sizes. Use of the RANDS platform allows NCHS to produce more timely data than would be possible using traditional data collection methods. RANDS is not designed to replace NCHS’ higher quality, core data collections. Below are experimental estimates of loss of work due to illness with coronavirus for three rounds of RANDS during COVID-19. Data collection for the three rounds of RANDS during COVID-19 occurred between June 9, 2020 and July 6, 2020, August 3, 2020 and August 20, 2020, and May 17, 2021 and June 30, 2021. Information needed to interpret these estimates can be found in the Technical Notes. RANDS during COVID-19 included a question about the inability to work due to being sick or having a family member sick with COVID-19. The National Health Interview Survey, conducted by NCHS, is the source for high-quality data to monitor work-loss days and work limitations in the United States. For example, in 2018, 42.7% of adults aged 18 and over missed at least 1 day of work in the previous year due to illness or injury and 9.3% of adults aged 18 to 69 were limited in their ability to work or unable to work due to physical, mental, or emotional problems. The experimental estimates on this page are derived from RANDS during COVID-19 and show the percentage of U.S. adults who did not work for pay at a job or business, at any point, in the previous week because either they or someone in their family was sick with COVID-19. Technical Notes: https://www.cdc.gov/nchs/covid19/rands/work.htm#limitations

This page is no longer updated. It has been superseded by the Business insights and impacts on the UK economy dataset page (see link in Notices). It contains comprehensive weighted datasets for Wave 7 onwards. All future BICS datasets will be available there. The datasets on this page include mainly unweighted responses from the voluntary fortnightly business survey, which captures businesses’ responses on how their turnover, workforce prices, trade and business resilience have been affected in the two-week reference period, up to Wave 17.

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.

The indicators and analysis presented in this bulletin are based on responses from the new voluntary fortnightly business survey, which captures businesses responses on how their turnover, workforce prices, trade and business resilience have been affected in the two week reference period. These data relate to the period 6 April 2020 to 19 April 2020.

