As of April 2020, ** percent of beauty retailers in the United States were considering not reopening underperforming stores after the COVID-19 lockdown. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

In the first five months of 2020, retail space closures in the United States measured **** million square feet. This trend is likely to continue as the COVID-19 pandemic continues to impact footfal in stores.

As of April 2020, * percent of apparel retailers in the United States stated that they were open in certain locations. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

The COVID-19 HOT TOPIC: Retailers’ response to COVID-19 report looks at how retailers have adjusted their operations in reaction to the pandemic. We look at the key themes including limited purchases of certain items, store closures and looking after staff. Read More

This dataset is no longer being updated as of 7/1/2021. It is being retained on the Open Data Portal for its potential historical interest.

A list of retail stores, restaurants, personal services and other businesses open and closed during the COVID-19 pandemic. Also indicates if business is offering delivery, pick up or on-line sales.

Updated at least biweekly during Covid-19 Pandemic.

Extract from raw data from “It remains open”: list of places open or closed during the confinement period. To edit the data, you can contribute directly to OpenStreetMap or It remains open, all contribution info is here. The file is in CSV format (separated by commas), with UTF-8 encoding. It is updated every hour. The data structure is as follows: * osm_id: OpenStreetMap identifier of the place * name: name of the place * cat: category (office tags, shop, craft, amenity from OpenStreetMap) * brand: name of the sign/network * Wikidata: Wikidata ID associated with the sign * url_hours: URL link to which the business schedules of the associated sign are entered * info: free text to give more details on access conditions * status: state of opening or closure. Values: open = as usual, open_adapted = hours likely to have changed, partial = potentially closed place, closed = closed place. * opening_hours: opening hours during containment (see OSM wiki) * lon: longitude (WGS84, decimal degrees) * Lat: latitude (WGS84, decimal degrees)

The aim of the special survey of the GESIS panel on the outbreak of the corona virus SARS-CoV-2 in Germany was to collect timely data on the effects of the corona crisis on people´s daily lives. The study focused on questions of risk perception, risk minimization measures, evaluation of political measures and their compliance, trust in politics and institutions, changed employment situation, childcare obligations, and media consumption. Due to the need for timely data collection, only the GESIS panel sub-sample of online respondents was invited (about three quarters of the sample). Since, due to time constraints, respondents could only participate in the online survey but not by mail, the results cannot be easily transferred to the overall population. Further longitudinal surveys on Covid-19 with the entire sample of the GESIS panel are planned for 2020.

Topics: Risk perception: Probability of events related to corona infection in the next two months (self, infection of a person from close social surrondings, hospital treatment, quarantine measures regardless of whether infected or not, infecting other people)

Risk minimization: risk minimization measures taken in the last seven days (avoided certain (busy) places, kept minimum distance to other people, adapted school or work situation, quarantine due to symptoms or without symptoms, washed hands more often, used disinfectant, stocks increased, reduced social interactions, worn face mask, other, none of these measures).

Evaluation of the effectiveness of various policy measures to combat the further spread of corona virus (closure of day-care centres, kindergartens and schools, closure of sports facilities, closure of bars, cafés and restaurants, closure of all shops except supermarkets and pharmacies, ban on visiting hospitals, nursing homes and old people´s homes, curfew for persons aged 70 and over or people with health problems or for anyone not working in the health sector or other critical professions (except for basic purchases and urgent medical care).

Curfew compliance or refusal: Willingness to obey a curfew vs. refusal; reasons for the compliance with curfew (social duty, fear of punishment, protection against infection, fear of infecting others (loved ones, infecting others in general, a risk group); reasons for refusal of curfew (restrictions too drastic or not justified, other obligations, does not stop the spread, not affected by the outbreak, boring at home, will not be punished).

Evaluation of the effectiveness of various government measures (medical care, restrictions on social life such as closure of public facilities and businesses, reduction of economic damage, communication with the population).

Trust in politics and institutions with regard to dealing with the coronavirus (physician, local health authority, local and municipal administration, Robert Koch Institute (RKI), Federal Government, German Chancellor, Ministry of Health, World Health Organization (WHO), scientists).

Changed employment situation: employment status at the beginning of March; change in occupational situation since the spread of coronavirus: dependent employees: number of hours reduced, number of hours increased, more home office, leave of absence with/ without continued wage payment , fired, no change; self-employed: working hours reduced, working hours increased, more home office, revenue decreased, revenue increased, company temporarily closed by the authorities, company temporarily voluntarily closed, financial hardship, company permanently closed or insolvent, no change.

