Abstract

A population and housing census (PHC) is huge undertaking which is a count of the entire population of the country. A census is conducted in ten-year intervals, and the recent PHC for Kingdom of Eswatini was undertaken in 2007. A population census is the total process of collecting, compiling, evaluating, analyzing and publishing of demographic information and any other relevant data pertaining to all persons in a country. The 2007 Kingdom of Eswatini Population and Housing Census results were widely disseminated to a wide range of stakeholders for use.

Geographic coverage

National

Analysis unit

• Individual,
• Households.

Kind of data

Census/enumeration data [cen]

Mode of data collection

Face-to-face [f2f]

Cleaning operations

• Data entry program (in house) ready 2006
• Modified 2007 for minimising automation (TA).
• Manager for moving and recording batches.
• Lean staff Oct. 2007 (8)full staff Feb. 2008 (36)
• Done by region at min of 100 cases/day.
• Overtime for weekends to meet deadlines.

Swaziland SZ: Population: Total data was reported at 1,367,254.000 Person in 2017. This records an increase from the previous number of 1,343,098.000 Person for 2016. Swaziland SZ: Population: Total data is updated yearly, averaging 816,569.000 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 1,367,254.000 Person in 2017 and a record low of 349,174.000 Person in 1960. Swaziland SZ: Population: Total data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eswatini – Table SZ.World Bank.WDI: Population and Urbanization Statistics. Total population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship. The values shown are midyear estimates.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Sum; Relevance to gender indicator: disaggregating the population composition by gender will help a country in projecting its demand for social services on a gender basis.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

Abstract

The Kingdom of Eswatini Multiple Indicator Cluster Survey (MICS5) 2014 was conducted in 2014 by the Central Statistical Office with technical and financial support from UNICEF. The survey provides statistically sound and internationally comparable data essential for developing evidence-based policies and programmes, and for monitoring progress toward national goals and global commitments. Among these global commitments are those emanating from the World Fit for Children Declaration and Plan of Action, the goals of the United Nations General Assembly Special Session on HIV/AIDS, the Education for All Declaration and the Millennium Development Goals (MDGs).

The 2014 Kingdom of Eswatini MICS5 has as its primary objectives to:

• Provide up-to-date information on the situation of women, children, men and other vulnerable populations in Kingdom of Eswatini;

• Generate data for the critical assessment of the progress made in various areas, and to put additional efforts in those areas that require more attention;

• Furnish data needed for monitoring progress toward goals established in the Millennium Declaration and other internationally agreed upon goals, as a basis for future action;

• Collect disaggregated data for the identification of disparities, to allow for evidence based policy-making aimed at social inclusion of the most vulnerable;

• Contribute to the generation of baseline data for the post-2015 agenda;

• Validate data from other sources and the results of focused interventions.

• Track progress made in the implementation of national commitments, strategies and frameworks, National Development Strategy (NDS) Vision 2022, PRSAP 2008, extended National Strategic Framework 2014-2018, National Health Sector Strategic Plan (NHSSPII), and National Plan of Action for Children 2011-2015. · Identify new areas of concern for government and partners.

Geographic coverage

The 2014 Kingdom of Eswatini MICS was designed to provide estimates for indicators on the situation of the country at the national level, for urban and rural areas, and for the four administrative regions of Kingdom of Eswatini: Hhohho, Manzini, Shiselweni and Lubombo.

Analysis unit

• Individuals

• Households

Universe

The survey covered all de jure household members (usual residents), all women age 15-49 years, all men age 15-49 years and all children under 5 living in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

Sample design features include target sample size, sample allocation, sampling frame and listing, choice of domains, sampling stages, stratification, and the calculation of sample weights.

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample.

The sample size required based on the desired level of precision for the Kingdom of Eswatini MICS was calculated as 5,205 households. For calculating this sample size, the key indicator used was the prevalence of pneumonia among children age 0-59 months, estimated to be 0.13 from the 2010 MICS.

The number of households selected per cluster for the 2014 Kingdom of Eswatini MICS5 was determined as 15 households, based on a number of considerations, including the design effect, the budget available, and the time that would be needed per team to complete one cluster. Dividing the total number of households by the number of sample households per cluster, it was calculated that 347 sample clusters would need to be selected nationwide.

SAMPLING FRAME AND SELECTION OF CLUSTERS

The 2007 census frame was used for the selection of clusters. Census enumeration areas were defined as primary sampling units (PSUs), and were selected from each of the sampling strata by using systematic pps (probability proportional to size) sampling procedures, based on the number of households in each enumeration area from the 2007 Population and Housing Census frame. The first stage of sampling was thus completed by selecting the required number of enumeration areas from each of the four regions, separately for the urban and rural strata.

LISTING ACTIVITIES

The sampling frame (the 2007 population census) was not up-to-date, so the more recent listing of households conducted for the ILFS 2013/14 was used for the selection of the 5,211 households from the 347 sample clusters for the MICS in order to reduce the total survey costs, as described above. Therefore, a separate new listing of households was not conducted for the MICS.