This 6MB download is a zip file containing 5 pdf documents and 2 xlsx spreadsheets. Presentation on COVID-19 and the potential impacts on employment May 2020Waka Kotahi wants to better understand the potential implications of the COVID-19 downturn on the land transport system, particularly the potential impacts on regional economies and communities. To do this, in May 2020 Waka Kotahi commissioned Martin Jenkins and Infometrics to consider the potential impacts of COVID-19 on New Zealand’s economy and demographics, as these are two key drivers of transport demand. In addition to providing a scan of national and international COVID-19 trends, the research involved modelling the economic impacts of three of the Treasury’s COVID-19 scenarios, to a regional scale, to help us understand where the impacts might be greatest. Waka Kotahi studied this modelling by comparing the percentage difference in employment forecasts from the Treasury’s three COVID-19 scenarios compared to the business as usual scenario. The source tables from the modelling (Tables 1-40), and the percentage difference in employment forecasts (Tables 41-43), are available as spreadsheets. Arataki - potential impacts of COVID-19 Final Report Employment modelling - interactive dashboard The modelling produced employment forecasts for each region and district over three time periods – 2021, 2025 and 2031. In May 2020, the forecasts for 2021 carried greater certainty as they reflected the impacts of current events, such as border restrictions, reduction in international visitors and students etc. The 2025 and 2031 forecasts were less certain because of the potential for significant shifts in the socio-economic situation over the intervening years. While these later forecasts were useful in helping to understand the relative scale and duration of potential COVID-19 related impacts around the country, they needed to be treated with care recognising the higher levels of uncertainty. The May 2020 research suggested that the ‘slow recovery scenario’ (Treasury’s scenario 5) was the most likely due to continuing high levels of uncertainty regarding global efforts to manage the pandemic (and the duration and scale of the resulting economic downturn). The updates to Arataki V2 were framed around the ‘Slower Recovery Scenario’, as that scenario remained the most closely aligned with the unfolding impacts of COVID-19 in New Zealand and globally at that time. Find out more about Arataki, our 10-year plan for the land transport system May 2021The May 2021 update to employment modelling used to inform Arataki Version 2 is now available. Employment modelling dashboard - updated 2021Arataki used the May 2020 information to compare how various regions and industries might be impacted by COVID-19. Almost a year later, it is clear that New Zealand fared better than forecast in May 2020.Waka Kotahi therefore commissioned an update to the projections through a high-level review of:the original projections for 2020/21 against performancethe implications of the most recent global (eg International monetary fund world economic Outlook) and national economic forecasts (eg Treasury half year economic and fiscal update)The treasury updated its scenarios in its December half year fiscal and economic update (HYEFU) and these new scenarios have been used for the revised projections.Considerable uncertainty remains about the potential scale and duration of the COVID-19 downturn, for example with regards to the duration of border restrictions, update of immunisation programmes. The updated analysis provides us with additional information regarding which sectors and parts of the country are likely to be most impacted. We continue to monitor the situation and keep up to date with other cross-Government scenario development and COVID-19 related work. The updated modelling has produced employment forecasts for each region and district over three time periods - 2022, 2025, 2031.The 2022 forecasts carry greater certainty as they reflect the impacts of current events. The 2025 and 2031 forecasts are less certain because of the potential for significant shifts over that time. Data reuse caveats: as per license. Additionally, please read / use this data in conjunction with the Infometrics and Martin Jenkins reports, to understand the uncertainties and assumptions involved in modelling the potential impacts of COVID-19. COVID-19’s effect on industry and regional economic outcomes for NZ Transport Agency [PDF 620 KB] Data quality statement: while the modelling undertaken is high quality, it represents two point-in-time analyses undertaken during a period of considerable uncertainty. This uncertainty comes from several factors relating to the COVID-19 pandemic, including: a lack of clarity about the size of the global downturn and how quickly the international economy might recover differing views about the ability of the New Zealand economy to bounce back from the significant job losses that are occurring and how much of a structural change in the economy is required the possibility of a further wave of COVID-19 cases within New Zealand that might require a return to Alert Levels 3 or 4. While high levels of uncertainty remain around the scale of impacts from the pandemic, particularly in coming years, the modelling is useful in indicating the direction of travel and the relative scale of impacts in different parts of the country. Data quality caveats: as noted above, there is considerable uncertainty about the potential scale and duration of the COVID-19 downturn. Please treat the specific results of the modelling carefully, particularly in the forecasts to later years (2025, 2031), given the potential for significant shifts in New Zealand's socio-economic situation before then. As such, please use the modelling results as a guide to the potential scale of the impacts of the downturn in different locations, rather than as a precise assessment of impacts over the coming decade.

In March 2020, Mayor Carter announced the Saint Paul Bridge Fund to provide emergency relief for families and small businesses most vulnerable to the economic impacts of the COVID-19 pandemic. The program was funded through $3.25 million dollars from the Saint Paul Housing and Redevelopment Authority along with contributions from philanthropic, corporate and individual donors. Through these additional contributions, the fund provided $4.1 million to families and small businesses in Saint Paul.Data previously shared in this space included only the 380 recipients funded through "Phase 1". This dataset includes all three phases that were ultimately rolled out through the Bridge Fund for Small Business program.Nearly 2,000 unique applications applied for a small business grant of $7,50036% were from ACP50 areas (Areas of Concentrated Poverty where 50% or more of the residents are people of color)The applications were reviewed in order of a random number assigned at application close. Of these applications:633 small businesses were awarded a $7,500 grant36% of applications in the city were from ACP50 areas86% of applicants in the city cited they were ordered closed under one of the Governor’s Executive OrdersThis is a dataset of the small businesses that applied for the Bridge Fund and includes:Self-reported survey responsesAward informationGeographic information Additional information about the Saint Paul Bridge Fund may be found at stpaul.gov/bridge-fund.

State and territorial executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when individuals in states and territories were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes. Data consists exclusively of state and territorial orders, many of which apply to specific counties within their respective state or territory; therefore, data is broken down to the county level.

These data are derived from the publicly available state and territorial executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15, 2020 through May 31, 2021. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

State, territorial, and county executive orders, administrative orders, resolutions, and proclamations are collected from government websites and cataloged and coded using Microsoft Excel by one coder with one or more additional coders conducting quality assurance.

Data were collected to determine when individuals in states, territories, and counties were subject to executive orders, administrative orders, resolutions, and proclamations for COVID-19 that require or recommend people stay in their homes.

