2017 DLI CONTACT & ALTERNATES SURVEY. Visit https://dataone.org/datasets/sha256%3A58b129063741ca40e5aefe495d034b19dd9d5ce037b602e992efafa00046e8aa for complete metadata about this dataset.

Abstract

The spread of COVID-19 and government-imposed social distancing practices across the globe has severely limited the use of traditional, face-to-face interviews. Phone surveys, on the other hand, do not require face-to-face interactions and could elicit information from individuals, households rapidly and at low cost. These platforms also offer flexibility to alter sampling and/or questionnaire design in response to evolving needs. The objective of this survey is to monitor the impact of COVID-19 and the economic downturn on Iraqi individuals and households, and consequently better inform government mitigation policies – in the short- and medium-run. The short and repeated household phone-survey collected information on key indicators such as employment, food insecurity, subjective wellbeing and access to market, healthcare, and education to identify the most vulnerable groups and assess their needs. The phone survey was implemented on a monthly basis to monitor changes over time.

Geographic coverage

The survey covered all 18 governorates of Iraq.

Analysis unit

Individual and Household

Kind of data

Sample survey data [ssd]

Frequency of data collection

Data was collected monthly

Sampling procedure

The data collection methodology consists of a countrywide survey covering the 18 governorates in Iraq. The sample size is disaggregated by 18 governorates and the survey firm applied a random sampling approach to reach participants from different governorates in order to reach the given geographical quotas. The governorate population and details of quota are provided in Annex I of the survey report provided as supporting documentation.

All major Mobile Network Operators (MNOs) active in the country were included within the sampling frame to ensure a representative sample. The sample size is designed to detect changes in the prevalence of food insecurity (mainly people with inadequate food consumption) at governorate level as reported in the 2016 Comprehensive Food Security and Vulnerability Analysis (CFSVA) survey in Iraq.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaires are provided as supporting documentation, in English.

Response rate

The response rate for each round of the survey remained above 75 percent. For example, in August, a total of 1,843 individuals were contacted out of which 1,621 (each from a unique household) agreed and completed the survey; yielding a response rate of 80.1 percent. While the survey is designed to be a panel, households that could not be tracked are replaced with new households to meet the required quota. Response rate for both September and October rounds were above 75 percent. The survey allowed for maximum of 5 telephone contact attempts to reach the targeted respondents. Average number of attempts per phone number was below 1.5 calls for all three rounds.

The survey was completed online and by phone from January 15, 2018 to February 4, 2018.

Abstract

Access to up-to-date socio-economic data is a widespread challenge in Papua New Guinea and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 as a way to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See https://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details.

For PNG, after five rounds of data collection from 2020-2022, in April 2023 a monthly HFPS data collection commenced and continued for 18 months (ending September 2024) –on topics including employment, income, food security, health, food prices, assets and well-being. This followed an initial pilot of the data collection from January 2023-March 2023. Data for April 2023-September 2023 were a repeated cross section, while October 2023 established the first month of a panel, which is ongoing as of March 2025. For each month, approximately 550-1000 households were interviewed. The sample is representative of urban and rural areas but is not representative at the province level. This dataset contains combined monthly survey data for all months of the continuous HFPS in PNG. There is one date file for household level data with a unique household ID, and separate files for individual level data within each household data, and household food price data, that can be matched to the household file using the household ID. A unique individual ID within the household data which can be used to track individuals over time within households.

Geographic coverage

Urban and rural areas of Papua New Guinea

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The initial sample was drawn through Random Digit Dialing (RDD) with geographic stratification from a large random sample of Digicel’s subscribers. As an objective of the survey was to measure changes in household economic wellbeing over time, the HFPS sought to contact a consistent number of households across each province month to month. This was initially a repeated cross section from April 2023-Dec 2023. The resulting overall sample has a probability-based weighted design, with a proportionate stratification to achieve a proper geographical representation. More information on sampling for the cross-sectional monthly sample can be found in previous documentation for the PNG HFPS data.

