According to a survey conducted in Europe in 2021, 77 percent of respondents in Denmark reported they trusted their government's main motivations behind the lockdown restrictions, the highest share among all European countries. On the other hand, 34 percent of respondents in Poland said they were suspicious of the motivations behind lockdown restrictions, while a further 27 percent thought lockdown restrictions were an excuse to control the public.

On a month-on-month basis, sales volume of textile, clothing and footwear retail in the European Union member state countries underwent a decline of over 50 percent in the months of March and April 2020, when the coronavirus outbreak reached a high point in Europe. With the loosening of lockdown measures starting in May in many EU countries, retail trade started to recover, with a growth of 176.5 percent on April 2020. More recently, retail trade of textiles and clothing went back to more normal levels.

As of November 24, 2024 there were over 274 million confirmed cases of coronavirus (COVID-19) across the whole of Europe since the first confirmed cases in France in January 2020. France has been the worst affected country in Europe with 39,028,437 confirmed cases, followed by Germany with 38,437,756 cases. Italy and the UK have approximately 26.8 million and 25 million cases respectively. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

Dataset corresponding to a paper that has been published in Appetite (Philippe K, Chabanet C, Issanchou S, Monnery-Patris S. Child eating behaviors, parental feeding practices and food shopping motivations during the COVID-19 lockdown in France: (How) did they change? Appetite. 2021 Jun 1;161:105132. doi: 10.1016/j.appet.2021.105132. Epub 2021 Jan 23. PMID: 33493611; PMCID: PMC7825985). The objective of the study was to evaluate possible changes in eating behaviors in children aged 3–12 years, in parental eating and cooking behaviors, in parental feeding practices, and also in parental motivations when shopping for food during the lockdown, compared to the period before the lockdown. Information about the dataset and the corresponding documents can be found in the document "Metadata-paper-COVID.docx".

We are releasing a Twitter dataset connected to our project Digital Narratives of Covid-19 (DHCOVID) that -among other goals- aims to explore during one year (May 2020-2021) the narratives behind data about the coronavirus pandemic.In this first version, we deliver a Twitter dataset organized as follows:

Each folder corresponds to daily data (one folder for each day): YEAR-MONTH-DAYIn every folder there are 9 different plain text files named with ""dhcovid"", followed by date (YEAR-MONTH-DAY), language (""en"" for English, and ""es"" for Spanish), and region abbreviation (""fl"", ""ar"", ""mx"", ""co"", ""pe"", ""ec"", ""es""):dhcovid_YEAR-MONTH-DAY_es_fl.txt: Dataset containing tweets geolocalized in South Florida. The geo-localization is tracked by tweet coordinates, by place, or by user information.dhcovid_YEAR-MONTH-DAY_en_fl.txt: We are gathering only tweets in English that refer to the area of Miami and South Florida. The reason behind this choice is that there are multiple projects harvesting English data, and, our project is particularly interested in this area because of our home institution (University of Miami) and because we aim to study public conversations from a bilingual (EN/ES) point of view.dhcovid_YEAR-MONTH-DAY_es_ar.txt: Dataset containing tweets from Argentina.dhcovid_YEAR-MONTH-DAY_es_mx.txt: Dataset containing tweets from Mexico.dhcovid_YEAR-MONTH-DAY_es_co.txt: Dataset containing tweets from Colombia.dhcovid_YEAR-MONTH-DAY_es_pe.txt: Dataset containing tweets from Perú.dhcovid_YEAR-MONTH-DAY_es_ec.txt: Dataset containing tweets from Ecuador.dhcovid_YEAR-MONTH-DAY_es_es.txt: Dataset containing tweets from Spain.dhcovid_YEAR-MONTH-DAY_es.txt: This dataset contains all tweets in Spanish, regardless of its geolocation.

For English, we collect all tweets with the following keywords and hashtags: covid, coronavirus, pandemic, quarantine, stayathome, outbreak, lockdown, socialdistancing. For Spanish, we search for: covid, coronavirus, pandemia, quarentena, confinamiento, quedateencasa, desescalada, distanciamiento social.The corpus of tweets consists of a list of Tweet Ids; to obtain the original tweets, you can use ""Twitter hydratator"" which takes the id and download for you all metadata in a csv file.We started collecting this Twitter dataset on April 24th, 2020 and we are adding daily data to our GitHub repository. There is a detected problem with file 2020-04-24/dhcovid_2020-04-24_es.txt, which we couldn't gather the data due to technical reasons.For more information about our project visit https://covid.dh.miami.edu/ For more updated datasets and detailed criteria, check our GitHub Repository: https://github.com/dh-miami/narratives_covid19/

As of April 2021, all restaurant chefs surveyed in Australia reported having re-opened their establishments after the COVID-19 lockdowns. Meanwhile, ** percent of respondents in Israel said the same about their workplaces. In contrast, only ** percent of surveyed Swiss chefs claimed to be working in a fully re-opened restaurant.

