Abstract

The COVID-19 web survey has been utilized to track American attitudes on topics related to the COVID-19 pandemic, including well-being. The survey began fielding on March 13, 2020, with daily random samples of U.S. adults, aged 18 and older, who are members of the Gallup Panel. Approximately 1,200 daily completes were collected from March 13 through April 26, 2020. From April 27 to August 16, 2020, approximately 500 daily completes were collected. Starting August 17, 2020, the survey moved from daily surveying to a survey conducted one time per month over a two-week field period (typically the last two weeks of the month). Beginning in 2022, the COVID survey moved to quarterly data collection.

The Gallup Panel COVID-19 Survey table includes survey responses from March 2020 through Q1 2023. Starting in Q2 2023, the original COVID-19 survey was narrowed down to serve as a wellbeing-focused survey (see Gallup Panel Wellbeing Survey table).

Methodology

Results for this Gallup poll are based on self-administered web surveys conducted with a random sample of U.S. adults aged 18 and older, who are members of the Gallup Panel. The survey was conducted in English. Individuals without Internet access were not covered by this study.

The Gallup Panel is a probability-based, nationally representative panel of U.S. adults. Members are randomly selected using random-digit-dial phone interviews that cover landline and cellphones and address-based sampling methods. The Gallup Panel is not an opt-in panel.

Gallup weights the obtained samples each day to adjust for the probability of select and to correct for nonresponse bias. Nonresponse adjustments are made by adjusting the sample to match the national demographics of gender, age, race, Hispanic ethnicity, education and region. Demographic weighting targets are based on the most recent Current Population Survey figures for the aged-18-and-older U.S. population. Respondents receive a small post-paid incentive of $1 incentive for completing the survey.

Bulk Data Access

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Abstract

In the West Africa Economic Monetary Union (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 is a sub-sample of the Enquête Harmonisée sur les Conditions de Vie des Ménages (EHCVM), a harmonized household survey conducted in 2018/19 household survey in the WAEMU countries.

For Burkina Faso, the survey, which is implemented by the Institut National de la Statistique et la Demographie (INSD), is conducted using cell phone numbers of household members collected during the 2018/19 EHCVM survey. The extensive information collected in the EHCVM provides a rich set of background information for the COVID-19 High Frequency Phone Survey of households. This background information can be leveraged to assess the differential impacts of the pandemic in the country. Every month, the sampled households will be asked a set of core questions on the key channels through which individuals and households are expected to be affected by the COVID-19-related restrictions. Employment, access to basic services, non-labor sources of income are channels likely to be impacted. The core questionnaire is complemented by questions on selected topics that rotate each month. This provides data to the government and development partners in near real-time, supporting an evidence-based response to the crisis.

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.

Phase 1 was conducted on a monthly basis during the period of June 2020 and July 2021 for11 Rounds. Phase 2 (starting from Round 12) was conducted on a bi-monthly basis starting in April 2022. Phase 3 (starting from Round 18) will be conducted on a bi-monthly basis, starting in July 2023.

Geographic coverage

National coverage, including Ouagadougou, rural and other urban

Analysis unit

• Households
• Individuals

Universe

The survey covered a sub-sample of the households of the 2018/19 - Enquête Harmonisée sur le Conditions de Vie des Ménages (EHCVM) survey which excluded populations in prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample of the HFS is a subsample of the 2018/19 Harmonized Living Conditions Household Survey (EHCVM). The EHCVM 2018/19 is built on a nationally and regionally representative sample of households in Burkina Faso. EHCVM 2018/19 interviewed 7,010 households in urban and rural areas. In the EHCVM interview, households were asked to provide phone numbers of the household head, or a household member, or a non-household member (e.g. friends or neighbors) so that they can be contacted for follow-up questions. At least one valid phone number was obtained for 6877 households. These households established the sampling frame for the HFS. To obtain representative strata at the national, capital (Ouagadougou), urban, and rural level, the target sample size for the HFS is 1,800 household (assuming a 50% non-response rate the minimum required sample is 1479). To account for non-response and attrition, 2500 households were called in baseline round of the HFS. 1,968 households were fully interviewed during the first round of interviews. Those 1,968 households constitute the final successful sample and will be contacted in subsequent rounds of the survey.

In addition to the 1,968 households successfully interviewed in Round 1, in Round 2, 242 additional households were sampled from the rural strata, in order to increase the representativeness in this domain. In Round 12, 231 additional households were selected from the rural stratum from the 2018/19 EHCVM sample. In Round 18, 858 additional households were selected from panel component of the 2021/22 EHCVM sample.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

BASELINE (Round 1): The Household Questionnaire provides information on demographics; knowledge regarding the spread of COVID-19; behavior and social distancing; access to basic services; employment.

