According to a study in mid-March 2020, around **** percent of jobs in the leisure and hospitality industry in the United States are at risk from the global coronavirus pandemic (COVID-19). This amounts to around **** million jobs nationwide.

In the wake of COVID-19 and associated lockdowns, businesses in both the oil and gas industry and the recreation industry saw a ** percent reduction in revenues when comparing the revenues generated between ********** to ********** with revenues generated between ********** to **********. The top performing industries during the same time period can be accessed here.

The only industries that registered a positive change in the GDP in the 2nd quarter of 2020 compared to the 1st quarter, were health services, and public administration and defense. In contrast, the most affected industry by the coronavirus (COVID-19) pandemic in Romania was tourism and hospitality, followed by culture and arts. However, by the 3rd quarter of 2020, all the industries apart from education, agriculture, and public administration and defense, registered a positive change in GDP.

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

The outbreak of COVID-19, also known as novel coronavirus, is impacting almost all industries and sectors worldwide. Two of the most impacted sectors are manufacturing and travel & transportation. Both sectors are set to be severely impacted by coronavirus pandemic. The impact is ranked on a 5-point scale from minor impact to severe impact: 1 - minor impact 2 - moderate impact 3 - significant impact 4- major impact 5 - severe impact

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.

The outbreak of coronavirus in Poland will significantly reduce labor demand. According the source, bankruptcies of companies, dismissals of employees, the need to take care of children due to closed educational institutions, and limited possibilities of remote work in some sectors have a direct impact on the labor market during the pandemic. In total, nearly 4.2 million people work in industries strongly exposed to the economic consequences of the lockdown. Of this figure, three million are employed, and just over one million are business owners and co-owners. More than half of the jobs at risk are in the trade.

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

Continued Claims for UI released by the CT Department of Labor. Continued Claims are total number of individuals being paid benefits in any particular week. Claims data can be access directly from CT DOL here: https://www1.ctdol.state.ct.us/lmi/claimsdata.asp

Claims are disaggregated by age, education, industry, race/national origin, sex, and wages.

The claim counts in this dataset may not match claim counts from other sources.

Unemployment claims tabulated in this dataset represent only one component of the unemployed. Claims do not account for those not covered under the Unemployment system (e.g. federal workers, railroad workers or religious workers) or the unemployed self-employed.

Claims filed for a particular week will change as time goes on and the backlog is addressed.

For data on continued claims at the town level, see the dataset "Continued Claims for Unemployment Benefits by Town" here: https://data.ct.gov/Government/Continued-Claims-for-Unemployment-Benefits-by-Town/r83t-9bjm

For data on initial claims see the following two datasets:

"Initial Claims for Unemployment Benefits in Connecticut," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits/j3yj-ek9y

"Initial Claims for Unemployment Benefits by Town," https://data.ct.gov/Government/Initial-Claims-for-Unemployment-Benefits-by-Town/twvc-s7wy

Report on the impact COVID-19 has had on the Apparel market as it pertains to the sports industry. Read More

COVID-19, commonly referred to as the Coronavirus, is dominating headlines the world over. No industry has seen a greater impact than airlines. Read More

COVID-19 accelerates significant opportunities for long-term growth in electronic payments Read More

Regression outputs tables for firm level regressions, industry turnover during the coronavirus (COVID-19) pandemic.

