The COVID-19 pandemic hit many industries hard. Lots of people lost their jobs or were forced to reduce their employment radically throughout 2020. As a result, 131 million more people globally were classified as poor, meaning that they lived on two U.S. dollars or less daily.

Coronavirus-19 Deaths (Hourly Update) vs. Median Household Income (ACS)See Detailed graphs and tables describing the COVID-19 crisis in New Mexico, updated daily (includes some county level data not found elsewhere) - https://sites.google.com/view/new-mexico-covid19-tracking/homeCDC's Description of the Social Vulnerability Index (takes into account 15 different selected indicators):https://svi.cdc.gov/

The data set provides readers with data on the first half of the workforce for the years 2011 to 2020, per capita income for the first half of 2020 compared to 2019, and the unemployment rate in the working age. activities in the first half of the year from 2011 to 2020.

As a consequence of the Coronavirus outbreak in the United Kingdom there has been an unprecedented lockdown of UK society. Due to this, many businesses have been forced to close or suspend activities for the foreseeable future, with many worrying about how this will effect their personal finances. According to a survey from March 2020, Coronavirus had already impacted on the personal finances of over a quarter of British respondents, with a further 42 percent fearing it will in the future.

Ireland DE: LU: Change in Personal Income Tax Revenue data was reported at -794.000 EUR mn in Dec 2021. This records an increase from the previous number of -856.000 EUR mn for Sep 2021. Ireland DE: LU: Change in Personal Income Tax Revenue data is updated quarterly, averaging -833.000 EUR mn from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of -794.000 EUR mn in Dec 2021 and a record low of -945.000 EUR mn in Mar 2021. Ireland DE: LU: Change in Personal Income Tax Revenue data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.F013: Potential Costs and Distributional Effect: COVID-19 Related Unemployment. [COVID-19-IMPACT]

Ireland DE: LU: Change in Market Income data was reported at -3,740.000 EUR mn in Dec 2021. This records an increase from the previous number of -4,008.000 EUR mn for Sep 2021. Ireland DE: LU: Change in Market Income data is updated quarterly, averaging -4,196.000 EUR mn from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of -3,740.000 EUR mn in Dec 2021 and a record low of -4,384.000 EUR mn in Jun 2021. Ireland DE: LU: Change in Market Income data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.F013: Potential Costs and Distributional Effect: COVID-19 Related Unemployment. [COVID-19-IMPACT]

Ireland DE: HU: Change in Market Income data was reported at -5,178.000 EUR mn in Dec 2021. This records an increase from the previous number of -6,474.000 EUR mn for Sep 2021. Ireland DE: HU: Change in Market Income data is updated quarterly, averaging -7,407.500 EUR mn from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of -5,178.000 EUR mn in Dec 2021 and a record low of -8,341.000 EUR mn in Jun 2021. Ireland DE: HU: Change in Market Income data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.F013: Potential Costs and Distributional Effect: COVID-19 Related Unemployment. [COVID-19-IMPACT]

Abstract

In the WAEMU countries, COVID-19 is expected to affect households in many ways. First, governments might reduce social transfers to households due to the decline in revenue arising from the potential COVID-19 economic recession. Second households deriving income from vulnerable sectors such as tourism and related activities will likely face risk of unemployment or loss of income. Third an increase in prices of imported goods can also negatively impact household welfare, as a direct consequence of the increase of these imported items or as indirect increase of prices of local good manufactured using imported inputs. In this context, there is a need to produce high frequency data to help policy makers in monitoring the channels by which the pandemic affects households and assessing its distributional impact. To do so, the sample of the longitudinal survey will be a sub-sample of the 2018/19 household survey in each country.