Round 2: Household Roster; Access to Basic Services; Employment (with a focus on non-farm enterprises); Food Security; Shocks; Fragility, conflict, and violence.

Round 3: Household Roster; Knowledge regarding the spread of COVID-19; Behavior and social distancing; Access to Basic Services; Employment (with a focus on farm household activities); Food Security; Other revenues; Social protection.

Round 4: The following modules were administered in Round 4: Household Roster; Access to Basic Services; Credit; Employment and revenue (with a focus on livestock activities); Food Security; Other revenues; Shocks; Fragility, Conflict and Violence.

Round 5: Household Roster; Knowledge regarding the spread of COVID-19; Behavior and social distancing; Access to Basic Services; Education at individual level; Employment; Food Security; Other revenues; Social protection.

Round 6: Household Roster; Access to Basic Services; Education; Employment and revenues (with a focus on harvest activities and revenues from crop selling); Food Security; Other revenues; Shocks; Fragility, conflict and violence.

Round 7: Household Roster; Access to Basic Services; Education; Employment and revenues (with a focus on harvest activities and revenues from crop selling); Food Security; Other revenues; Shocks; Fragility, conflict and violence.

Round 8: Household Roster; Early Child Development; Access to Basic Services; Employment and revenues; Food Security; Other revenues; Shocks; Fragility, conflict and violence.

Round 9: Household Roster; Access to Basic Services; Employment and revenues; Food Security and Other revenues.

Round 10: Household Roster; Mental health; Knowledge regarding the spread of COVID-19; Behavior and social distancing; Covid-19 Testing and Vaccination; Access to Basic Services; Credit; ; Employment and revenue (with a focus on livestock activities); Food Security; Other revenues; Shocks; Concerns regarding the impact of COVID-19 on personal health and financial wealth of the household; Fragility, Conflict and Violence

Round 11: Household basic information; Access to Basic Services; Employment and revenue (with a focus on agricultural activities); Food Security; Other revenues; Concerns regarding the current situation; Social Safety Nets.

Round 12: Household Roster; Covid-19 Vaccination; Access to Health Care; and Employment and Income.

Round 13: Household Roster; Access to Health Care; Credit; Employment and Income; Food Security; Other Revenues; and Economic Sentiments.

Round 14: Household Roster; Access to Health Care; Vaccination; Concerns; Economic Sentiments.

Round 15: Household Roster; Displacement; Education; Access to basic foodstuffs; Employment and Income; Food Security; Other Revenues; Economic Sentiments; Items Price.

Round 16: Household Roster; Access to Health Care; Vaccination; Agriculture; Livestock; Shocks; Climate Change; Economic Sentiments; Items Price.

Round 17: Household Roster; Access to Basic Foodstuffs; Access to HealthCare – individual level; Credit; Employment and Income; Food Security; and Other Revenues.

Round 18: Household Roster; Access to Basic Goods and Services; Access to Health Care – individual level; Price of items; Employment and Income; Food Security; Food Consumption Score; Economic Sentiments; and Subjective Welfare.

Round 19: Household Roster; Access to Basic Goods and Services; Access to Health Care – individual level; Price of items; Employment and Income; Food Security; Shocks; Food Consumption Score; Economic Sentiments; and Subjective Welfare.

Round 20: Households Roster; Access to basic goods and services; Access to Health Care - Individual level; Price ofItems; Employment and Income; Food Security; Food Consumption Score; Economic Sentiments; SubjectiveWelfar.

Round 21: Household Roster; Access to Basic Goods and Services; Education; Price of items; Employment and Income; Agriculture; Livestock; Food Security; Food Consumption Score; Economic Sentiments; Subjective Welfare.

Round 22: Household Roster; Household Mobility; Access to Basic Goods and Services; Price of items; Access to Health Care - individual level; Employment and Income; Food Security; Food Consumption Score; Shocks; Economic Sentiments; and Subjective Welfare.

Round 23: Household Roster; Access to Basic Goods and Services; Price of items; Employment and Income; Food Security; Food Consumption Score; Economic Sentiments; and Subjective Welfare.

All the interview materials were translated in French for the INSD. The questionnaire was administered in local languages with about varying length (about 25 minutes).

