The coronavirus outbreak caused the turnovers of flower, frozen vegetables, and other preserves to more than double in Dutch supermarkets in March 2020. Pasta, baby food, sugar, cereals, and fruit conserves all enjoyed a revenue increase of over 75 percent. Of all food products, starch and baking mixes saw the most dramatic upturn, with a turnover amounting to more than 260 percent of the starch turnover in week 12 of 2019. Similarly, rice turnover almost tripled in week 11. This dramatic increase was caused by the COVID-19 outbreak in the Netherlands.

Turnover and sales progression as a result of COVID-19

These turnover figures are part of a data set showing the impact of COVID-19 on supermarket turnover in the Netherlands. Transactional data of major Dutch supermarkets was collected by the Central Bureau for Statistics (CBS) and analyzed per product group. Market researcher Nielsen gathered similar data for week nine of 2020, when rice had a relatively modest sales increase of 46 percent. However, as both research agencies used slightly different data collection methods, caution is advised when it comes to comparing their numbers. Nonetheless, the two data sets indicate that the food stockpiling trend set in motion in week 9 of 2020 intensified strongly in weeks 11 and 12.

COVID-19 and consumer behavior

Purchasing highly conservable food products and hygiene or cleaning products in bulk was a common practice in March 2020. As consumers anticipated either self-isolation or a lack of supplies in supermarkets, hoarding food and hygiene products functioned to restock the “pandemic pantry”. The increasing number of infections catalyzed this change in consumer behavior. Although public life in the Netherlands was still relatively unrestrained, European countries such as France and Spain at that time were on the verge of a lockdown. The apprehension of such a lockdown of society likely caused consumers to stock up on food supplies.

As global communities responded to COVID-19, we heard from public health officials that the same type of aggregated, anonymized insights we use in products such as Google Maps would be helpful as they made critical decisions to combat COVID-19. These Community Mobility Reports aimed to provide insights into what changed in response to policies aimed at combating COVID-19. The reports charted movement trends over time by geography, across different categories of places such as retail and recreation, groceries and pharmacies, parks, transit stations, workplaces, and residential.

ObjectiveAs a new type of consumer subject in the market that was formerly dominated by multiple person families, single households are driving the change in the buying structure. Food purchase activities have undergone significant changes since the outbreak of the COVID‐19. The objective of this study was to assess and compare variations in food consumption, purchase and handling during the COVID-19 pandemic between single person households (SPH) and multiple person households.MethodA cross-sectional study conducted among 211 individuals in communities in Harris and Waller Counties, Texas. Sociodemographic, food purchase, food consumption and food handling activities during the COVID-19 pandemic were assessed with a validated COVID-19 Nutrition questionnaire.ResultsNon-Hispanic Black participants constituted 42.6%, and 28.4% were Hispanics. Participants were made up of mostly aged 18–24 years (39.3%), 47.9% single household composition, 30.4% in full time employment, and 29.1% partook in food assistance programs. A large proportion of them had never used grocery pickup services, online grocery shopping and a farmers’ market. During the COVID-19 pandemic, majority of the participants used more of large supermarkets, restaurant/fast food, and online grocery but food consumption seemed to remain the same for the majority of participants. For beverages, majority of participants consumed more water, less soda, and no alcohol. There was a significant association between single person household and higher restaurant/fast foods purchase. Many of the participants reported weight gain and less physical activity during the pandemic.ConclusionRestaurant meal purchases was more prevalent in single-person families. The results from the study have the potential to contribute to how public policy officials, food service, and health authorities forecast how different categories of consumers will react in pandemics and may be used to inform area-specific alleviation strategies to minimize the impact of the COVID-19 pandemic and future events.

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.

BackgroundTo limit the spread of COVID-19, a strict lockdown was imposed in France between March and May 2020. Mobility limitations and closure of non-essential public places (restaurants, open-air markets, etc.) affected peoples' food environment (FE) and thus their food purchasing practices (FPPs). This study aimed to explore changes in FPPs of French households during lockdown and associations with individual and environmental factors.MethodsIn April of 2020 households from the Mont'Panier cross-sectional study (n = 306), a quota sampling survey conducted in the south of France, were asked to complete an online questionnaire about their FPPs during lockdown and related factors, including perceived FE (distance to closest general food store, perception of increased food prices, etc.). Objective FE (presence, number, proximity, and density of food outlets) was assessed around participant's home using a geographical information system. Multiple correspondence analysis based on changes in frequency of use and quantity of food purchased by food outlet, followed by a hierarchical cluster analysis, resulted in the identification of clusters. Logistic regression models were performed to assess associations between identified clusters and household's sociodemographic characteristics, perceived, and objective FE.ResultsFive clusters were identified. Cluster “Supermarket” (38% of the total sample), in which households reduced frequency of trips, but increased quantity bought in supermarkets during lockdown, was associated with lower incomes and the perception of increased food prices. Cluster “E-supermarket” (12%), in which households increased online food shopping with pickup at supermarket, was associated with higher incomes. Cluster “Diversified” (22%), made up of households who reduced frequency of trips to diverse food outlet types, was associated with the perception of increased food prices. Cluster “Organic Food Store” (20%), in which households did not change frequency of trips, nor quantity purchased in organic food stores, was associated with being older (35–50 y vs.

Context During the COVID-19, the fresh supermarket retail industry suffered serious losses. After the COVID-19, they recovered to some extent. At the same time, with the combination of online and offline channels, many professional fruit brands have achieved profits. Based on the topic of Bain's business competition in 2021, I made a questionnaire to collect answers from the public to learn more about the fruit retail market.

Content Responses were collected from 100 volunteers. The content includes the volunteers' age, gender, region, fruit preference, factors of concern, place of purchase, favorite brand and supermarket.

Acknowledgements Thanks to Bain for the topic and 100 volunteers for their help

Inspiration Welcome friends to find some characteristics of consumers in the fruit field according to the survey results.

This dataset measures the mobility trend in different dimensions (location categories) for Brazil, Federation Units and Municipalities. It is based on Google's Mobility Report. Location categories are: * supermarkets and pharmacies * parks * public transport stations * retail and leisure places * working places * dwelling For aggregation purposes, daily measurements were transformed into weekly averages (by epidemiological week).

This dataset was used as part project - Evaluating Effects of Social Inequalities on the COVID-19 Pandemic in Brazil. Maria Yury Ichihara and colleagues at the Centre for Data and Knowledge Integration for Health (Cidacs) at Fiocruz in Brazil created a social disparities index to measure inequalities relevant to the COVID-19 pandemic, such as unequal access to healthcare, to identify regions that are more vulnerable to infection and to better focus prevention efforts.

In Brazil, markers of inequality are associated with COVID-19 morbidity and mortality. They developed the index with available COVID-19 surveillance data, hosted on the Cidacs platform, and built a public data visualisation dashboard to share the index and patterns of COVID-19 incidence and mortality with the broader community. This enabled health managers and policymakers to monitor the pandemic situation in the most vulnerable populations and target social and health interventions.

Find this dataset through Google - https://www.google.com/covid19/mobility/