A monthly panel was established in October 2023, that is ongoing as of March 2025. In each subsequent round of data collection after October 2024, the survey firm would first attempt to contact all households from the previous month, and then attempt to contact households from earlier months that had dropped out. After previous numbers were exhausted, RDD with geographic stratification was used for replacement households.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

he questionnaire, which can be found in the External Resources of this documentation, is in English with a Pidgin translation.

The survey instrument for Q1 2025 consists of the following modules: -1. Basic Household information, -2. Household Roster, -3. Labor, -4a Food security, -4b Food prices -5. Household income, -6. Agriculture, -8. Access to services, -9. Assets -10. Wellbeing and shocks -10a. WASH

Cleaning operations

The raw data were cleaned by the World Bank team using STATA. This included formatting and correcting errors identified through the survey’s monitoring and quality control process. The data are presented in two datasets: a household dataset and an individual dataset. The individual dataset contains information on individual demographics and labor market outcomes of all household members aged 15 and above, and the household data set contains information about household demographics, education, food security, food prices, household income, agriculture activities, social protection, access to services, and durable asset ownership. The household identifier (hhid) is available in both the household dataset and the individual dataset. The individual identifier (id_member) can be found in the individual dataset.

This study examines whether or not prior experiences with the police, both directly and indirectly through the experiences of others, can influence one's decision to report a crime. Data from the National Crime Victimization Survey (NCVS) was linked with the Police-Public Contact Survey (PPCS) to construct a dataset of the police-related experiences of crime victims and non-victims. Variables include information on the prevalence, frequency, and the nature of respondents' encounters with the police in the prior year, as well as respondents' personal and household victimization experiences that occurred after the administration of the PPCS, including whether the crime was reported to the police. Demographic variables include age, race, gender, education, and socioeconomic status. The ICPSR's holdings for both the NCVS and the PPCS are available in the NCVS series.

In the paper [1], we have provided a comprehensive overview of applicable solutions for proximity detection and contact tracing used to tackle the spread of the COVID-19 pandemic. On the webpage [2], we have provided the most recent findings of the existing solutions.

Structure description of JSON data format is attached in the file ReadMe.pdf

References:

[1] https://www.mdpi.com/2306-5729/5/4/87

[2] https://sites.tuni.fi/survey-of-digital-solutions/

In 2023, the ******** of contact center workers in the United States stated they agreed artificial intelligence (AI) had ******** customer service when it came to customer information tasks during their workday. ** percent agreed that AI had made their work easier.

Abstract

The coronavirus disease 2019 (COVID-19) pandemic and its effects on households create an urgent need for timely data and evidence to help monitor and mitigate the social and economic impacts of the crisis on the Somali people, especially the poor and most vulnerable. To monitor the socioeconomic impacts of the COVID-19 pandemic and inform policy responses and interventions, the World Bank as part of a global initiative designed and conducted a nationally representative COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households. The survey covers important and relevant topics, including knowledge of COVID-19 and adoption of preventative behavior, economic activity and income sources, access to basic goods and services, exposure to shocks and coping mechanisms, and access to social assistance.

Geographic coverage

National. Jubaland, South West, HirShabelle, Galmudug, Puntland, and Somaliland (self-declared independence in 1991), and Banadir.

Analysis unit

• Households

Universe

Households with access to phones.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample allocation for the COVID-19 SHFPS has been developed to provide representative and reliable estimates nationally, and at the level of Jubaland, South West, HirShabelle, Galmudug, Puntland, Somaliland, Banadir Regional Administration and by population type (i.e. urban, rural, nomads, and IDPs populations). The sampling procedure had two steps. The sample was stratified according to the 18 pre-war regions—which are the country’s first-level administrative divisions—and population types. This resulted in 57 strata, of which 7 are IDP, 17 are nomadic, 16 are exclusively urban strata, 15 exclusively rural, and 2 are combined urban-rural strata. The sample size in some strata was too small, thus urban and rural areas were merged into one single strata; this was the case for Sool and Sanaag.

Round 1 of the COVID-19 SHFPS was implemented between June and July 2020. The survey interviewed 2,811 households (1,735 urban households, 611 rural households, 435 nomadic households, and 30 IDP households in settlements). The sample of 2,811 households was contacted using a random digit dialing protocol. The sampling frame was the SHFPS Round 1 data - the same households from Round 1 are tracked over time, allowing for the monitoring of the well-being of households in near-real time and enabling an evidence-based response to the COVID-19 crisis.