For Mali, the survey which is implemented by the National Statistical Office (INSTAT), is conducted using cell phone numbers of household members collected during the 2018/19 survey. This has the advantage of conducting cost effectively welfare analysis without collecting new consumption data. The 35 minutes questionnaires covered 10 modules (knowledge, behavior, access to services, food security, employment, safety nets, shocks, etc…). Data collection is planned for six months (six rounds) and the questionnaire is designed with core modules and rotating modules. Survey data collection started on May 11th, 2020 and households are expected to be called back every three to four weeks.

The main objectives of the survey are to: • Identify type of households directly or indirectly affected by the pandemic; • Identify the main channels by which the pandemic affects households; • Provide relevant data on income and socioeconomic indicators to assess the welfare impact of the pandemic.

Geographic coverage

National coverage including rural and urban

Analysis unit

• Households
• Individuals

Universe

The survey covered only households of the 2018/19 survey which excluded populations in prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Mali COVID-19 impact monitoring survey is a high frequency Computer Assisted Telephone Interview (CATI). The survey’s sample was drawn from the population of the 2018/19 - Enquête Harmonisée des Conditions de Vie des Ménages (EHCVM) -, which was conducted between October 2018 and July 2019. EHCVM is itself a sample survey representative at national, regional and by urban/rural. For the 7,000 HHs in EHCVM, phone numbers were collected for about 90 percent of them. Each HH has between 1-4 phone numbers. The sampling, which was similar across WAEMU, aimed at having representative estimates by three zones: the capital city of Bamako, other urban areas and the rural area. The minimum sample size was 1,908 for which 1,766 were successfully interviewed, that is about 98 % of the expected minimal sample size at the national level. Given that Mali is conducting a phone survey for the first time, a total of 2,270 were drawn (25% increase) to take into account unknown non-response rates or presence of invalid numbers in the database.

The total number of completed interviews in round one is 1,766. The total number of completed interviews in round two is 1,935. The total number of completed interviews in round three is 1,901. The total number of completed interviews in round four is 1,797. The total number of completed interviews in round five is 1,766.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

All the interview materials were translated in french for the NSO. The questionnaire was administered in local languages with about varying length (30-35 minutes) and covered the following topics: 1- Household Roster 2- Knowledge of COVID-19 3- Behaviour and Social Distancing 4- Access to Basic Services 5- Employment and Income 6- Prices and Food Security 7- Other Impacts of COVID-19 8- Income Loss 9- Coping/Shocks 10- Social Safety Nets 11- Fragility 12- Governance and socio-political crisis

Cleaning operations

At the end of data collection, the raw dateset was cleaned by the NSO. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes.

Response rate

The minimum sample expected is 1,809 households (with 603 households per domain). This sample was therefore 99% covered for Bamako, about 100% for other urban areas and 91% for rural areas. Overall, the minimum sample is 98% covered. This level of coverage provides reliable data at national level and for each domain.

Round one response rate was 77.8%. Round two response rate was 85.2%. Round three response rate was 83.7%. Round four response rate was 79.2%. Round five response rate was 79.7%.

Ireland DE: Change in Market Income data was reported at -4,456.000 EUR mn in Dec 2021. This records an increase from the previous number of -5,247.000 EUR mn for Sep 2021. Ireland DE: Change in Market Income data is updated quarterly, averaging -5,829.000 EUR mn from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of -4,456.000 EUR mn in Dec 2021 and a record low of -6,411.000 EUR mn in Jun 2021. Ireland DE: Change in Market Income data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.F013: Potential Costs and Distributional Effect: COVID-19 Related Unemployment. [COVID-19-IMPACT]