Childcare: children under 12 in the household; organisation of childcare during the closure of day-care centres, kindergartens and schools (staying at home, partner stays at home, older siblings take care, grandparents are watching, etc.)

Media consumption on Corona: information sources used for Corona (e.g. nationwide public or private television or radio, local public or private television or radio, national newspapers or local newspapers, Facebook, other social media, personal conversations with friends and family, other, do not inform myself on the subject); frequency of Facebook usage; information about Corona obtained from regional Facebook page or regional Facebook group.

Demography: sex; age (categorized); education (categorized); intention to vote and choice of party (Sunday question); Left-right self-assessment; marital status; size of household.

Additionally coded: Respondent ID;...

The Project involved getting photos of closed due to COVID signs in shops and businesses in York UK.

One column of "text" includes all the transcripts of the signs with phone numbers removed.

As of March 15, 2020, 23 percent of respondents in the United States said that their frequency of purchasing goods online had increased compared to one month previously. Over forty percent of those surveyed stated that their frequency of e-commerce shopping had not changed at all.

COVID-19 contributes to growth of e-commerce In general, e-commerce sales have increased in recent years, a trend that was expected to continue through 2024. It is likely that this sector will see further increases due to COVID-19, as many people choose to stay at home and amend their daily routines to avoid catching the airborne virus. However, most retailers still expect some downside revenue implications due to the pandemic.

Consumer purchasing patterns under COVID-19 As they spend longer stretches at home, consumers are purchasing more nonperishable food-items, cleaning supplies, and home entertainment products. This is often done through online marketplaces, such as Walmart or Amazon. In contrast, there has been a decrease in spending in clothing and furniture stores, as most of these locations have been temporarily shut down to help contain the spread of coronavirus.

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

COVID-19 Stats & Trends

Context

This dataset seeks to provide insights into what has changed due to policies aimed at combating COVID-19 and evaluate the changes in community activities and its relation to reduced confirmed cases of COVID-19. The reports chart movement trends, compared to an expected baseline, over time (from 2020/02/15 to 2020/02/05) by geography (across 133 countries), as well as some other stats about the country that might help explain the evolution of the disease.

Content

1. Grocery & Pharmacy: Mobility trends for places like grocery markets, food warehouses, farmers' markets, specialty food shops, drug stores, and pharmacies.
2. Parks: Mobility trends for places like national parks, public beaches, marinas, dog parks, plazas, and public gardens.
3. Residential: Mobility trends for places of residence.
4. Retail & Recreation: Mobility trends for places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.
5. Transit stations: Mobility trends for places like public transport hubs such as subway, bus, and train stations.
6. Workplaces: Mobility trends for places of work.
7. Total Cases: Total number of people infected with the SARS-CoV-2.
8. Fatalities: Total number of deaths caused by CoV-19.
9. Government Response Stringency Index: Additive score of nine indicators of government response to CoV-19: School closures, workplace closures, cancellation of public events, public information campaigns, stay at home policies, restrictions on internal movement, international travel controls, testing policy, and contact tracing.
10. COVID-19 Testing: Total number of tests performed.
11. Total Vaccinations: Total number of shots given.
12. Total People Vaccinated: Total number of people given a shot.
13. Total People Fully Vaccinated: Total number of people fully vaccinated (might require two shots of some vaccines).
14. Population: Total number of inhabitants.
15. Population Density per km2: Number of human inhabitants per square kilometer.
16. Health System Index: Overall performance of the health system.
17. Human Development Index (HDI): Summary index based on life expectancy at birth, expected years of schooling for children and mean years of schooling for adults, and GNI per capita.
18. GDP (PPP) per capita: Gross Domestic Product (GDP) per capita based on Purchasing Power Parity (PPP), taking into account the relative cost of local goods, services and inflation rates of the country, rather than using international market exchange rates, which may distort the real differences in per capita income.
19. Elderly Population (percentage): Percentage of the population above the age of 65 years old.