Round 2 of the COVID-19 SHFPS was implemented in January 2021. A total of 1,756 households were surveyed (738 urban households, 647 rural households, 309 nomadic households, and 62 IDP households in settlements). Of the 1,756 households, 91 percent were successfully re-contacted from Round 1, with the remainder reached via random digit dialing. Administration of the questionnaire took on average 30 minutes.

Sampling deviation

The target sample for Round 1 was 3,000 households. The realized sample consists of 2,811 households. Reaching rural and nomadic-lifestyle respondents proved to be difficult in a phone survey setting due to lifestyle considerations and relatively lower phone penetration compared to urban settings. To overcome this challenge, the following were performed: - Lowering the sample size of the rural stratum - Reducing the number of interviews in the oversampled urban strata of Kismayo (Jubaland – Lower Juba/Urban) and Baidoa (South West State – Bay/Urban) - Utilizing snowball sampling methodology (i.e. referrals) to increase the sample for hard-to-reach population types, namely the nomadic households.

In Round 2, initially, a sample size of 1,800 households was targeted. However, due to implementation challenges in reaching specific population groups via phone, the sample size was slightly reduced. At the end of the data collection, 1,756 households had been interviewed.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaire of the COVID-19 Somali High-Frequency Phone Survey (SHFPS) of households consists of the following sections:

• Interview information (R1, R2)
• Household roster (R1, R2)
• Knowledge regarding the spread of COVID-19 (R1, R2)
• Behavior and social distancing (R1, R2)
• Concerns related to the COVID-19 pandemic (R1, R2)
• COVID-19 vaccine (R2)
• Access to basic goods and services (R1, R2)
• Employment (R1, R2)
• Income loss (R1, R2)
• Remittances (R1, R2)
• Mortality (R2)
• Shocks and coping mechanisms (R1, R2)
• Food insecurity (R1, R2)
• Social assistance and safety nets (R1, R2)
• Interaction with internally displaced persons (R2)

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 interviewed were kept in the dataset, and all personal information and internal survey variables were dropped from the clean dataset.

Response rate

The response rate is defined as the percentage of reached eligible households willing to participate in the survey. It is calculated as the number of interviewed households over the number of reached eligible households, thus excluding unreached households (i.e. invalid numbers or failure to contact the household) and households that were reached but were not eligible to participate in the survey (as determined by the minimum age requirement of the main respondent and sampling criteria).

The response rate for Round 1 was nearly 80 percent. In Round 2, 91 percent of the 1,756 households surveyed were successfully re-contacted from Round 1, with the remainder reached via random digit dialing.

Abstract

The recent global economic slowdown, caused by the COVID-19 pandemic, created an urgent need for timely data to monitor the socioeconomic impacts of the pandemic. Tanzania is among other countries in the world which are affected by the recent global economic slowdown, caused by the COVID-19 pandemic. Therefore, there is an urgent need for timely data to monitor and mitigate the socio-economic impacts of the crisis in the country. Responding to this need, the National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician (OCGS), Zanzibar in collaboration with the World Bank and Research on Poverty Alleviation (REPOA) implemented a rapid household telephone survey called the Tanzania High-Frequency Welfare Monitoring Survey (HFWMS).

Thus, the main objective of the survey is to obtain timely data that is critical for evidence-based decision making aimed at mitigating the socio-economic impact of the downturn caused by COVID-19 pandemic by filling critical gaps of information that can be used by the government and stakeholders to help design policies to mitigate the negative impacts on its population.

Geographic coverage

National

Analysis unit

Households Individuals

Universe

The survey covered all de jure households excluding prisons, hospitals, military barracks, and school dormitories.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary sample for this activity was drawn from the 2014/15 NPS and 2017/18 HBS. Target sample completion each month is estimated at 3000 households. The 2014/15 NPS acted as the primary sample frame, complimented by the 2017/18 HBS.