These data were collected using the HEartS Professional China survey from performing arts workers in China in October 2020 and August 2021. HEartS Professional China is an adaptation of the HEartS Professional surveys which were used in 2020-2021. All the surveys were designed as multi-strategy data collection tools with two main purposes: (1) to chart working patterns, income, sources of support, and indicators of mental and social well-being to identify trends in the effects of the lockdown at the time and (2) to explore the individual work and wellbeing experiences of performing arts professionals in their own words, to identify the subjective effects of lockdown in terms of challenges and opportunities. The survey covers six areas: 1) demographics; (2) information on illness or self-isolation related to COVID-19; (3) work profiles and income; (4) changes to work profiles and income as a result of the pandemic, as well as sources of support; (5) open-response questions about work and wellbeing experiences of lockdown including challenges and opportunities; and (6) validated measures of health, wellbeing, and social connectedness. The HEartS Professional surveys are adaptations of the HEartS Survey which charts the Health, Economic, and Social impacts of the ARTs (https://doi.org/10.5061/dryad.3r2280gdj).

This research project mapped and monitored responses to household food insecurity during the COVID-19 pandemic.

During the COVID-19 pandemic, governments, local authorities, charities and local communities worked to ensure access to food for those facing new risks of food insecurity due to being unable to go out for food or due to income losses arising from the crisis. New schemes were developed, such as governments replacing incomes of people at risk of unemployment on account of lockdowns, providing food parcels for people asked to shield, referrals for people to receive voluntary help with grocery shopping, and free school meals replacement vouchers or cash transfers. These worked alongside existing provision for those unable to afford food – such as food banks – which have been adapting their services to continue to meet increasing demand from a range of population groups. This resulted in a complex set of support structures which developed and changed as the COVID-19 pandemic, and its impacts, evolved.

About the project

The project was funded by the Economic and Social Research Council (ESRC) through the UKRI Ideas to Address COVID-19 grant call and ran for two years from July 2020. The research aimed to provide collaborative monitoring and analysis of food support systems to inform food access policy and practice. The research team was led by the University of Sheffield and King’s College London alongside colleagues from Sustain: the alliance for better food and farming and Church Action on Poverty. Full details of the team are below. Collaboration with partners and stakeholders was at the heart of the project. The research team worked with stakeholders from national and local government, the civil service, third sector, NGOs as well as people who were accessing food and financial assistance during the pandemic.

The End of project summary of key findings were published in August 2022. Details of the workpackages and research reports can be found below.

Project work packages

Work package 1: National level food access systems mapping and monitoring

Looking at food access support across the UK during the COVID-19 pandemic, national level mapping and monitoring was undertaken in England, Northern Ireland, Scotland and Wales as well as at a UK level. National level stakeholders (for example from devolved governments and national voluntary organisations) from across the four nations worked with us to understand and monitor how support for food access has operated and evolved across the UK.

Work package 1 publications: Mapping responses to the risk of rising food insecurity during the COVID-19 crisis across the UK (published August 2020) Monitoring responses to the risk of rising food insecurity during the COVID-19 crisis across the UK (published December 2020) Mapping and monitoring responses to the risk of rising food insecurity during the COVID-19 crisis across the UK - Autumn 2020 to Summer 2021 (published August 2022)

Work package 2: Participatory Policy Panel

To fully understand food access responses, it was crucial to hear directly from those with lived experience of food insecurity during the pandemic. In partnership with Church Action on Poverty, we convened a participatory policy panel made up of people who have direct experience of a broad range of support to access food. Meeting regularly throughout the project (Oct 2020-Dec 2021), the panel used a range of participatory and creative methods to share and reflect on their experiences and contribute these to policy recommendations.

Work package 2 publications: Navigating Storms (published October 2021) Food Experiences During COVID-19 Participatory Panel Deliberative Policy Engagement (published August 2022) Food Experiences During COVID-19 - Participatory Methods in Practice: Key Learning (published August 2022)

Work package 3: Local area case studies

Fourteen local areas across the UK were the focus for more in depth case study research. Working with local stakeholders in each area, the research mapped what local responses looked like and how they operated. The research followed the developments in these areas throughout the duration of the project.