SELECTION OF HOUSEHOLDS

The list of households from the ILFS 2013/14 for each of the 347 sample EAs was used for selecting the sample households for MICS. The households were sequentially numbered from 1 to N (the total number of households in each enumeration area) at the Central Statistical Office, where the selection of 15 households in each enumeration area was carried out using random systematic selection procedures. The survey also had a questionnaire for men that was administered in every third household in each sampled cluster for interviews with all eligible men.

Mode of data collection

Face-to-face [f2f]

Research instrument

Four sets of questionnaires were used in the survey: 1) a household questionnaire which was used to collect basic demographic information on all de jure household members (usual residents), the household, and the dwelling; 2) a questionnaire for individual women administered in each household to all women age 15-49 years; 3) a questionnaire for individual men administered in every three households to all men age 15-59 years; and 4) an under-five questionnaire, administered to mothers (or caretakers) of all children under-five years of age living in the household.

The questionnaires are based on the MICS5 model questionnaires. From the MICS5 model English, version, the questionnaires were customised and translated into siSwati and were pre-tested in Moti, Sphocosini and the Police College in July 2014. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. A copy of the Kingdom of Eswatini MICS5 questionnaires is provided as a Related Material.

In addition to the administration of questionnaires, fieldwork teams tested the salt used for cooking in the households for iodine content, observed the place for handwashing, and measured the weights and heights of children age under-five years. Details and findings of these observations and measurements are provided in the respective sections of the report

A number of country specific modifications were also made to better serve the data needs of the country. The modifications include the following:

Modules that are not part of the generic MICS5 that have been included in the Kingdom of Eswatini 2014 MICS5:

Household Questionnaire

• Children Orphaned or made Vulnerable (children 0-17 years)

• Basic Needs (children age 5-17 years)

Questionnaire for Individual Women

• Non Communicable Diseases

• Social Participation

Questionnaire for Individual Men

• Non Communicable Diseases

• Social Participation

Modules that are part of the generic MICS5 that have been omitted:

Household Questionnaire

• Child Labour

• Insecticide Treated Nets

• Indoor Residual Spraying

Women Questionnaire

• Female Genital Cutting Under-Five Questionnaire

• Malaria

Cleaning operations

Data was entered using the CSPro software, Version 5.0. The data was entered on seven desktop computers and carried out by seven data entry operators and one data entry supervisor. For quality assurance purposes, all questionnaires were double-entered and internal consistency checks were performed. Procedures and standard programs developed under the global MICS programme and adapted to the Kingdom of Eswatini MICS5 questionnaire were used throughout. Data processing began simultaneously with data collection in August 2014 and was completed in November 2014. Data were analysed using the Statistical Package for Social Sciences (SPSS) software, Version 21. Model syntax and tabulation plans developed by UNICEF were customized and used for this purpose.

Response rate

Of the 5,205 households selected for the sample, 4,981 were found to be occupied. Of these, 4,865 were successfully interviewed for a household response rate of 98 percent.

In the interviewed households, 5,001 women (age 15-49 years) were identified. Of these, 4,762 were successfully interviewed, yielding a response rate of 95 percent within the interviewed households.

The survey also sampled men (age 15-59 years) but required only a subsample. All men (age 15-59 years) were identified in every third household. A total of 1,629 men (age 15-59 years) were listed in the household questionnaires. Questionnaires were completed for 1,459 eligible men, which corresponds to a response rate of 90 percent within eligible interviewed households.

There were 2,728 children under-five years listed in the household questionnaires. Questionnaires were completed for 2,693 of these children, which corresponds to a response rate of 99 percent within interviewed households.

Sampling error estimates

The sample of respondents selected for the Kingdom of EswatiniMultiple Indicator Cluster Survey is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between the estimates from all possible samples. The extent of variability is not known

Eswatini SZ: SPI: Pillar 4 Data Sources Score: Scale 0-100 data was reported at 32.633 NA in 2024. This records an increase from the previous number of 30.983 NA for 2023. Eswatini SZ: SPI: Pillar 4 Data Sources Score: Scale 0-100 data is updated yearly, averaging 33.350 NA from Mar 2016 (Median) to 2024, with 9 observations. The data reached an all-time high of 38.125 NA in 2020 and a record low of 30.983 NA in 2023. Eswatini SZ: SPI: Pillar 4 Data Sources Score: Scale 0-100 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eswatini – Table SZ.World Bank.WDI: Governance: Policy and Institutions. The data sources overall score is a composity measure of whether countries have data available from the following sources: Censuses and surveys, administrative data, geospatial data, and private sector/citizen generated data. The data sources (input) pillar is segmented by four types of sources generated by (i) the statistical office (censuses and surveys), and sources accessed from elsewhere such as (ii) administrative data, (iii) geospatial data, and (iv) private sector data and citizen generated data. The appropriate balance between these source types will vary depending on a country’s institutional setting and the maturity of its statistical system. High scores should reflect the extent to which the sources being utilized enable the necessary statistical indicators to be generated. For example, a low score on environment statistics (in the data production pillar) may reflect a lack of use of (and low score for) geospatial data (in the data sources pillar). This type of linkage is inherent in the data cycle approach and can help highlight areas for investment required if country needs are to be met.;Statistical Performance Indicators, The World Bank (https://datacatalog.worldbank.org/dataset/statistical-performance-indicators);Weighted average;

