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 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.

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.

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.

According to recent estimates, the most affected sectors by the coronavirus pandemic in Latin America would be wholesale and retail trade as well as services in general, such as tourism, foodservice, transport, and communications. In 2020, this group of most affected sectors was forecasted to represent more than 16 percent of Brazil’s gross domestic product (GDP). Among the countries shown in this graph, Brazil is the nation where sectors moderately affected by the pandemic could represent the highest contribution to GDP (75.8 percent).

Which Latin American economies were most vulnerable to the pandemic? In 2020, the economic sectors most affected by the coronavirus pandemic - wholesale and retail, hotels and restaurants, transport and services in general - were forecasted to account for 35.5 percent of Panama’s GDP. In addition, the moderately and most affected economic segments were estimated to contribute the most to Panama’s GDP (a combined 97.6 percent) than any other country in this region. A similar scenario was projected in Mexico, where the sectors that would least suffer the pandemic's negative effects would account for only 3.4 percent of GDP.

Did the pandemic put a stop to economic growth in Latin America? Economic growth changed dramatically after the COVID-19 outbreak. Most of the largest economies in Latin America fell under recession in 2020. Estimates predict a more optimistic scenario for 2021, with countries such as Mexico, Colombia, and Argentina growing their GDP at least five percent.

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 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.

IBISWorld has looked at which UK regions have received the most financial support since the outbreak of COVID-19, assessing the reasons why.

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

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

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

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 5.8 percentage points form the baseline of no virus outbreak. Transportation, trade and communication services were other hard-hit industries.

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 Scottish economy, such as the United Kingdom (UK) economy, has been exposed to several adverse shocks over the past 5 years. Examples of these are the effect of the United Kingdom exiting the European Union (Brexit), the effects of the COVID-19 pandemic, and more recently Russia–Ukraine war, which can result in adverse direct and indirect economic losses across various sectors of the economy. These shocks disrupted the food and drink supply chains. The purpose of this article is 3-fold: (1) to explore the degree of resilience of the Scottish food and drink sector, (2) to estimate the effects on interconnected sectors of the economy, and (3) to estimate the economic losses, which is the financial value associated with the reduction in output. This article focuses on the impact that the sudden contraction that the “accommodation and food service activities”, resulting from the pandemic, had on the food and drink sectors. For this analysis, the study relied on the dynamic inoperability input–output model (DIIM), which takes into account the relationships across the different sectors of the Scottish economy over time. The results indicate that the accommodation and food service sector was the most affected by the COVID-19 pandemic lockdown contracting by approximately 60%. The DIIM shows that the disruption to this sector had a cascading effect on the remaining 17 sectors of the economy. The processed and preserved fish, fruits, and vegetable sector is the least resilient, while preserved meat and meat product sector is the most resilient to the final demand disruption in the accommodation and food service sector. The least economically affected sector was the other food product sector, while the other service sector had the highest economic loss. Although the soft drink sector had a slow recovery rate, economic losses were lower compared to the agricultural, fishery, and forestry sectors. From the policy perspective, stakeholders in the accommodation and food service sector should re-examine the sector and develop capacity against future pandemics. In addition, it is important for economic sectors to collaborate either vertically or horizontally by sharing information and risk to reduce the burden of future disruptions. Finally, the most vulnerable sectors of the economy, i.e., other service sectors should form a major part of government policy decision-making when planning against future pandemics.

The Covid19 Liquidity Line of Guarantees has mobilized financing for companies in all sectors of activity. The sectoral distribution data show that companies in the sectors most affected by COVID-19 have received the most guaranteed financing, which has enabled them to cover their liquidity needs and maintain their activity. . This file shows the closing data of the Covid19 Liquidity line of guarantees by sector of activity. It provides information on the number of operations, the number of companies that have requested guarantees, the amount of the guarantee requested and the total amount of financing that these guarantees have made possible, broken down by the different sectors of activity.

Note: This dataset is no longer being updated as of June 2, 2025.

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021.

AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs.

LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors.

The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH.

While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both.

Several additional data limitations should be kept in mind:

• Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code.

• Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate.

• However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures.

• Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk.

• The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

This dataset contains numbers of COVID-19 outbreaks and associated cases, categorized by setting, reported to CDPH since January 1, 2021. AB 685 (Chapter 84, Statutes of 2020) and the Cal/OSHA COVID-19 Emergency Temporary Standards (Title 8, Subchapter 7, Sections 3205-3205.4) required non-healthcare employers in California to report workplace COVID-19 outbreaks to their local health department (LHD) between January 1, 2021 – December 31, 2022. Beginning January 1, 2023, non-healthcare employer reporting of COVID-19 outbreaks to local health departments is voluntary, unless a local order is in place. More recent data collected without mandated reporting may therefore be less representative of all outbreaks that have occurred, compared to earlier data collected during mandated reporting. Licensed health facilities continue to be mandated to report outbreaks to LHDs. LHDs report confirmed outbreaks to the California Department of Public Health (CDPH) via the California Reportable Disease Information Exchange (CalREDIE), the California Connected (CalCONNECT) system, or other established processes. Data are compiled and categorized by setting by CDPH. Settings are categorized by U.S. Census industry codes. Total outbreaks and cases are included for individual industries as well as for broader industrial sectors. The first dataset includes numbers of outbreaks in each setting by month of onset, for outbreaks reported to CDPH since January 1, 2021. This dataset includes some outbreaks with onset prior to January 1 that were reported to CDPH after January 1; these outbreaks are denoted with month of onset “Before Jan 2021.” The second dataset includes cumulative numbers of COVID-19 outbreaks with onset after January 1, 2021, categorized by setting. Due to reporting delays, the reported numbers may not reflect all outbreaks that have occurred as of the reporting date; additional outbreaks may have occurred that have not yet been reported to CDPH. While many of these settings are workplaces, cases may have occurred among workers, other community members who visited the setting, or both. Accordingly, these data do not distinguish between outbreaks involving only workers, outbreaks involving only residents or patrons, or outbreaks involving both. Several additional data limitations should be kept in mind: Outbreaks are classified as “Insufficient information” for outbreaks where not enough information was available for CDPH to assign an industry code. Some sectors, particularly congregate residential settings, may have increased testing and therefore increased likelihood of outbreak recognition and reporting. As a result, in congregate residential settings, the number of outbreak-associated cases may be more accurate. However, in most settings, outbreak and case counts are likely underestimates. For most cases, it is not possible to identify the source of exposure, as many cases have multiple possible exposures. Because some settings have been at times been closed or open with capacity restrictions, numbers of outbreak reports in those settings do not reflect COVID-19 transmission risk. The number of outbreaks in different settings will depend on the number of different workplaces in each setting. More outbreaks would be expected in settings with many workplaces compared to settings with few workplaces.

In a survey conducted in Chile at the end of March 2020, nine out of ten company executives thought that the tourism and hospitality sector would be one of the most affected by the coronavirus (COVID-19) pandemic. In turn, respondents' answers showed that the public sector, along with telecommunications and technology, would be likely spared from this crisis' negative effects. According to the same survey, over two thirds of Chilean respondents expected the country's GDP to fall in 2020.

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