Objective: To analyze the changes in the Emergency Department (ED) activity of two hospitals during the 2020 lockdown and corresponding timeframes in 2019 and 2021 to assess whether a more structured primary healthcare service could have influenced the COVID-19 pressure on the ED. Subject and Methods: This is a multicenter, retrospective study on adult subjects registered to the selected ED during the timeframes considered. Patients

This dataset contains the underlying data for the following publication: Lalas, D., Gakis, N., Mirasgedis, S., Georgopoulou, E., Sarafidis, Y., & Doukas, H. (2021). Energy and GHG Emissions Aspects of the COVID Impact in Greece. Energies, 14(7), 1955. https://doi.org/10.3390/en14071955.

Vaccinations in London Between 8 December 2020 and 15 September 2021 5,838,305 1st doses and 5,232,885 2nd doses have been administered to London residents.

Differences in vaccine roll out between London and the Rest of England London Rest of England Priority Group Vaccinations given Percentage vaccinated Vaccinations given Percentage vaccinated Group 1 Older Adult Care Home Residents 21,883 95% 275,964 96% Older Adult Care Home Staff 29,405 85% 381,637 88% Group 2 80+ years 251,021 83% 2,368,284 93% Health Care Worker 174,944 99% 1,139,243 100%* Group 3 75 - 79 years 177,665 90% 1,796,408 99% Group 4 70 - 74 years 252,609 90% 2,454,381 97% Clinically Extremely Vulnerable 278,967 88% 1,850,485 95% Group 5 65 - 69 years 285,768 90% 2,381,250 97% Group 6 At Risk or Carer (Under 65) 983,379 78% 6,093,082 88% Younger Adult Care Home Residents 3,822 92% 30,321 93% Group 7 60 - 64 years 373,327 92% 2,748,412 98% Group 8 55 - 59 years 465,276 91% 3,152,412 97% Group 9 50 - 54 years 510,132 90% 3,141,219 95% Data as at 15 September 2021 for age based groups and as at 12 September 2021 for non-age based groups * The number who have received their first dose exceeds the latest official estimate of the population for this group There is considerable uncertainty in the population denominators used to calculate the percentage vaccinated. Comparing implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following datasets can be used to estimate vaccine uptake by age group for London:

ONS 2020 mid-year estimates (MYE). This is the population estimate used for age groups throughout the rest of the analysis.


Number of people ages 18 and over on the National Immunisation Management Service (NIMS)


ONS Public Health Data Asset (PHDA) dataset. This is a linked dataset combining the 2011 Census, the General Practice Extraction Service (GPES) data for pandemic planning and research and the Hospital Episode Statistics (HES). This data covers a subset of the population.

Vaccine roll out in London by Ethnic Group Understanding how vaccine uptake varies across different ethnic groups in London is complicated by two issues:

Ethnicity information for recipients is unavailable for a very large number of the vaccinations that have been delivered. As a result, estimates of vaccine uptake by ethnic group are highly sensitive to the assumptions about and treatment of the Unknown group in calculations of rates.

For vaccinations given to people aged 50 and over in London nearly 10% do not have ethnicity information available,

The accuracy of available population denominators by ethnic group is limited. Because ethnicity information is not captured in official estimates of births, deaths, and migration, the available population denominators typically rely on projecting forward patterns captured in the 2011 Census. Subsequent changes to these patterns, particularly with respect to international migration, leads to increasing uncertainty in the accuracy of denominators sources as we move further away from 2011.

Comparing estimated population sizes and implied vaccination rates for multiple sources of denominators provides some indication of uncertainty in the true values. Confidence is higher where the results from multiple sources agree more closely. Because the denominator sources are not fully independent of one another, users should interpret the range of values across sources as indicating the minimum range of uncertainty in the true value. The following population estimates are available by Ethnic group for London:

GLA Ethnic group population projections - 2016 as at 2021


ONS Population Denominators produced for Race Disparity Audit as at 2018


ETHPOP population projections produced by the University of Leeds as at 2020

Antibody prevalence estimates As part of the ONS Coronavirus (COVID-19) Infection Survey ONS publish a modelled estimate of the percent of the adult population testing positive for antibodies to Coronavirus by region. Antibodies can be generated by vaccination or previous infection.