The sample for the HFWMPS was drawn from the 2014/15 NPS and 2017/18 HBS. Both surveys were conducted over a 12-month period and are nationally representative. During the implementation of the surveys, phone numbers are collected from interviewed households and reference persons who are in close contact with the household in order to assist in locating and interviewing households who may have moved in subsequent waves of the survey. This comprehensive set of phone numbers as well as the already well-established relationship between NBS and these households made this an ideal frame from which to conduct the HFWMS in Tanzania.

To obtain a nationally representative sample for the Tanzania HFWMS, a sample size of approximately 3,000 successfully interviewed households was targeted. However, to reach that target, a larger pool of households needed to be selected from the frame due to non-contact and non-response common for telephone surveys. Thus, about 5,750 households were selected to be contacted.

All 5,750 households were contacted in the baseline round of the phone survey. [Error! Reference source not found. ] presents the interview result for the baseline sample. 49.2 percent of sampled households were successfully contacted. Of those contacted, 96 percent or 2,708 households were fully interviewed. These 2,708 households constitute the final successful sample and will be contacted in subsequent rounds of the survey.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Each survey round consists of one questionnaire - a Household Questionnaire administered to all households in the sample.

Baseline The questionnaire gathers information on demographics; employment; education; access to basic services; food security; TASAF; and mental health. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment: Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Education: School attendance, type of school attended, learning activities of children at home, return to school, contact with children’s teachers during school closure.
• Access to Basic Services:Household’s access to staple food (maize grain, cassava, rice, and maize flour), medical treatment, and reasons for not being able to access the services.
• Food Security: Household’s food security status during the last 30 days.
• TASAF: Households access to the TASAF money, use of the money received, challenges encountered in accessing the funds.
• Mental Health: Information on 8 items pertaining to measuring mental health.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview.

Round 2 The questionnaire gathers information on demographics; employment; non-farm enterprise; tourism; education; access to health services; and TASAF. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment: Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, and reason for not able to perform activities as usual.
• Non-farm Enterprise: Status and information of non-farm income-generating activities, reason for stopped operating, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Tourism: Employment of household members in tourism sector, and who benefits from tourism.
• Education (selected members aged 4-18 years): School attendance, reason for not attending, grade attending, type of school, absence and reason for being absent.
• Access to Health Services: Women’s access to pre-natal/post-natal care, household’s access to preventative care and medical treatment, and reasons for not being able to access the services.
• TASAF: Households access to the TASAF money, use of the money received, challenges encountered in accessing the funds.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview

Round 3 The questionnaire gathers information on demographics; employment (respondent and other household members); non-farm enterprise; credit; women savings; and shocks and coping. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment (respondent): Status and information of income-generating activities (wage work, family business and farming), reason for stopped working, and reason for not able to perform activities as usual.
• Employment (other members): Status in employment (current and 2020), consistency of work in 2020, why currently not working, job search, change in jobs, actual job.
• Non-farm Enterprise: Status and information of non-farm income-generating activities, reason for stopped operating, reason for not able to perform activities as usual, and reason for reduced revenue from family business.
• Credit: Household’s debts status since the beginning of the coronavirus crisis; use of loan, ability to repay loan when their scheduled payment is due.
• Women Savings: Women having bank accounts to financial institutions and changes in their savings since the start of the pandemic.
• Shocks and Coping: Shocks that affected household since the baseline interview and their coping strategies.
• Recontact: Data on how the household can be recontacted in the future.
• Interview Results: Result of interview including observation notes by enumerator regarding the interview, respondent and language of interview.

Round 4 The questionnaire gathers information on demographics; employment; non-farm enterprise; digital technology; and income changes. The contents of questionnaire are outlined below:

• Cover: Household identifiers and enumerator identifiers.
• Interview Information: Details of call attempts, result and respondent of call attempt, interview consent, date and time of call back, phone numbers called, the information of the person that the listed phone number belongs to.
• Basic Information: Roster of members of the household, relationship to the household head, gender, age, relationship to head, reason for joining the household if new, and reason for leaving the household if left.
• Employment (respondent): Status and information of