References & Acknowledgements

Bing COVID-19 data. Available at: https://github.com/microsoft/Bing-COVID-19-Data COVID-19 Community Mobility Report. Available at: https://www.google.com/covid19/mobility/ COVID-19: Government Response Stringency Index. Available at: https://ourworldindata.org/grapher/covid-stringency-index Coronavirus (COVID-19) Testing. Available at: https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-all-observations.csv Coronavirus (COVID-19) Vaccination. Available at: https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv List of countries and dependencies by population. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries and dependencies by population density. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries by Human Development Index. Available at: http://hdr.undp.org/en/data Measuring Overall Health System Performance. Available at: https://www.who.int/healthinfo/paper30.pdf?ua=1 List of countries by GDP (PPP) per capita. Available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD List of countries by age structure (65+). Available at: https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS

Authors

• Diogo Silva, up201706892@fe.up.pt

The coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel coronavirus a pandemic on March 11, 2020. Read More

Almost one quarter of all businesses have temporarily closed or paused trading due to the Coronavirus (COVID-19) pandemic in the United Kingdom as of April 2020. The sector with the highest share of business closures were those in the arts, entertainment, and recreation sector, with over ** percent of them currently closed, compared with just *** percent of human health, and social work businesses.

The Coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious Coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel Coronavirus a pandemic on March 11, 2020. Read More

The COVID-19 HOT TOPIC: Livestreaming Engagement during the Coronavirus Pandemic report looks at the success of livestreaming in China and how it adapted during the COVID-19 pandemic. The report also looks at how brands in the West are utilising livestreaming, and how this can further evolve to offset lost sales due to temporary store closures during the pandemic. Read More

During the COVID-19 outbreak, we experienced the suspension of both work-related and spare activities, with the closure of shops, companies, services, as well as schools. Children probably are the ones who have suffered the most from this situation, due to the limited socialization with peers and boredom experienced at home. In this context, schools and childhood services tried to relieve the negative effects brought by the pandemic through actions aimed at actively engaging students and their parents in promoting child development and wellbeing. Therefore, several worldwide actions have been implemented to guarantee educational continuity. However, most of these actions targeted 3–18years old children/adolescents, while the subgroup 0–3 was rarely included. Cooperativa Sociale Aeris, a social enterprise based in northern Italy that deals with socio-educational and welfare services, took several measures to overcome problems resulting from the closure of its services dedicated to 0–3 aged children. In this manuscript, we depict how Aeris kept engaged children and their parents, reporting families’ evaluation on the actions taken. For assessing their proposed activities, Aeris promptly distributed an on-line survey to the families in May 2020. The answers showed that the organized activities had a positive impact on both children and parents, diminishing the sense of loneliness and boredom for the former, and acting as an important support for the latter. Therefore, this manuscript could work as a reference for policy-makers and managers of educational services in implementing activities and initiatives during home schooling.

The Coronavirus (SARS-CoV-2) outbreak, dubbed COVID-19, is first and foremost a human tragedy, affecting millions of people globally. The contagious Coronavirus, which broke out at the close of 2019, has led to a medical emergency across the world, with the World Health Organization officially declaring the novel Coronavirus a pandemic on March 11, 2020. Read More

Context

Coronavirus infection is currently the most important health topic. It surely tested and continues to test to the fullest extent the healthcare systems around the world. Although big progress is made in handling this pandemic, a tremendous number of questions are needed to be answered. I hereby present to you the local Bulgarian COVID-19 dataset with some context. It could be used as a comparator because it stands out compared to other countries and deserves analysis.

Context for Bulgarian population: Population - 6 948 445 Median age - 44.7 years Aged >65 - 20.801 % Aged >70 - 13.272%

Summary of the results: - first pandemic wave was weak, probably because of the early state of emergency (5 days after the first confirmed case). Whether this was a good decision or it was too early and just postpone the inevitable is debatable. -healthcare system collapses (probably due to delayed measures) in the second and third waves which resulted in Bulgaria gaining the top ranks for mortality and morbidity tables worldwide and in the EU. - low percentage of vaccinated people results in a prolonged epidemic and delaying the lifting of the preventive measures.

Some of the important moments that should be considered when interpreting the data: 08.03.2020 - Bulgaria confirmed its first two cases. The government issued a nationwide ban on closed-door public events (first lockdown); 13.03.2020- after 16 reported cases in one day, Bulgaria declared a state of emergency for one month until 13.04.2020. Schools, shopping centres, cinemas, restaurants, and other places of business were closed. All sports events were suspended. Only supermarkets, food markets, pharmacies, banks, and gas stations remain open. 03.04.2020 - The National Assembly approved the government's proposal to extend the state of emergency by one month until 13.05.2020; 14.05.2020 - the national emergency was lifted, and in its place was declared a state of an emergency epidemic situation. Schools and daycares remain closed, as well as shopping centers and indoor restaurants; 18.05.2020 - Shopping malls and fitness centers opened; 01.06.2020 - Restaurants and gaming halls opened; 10.07.2020 - discos and bars are closed, the sports events are without an audience; 29.10.2020 - High school and college students are transitioning to online learning; 27.11.2020 - the whole education is online, restaurants, nightclubs, bars, and discos are closed (second lockdown 27.11 - 21.12); 05.12.2020 - the 14-day mortality rate is the highest in the world; 16.01.2021 - some of the students went back to school; 01.03.2021 - restaurants and casinos opened; 22.03.2021 - restaurants, shopping malls, fitness centers, and schools are closed (third lockdown for 10 days - 22.03 - 31.03); 19.04.2021 - children daycare facilities, fitness centers, and nightclubs are opened;