Vaccine effects on cases, hospitalisations and deaths When the vaccine roll out began in December 2020 coronavirus cases, hospital admissions and deaths were rising steeply. The peak of infections came in London in early January 2021, before reducing during the national lockdown and as the vaccine roll out progressed. As the vaccine roll out began in older age groups the effect of vaccinations can be separated from the effect of national lockdown by comparing changes in cases, admissions and deaths

Due to changes in the collection and availability of data on COVID-19, this website will no longer be updated. The webpage will no longer be available as of 11 May 2023. On-going, reliable sources of data for COVID-19 are available via the COVID-19 dashboard and the UKHSA

GLA Covid-19 Mobility Report Since March 2020, London has seen many different levels of restrictions - including three separate lockdowns and many other tiers/levels of restrictions, as well as easing of restrictions and even measures to actively encourage people to go to work, their high streets and local restaurants. This reports gathers data from a number of sources, including google, apple, citymapper, purple wifi and opentable to assess the extent to which these levels of restrictions have translated to a reductions in Londoners' movements. The data behind the charts below come from different sources. None of these data represent a direct measure of how well people are adhering to the lockdown rules - nor do they provide an exhaustive data set. Rather, they are measures of different aspects of mobility, which together, offer an overall impression of how people Londoners are moving around the capital. The information is broken down by use of public transport, pedestrian activity, retail and leisure, and homeworking. Public Transport For the transport measures, we have included data from google, Apple, CityMapper and Transport for London. They measure different aspects of public transport usage - depending on the data source. Each of the lines in the chart below represents a percentage of a pre-pandemic baseline.

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Citymapper Citymapper mobility index 2021-09-05 Compares trips planned and trips taken within its app to a baseline of the four weeks from 6 Jan 2020 7.9% 28% 19% Google Google Mobility Report 2022-10-15 Location data shared by users of Android smartphones, compared time and duration of visits to locations to the median values on the same day of the week in the five weeks from 3 Jan 2020 20.4% 40% 27% TfL Bus Transport for London 2022-10-30 Bus journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 34% 24% TfL Tube Transport for London 2022-10-30 Tube journey ‘taps' on the TfL network compared to same day of the week in four weeks starting 13 Jan 2020 - 30% 21% Pedestrian activity With the data we currently have it's harder to estimate pedestrian activity and high street busyness. A few indicators can give us information on how people are making trips out of the house:

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Walking Apple Mobility Index 2021-11-09 estimates the frequency of trips made on foot compared to baselie of 13 Jan '20 22% 47% 36% Parks Google Mobility Report 2022-10-15 Frequency of trips to parks. Changes in the weather mean this varies a lot. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail & Rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 30% 55% 41% Retail and recreation In this section, we focus on estimated footfall to shops, restaurants, cafes, shopping centres and so on.

activity Source Latest Baseline Min value in Lockdown 1 Min value in Lockdown 2 Min value in Lockdown 3 Grocery/pharmacy Google Mobility Report 2022-10-15 Estimates frequency of trips to grovery shops and pharmacies. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Retail/rec Google Mobility Report 2022-10-15 Estimates frequency of trips to shops/leisure locations. Compared to baseline of 5 weeks from 3 Jan '20 32% 55.00% 45.000% Restaurants OpenTable State of the Industry 2022-02-19 London restaurant bookings made through OpenTable 0% 0.17% 0.024% Home Working The Google Mobility Report estimates changes in how many people are staying at home and going to places of work compared to normal. It's difficult to translate this into exact percentages of the population, but changes back towards ‘normal' can be seen to start before any lockdown restrictions were lifted. This value gives a seven day rolling (mean) average to avoid it being distorted by weekends and bank holidays.

name Source Latest Baseline Min/max value in Lockdown 1 Min/max value in Lockdown 2 Min/max value in Lockdown 3 Residential Google Mobility Report 2022-10-15 Estimates changes in how many people are staying at home for work. Compared to baseline of 5 weeks from 3 Jan '20 131% 119% 125% Workplaces Google Mobility Report 2022-10-15 Estimates changes in how many people are going to places of work. Compared to baseline of 5 weeks from 3 Jan '20 24% 54% 40% Restriction Date end_date Average Citymapper Average homeworking Work from home advised 17 Mar '20 21 Mar '20 57% 118% Schools, pubs closed 21 Mar '20 24 Mar '20