The Tempe Fire Medical Rescue Department (TFMR) is an “all-hazards” department that responds to all types of calls for service. The City of Tempe collects data from an annual Community Survey and the monthly TFMR Customer Service Survey to gauge resident perceptions about the quality and satisfaction of city services, programs and direction. The survey results help to determine priorities for the community as part of the City's ongoing strategic management process. This page provides data for the Fire Services Satisfaction performance measure. The performance measure dashboard is available at 1.04 Fire Services Satisfaction Includes detailed responses to Tempe Fire Medical Rescue Customer Satisfaction Survey. Surveys involving medical patients are sent out weekly to Tempe Medical Fire Rescue patients who provided email address at time of treatment. Results are calculated monthly for the prior months responses for review by Tempe Fire Medical Rescue administrators. Respondents are asked to answer several questions about their experience. Detailed information about the questions are included in the data dictionary for this dataset. Additional Information Source: Tempe Fire Medical Rescue Customer Satisfaction SurveyContact: Wydale Holmes / Hans Silberschlag (Fire Customer Survey)Contact E-Mail: wydale_holmes@tempe.govData Source Type: ExcelPreparation Method: Data downloaded from website (Survey Monkey)Publish Frequency: Monthly (Fire Customer Survey)Publish Method: ManualData Dictionary

Access to up-to-date socio-economic data is a widespread challenge in Tonga and other Pacific Island Countries. To increase data availability and promote evidence-based policymaking, the Pacific Observatory provides innovative solutions and data sources to complement existing survey data and analysis. One of these data sources is a series of High Frequency Phone Surveys (HFPS), which began in 2020 as a way to monitor the socio-economic impacts of the COVID-19 Pandemic, and since 2023 has grown into a series of continuous surveys for socio-economic monitoring. See https://www.worldbank.org/en/country/pacificislands/brief/the-pacific-observatory for further details. For Tonga, after two rounds of data collection from in 2022, monthly HFPS data collection commenced in April 2023 and continued until November 2024 (but with some gaps in the months of collection). The survey collected socio-economic data on topics including employment, income, food security, health, food prices, assets and well-being. Each month of collection has approximately 415 households in the sample and is representative of urban and rural areas. This dataset contains combined monthly survey data for all months of the continuous HFPS in Tonga.

Cleaned, labelled and anonymized version of the master file provided by the World Bank.

• Collection start: 2023
• Collection end: 2024

Heterogeneities in contact networks have a major effect in determining whether a pathogen can become epidemic or persist at endemic levels. Epidemic models that determine which interventions can successfully prevent an outbreak need to account for social structure and mixing patterns. Contact patterns vary across age and locations (e.g. home, work, and school), and including them as predictors in transmission dynamic models of pathogens that spread socially will improve the models’ realism. Data from population-based contact diaries in eight European countries from the POLYMOD study were projected to 144 other countries using a Bayesian hierarchical model that estimated the proclivity of age-and-location-specific contact patterns for the countries, using Markov chain Monte Carlo simulation. Household level data from the Demographic and Health Surveys for nine lower-income countries and socio-demographic factors from several on-line databases for 152 countries were used to quantify similarity of countries to estimate contact patterns in the home, work, school and other locations for countries for which no contact data are available, accounting for demographic structure, household structure where known, and a variety of metrics including workforce participation and school enrolment. Contacts are highly assortative with age across all countries considered, but pronounced regional differences in the age-specific contacts at home were noticeable, with more inter-generational contacts in Asian countries than in other settings. Moreover, there were variations in contact patterns by location, with work-place contacts being least assortative. These variations led to differences in the effect of social distancing measures in an age structured epidemic model. Contacts have an important role in transmission dynamic models that use contact rates to characterize the spread of contact-transmissible diseases. This study provides estimates of mixing patterns for societies for which contact data such as POLYMOD are not yet available.

Abstract

The World Bank conducted Phase 2 of the High-Frequency Phone Survey (HFPS) project in 2021 to continue to assess the socio-economic impacts of the COVID-19 pandemic on Latin America and The Caribbean households. Phase 2 was conducted in partnership with the UNDP LAC Chief Economist office and included two waves.