These data are derived from the publicly available state, territorial, and county executive orders, administrative orders, resolutions, and proclamations (“orders”) for COVID-19 that expressly require or recommend individuals stay at home found by the CDC, COVID-19 Community Intervention and At-Risk Task Force, Monitoring and Evaluation Team & CDC, Center for State, Tribal, Local, and Territorial Support, Public Health Law Program from March 15 through May 5, 2020. These data will be updated as new orders are collected. Any orders not available through publicly accessible websites are not included in these data. Only official copies of the documents or, where official copies were unavailable, official press releases from government websites describing requirements were coded; news media reports on restrictions were excluded. Recommendations not included in an order are not included in these data. These data do not include mandatory business closures, curfews, or limitations on public or private gatherings. These data do not necessarily represent an official position of the Centers for Disease Control and Prevention.

The outbreak of coronavirus (COVID-19) in Poland in 2020 had a significant impact on the sales value among micro and small companies. Nevertheless, in mid-May, the situation of micro and small companies improved compared to the beginning of April. The most significant drop in the value of sales among medium and large companies was recorded in the middle, and at the end of April, it concerned 65 percent of medium and 58 percent of large companies.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Updated weekly Public Health — Seattle & King County is monitoring changes in key economic, social, and other health indicators resulting from strategies to slow the spread of COVID-19. The metrics below were selected based on studies from previous outbreaks, which have linked strategies such as social distancing, school closures, and business closures to specific outcomes. Individual indicators in the grid below are updated daily, weekly, or monthly, depending on the source of data. Additional data will be added over time.

This statistics bank shows how business has made use of ordinary and extraordinary support schemes throughout the corona crisis.

A number of measures were initiated to increase activity in Norwegian business, prevent unnecessary closures and to get as many people as possible into work during the corona crisis. Several actors in the industry-oriented instrument apparatus were given additional tasks and new extraordinary measures were created, such as the compensation scheme through the Tax Agency.

In order to be able to monitor the use of the measures, the Ministry of Trade and Fisheries has commissioned Innovation Norway to expand its reporting to include regularly updated data on how the measures affect business. Innovation Norway has, with assistance from Societal Economic Analysis, also obtained information on schemes other than its own in order to get a more complete picture of the use of measures.

The statistics bank contains statistics on allocations per week from the business-oriented policy apparatus. The statistics bank is updated every month and contains data from week 1 of 2020.

A. SUMMARY This dataset shows San Francisco COVID-19 deaths by population characteristics. This data may not be immediately available for recently reported deaths. Data updates as more information becomes available. Because of this, death totals may increase or decrease.

Population characteristics are subgroups, or demographic cross-sections, like age, race, or gender. The City tracks how deaths have been distributed among different subgroups. This information can reveal trends and disparities among groups.

B. HOW THE DATASET IS CREATED As of January 1, 2023, COVID-19 deaths are defined as persons who had COVID-19 listed as a cause of death or a significant condition contributing to their death on their death certificate. This definition is in alignment with the California Department of Public Health and the national https://preparedness.cste.org/wp-content/uploads/2022/12/CSTE-Revised-Classification-of-COVID-19-associated-Deaths.Final_.11.22.22.pdf">Council of State and Territorial Epidemiologists. Death certificates are maintained by the California Department of Public Health.

Data on the population characteristics of COVID-19 deaths are from: *Case reports *Medical records *Electronic lab reports *Death certificates

Data are continually updated to maximize completeness of information and reporting on San Francisco COVID-19 deaths.

To protect resident privacy, we summarize COVID-19 data by only one population characteristic at a time. Data are not shown until cumulative citywide deaths reach five or more.

Data notes on select population characteristic types are listed below.

Race/ethnicity * We include all race/ethnicity categories that are collected for COVID-19 cases.

Gender * The City collects information on gender identity using these guidelines.

C. UPDATE PROCESS Updates automatically at 06:30 and 07:30 AM Pacific Time on Wednesday each week.

Dataset will not update on the business day following any federal holiday.

D. HOW TO USE THIS DATASET Population estimates are only available for age groups and race/ethnicity categories. San Francisco population estimates for race/ethnicity and age groups can be found in a dataset based on the San Francisco Population and Demographic Census dataset.These population estimates are from the 2018-2022 5-year American Community Survey (ACS).