The data collection consists of 40 qualitative interviews with Polish migrant essential workers living in the UK and 10 in-depth expert interviews with key stakeholders providing information and support to migrant workers in the UK. All migrant interviews are in Polish. Six of the expert interviews with key stakeholders are in English and four are in Polish. Fieldwork was conducted fully online during the Covid-19 pandemic between March and August 2021, following the third UK-wide Covid-19 lockdown. Restrictions were still in place in some localities. Interviews took place shortly after the end of the transition period concluding the UK’s European Union exit on 1 January 2021. All Polish migrant worker interviewees entered the UK before 1 January 2021 and had the option to apply to the EU Settlement Scheme.

The objectives of the qualitative fieldwork were to: 1. To synthesise empirical and theoretical knowledge on the short- and long-term impacts of COVID-19 on migrant essential workers. 2. To establish how the pandemic affected Polish migrant essential worker's lives; and expert interviews with stakeholders in the public and third/voluntary sector to investigate how to best support and retain migrant essential workers in COVID-19 recovery strategies. The project also involved: - co-producing policy outputs with partner organisations in England and Scotland; and - an online survey to measure how Polish migrant essential workers across different roles and sectors were impacted by COVID-19 in regard to health, social, economic and cultural aspects, and intentions to stay in the UK/return to Poland (deposited separately to University of Sheffield). Key findings included significant new knowledge about the health, social, economic and cultural impacts of Covid-19 on migrant essential workers. Polish essential workers were severely impacted by the pandemic with major mental health impacts. Mental health support was insufficient throughout the UK. Those seeking support typically turned to private (online) services from Poland as they felt they could not access them in the UK because of language or cultural barriers, lack of understanding of the healthcare system and pathways to mental health support, support being offered during working hours only, or fear of the negative impact of using mental health services on work opportunities. Some participants were in extreme financial hardship, especially those with pre-settled status or those who arrived in the UK during the pandemic. The reasons for financial strain varied but there were strong patterns linked to increased pressure at work, greater exposure to Covid-19 as well as redundancies, pay cuts and rejected benefit applications. There was a tendency to avoid applying for state financial support. These impacts were compounded by the sense of isolation, helplessness, or long-distance grief due to inability to visit loved ones in Poland. Covid-19 impacted most detrimentally on women with caring responsibilities, single parents and people in the health and teaching sectors. The most vulnerable Polish migrant essential workers - e.g. those on lower income, with pre-existing health conditions, restricted access to support and limited English proficiency - were at most risk. Discrimination was reported, including not feeling treated equally in the workplace. The sense of discrimination two-fold: as essential workers (low-paid, low-status, unsafe jobs) and as Eastern Europeans (frequent disciplining practices, treated as threat, assumed to be less qualified). In terms of future plans, some essential workers intended to leave the UK or were unsure about their future place of residence. Brexit was a major reason for uncertain settlement plans. Vaccine hesitancy was identified, based on doubts about vaccination, especially amongst younger respondents who perceived low risks of Covid-19 for their own health, including women of childbearing age, who may have worries over unknown vaccine side-effects for fertility. Interview participants largely turned to Polish language sources for vaccination information, especially social media, and family and friends in Poland. This promoted the spread of misinformation as Poland has a strong anti-vaccination movement.

COVID-19 has exposed the UK's socio-economic dependence on a chronically insecure migrant essential workforce. While risking their lives to offset the devastating effects of the pandemic, migrant workers reportedly find themselves in precarious professional and personal circumstances (temporary zero-hours contracts, work exploitation, overcrowded accommodation, limited access to adequate health/social services including Universal Credit). This project will investigate the health, social, economic and cultural impacts of COVID-19 on the migrant essential workforce and how these might impact on their continued stay in the UK. It will focus on the largest non-British nationality in the UK, the Polish community, who - while employed across a range of roles and sectors - are overrepresented in lower-paid essential work. We will use this group as an illustrative case study to make wider claims and policy recommendations about migrant work during the pandemic. Using a mixed-methods approach, we will conduct: an online survey to map COVID-19 impacts; in-depth qualitative interviews to establish how the pandemic has affected worker's lives; and expert interviews with stakeholders to investigate how to best support and retain migrant essential workers in COVID-19 recovery strategies. The results will generate the first comprehensive UK-wide dataset on the experiences of migrant essential workers against the backdrop of COVID-19. The research, co-produced with partner organisations (Polish Expats Associations, Fife Migrants Forum, PKAVS Minority Communities Hub and Polish Social and Cultural Association), will generate a policy briefing, a toolkit for employers in the essential work sectors, information resources for migrant workers, alongside media and academic outputs.