Ecuador has been part of all waves of data collection as part of the Regional effort. In 2022, in partnership with the Joint Data Center on Forced Displacement, two additional waves of data were collected in February and June. This study presents these last waves of data (Wave 3 and Wave 4).

Geographic coverage

National level excluding the Galapagos Islands.

Analysis unit

Households and individuals of 18 years of age and older.

Sampling procedure

Phase 2 Wave 1 samples for the Original Countries included two components: a) a panel formed by respondents to Phase 1 Wave 1, and b) a supplement fresh sample of phone numbers to compensate for attrition between Phase 1 Wave 1 and Phase 2 Wave 1, and to slightly increase the overall sample size.

The samples of the Added Countries (i.e. those only included in Phase 2) is based on a dual frame of cell phone and landline numbers generated through a Random Digit Dialing (RDD) process. In the first phase, a large sample was selected in both frames, and then screened through an automated process to identify the active, eligible numbers. A smaller second-phase sample was selected from the active residential numbers from in the first-phase sample and was delivered to the country teams. See Sampling Design and Weighting document for more detail.

Sampling deviation

Ecuador is the only country from Phase I where a fully fresh sample of phone numbers is used for Phase II and was treated as an Added Country. Waves 3 and 4 were collected only for Ecuador, replicating the procedures applied for Wave 2. See Sampling Design and Weighting document for more detail.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Questionnaires are available in Spanish. Note that questionnaires for Waves 3 and 4 have some variations from previous waves.

Abstract

To facilitate comparisons with the Latin America and the Caribbean (LAC) High-Frequency Surveys collected in 2021, harmonized versions of the COVID-19 High Frequency Phone Surveys 2022 Brazil databases have been produced. The databases follow the same structure as those for the countries in the region (for example, see: COVID-19 LAC High Frequency Phone Surveys 2021 (Wave 1)).

The Brazil 2021 COVID-19 Phone Survey was conducted to provide information on how the pandemic had been affecting Brazilian households in 2021, collecting information along multiple dimensions relevant to the welfare of the population (e.g. changes in employment and income, coping mechanisms, access to health and education services, gender inequalities, and food insecurity). A total of 2,166 phone interviews were conducted across all Brazilian states between July 26 and October 1, 2021. The survey followed an Random Digit Dialing (RDD) sampling methodology using a dual sampling frame of cellphone and landline numbers. The sampling frame was stratified by type of phone and state. Results are nationally representative for households with a landline or at least one cell phone and of individuals of ages 18 years and above who have an active cell phone number or a landline at home.

Geographic coverage

National level.

Analysis unit

Households and individuals of 18 years of age and older.

Sampling procedure

The sample is based on a dual frame of cell phone and landline numbers that was generated through a Random Digit Dialing (RDD) process and consisted of all possible phone numbers under the national phone numbering plan. Numbers were screened through an automated process to identify active numbers and cross-checked with business registries to identify business numbers not eligible for the survey. This method ensures coverage of all landline and cellphone numbers active at the time of the survey. The sampling frame was stratified by type of phone and state. See Sampling Design and Weighting document for more detail.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Available in Portuguese. The questionnaire followed closely the LAC HFPS Questionnaire of Phase II Wave I but had some critical variations.

Abstract

As part of the efforts of the World Bank Group to understand the impact of COVID-19 on the private sector, the Enterprise Analysis unit is conducting follow-up surveys on recently completed Enterprise Surveys (ES) in several countries. These short surveys follow the baseline ES and are designed to provide quick information on the impact and adjustments that COVID-19 has brought about in the private sector.

Geographic coverage

National coverage

Analysis unit

Enterprise

Universe

The universe of inference is all registered establishments with five or more employees that are engaged in one of the following activities defined using ISIC Rev. 3.1: manufacturing (groupd D), construction (group F), services sector (groups G and H), transport, storage, and communcations sector (group I) and information technology (division 72 of group K)

Kind of data

Sample survey data [ssd]

Sampling procedure

The follow-up surveys re-contact all establishments sampled in the standard ES using stratified random sampling (https://www.enterprisesurveys.org/content/dam/enterprisesurveys/documents/methodology/Sampling_Note.pdf). Total sample target: 1446

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

The questionnaires contain the following modules: - Control information and introduction - General information - Sales - Production - Labor - Finance - Policies - Expectations - Information on permanently closed establishments - Interview protocol

Response rate

Response rate is 83.8%.