Cleaning operations

At the end of data

Abstract

The COVID-19 Socioeconomic-/Cash-Based Intervention Post-Distribution Monitoring (CBI PDM) was conducted in September 2021 to assess the needs of the refugees in Eastern Nepal and Kathmandu. The survey consists of two parts. The first part of the survey measures the impact of COVID-19 on refugees' knowledge, behavior and health as well as refugees' economic livelihoods and the second part monitors the latest cash assistance programme. As a response to COVID-19, UNHCR has since the start of the pandemic launched multiple new cash grants and expanded existing programs. UNHCR's cash assistance complements governments' efforts by contributing with an additional safety net for vulnerable refugees and others left behind. Also during the course of 2021, UNHCR has continued to support the COVID-19 emergency response with cash assistance. UNHCR uses PDM as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of the recipients.

Geographic coverage

The survey covers Eastern Nepal (Pathari sanichare and Beldangi refugee camps) and refugees living in Kathmandu.

Analysis unit

Households

Universe

The sample universe covers all urban refugee households (239) living in Kathmandu as well as all 2,409 Bhutanese refugee households living in Pathari sanichare and Beldangi camps.

Kind of data

Sample survey data [ssd]

Sampling procedure

Stratified random sampling was implemented drawing two samples seperately for urban and Bhutanese (camp) refugees.

Mode of data collection

Self-administered questionnaire: E-mail

Abstract

To monitor the socioeconomic impacts of the coronavirus disease 2019 (COVID-19) pandemic and inform policy responses and interventions, the COVID-19 High-Frequency Phone Survey (HFPS) of households was designed as part of a World Bank global initiative. For Cambodia, a total of 5 survey rounds are planned, with households being called back every 1 to 2 months. This allows for the impact of the pandemic to be tracked as it unfolds and provides data to the government and development partners in near real-time, supporting an evidence-based response to the crisis.

In June 2020, Cambodia launched a Cash Transfer Program to support poor and vulnerable households during COVID-19. To more closely monitor the impact of COVID-19 among poor and vulnerable households in Cambodia and the impact of the Cambodia's Cash Transfer Program for Poor and Vulnerable Households during COVID-19, a sample of 1,000 IDPoor households was drawn for the phone survey from the beneficiary list of the conditional cash transfer for pregnant women and children under 2.

The questionnaire covers a series of topics, such as knowledge of Covid-19 and social behavior, access to food, food insecurity, impact of the Covid-19 on income sources and coping mechanisms, access to social assistance, and impact of Covid-19 on economic activity. A modular approach is used in the questionnaire design, which allows for modules to be dropped and/or added in different waves/rounds of the survey. The questionnaire is designed to be administered between 20 to 25 minutes.

Data collection for the first round started in June 2020. The survey is implemented using Computer Assisted Telephone Interviewing.

Geographic coverage

National coverage and 5 geographical regions (Phnom Penh and other urban areas, Plains, Tonle Sap, Coastal, Plateau and Mountains).

Analysis unit

• Households
• Individuals

Universe

The survey covered all de jure households (with a phone number) excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The beneficiary list of the conditional cash transfer program for pregnant women and child under 2 was assigned into 5 strata i.e. Phnom Penh and other urban areas, Plain, Tonle Sap, Coastal, Plateau and Mountain. The sample was randomly selected with proportional to the size of the IDPoor households in each strata. The phone survey successfully interviewed 984 households in June (Round 1). In August (Round 2), 784 households have been re-interviewed and 271 replacement households were added. Of these, 841 were successfully reached again in October (Round 3), with 527 interviewed in all three rounds. In December, 1,277 households were successfully interviewed, of which 945 households were re-contacted and 332 households were added as replacement households. In March 2021, 1,309 households were interviewed, of which 991 households were re-interviewed and 318 households were replacement households. In February 2022, 812 households were successfully interviewed while only 801 households were interviewed in April 2022.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The Cambodia COVID-19 High Frequency Phone Survey of households questionnaire consists of the following sections:

Round 1 - Interview Information - Household Roster - Social Economic Status - Knowledge Regarding the Spread of COVID-19 - Behavior and Social Distancing - Access to Basic Services - Employment - Income Loss - FIES - Shocks and Coping - Safety Nets

Round 2 - Interview Information - Household Roster - Migration - Access to Basic Services - Employment - Income Loss - FIES - Safety Nets - Relief Transfer

Round 3 - Interview Information - Household Roster - Social Economic Status - Knowledge Regarding the Spread of COVID-19 - Access to Basic Services - Employment - Income Loss - FIES - Safety Nets - Relief Transfer