Work package 3 publications: Comparing local responses to household food insecurity during COVID-19 across the UK (March – August 2020) – Executive Summary (published July 2021) Comparing local responses to household food insecurity during COVID-19 across the UK (March – August 2020) (published July 2021). Eight local case study reports covering responses in those areas between March and August 2020: Argyll and Bute, Belfast, Cardiff, Derry and Strabane, Herefordshire, Moray, Swansea, West Berkshire (published July 2021). Local Area Case Studies – Methodological Appendix (published July 2021) Local responses to household food insecurity during COVID-19 across the UK (March – August 2020): Full report (published July 2021) Local responses to household food insecurity across the UK...

About this dataset

Context

The dataset tabulates the Antonito median household income by race. The dataset can be utilized to understand the racial distribution of Antonito income.

Content

The dataset will have the following datasets when applicable

Please note: The 2020 1-Year ACS estimates data was not reported by the Census Bureau due to the impact on survey collection and analysis caused by COVID-19. Consequently, median household income data for 2020 is unavailable for large cities (population 65,000 and above).

• Antonito, CO median household income breakdown by race betwen 2011 and 2021
• Median Household Income by Racial Categories in Antonito, CO (2021, in 2022 inflation-adjusted dollars)

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Interested in deeper insights and visual analysis?

Explore our comprehensive data analysis and visual representations for a deeper understanding of Antonito median household income by race. You can refer the same here

Abstract

In Chad, COVID-19 is expected to affect households in many ways. First, governments might reduce social transfers to households due to the decline in revenue arising from the potential COVID-19 economic recession. Second households deriving income from vulnerable sectors such as tourism and related activities will likely face risk of unemployment or loss of income. Third an increase in prices of imported goods can also negatively impact household welfare, as a direct consequence of the increase of these imported items or as indirect increase of prices of local good manufactured using imported inputs. In this context, there is a need to produce high frequency data to help policy makers in monitoring the channels by which the pandemic affects households and assessing its distributional impact. To do so, the sample of the longitudinal survey will be a sub-sample of the 2018/19 Enquête sur la Consommation des Ménages et le Secteur Informel au Tchad (Ecosit 4) in Chad.

This has the advantage of conducting cost effectively welfare analysis without collecting new consumption data. The 30 minutes questionnaires covered many modules, including knowledge, behavior, access to services, food security, employment, safety nets, shocks, coping, etc. Data collection is planned for four months (four rounds) and the questionnaire is designed with core modules and rotating modules.

The main objectives of the survey are to: • Identify type of households directly or indirectly affected by the pandemic; • Identify the main channels by which the pandemic affects households; • Provide relevant data on income and socioeconomic indicators to assess the welfare impact of the pandemic.

Geographic coverage

National coverage, including Ndjamena (Capital city), other urban and rural

Analysis unit

• Households
• Individuals

Universe

The survey covered only households of the 2018/19 Enquête sur la Consommation des Ménages et le Secteur Informel au Tchad (ECOSIT 4) which excluded populations in prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The Chad COVID-19 impact monitoring survey is a high frequency Computer Assisted Telephone Interview (CATI). The survey’s sample was drawn from the Enquête sur la Consommation des Ménages et le Secteur Informel au Tchad (Ecosit 4) which was conducted in 2018-2019. ECOSIT 4 is a survey with a sample size of 7,493 household’s representative at national, regional and by urban/rural. During the survey, each household was asked to provide a phone number of at least one member or a non-household member (e.g. friends or neighbors) so that they can be contacted for follow-up questions. The sampling of the high frequency survey aimed at having representative estimates by national and area of residence: Ndjamena (capital city), other urban and rural area. The minimum sample size was 2,000 for which 1,748 households (87.5%) were successfully interviewed at the national level. To account for non-response and attrition and given that this survey was the first experience of INSEED, 2,833households were initially selected, among them 1,832 households have been reached. The 1,748 households represent the final sample and will be contacted for the next three rounds of the survey.