This dataset includes several characteristic types. Filter the “Characteristic Type” column to explore a topic area. Then, the “Characteristic Group” column shows each group or category within that topic area and the number of cumulative deaths.

Cumulative deaths are the running total of all San Francisco COVID-19 deaths in that characteristic group up to the date listed.

To explore data on the total number of deaths, use the COVID-19 Deaths Over Time dataset.

E. CHANGE LOG

This is a list of locations of which the following conditions apply:ACTIVITY TYPE ID 4 SURVEY – Surveillance was conducted on the business and no violations were found. Reviews conducted during routine inspections of permitted establishments from 1/21/21 on.LMPHW Narrative: Louisville Metro Public Health and Wellness (LMPHW) investigates and responds to reports of alleged violations related to COVID-19. LMPHW has provided an open dataset of businesses that were observed to not be following the covid requirements as prescribed by the Governor’s Office. The data does not distinguish between the type of enforcement action taken with the exception of the closure of a facility for operating when they were to be closed. The data shows that an order or citation was issued with or without a fine assessed. A minimum of one violation or multiple violations were observed on this day. Violations include but are not limited to failure to wear a face covering, lack of social distancing, failure to properly isolate or quarantine personnel, failure to conduct health checks, and other violations of the Governor’s Orders. Closure orders documented in the data portal where issued by either LMPHW, Shively Police or the Kentucky Labor Cabinet. Detail the Enforcement Process: The Environmental Division receives complaints of non-compliance on local businesses. Complaints are received from several sources including: Metro Call, Louisville Metro Public Health and Wellness’ Environmental call line, Facebook, email, and other sources. Complaints are investigated by inspectors in addition to surveillance of businesses to ensure compliance. Violations observed result in both compliance guidance being given to the business along with an enforcement notice which consists of either a Face Covering Citation and/or a Public Health Notice and Order depending on the type of violation. Citations result in fines being assessed. Violations are to be addressed immediately.Community members can report a complaint via Metro Call by calling 574-5000. For COVID 19 Guidance please visit Louisville Metro’s Covid Resource Center at https://louisvilleky.gov/government/louisville-covid-19-resource-center or calling the Covid Helpline at (502)912-8598.ACTIVITY TYPE ID 12 indicates an Enforcement Action has been taken against the establishment which include Notice to Correct, Citation which include financial penalties and/or Cease Operation. LMPHW Narrative Example: Louisville Metro Public Health and Wellness (LMPHW) investigates and responds to reports of alleged violations related to COVID-19. They also conduct surveillance of businesses to determine compliance. LMPHW has provided an open dataset of businesses that were observed to be following the covid requirements as prescribed by the Governor’s Office. ACTIVITY TYPE ID 4 SURVEY – Surveillance was conducted on the business and no violations were found. ACTIVITY TYPE ID 7 FIELD – A complaint was investigated on the business and no violations were found.ACTIVITY TYPE ID 12 Enforcement Action – Action has been taken against the establishment which could include Notice to Correct, Citation which include financial penalties and/or Cease Operation. ACTIVITY TYPE ID 12 Enforcement Action – Action Code Z – The establishment has been issued an order to cease operation.Data Set Explanation:Activity Type ID 4 Survey has two separate files: COVID_4_Surveillance_Open_Data – Surveillance conducted prior to 1/21/2021 in which were conducted as part of random survey of businessesCOVID_4_Compliance_Reviews_Open_Data – Reviews conducted during routine inspections of permitted establishments from 1/21/21 on. Data Dictionary: REQ ID-ID of RequestRequest Date-Date of Requestperson premiseaddress1zipActivity Date-Date Activity OccurredACTIVITY TYPE IDActivity Type Desc-Description of ActivityContact:Gerald Kaforskigerald.kaforski@louisvilleky.gov