Round 4 - Interview Information - Household Roster - Social Economic Status - Access to Basic Services - Employment - Income Loss - FIES - Shocks and Coping - Safety Nets - Relief Transfer - Payment Method

Round 5 - Interview Information - Household Roster - Social Economic Status - Access to Basic Services - Employment - Income Loss - FIES - Safety Nets - Relief Transfer

Round 6 - Interview Information - Household Roster - Social Economic Status - Access to Basic Services - Employment - Income Loss - FIES - Shocks and Coping - Safety Nets - Relief Transfer - Education - SWIFT

Round 7 - Interview Information - Household Roster - Social Economic Status - Disability - Access to Basic Services - Employment - Income Loss - FIES - Shocks and Coping - Safety Nets - Relief Transfer - Education - SWIFT

Cleaning operations

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

Only households that consented to being successfully interviewed were kept in the dataset, and all personal information and internal survey variables were dropped from the clean dataset.

Response rate

Replacement sampling approach was applied to reach the target sample.

The COVID-19 pandemic has dramatically altered family life in the United States. Over the long duration of the pandemic, parents had to adapt to shifting work conditions, virtual schooling, the closure of daycare facilities, and the stress of not only managing households without domestic and care supports but also worrying that family members may contract the novel coronavirus. Reports early in the pandemic suggest that these burdens have fallen disproportionately on mothers, creating concerns about the long-term implications of the pandemic for gender inequality and mothers’ well-being. Nevertheless, less is known about how parents’ engagement in domestic labor and paid work has changed throughout the pandemic, what factors may be driving these changes, and what the long-term consequences of the pandemic may be for the gendered division of labor and gender inequality more generally. The Study on U.S. Parents’ Divisions of Labor During COVID-19 (SPDLC) collects longitudinal survey data from partnered U.S. parents that can be used to assess changes in parents’ divisions of domestic labor, divisions of paid labor, and well-being throughout and after the COVID-19 pandemic. The goal of SPDLC is to understand both the short- and long-term impacts of the pandemic for the gendered division of labor, work-family issues, and broader patterns of gender inequality. Survey data for this study is collected using Prolifc (www.prolific.co), an opt-in online platform designed to facilitate scientific research. The sample is comprised U.S. adults who were residing with a romantic partner and at least one biological child (at the time of entry into the study). In each survey, parents answer questions about both themselves and their partners. Wave 1 of SPDLC was conducted in April 2020, and parents who participated in Wave 1 were asked about their division of labor both prior to (i.e., early March 2020) and one month after the pandemic began. Wave 2 of SPDLC was collected in November 2020. Parents who participated in Wave 1 were invited to participate again in Wave 2, and a new cohort of parents was also recruited to participate in the Wave 2 survey. Wave 3 of SPDLC was collected in October 2021. Parents who participated in either of the first two waves were invited to participate again in Wave 3, and another new cohort of parents was also recruited to participate in the Wave 3 survey. This research design (follow-up survey of panelists and new cross-section of parents at each wave) will continue through 2024, culminating in six waves of data spanning the period from March 2020 through October 2024. An estimated total of approximately 6,500 parents will be surveyed at least once throughout the duration of the study. SPDLC data will be released to the public two years after data is collected; Waves 1 and 2 are currently publicly available. Wave 3 will be publicly available in October 2023, with subsequent waves becoming available yearly. Data will be available to download in both SPSS (.sav) and Stata (.dta) formats, and the following data files will be available: (1) a data file for each individual wave, which contains responses from all participants in that wave of data collection, (2) a longitudinal panel data file, which contains longitudinal follow-up data from all available waves, and (3) a repeated cross-section data file, which contains the repeated cross-section data (from new respondents at each wave) from all available waves. Codebooks for each survey wave and a detailed user guide describing the data are also available.

In a May 2020 survey of U.S. registered voters, over 63 percent of respondents indicated that nursing homes and assisted living facilities needed more money to respond to the threat that COVID-19 poses to the seniors they serve. This statistic shows opinions on the financial needs of nursing homes for responding to the threat of coronavirus in the U.S., May 2020.