Understanding the dynamic link between the development of COVID-19 pandemic and industry sector risk spillovers is crucial to explore the underlying mechanisms by which major public health events affect economic systems. This paper applies ElasticNet method proposed by Diebold and Yilmaz (2009, 2012, 2014) to estimate the dynamic risk spillover indicators of 20 industrial sectors in China from 2016 to 2022, and systematically examines the impact of industry risk network fluctuations and the transmission path caused by COVID-19 shock. The findings reveal that risk spillovers of Chinese industries show a dynamic change of "decline-fluctuation-rebound" with the three phases of COVID-19 epidemic. At the beginning of the epidemic, machinery and equipment, paper and printing, tourism and hotels, media and information services, and agriculture were the exporters of epidemic risk, while materials, transportation equipment, commercial trade, health care, and environmental protection were the importers of epidemic risk; However, as the epidemic developed further, the direction and effect of risk transmission in the industry was reversed. Examining the network characteristics of the pair sectors, we found that under the epidemic shock, the positive risk spillover from tourism and hotels, culture, education and sports to consumer goods, finance, and energy industries was significantly increased, and finance and real estate industries were affected by the risk impact of more industries, while the number of industries affected by information technology and computer industry was significantly reduced. This paper shows that there is inter-industry risk transmission of the COVID-19 epidemic shock, and the risk transmission feeds back in a cycle between industries as the epidemic develops, driving the economy into a vicious circle. The role of the service sector in blocking the spread of negative shocks from the epidemic should be emphasized and brought into play to avoid increasing the overall economic vulnerability. This study will help to deepen the understanding of scholars and policy makers on the network transmission effects of the epidemic.

Supply and demand shocks in the COVID-19 pandemic: An industry and occupation perspective
R. Maria del Rio-Chanona, Penny Mealy, Anton Picheler, Francois Lafond, J. Doyne Farmer
contact:
Results
The supply, demand, and total shocks at the industry and occupation level are in files:

industry_variables_and_shock.csv
occupation_variables_and_shock.csv

To reproduce our results we also include
The employment data between industries and occupations
industry_occupation_employment.csv
The classification of work activities
iwa_remotelabor_labels.csv
The essential score of industries at the NAICS 4d level
essential_score_industries_naics_4d_rev.csv

Update with respect to the previous version

We have now included our code to reproduce our study from scratch.

Measuring COVID-19 and stay home orders given in most of the world, In the US market, the advertising expenses have been cancelled, postponed and in some limited cases improved. Yet the same results do not affect all sectors and businesses. For certain sectors, businesses in the advertisement sector are now showing sparkling bright lights. Nonetheless, several businesses are just switching off their advertisement budgets, at least for now. Many advertising supervi.....

The Americas COVID-19 testing market was valued at around USD 5.8 Billion in 2025, backed by the continued need for diagnostic products and services amid persistent monitoring and surveillance initiatives. The global market is estimated to be over USD 10.5 Billion by 2035 at a CAGR of 6.2%.

Metric	Value
Market Size in 2025	USD 5.8 Billion
Projected Market Size in 2035	USD 10.5 Billion
CAGR (2025 to 2035)	6.2%

Country Wise Outlook

Country	CAGR (2025 to 2035)
USA	6.3%

Country	CAGR (2025 to 2035)
Canada	6.1%

Country	CAGR (2025 to 2035)
Mexico	6.2%

Country	CAGR (2025 to 2035)
Brazil	6.3%

Country	CAGR (2025 to 2035)
Argentina	6.1%

The “KOMPAKK index of economic sectors closure during the first wave of COVID-19” is a dataset on the German federal state-specific sector closures compiled from the original state decrees (March/April 2020). A large and growing number of studies shows the severe social and economic consequences of the governmental measures introduced to reduce the spread of the Covid-19 virus in March and April 2020 in Germany. However, we still lack a systematic analysis of intra-German differences in regulations and outcomes. The German federalist system leaves decisions over the implementation of decrees by the federal government to the federal states. This meant that the 16 states issued individual decrees over economic sector closure and social distancing measures during the course of the pandemic. We retrieved all decrees issued from 15.03.2020 to 17.04.2020 from the official website of each of the 16 federal states of Germany. All decrees used for generating the dataset are also available in the file “KOMPAKK_federalstatesdecrees.zip”.

With the Coronavirus Job Retention Scheme having drawn to a close on 30 September 2021, we've looked at which regions and sectors were the biggest users of the scheme.

The impact of coronavirus COVID-19 outbreak with a prolonged shutdown of business operation could be devastating on China's economy. Recreation industry was estimated to suffer the most with a drop by *** percentage points form the baseline of no virus outbreak. Transportation, trade and communication services were other hard-hit industries.