Sampling deviation

None

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

The questionnaire is in French and has been administrated in French and local languages. The length of an interview varies between 20 and 30 minutes. The questionnaires consisted of the following sections: 1- Household Roster 2- Knowledge of COVID-19 3- Behavior and Social Distancing 4- Access to Basic Services 5- Employment and Income 6- Prices and Food Security 7- Other Impacts of COVID-19 8- Income Loss 9- Coping/Shocks 10- Social Safety Nets 11- Fragility 12. Gender based Violence (for the fourth wave) 13. Vaccine (for the fourth wave)

Cleaning operations

At the end of data collection, the raw dataset was cleaned by the INSEED with the support of the WB team. This included formatting, and correcting results based on monitoring issues, enumerator feedback and survey changes.

Response rate

The minimum sample expected is 2,000 households covering Ndjamena, other urban and rural areas. Overall, the survey has been completed for 1,748 households that is about 87.5 % of the expected minimal sample size at the national level. This provide reliable estimates at national and area of residence level.

Attitudes towards the Coronavirus (COVID-19) pandemic. Topics: satisfaction with the national government in general; satisfaction with the measures of the national government to fight the Coronavirus pandemic; preferred statement with regard to the consequences of the restriction measures in the own country: health benefits are greater than economic damage, economic damage is greater than health benefits; satisfaction with solidarity between EU member states in fighting the Coronavirus pandemic; awareness of measures taken by the EU to respond to the Coronavirus pandemic; satisfaction with these measures; EU should have more competences to deal with crises such as the Coronavirus pandemic; preferred EU measures to respond to the Corona crisis; preferred statement: EU should have greater financial means to be able to overcome the consequences of the Coronavirus pandemic, EU has sufficient financial means to be able to overcome the consequences of the Coronavirus pandemic; preferred fields on which to spend most of the EU budget on; EU should only provide funds to Member States conditional upon their government’s implementation of the rule of law and of democratic principles; attitude towards the appropriateness of EU measures to make its economy climate neutral by 2050; importance to put EU core values as a priority in its relations with major international actors; preferred statement: fight against the Coronavirus pandemic fully justifies recent limitations to individual freedom, fully opposed to any limitation of individual freedom regardless of the pandemic; current emotional status; personally experienced effects of the Coronavirus pandemic in the own country: loss of income, difficulties paying rent or bills or bank loans, use of personal savings sooner than planned, unemployment, bankruptcy, difficulties having proper and decent-quality meals, asked for financial help to family or friends, other financial issues; impact of the Coronavirus pandemic on personal income; use of selected online social networks in the last week; attitude towards the European Union; EU image; impact of the pandemic on EU image; participation in the last elections to the European Parliament. Demography: sex; age; age at end of education; head of household; occupation of main income earner in the household; professional position of main income earner in the household; employment status; marital status; household composition and household size; region. Additionally coded was: respondent ID; country; date of interview; weighting factor. Einstellungen zur Corona-Pandemie (COVID-19). Themen: Zufriedenheit mit der nationalen Regierung im Allgemeinen; Zufriedenheit mit den Maßnahmen der nationalen Regierung zur Bekämpfung der Corona-Pandemie; präferierte Aussage im Hinblick auf die Konsequenzen der beschlossenen Einschränkungen im eigenen Land: gesundheitlicher Nutzen ist größer als der wirtschaftliche Schaden, wirtschaftlicher Schaden ist größer als der gesundheitliche Nutzen; Zufriedenheit mit der Solidarität unter den EU-Mitgliedstaaten bei der Bekämpfung der Corona-Pandemie; Kenntnis über Maßnahmen der EU zur Bewältigung der Corona-Pandemie; Zufriedenheit mit diesen Maßnahmen; EU sollte mehr Kompetenzen im Umgang mit Krisen wie der Corona-Pandemie haben; präferierte EU-Maßnahmen zur Bewältigung der Corona-Krise; präferierte Aussage: EU sollte mehr finanzielle Mittel zur Bewältigung der Auswirkungen der Coronavirus-Pandemie zur Verfügung haben, EU hat ausreichend finanzielle Mittel zur Bewältigung der Auswirkungen der Coronavirus-Pandemie zur Verfügung; präferierte Bereiche, für die der größte Teil des Haushalts ausgegeben werden sollte; EU sollte finanzielle Unterstützung von Mitgliedstaaten von der Implementierung rechtsstaatlicher und demokratischer Prinzipien abhängig machen; Einstellung zur Angemessenheit der EU-Maßnahmen in Bezug auf das Erreichen des Ziels einer klimaneutralen Wirtschaft bis 2050; Wichtigkeit, die EU-Grundwerte prioritär in die Beziehungen zu wichtigen internationalen Akteuren einzubringen; präferierte Aussage: Kampf gegen die Corona-Pandemie rechtfertigt die kürzlichen Einschränkungen der individuellen Freiheit vollkommen, Ablehnen jeglicher Einschränkungen der individueller Freiheit unabhängig von der Pandemie; derzeitiger Gefühlszustand; persönliche Erfahrungen mit den Auswirkungen der Corona-Pandemie im eigenen Land: Einkommensverlust, Schwierigkeiten bei der Bezahlung von Mieten oder Rechnungen oder Darlehen, Verwendung von Ersparnissen früher als geplant, Arbeitslosigkeit, Konkurs, keine vernünftigen Mahlzeiten, Bitte um finanzielle Unterstützung durch Familie oder Freunde, andere finanzielle Angelegenheiten; Auswirkung der Coronavirus-Pandemie auf das persönliche Einkommen; Nutzung ausgewählter sozialer Netzwerke im Internet in der letzten Woche; Einstellung zur Europäischen Union; Image der EU; Auswirkungen der Pandemie auf das Image der EU; Teilnahme an den letzten Europawahlen. Demographie: Geschlecht; Alter; Alter bei Beendigung der Ausbildung; Haushaltsvorstand; Beruf des Haupteinkommensbeziehers im Haushalt; berufliche Stellung des Haupteinkommensbeziehers im Haushalt; Beschäftigungsstatus; Familienstand; Haushaltszusammensetzung und Haushaltsgröße; Region. Zusätzlich vercodet wurde: Befragten-ID; Land; Interviewdatum; Gewichtungsfaktor.