Snapshot img

The energy storage market share is expected to increase by 50013.15-megawatt units from 2021 to 2026, and the market’s growth momentum will accelerate at a CAGR of 61.52%.

This energy storage market research report provides valuable insights on the post COVID-19 impact on the market, which will help companies evaluate their business approaches. Furthermore, this report extensively covers energy storage market segmentation by the following:

Type - Utility-scale and behind the meter
Geography - APAC, North America, Europe, MEA, and South America

The energy storage market report also offers information on several market vendors, including ABB Ltd., Amsted Industries Inc., EVAPCO Inc., General Electric Co., GS Yuasa Corp., Ingersoll Rand Inc., LG Electronics Inc., Panasonic Corp., Samsung SDI Co. Ltd., and Tesla Inc. among others.

What will the Energy Storage Market Size be During the Forecast Period?

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Which are the Key Regions for Energy Storage Market?

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58% of the market’s growth will originate from APAC during the forecast period. China and South Korea (Republic of Korea) are the key markets for energy storage in APAC. Market growth in this region will be faster than the growth of the market in North America and Europe.

The significant increase in the demand for energy due to the rapid growth in population and improvements in the standard of living will facilitate the energy storage market growth in APAC over the forecast period. This market research report entails detailed information on the competitive intelligence, marketing gaps, and regional opportunities in store for vendors, which will assist in creating efficient business plans.

COVID Impact and Recovery Analysis

In 2020, the outbreak of COVID-19 led to a disrupted supply chain and the delay in new capacity installations, which hindered the growth of the regional market. However, in the first half of 2021, the resumption of operations in manufacturing hubs with the lifting of lockdown measures and the increased preference for sustainable power sources proliferated the growth of the regional market. Such factors are expected to fuel the regional market's growth during the forecast period.

What are the Revenue-generating Type Segments in the Energy Storage Market?

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The energy storage market share growth by the utility-scale segment will be significant during the forecast period. The growth of renewable energy generation and distribution will drive the growth of the segment owing to their role in integrating a greater share of variable renewable energy (VRE) in the system by providing the flexibility needed during the forecast period.

This report provides an accurate prediction of the contribution of all the segments to the growth of the energy storage market size and actionable market insights on post COVID-19 impact on each segment.

Energy Storage Market: Key Drivers, Trends, and Challenges

The growing energy storage requirement is notably driving the energy storage market growth, although factors such as high upfront costs may impede the market growth. Our research analysts have studied the historical data and deduced the key market drivers and the COVID-19 pandemic impact on the energy storage industry. The holistic analysis of the drivers will help in deducing end goals and refining marketing strategies to gain a competitive edge.

Key Energy Storage Market Driver

One of the key factors driving the global energy storage market growth is the growing energy storage requirement as companies incur heavy losses if there is a power outage for even a minute. For critical operations such as hospitals and nursing facilities, power outages can put lives at risk. Similarly, if a large manufacturing plant has to suspend operations due to revenue losses from outages, they would be millions as product deliveries get delayed. For example, on November 1, 2012, Hurricane Sandy decimated most areas on the east coast of the US, and millions of people had no electricity supply. The hurricane caused billions of dollars in losses to businesses and properties. Thus, power backup is imperative to run operations smoothly in every sector. Therefore, the greater need for energy storage will strongly support the growth of the global energy storage market during the forecast period.