In 2019, the National Survey of Early Care and Education (NSECE) team conducted a set of four integrated surveys of 1) households with children under age 13, 2) home-based providers, 3) center-based providers, and 4) the center-based workforce as a cross-sectional follow-up to the original 2012 NSECE. Together they characterize the supply of and demand for early care and education (ECE) in the U.S. and permit better understanding of how well families' needs and preferences mirror providers' offerings and constraints. The NSECE surveys make particular effort to measure the experiences of low-income families, as these families are the focus of a significant component of ECE and school-age public policy. In light of the onset of the COVID-19 pandemic in Spring 2020, the Office of Planning, Research, and Evaluation (OPRE) funded a new data collection effort beginning in 2020 to learn how the pandemic was affecting ECE providers and the individuals who work directly with children in ECE settings. The NSECE project team sought to re-interview center-based providers, center-based workforce members, listed home-based providers, and unlisted and paid home-based providers, who completed surveys in the 2019 NSECE. Households participating in the 2019 NSECE were not included in the NSECE COVID-19 Longitudinal Follow-up. Data collection for the NSECE COVID-19 Longitudinal Follow-up took place across two waves between late 2020 and early 2022. The NSECE was first conducted in 2012. Before that effort, there had been a 20-year long absence of nationally representative data on the use and availability of ECE. The NSECE was conducted again in 2019 to update the information from 2012 and shed light on how the ECE and school-age care landscape changed from 2012 to 2019. The 2019 NSECE followed a similar design as the 2012 survey, including surveying households with children under age 13, home-based providers, center-based providers, and staff working in center-based classrooms. The 2019 NSECE is funded by the Office of Planning, Research, and Evaluation (OPRE) in the Administration for Children and Families (ACF), U.S. Department of Health and Human Services (HHS). The project team is led by NORC at the University of Chicago, with partners Chapin Hall at the University of Chicago and Child Trends, as well as other collaborating individuals and organizations. For additional information about this study, please see: NSECE project page on the OPRE website NSECE study page on NORC's website NSECE Data Users Page For more information, tutorials, and reports related to the NSECE, please visit the Child and Family Data Archive's Data Training Resources from the NSECE page.

Background SARS-CoV-2 vaccines have significantly reduced human and economic losses. Nevertheless, vaccine hesitancy remains a major issue in many countries, including Germany. Recent studies have shown that public health framing and incentives can boost immunization rates. However, available evidence is fragmented and inconclusive regarding the effectiveness of different framing messages, types of incentives, and the size of financial incentives across different populations. Methods This randomized, controlled survey experiment elicited the attitudes of 6,685 Germans towards 4 financial/non-financial SARS-CoV-2 immunization incentives (food voucher, football tickets, participation in lottery, immediate monetary compensation), and tested whether framing (individual/collective, health/economic consequences) affected said attitudes. We assigned participants to five study arms (control: no frame; experiment: 1 of 4 frames) and measured attitudes towards immunization incentives, and the amount of monetary compensation deemed appropriate, should such an incentive be considered. Results While >75% of our sample considered all 4 incentives to be not meaningful, all frames increased favorable views towards the financial incentives lottery/money and the average amount deemed acceptable for immediate monetary compensation. Interaction models showed that all frames have similar effects across core subgroups, e.g. age-cohorts, gender, vaccine doses. Conclusions Across a sample of 6,685 Germans, we show that 4 different frames detailing the potential individual/collective consequences of COVID-19 have very similar effects on attitudes towards monetary incentives for SARS-CoV-2 immunization. Our results suggest that the existence of frames rather than specific narratives is key to increasing favorable views towards immunization incentives.

BackgroundsVaccination remains one of the most effective ways to protect populations from COVID-19 infection, severe conditions, and death. This study aims to examine whether the gain/loss-framing of information, provision of subsidized pre-vaccination physician consultation, and cash incentives can improve COVID-19 acceptance amongst adults.MethodsA survey experiment was conducted within a broader cross-sectional survey of people aged 18–64 years in Hong Kong, China. The participants were randomly assigned to one of the eight groups derived from full-factorial design of the three strategies with stratification by age and sex. The vaccine acceptance rate was compared between people with and without any of the strategies. The heterogeneous effects of these strategies were identified for those with different perceptions of the pandemics and vaccine in multiple logistic regressions.ResultsThe survey experiment collected 1,000 valid responses. It found that loss-framed information and provision of subsidized physician consultation to assess suitability to be vaccinated, can improve vaccine acceptance, while cash incentives did not make a difference. The improvement effect of loss-framing information and physician consultation is stronger among those with higher perceived infection risk and severity of condition, as well as unvaccinated people with lower confidence in vaccine safety.ConclusionsThe findings indicated that individualized loss-framing messages and equitable provision of subsidized pre-vaccination physician consultations can be incorporated in efforts to promote vaccine acceptance and vaccination roll-out speed. However, it remains inconclusive whether and how universal cash incentives may be deployed to support vaccination promotion.