Ireland DE: Change in Personal Income Tax Revenue data was reported at -1,117.000 EUR mn in Dec 2021. This records an increase from the previous number of -1,298.000 EUR mn for Sep 2021. Ireland DE: Change in Personal Income Tax Revenue data is updated quarterly, averaging -1,225.000 EUR mn from Mar 2021 (Median) to Dec 2021, with 4 observations. The data reached an all-time high of -1,117.000 EUR mn in Dec 2021 and a record low of -1,342.000 EUR mn in Mar 2021. Ireland DE: Change in Personal Income Tax Revenue data remains active status in CEIC and is reported by Economic and Social Research Institute. The data is categorized under Global Database’s Ireland – Table IE.F013: Potential Costs and Distributional Effect: COVID-19 Related Unemployment. [COVID-19-IMPACT]

SIA118 - Impact of COVID-19 supports on Poverty Rates. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).Impact of COVID-19 supports on Poverty Rates...

These datasets contain the results of three surveys carried out in Paraguayan border cities (Asunción, Ciudad del Este and Encarnación) to inquire about the socioeconomic consequences of the COVID-19 pandemic and its containment measures. They provide information regarding employment relations, impacts on household income, incidence of COVID-19 infections, home-schooling, State aid and community organizing, border relations, care and domestic work, as well as views on lockdown measures.