Key Energy Storage Market Challenge

One of the key challenges to the global energy storage market growth is the high upfront costs for subsystem components, installation, and integration. High costs increase cost competitiveness with non-storage options for electric utilities. For instance, despite liquid air energy

Contact matrices from 9 distinct periods of the UK COVID-19 epidemic: Lockdown 1 = 23rd March - 3rd June 2020 Lockdown 1 easing = 4th June - 29th July 2020 Reduced restrictions = 30th July - 3rd Sep 2020 Schools open = 4th Sept - 26th October 2020 Lockdown 2 = 5th November - 2nd December 2020 Lockdown 2 easing = 3rd December - 19th December 2020 Christmas = 20 December 2020 - 2nd January 2021 Lockdown 3 = 5th January - 8th March 2021 Lockdown 3 with schools open = 8th March - 16th March 2021 1. The file: contact_matrices_9_periods.csv contains the mean contact matrices. 2. The nine 'qs' files for the individual periods contain 1000 bootstrap samples of the contact matrix for the relevant period. each column is a different sample. The age-groups are not explicitly detailed, but follow the same order as in the contact_matrices_9_periods.csv file.

The coronavirus (COVID-19) pandemic turned the tourism industry upside down, as governments implemented travel restrictions and stay-at-home measures to face the global health crisis. In the Netherlands, due to the pandemic, the number of inbound tourists from Europe dropped sharply in 2020 over the previous year, declining from over ** million to roughly *** million. Overall, European tourists represented the vast majority of inbound tourists in the Netherlands in 2020. Looking at the forecasts for 2021, a ************ study analyzed different scenarios. In the best-case scenario, assuming that traveling from neighboring countries will be again permitted in April or May, European inbound tourists were forecast to reach almost *** million in 2021. In the worst-case scenario, with restrictions taking place until the end of 2021, the number of inbound tourists from Europe to the Netherlands was estimated to decrease further in 2021 to around *** million.

COVID-19 impact on inbound tourism in the Netherlands On **************, the Netherlands implemented a national lockdown to face a rise in the number of COVID-19 infections in the country. As a result of the emergency measures, the number of monthly international tourist arrivals in the Netherlands fell by roughly ** percent in ********** over the previous year. As the lockdown was gradually eased in May and June, this scenario improved during the summer months. However, as the country implemented other restrictions since October due to an increase in COVID-19 infections, the number of arrivals decreased again in the following months, reaching roughly *** thousand in December 2020.

COVID-19 impact on inbound tourism receipts in the Netherlands As a result of the COVID-19 impact, international tourist receipts in the Netherlands also went down significantly. In the second quarter of 2020, they amounted to roughly **** billion U.S. dollars, whereas they added up to around *** billion in the second quarter of 2019. Inbound tourism receipts partially recovered in the third quarter of 2020, but a loss of over *** billion U.S. dollars was recorded compared to the third quarter of 2019.

In January 2021, approximately **** million jobs in Europe's three largest economies were being supported by temporary employment schemes, with the UK's job retention scheme supporting approximately **** million jobs, France's Chômage partiel scheme *** million, while *** million workers were on Germany's Kurzarbeit system. Although some of these partial employment mechanisms were already in place before the COVID-19 pandemic, their usage accelerated considerably after the first Coronavirus lockdowns in Spring 2020. How much will this cost European governments? Early on in the pandemic, European governments moved swiftly to limit the damage that the Coronavirus pandemic would cause to the labor market. The spectre of mass unemployment, which would put a huge strain on European benefit systems anyway, was enough to encourage significant government spending and intervention. To this end, the European Union made 100 billion Euros of loans available through it's unemployment support fund (SURE). As of March 2021, Italy had received ***** billion Euros in loans from the SURE mechanism, and is set to be loaned **** billion Euros overall. Spain and Poland will receive the second and third highest amount from the plan, at **** billion, and ***** billion Euros respectively. What about the UK? The United Kingdom is not involved in the European Union's SURE scheme, but has also paid substantial amounts of money to keep unemployment at bay. As of January 31, 2021, there had been more than **** million jobs furloughed on the UK's job retention scheme. By this date, the expenditure of this measure had reached **** billion British pounds, with this figure expected to increase further, following the extension of the scheme to September 2021.

The share of trips made by public transport dropped in all European Union (EU) countries in 2020 and remained low in 2021, due to the COVID-19 pandemic and associated lockdowns and travel restrictions. Prior to the pandemic, around **** percent of inland passenger transport trips were made by public transportation. In 2019, Hungary had the largest share of trips made by public transportation in the EU, while Lithuania recorded the lowest modal share at *** percent.

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.

During a survey carried out among marketing professionals from Europe, the Middle East, and Africa (EMEA) in spring 2021, ** percent stated that they expected their or their client's mobile marketing and advertising budgets to increase in the upcoming 12 months. A year earlier, during the period of the first COVID-19-related lockdowns, only ** percent of respondents expected increases.