Abstract

To support the urban poor during the COVID-19 crisis, the UK government provided a monthly Cash Transfer (CT) of 4,000 Kenyan Shillings (KSH) (or £27) to approximately 52,000 vulnerable people living in informal settlements in Nairobi and Mombasa over a period of three months. The COVID-19 CT was implemented by a consortium led by GiveDirectly, and the monthly stipend was paid using mobile money transfers, with the first transfers taking place from October 2020. The CT was designed to support beneficiaries to buy food or meet other high-priority needs-such as purchasing water, paying for medical care, or making rent payments as well as to reduce the use of negative coping strategies (e.g., selling assets, borrowing money).

OPM was contracted to conduct the monitoring and evaluation of the COVID-19 CT. The main objective of this evaluation was to determine whether, and to what extent, the emergency COVID-19 CT had a positive effect on its target population in informal urban settlements in Kenya. The evaluation also provided an assessment of the implementation parameters and mechanisms adopted as part of the design and delivery of the COVID-19 CT.

To fulfil these aims, the evaluation was structured around two separate components-an impact evaluation and a process review-and drew on multiple research methods through a mixed methods research framework. The objective of the quantitative impact evaluation was to assess whether the COVID-19 CT has had an impact on its beneficiaries, and to quantify the scale of any effect detected. This estimation of impact was based on a longitudinal non-experimental design, focusing on a panel of beneficiaries interviewed at three points in time (baseline - prior to the intervention, midline, and endline - post-intervention) over the course of the implementation period. All quantitative data collection took place remotely using Computer-Assisted Telephone Interview (CATI) software.

Geographic coverage

Nairobi and Mombasa in Kenya

Analysis unit

Individuals Households

Universe

The study population consists of individuals included in the lists of enrolled beneficiaries covered by Give Directly for the COVID-19 CT.

Sampling procedure

The evaluation team implemented a stratified one-stage probability sampling strategy for the selection of survey respondents from the individuals included in the lists covered by Give Directly for the COVID-19 CT. The goal was to select at baseline a sample of 1,000 eligible individuals who would receive the COVID-19 CT, which would then be interviewed by the evaluation team at baseline, midline, and endline.

The sampling strategy considered the following process:

1) The sample was drawn once the COVID-19 CT beneficiaries were considered as enrolled into the intervention. After discussions with Give Directly, it was decided that an individual was considered a future COVID-19 CT recipient when he/she had responded to the short SMS-based survey delivered by Give Directly.

2) The sample was drawn in two separate batches. The first batch of recipients comprised 6,838 vulnerable individuals from informal settlements in Nairobi, while the second batch contained 1,596 vulnerable individuals from Mombasa. We sampled the same number of beneficiaries from the first and second batches (500 individuals from each batch).

3) Explicit stratification was first applied based on the geographical location of the COVID-19 CT recipient. This entailed that we sample 500 individuals from Nairobi from the first batch, and 500 from Mombasa from the second batch. This allowed us to disaggregate our quantitative findings between Nairobi and Mombasa, and produce informative descriptive and regression analyses for each of the two cities included in the intervention.

4) Implicit stratification was then applied based on the following categorical variables: i) local partner from which the eligible beneficiary was selected, and ii) gender of the COVID-19 CT recipient. The goal of this stratification process was to enhance the representativeness of our sample in terms of these variables, so that our evaluation sample resembled as much as possible the distribution of these characteristics in the target population (i.e. the list of beneficiaries of the COVID-19 CT used as sampling frame for our sample).

5) We did not cluster our survey respondents. Apart from spill-over effect issues, which were not a concern due to the lack of a counterfactual in our methodological approach, this is normally a logistical necessity for in-person surveys. This was not an issue either, given the remote nature of the data collection process.

6) Extensive replacement lists were created to maximise efficiency during survey implementation without sacrificing representativeness of the sample. A detailed replacement protocol was elaborated, which took into account the stratification process described above.
Given the longitudinal nature of the evaluation, the same baseline respondents were tracked and re-interviewed at midline and endline so as to create a panel of survey respondents.The final baseline quantitative survey sample achievement is shown below, including the distribution by county

Sample achievement Baseline Survey Nairobi 500 Mombasa 500 Total 1,000

Midline Survey Nairobi 483 Mombasa 489 Total 972

Endline Survey Nairobi 463 Mombasa 478 Total 941

Mode of data collection

Computer Assisted Telephone Interviewing (CATI)

As of July 2020, more than ** percent of Indonesians surveyed believed that the government's cash and food assistance during the coronavirus (COVID-19) pandemic were ineffective. This was a decrease from the previous survey period, during which about ** percent of respondents stated that they found the cash and food assistance to be ineffective. Meanwhile, the share of respondents who were of the opinion that the government's cash and food assistance were absolutely effective amounted to below **** percent for both survey periods.