The surveys are part of the project "Consequences of the Covid-19 crisis on Social Inequalities and Convivial Relations in Three Paraguayan Border Cities", which also applied qualitative methods by carrying out focus-groups with residents of Asunción, Ciudad del Este and Encarnación. The following questions guided the research: To what extent has access to protection measures against COVID-19 been affected by regional differences and/or hierarchies based on gender and class? How have containment measures (different stages of lockdown and mobility restrictions) affected income, access to education and other basic services, as well as the general well-being of the population, considering regional, gender, and class differences? What repercussions have the containment measures had within households, considering the distribution of domestic and care work, as well as the use of domestic space? What differences can be identified between households occupying different positions in the social structure? What impact have containment measures had on community relations, considering geographical and social differences?

By focusing on Paraguay, the project enables a deeper understanding of how people in countries with high levels of inequality, elevated degrees of informality and lack of social security were affected by COVID-19 containment measures, and how the population organized to cope with these difficult circumstances.

The datasets (in SPSS, one per city) are in Spanish. For ease of use, we provide a description of the variables in English in a separate file. The original questionnaire and a translation into English, as well as a document with technical information on the sampling method, expansion factors and social stratification model are also available for download.

These data were collected using the HEartS Professional Survey from performing arts workers in the United Kingdom in April–June 2020. HEartS Professional was designed as a multi-strategy data collection tool with two main purposes: (1) to chart working patterns, income, sources of support, and indicators of mental and social wellbeing in order to identify trends in the effects of the lockdown at the time and (2) to explore the individual work and wellbeing experiences of performing arts professionals in their own words, in order to identify the subjective effects of lockdown in terms of challenges and opportunities. The survey covers six areas: (1) demographics, (2) information on illness or self-isolation related to COVID-19, (3) work profiles and income, (4) changes to work profiles and income as a result of the pandemic, as well as sources of support, (5) open-response questions about work and wellbeing experiences of lockdown including challenges and opportunities, and (6) validated measures of health, wellbeing, and social connectedness. HEartS Professional is an adaptation of the HEartS Survey which charts the Health, Economic, and Social impacts of the ARTs (https://doi.org/10.5061/dryad.3r2280gdj).

Methods The sample was recruited through an online data collection platform, Qualtrics, from 1 April to 15 June 2020. 784 respondents started the survey and 447 completed it. Here we include the subset (n=385) of completed surveys that worked in the two performing arts areas: Music or sound arts (e.g. professional musician) and/or Performing arts (e.g. professional actor, dancer, circus performer etc.). The survey contains the following sections:

Demographic and socioeconomic information: Where available standardised Census questions were used to collect data on ethnicity, geographic region, highest educational qualifications, gender, age, and household composition and income. Illness or self-isolation related to Covid-19: Newly created questions. Work profiles and income: Newly created questions. Changes to work profiles and income as a result of the pandemic and sources of support: Newly created questions and Inclusion of Other in Self Scale. Open-response questions about work and wellbeing experiences of lockdown, including challenges and opportunities: Newly created questions (NB. data for the open questions are not included for confidentiality reasons). Measures of health, wellbeing, and social connectedness: The following validated and previously used measures are included

Mental Health Continuum Short Form 14-item scale Centre for Epidemiologic Studies Depression (CES-D) Short Form 8-item scale Self-rated General Health item (from SF-36) Physical activity scale recording mild, moderate, and vigorous physical activity frequency (from Whitehall II Study) Social Connectedness Revised 15-item scale

UCLA Three-item Loneliness Scale, Single item loneliness question De Jong Gierveld Loneliness Short Form 6-item scale 1-item questions on loneliness frequency and loneliness intensity

More information is provided in the Variables tab in the dataset.

ISE09 - COVID-19 Income Supports on Employees. Published by Central Statistics Office. Available under the license Creative Commons Attribution 4.0 (CC-BY-4.0).COVID-19 Income Supports on Employees...

According to a survey conducted towards the end of March 2020, 31 percent of respondents residing in G7 countries have already had their household income impacted by the coronavirus pandemic (COVID-19).