Sexual contact patterns determine the spread of sexually transmitted infections and are a central input parameter for mathematical models in this field. We evaluated the importance of country-specific sexual contact pattern parametrization for high-income countries with similar cultural backgrounds by comparing data from two independent studies (HaBIDS and SBG) in Germany, a country without systematic sexual contact pattern data, with data from the National Survey of Sexual Attitudes and Lifestyles (Natsal) in the UK, and the National Survey of Family Growth (NSFG) in the US, the two longest running sexual contact studies in high-income countries. We investigated differences in the distribution of the reported number of opposite-sex partners, same-sex partners and both-sex partners using weighted negative binomial regression adjusted for age and sex (as well as stratified by age). In our analyses, UK and US participants reported a substantially higher number of lifetime opposite-sex sexual partners compared to both German studies. The difference in lifetime partners was caused by a higher proportion of individuals with many partners in the young age group (

Abstract

Latin American and the Caribbean is one of the regions in the world most affected by the COVID-19 pandemic. The World Bank conducted a series of High-Frequency Phone Surveys (HFPS) to assess the impact of the coronavirus pandemic on the welfare of Latin American and Caribbean households. Between March and August 2020, the HFPS collected nationally representative information for thirteen countries: Argentina, Bolivia, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Guatemala, Honduras, Mexico, Paraguay, and Peru.

Geographic coverage

National coverage

Analysis unit

Households and individuals of 18 years of age and older.

Universe

Households with a landline or in which at least one member has a cell phone, and individuals 18 years of age or above who have an active cell phone number or a landline at home.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample is based on a dual frame of cell phone and landline numbers generated through a Random Digit Dialing (RDD) process. In the first phase, a large sample was selected in both frames, and then screened through an automated process to identify the active, eligible numbers. A smaller second-phase sample was selected from the active residential numbers from in the first-phase sample and was delivered to the country teams. See Sampling Design and Weighting document for more detail.

Mode of data collection

Computer Assisted Telephone Interview [cati]

Research instrument

Available in Spanish. The questionnaire for the first wave followed closely the World Bank’s HFPS Global Core Questionnaire but had some critical variations. There were also some modifications in the subsequent waves.

The Bolivia COVID-19 High Frequency Phone Survey questionnaires consist of the following sections: • Cover Page (Wave 1, 2, 3) • Basic Information (Wave 1, 2, 3)
• Knowledge Regarding the Spread of COVID-19 (Wave 1) • Behaviour and Social Distancing (Wave 1, 2, 3) • Access to Basic Services (Wave 1, 2, 3) • Employment (Wave 1, 2, 3) • Income Loss (Wave 1, 3) • Food Security (Wave 1, 2, 3) • Concerns (Wave 1, 2, 3) • Coping Strategies (Wave 1, 3) • Social Safety Nets (Wave 1, 2, 3) • Trust (Wave 3)

This dataset provides Customer Service Satisfaction results from the Annual Community Survey. The survey questions assess satisfaction with overall customer service for inpiduals who had contacted the city in the past year.

For years where there are multiple questions related to overall customer service and treatment, the average of those responses are provided in this dataset. Responses for each question are shown in the detailed dataset.

For years 2010-2014, respondents were first asked "Have you contacted the city in the past year?". If they answered that they had contacted the city, then they were asked additional questions about their experience. The "number of respondents" field represents the number of people who answered yes to the contact question.

Responses of "don't know" are not included in this dataset, but can be found in the dataset for the entire Community Survey. A survey was not completed for 2015.

The performance measure dashboard is available at 2.02 Customer Service Satisfaction.

Additional Information

Source: Community Attitude Survey

Contact: Wydale Holmes

Contact E-Mail: Wydale_Holmes@tempe.gov

Data Source Type: Excel and PDF

Preparation Method: Extracted from Annual Community Survey results

Publish Frequency: Annual

Publish Method: Manual

Data Dictionary

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

Analysis unit

Households

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- Vaccine

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.