The COVID-19 pandemic required people to adapt rapidly to the digital transformation of society for social survival, which highlighted the divide between those who can and cannot digitalize. Previous studies investigated factors promoting adaptation to digitalization; however, outcomes from adaptation to a digitalized society have not been sorted into a parsimonious model, even though there should be several multifaceted outcomes (e.g., usefulness, economic profit, and social outcome), each of which is promoted by different factors. If the effects of individual background factors can be revealed, including the technical-environment and survival-relevant personality in relation to each outcome, it would help in the creation of a society where more people play an active role by adapting to digitalization. This study aimed to construct such a model by identifying major outcomes gained in a digitalized society and investigating individual factors that contribute to the degree of gain of each of these outcomes. Five dimensions were identified by online surveys and factor analysis: Socialization (outcomes derived from new social connections created online), Space–time (freedom from time and space constraints), Economics (monetary outcome by using digital services), and Information (ease and amount of acquisition of information) were the positive outcomes, whereas Loneliness (feelings of not being able to keep up with digitization) was identified as a negative outcome. We determined that technical-environmental factors (e.g., familiarity with digital techniques and the amount of money that can be used for digitalization) facilitated gain in four positive outcomes. Notably, leadership and conscientiousness facilitated the Socialization gain while etiquette suppressed it. These factors’ effects would reflect the importance of a personality trait prioritizing construction and maintenance of social relationships. This study implies that material outcomes (i.e., Space–time, Economics, and Information) are promoted by technical-environmental support, whereas social outcomes may additionally require motivation and a positive attitude for purposeful social engagement.

A survey revealed that during the coronavirus (COVID-19) lockdown 28 percent of Italians subscribed to paid digital services. 17 percent of them subscribed to video on demand services. Audio on demand platforms and online newspapers followed with seven percent.

In a survey conducted by LocalCircles on the impact of COVID-19 on the purchasing habits in India, the majority of respondents reported the use of cash mainly for low-value transactions. These included buying groceries and giving out salaries to the domestic staff.

Studies show that cash transfer programs increase incumbent approval through their financial impact and clear association with the executive. But does this effect hold when it is the legislature rather than the incumbent proposing the program? Amid the 2020 COVID-19 pandemic, more than 60 million Brazilians received an emergency assistance payment that was proposed by Congress against resistance from the executive. This study leverages this unique case to examine if cash transfer programs affect presidential approval under circumstances of unclear responsibility. Survey results showed that while approval ratings increased, the public was divided about who was responsible for the program. Moreover, a survey-experiment that informed respondents about the negotiations between the president and Congress found that information improves views about Congress but does not affect presidential approval. The results suggest that even cash transfer programs may promote limited vertical accountability in contexts of unclear policy responsibility.

Abstract

As a response to COVID-19, UNHCR has since the start of the pandemic launched multiple new cash grants and expanded existing programs. UNHCR's cash assistance complements governments' efforts by contributing with an additional safety net for vulnerable refugees and others left behind. UNHCR uses Post-Distribution Monitoring (PDM) as a mechanism to collect refugees' feedback on the quality, sufficiency, utilization and effectiveness of the assistance items they receive. In order to ensure that the cash assistance provided meets the intended programme objectives and that desired outcomes are achieved, UNHCR conducts regular post-distribution and outcome monitoring with a sample or all of the recipients.

The COVID-19 CBI PDM Household Survey was conducted in Malaysia between August to September 2021. In Malaysia, UNHCR provided urgent cash assistance to mitigate the socio-economic impacts of COVID-19, which hit especially urban refugees hard. Some 80 percent of the cash recipients experienced loss of income during the movement control order in Malaysia. Despite the overall positive impact of cash assistance, 80 percent of the households resorted to negative coping strategies to meet basic needs, highlighting that the unmet needs are vast despite assistance.

Geographic coverage

The survey is conducted in Kuala Lumpur, Pahang, Penang and Selangor.

Analysis unit

Households

Universe

The total population spans all beneficiaries subject to the last four Cash-Based Intervention in 2020 in Malaysia.

Kind of data

Sample survey data [ssd]

Sampling procedure

The survey's objective was to deliver data of all refugee households that were beneficiaries of the last four rounds of cash-based interventions implemented in 2020. The total number of households that received cash-based interventions in that period was 487 and every second household was selected randomly.