United States SBP: KS: Business Didn't Close for 1 Day data was reported at 32.000 % in 20 Sep 2020. This records an increase from the previous number of 30.300 % for 13 Sep 2020. United States SBP: KS: Business Didn't Close for 1 Day data is updated weekly, averaging 67.800 % from Apr 2020 to 20 Sep 2020, with 15 observations. The data reached an all-time high of 92.900 % in 14 Jun 2020 and a record low of 27.100 % in 16 Aug 2020. United States SBP: KS: Business Didn't Close for 1 Day data remains active status in CEIC and is reported by U.S. Census Bureau. The data is categorized under Global Database’s United States – Table US.S025: Small Business Pulse Survey: by State: Midwest Region. [COVID-19-IMPACT]

This is a list of locations of which the following conditions apply:Coded in our database as 12 - Enforcement Action was taken on a complaint investigation or surveillance of the business. The Action taken was that a Notice of Correction (Order) or Citation was issued to the business.

LMPHW Narrative:

Louisville Metro Public Health and Wellness (LMPHW) investigates and responds to reports of alleged violations related to COVID-19. LMPHW has provided an open dataset of businesses that were observed to not be following the covid requirements as prescribed by the Governor’s Office. The data does not distinguish between the type of enforcement action taken with the exception of the closure of a facility for operating when they were to be closed. The data shows that an order or citation was issued with or without a fine assessed. A minimum of one violation or multiple violations were observed on this day. Violations include but are not limited to failure to wear a face covering, lack of social distancing, failure to properly isolate or quarantine personnel, failure to conduct health checks, and other violations of the Governor’s Orders. Closure orders documented in the data portal where issued by either LMPHW, Shively Police or the Kentucky Labor Cabinet.

Detail the Enforcement Process:

The Environmental Division receives complaints of non-compliance on local businesses. Complaints are received from several sources including: Metro Call, Louisville Metro Public Health and Wellness’ Environmental call line, Facebook, email, and other sources. Complaints are investigated by inspectors in addition to surveillance of businesses to ensure compliance. Violations observed result in both compliance guidance being given to the business along with an enforcement notice which consists of either a Face Covering Citation and/or a Public Health Notice and Order depending on the type of violation. Citations result in fines being assessed. Violations are to be addressed immediately.

Community members can report a complaint via Metro Call by calling 574-5000. For COVID 19 Guidance please visit Louisville Metro’s Covid Resource Center at https://louisvilleky.gov/government/louisville-covid-19-resource-center or calling the Covid Helpline at (502)912-8598.

ACTIVITY TYPE ID 12 indicates an Enforcement Action has been taken against the establishment which include Notice to Correct, Citation which include financial penalties and/or Cease Operation.

LMPHW Narrative Example:

Louisville Metro Public Health and Wellness (LMPHW) investigates and responds to reports of alleged violations related to COVID-19. They also conduct surveillance of businesses to determine compliance. LMPHW has provided an open dataset of businesses that were observed to be following the covid requirements as prescribed by the Governor’s Office.

ACTIVITY TYPE ID 4 SURVEY – Surveillance was conducted on the business and no violations were found.

ACTIVITY TYPE ID 7 FIELD – A complaint was investigated on the business and no violations were found.

ACTIVITY TYPE ID 12 Enforcement Action – Action has been taken against the establishment which could include Notice to Correct, Citation which include financial penalties and/or Cease Operation.

ACTIVITY TYPE ID 12 Enforcement Action – Action Code Z – The establishment has been issued an order to cease operation.

Data Set Explanation:

Activity Type ID 4 Survey has two separate files:

COVID_4_Surveillance_Open_Data – Surveillance conducted prior to 1/21/2021 in which were conducted as part of random survey of businesses

COVID_4_Compliance_Reviews_Open_Data – Reviews conducted during routine inspections of permitted establishments from 1/21/21 on. Data Dictionary: REQ ID-ID of RequestRequest Date-Date of Requestperson premiseaddress1zipActivity Date-Date Activity OccurredACTIVITY TYPE IDActivity Type Desc-Description of ActivityContact:Gerald Kaforskigerald.kaforski@louisvilleky.gov

At the end of March 2020, 71 percent of Poland's companies reported a decrease in the number of new orders due to the coronavirus outbreak. The situation improved in May. At the end of the month, 35 percent of companies reported a decrease.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Reasons business or organization did not access any funding or credit due to the COVID-19 pandemic, by North American Industry Classification System (NAICS), business employment size, type of business, business activity and majority ownership, second quarter of 2021.