Content

This dataset consists of 447 rows with 29 columns and covers the period 08.03.2020 - 28.05.2021. In the beginning, there are some missing values until the proper statistical report was established.

Inspiration

A publication proposal is sent to anyone who wishes to collaborate. Based on the results and the value of the findings and the relevance of the topic it is expected to publish: - in a local journal (guaranteed); - in a SCOPUS journal (highly probable); - in an IF journal (if the results are really insightful).

The topics could be, but not limited to: - descriptive analysis of the pandemic outbreak in the country; - prediction of the pandemic or the vaccination rate; - discussion about the numbers compared to other countries/world; - discussion about the government decisions; - estimating cut-off values for step-down or step-up of the restrictions.

Error or query reporting

If you find an error, have a question, or wish to make a suggestion, I encourage you to reach me.

The data correspond to the selected national public response measures presented in the weekly report COVID-19 Country overviews.Response measures collected include mass gathering cancellations (for specific events or a ban on gatherings of a particular size); closure of public spaces (including restaurants, entertainment venues, non-essential shops, partial or full closure of public transport etc.); closure of educational institutions (including daycare or nursery, primary schools, and secondary schools and higher education); ‘stay-at-home’ recommendations for risk groups or vulnerable populations (such as the elderly, people with underlying health conditions, physically disabled people etc.); ‘stay-athome’ recommendations for the general population (which are voluntary or not enforced); and ‘stay-at-home’ orders for the general population (these are enforced and also referred to as ‘lockdown’), use of protective masks in public spaces/on public transport (mutually exclusive voluntary recommendations and mandatory obligations shown separately) and also teleworking recommendations/closure of workplaces

It is based on data originally downloaded by the site https://www.ecdc.europa.eu/en/covid-19.

Raw data from ECDC, harmonization and homogenization of data from UNIPV - Laboratory of Geomatics

The outbreak of the COVID-19 pandemic has prompted the German government and the 16 German federal states to announce a variety of public health measures in order to suppress the spread of the coronavirus. These non-pharmaceutical measures intended to curb transmission rates by increasing social distancing (i.e., diminishing interpersonal contacts) which restricts a range of individual behaviors. These measures span moderate recommendations such as physical distancing, up to the closures of shops and bans of gatherings and demonstrations. The implementation of these measures are not only a research goal for themselves but have implications for behavioral research conducted in this time (e.g., in form of potential confounder biases). Hence, longitudinal data that represent the measures can be a fruitful data source. The presented data set contains data on 14 governmental measures across the 16 German federal states. In comparison to existing datasets, the data set at hand is a fine-grained daily time series tracking the effective calendar date, introduction, extension, or phase-out of each respective measure. Based on self-regulation theory, measures were coded whether they did not restrict, partially restricted or fully restricted the respective behavioral pattern. The time frame comprises March 08, 2020 until May 15, 2020. The project is an open-source, ongoing project with planned continued updates in regular (approximately monthly) intervals. New variables include restrictions on travel and gastronomy. The variable trvl (travel) comprises the following categories: fully restricted (=2) reflecting a potential general ban to travel within Germany (except for sound reasons like health or business); partially restricted (=1): travels are allowed but may be restricted through prohibition of accommodation or entry ban for certain groups (e.g. people from risk areas); free (=0): no travel and accommodation restrictions in place). The variable gastr (gastronomy) comprises: fully restricted (=2): closure of restaurants or bars; partially restricted (=1): Only take-away or food delivery services are allowed; free (=0): restaurants are allowed to open without restrictions). Further, the variables msk (recommendations to wear a mask) and zoo (restrictions of zoo visits) have been adjusted.:

Between January and March 2020, due to the coronavirus pandemic and the closure of many physical shops in Poland, the number of orders from online shops increased compared to a similar period in 2019. The most significant increase in orders for food products and cosmetics and health care products.

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