Mode of data collection

Telephone interview

ObjectivesTo examine changes in planning, selecting, and preparing healthy foods in relation to personal factors (time, money, stress) and social distancing policies during the COVID-19 crisis.MethodsUsing cross-sectional online surveys collected in 38 countries worldwide in April-June 2020 (N = 37,207, Mage 36.7 SD 14.43, 73.6% women), we compared changes in food literacy behaviors to changes in personal factors and social distancing policies, using hierarchical multiple regression analyses controlling for sociodemographic variables.ResultsIncreases in planning (4.7 SD 1.2, 4.9 SD 1.3), selecting (3.8 SD 1.7, 3.8 SD 1.7), and preparing (4.6 SD 1.3, 4.7 SD 1.3) healthy foods were found for women and men, and positively related to perceived time availability among women and stay-at-home policies for planning and preparing in women. Psychological distress was a barrier for women, and an enabler for men. COVID-19 induced financial stress was a barrier depending on various sociodemographic variables (all p < 0.01).ConclusionStay-at-home policies and feelings of having more time during COVID-19 seem to have improved food literacy among women. Stress and other social distancing policies relate to food literacy in more complex ways, highlighting the necessity of a health equity lens.

ObjectiveThis study assessed the relationship between self-rated political orientation and attitude toward the cash transfer policy during the COVID-19 pandemic.MethodsThis cross-sectional study conducted in South Korea during the pandemic included a stratified sample of 1,004 respondents (aged 19 years and older). We tested the hypotheses that political orientation shapes attitudes toward social policies and that other socioeconomic factors might have relatively minor importance. Logistic regression was used to identify associations between political orientation and attitude toward the cash transfer policy. Average marginal effects were calculated to determine the effect size of each variable.ResultsPolitical orientation, age, and residential area were correlated with attitudes toward the policy. Compared to the conservatives, the non-committed and the moderate showed about 10% more favorable attitudes, and the progressive group showed robust support. People in their 30s and 40s showed similar attitudes to the 18–29 group, while older people showed much lower support. Compared to the Seoul metropolitan area, residents of the Ho-nam area showed favorable attitudes, and those of the Yeong-nam area had relatively unfavorable attitudes.ConclusionsThis study suggests that attitudes toward the cash transfer policy are mainly associated with political orientation. Although these results illuminate pandemics' social and political dimensions, further efforts are needed to fully understand the determinants and mechanisms of attitudes toward policies outside the traditional health policy scope.

Europeans insist EU funds be linked to respect for Rule of Law

In the third round of Parliament’s special survey delving into European citizens’ attitudes and opinions over the course of the Covid-19 pandemic, results show that citizens across the EU fully support a clear conditionality of EU funds to the respect of the rule of law and democratic values. They survey confirms citizens’ call for EU to have more powers to tackle pandemic. In addition to the unbroken public support for a larger EU budget to overcome the consequences of the pandemic, more than half of respondents say that public health should be a spending priority, followed by economic recovery and climate change.

The survey was conducted by Kantar at the beginning of October 2020.

Key findings:

77% of Europeans insist EU funds be linked to respect for Rule of Law:

Nearly eight out of ten respondents (77%) across the EU support the concept that the EU should only provide funds to Member States conditional upon the national government's implementation of the rule of law and of democratic principles.

Citizens continue to see the EU as part of the solution in this crisis:

Two-thirds of respondents (66%) agree that the EU should have more competences to deal with crises such as the Coronavirus pandemic. Only a quarter (25%) disagrees with this statement. These findings are consistent with the results from both previous surveys conducted by the European Parliament in April and June 2020 respectively.

An absolute majority of Europeans continues to call for a larger EU budget to fight COVID-19:

54% of Europeans believe the EU should have greater financial means to be able to overcome the consequences of the Coronavirus pandemic.

More than half of respondents (54%) say that public health should be a spending priority for the EU budget,

followed by economic recovery and new opportunities for businesses (42%), climate change and environmental protection (37%) and employment and social affairs (35%).

Public health is the top spending priority

for respondents in 18 countries.

Broad majority of citizens fear direct impact on their personal financial situation

or have already suffered it: 39% of respondents say that the Covid-19 crisis has already impacted their personal income, while a further 27% expect such an impact in the future.

As novel coronavirus COVID-19 spreads around China, many businesses have to take special measures to prevent cash deficit. According to a survey on the epidemic impact on business in China released in the early February 2020, about **** percent of the surveyed companies planned to have a layoff and wage reduction.