Abstract

The Household Income and Expenditure Survey (HIES) was a multipurpose survey of households in Swaziland which collected information on different dimensions of the population's living conditions. The data was collected on a countrywide basis including among others; education, health and employment. The survey used the most comprehensive household surveys available in Swaziland and focused on three dimensions of poverty namely; consumption poverty, lack of access to assets/services and human development.

The survey covered an analysis of living conditions from another perspective other than just monetary poverty. It also provided an opportunity to study trends in household well-being over a ten year period and ensure evidence-based public policy decision-making in poverty reduction efforts. The HIES added to the policy debate and discussions in Swaziland on actions taken to reduce poverty so far and various programs being implemented to chart the progress towards the attainment of the Millennium Development Goals (MDGs) and to monitor other policy initiatives such as the Poverty Reduction Strategy and Action Plan (PRSAP). The questionnaires used for these two rounds were almost identical, meaning that the results can be directly compared. Each round covered a nationally representative sample of households spread over a twelve-month period.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The Household Income and Expenditure Survey (HIES) was administered to a representative sample of households. Both rounds of the HIES used in this study were conducted on a nationwide basis. The survey was based on the 2007 population and housing census (PHC) frame. A stratified multi-stage sample design was used for this survey. At the first stage a total of 375 enumeration areas (EA's) were selected. An exhaustive household listing exercise was carried out to update the lists prepared during the 2007 PHC. A collection of geo-coordinates of households also formed part of the exercise. This was to facilitate location of households during actual data collection. The final sample size was just under 4000 households. At the second stage a fixed number of households were selected by systematic random sampling within each of the selected enumeration areas.

Mode of data collection

Face-to-face [f2f]

This layer contains information about the numbers of food insecure people - by second-level administrative unit - estimated for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019. Data source: Eswatini Vulnerability Assessment and Analysis coordinated by the Eswatini Vulnerability Assessment Committee and the Central Statistics Office, 2011-2019. The main indicators used for the analysis were the percentage of food insecure population for long-term planning and the additional population figures in case of a major shock.

Geographic coverage

National coverage

Analysis unit

households/individuals

Kind of data

survey

Frequency of data collection

Yearly

Sampling procedure

Sample size:

This layer contains information about the recurrence of prevalence of stunting - by first-level administrative unit - used for the purposes of the Integrated Context Analysis (ICA) run in Eswatini in 2019. Data source: Eswatini Vulnerability Assessment and Analysis coordinated by the Eswatini Vulnerability Assessment Committee and the Central Statistics Office, 2009-2018. The key indicator used for the purposes of the analysis was the prevalence of stunting in children under the age of 5, with a threshold set at 20% because, according to the guidelines suggested by the World Health Organization (WHO), this is the break between the classes 'Medium' and 'High'.

Original dataset title: ICA Eswatini, 2019 - Recurrence of prevalence of stunting, 2009-2018

Abstract

This report presents results of the 2010 the Kingdom of Eswatini MICS, carried out by CSO in collaboration with UNICEF and other partners. Since its launch in the mid-1990s, MICS has become one of the largest sources of information on a range of indicators including child health, nutrition, water and sanitation, reproductive health, education, child protection and HIV/AIDS. The 2010 Kingdom of Eswatini MICS was implemented to assess the current situation of the Swazi population, particularly children and women, as well as to measure progress towards goals and targets emanating from international agreements: the Millennium Declaration, adopted by all 191 United Nations Member States in September 2000, and the WFFC Plan of Action, adopted by 189 Member States at the United Nations (UN) Special Session on Children in May 2002. Both of these commitments build upon promises made by the international community at the 1990 World Summit for Children.

The 2010 Kingdom of Eswatini MICS is based on a nationally representative sample of 5,475 households selected from 365 enumeration areas distributed in the four regions of the country. It is an important source of information for measuring progress towards targets set by these various strategic plans, as well international declarations including the MDGs, the United Nations General Assembly Special Session Declaration of Commitment on HIV/AIDS (UNGASS) and others commitments.

Geographic coverage

National

Analysis unit

• individuals
• households

Universe

The survey covered all de jure household members (usual residents), all women aged between 15-49 years, all children under 5 living in the household, and all men aged 15-59 years.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the sample design for the 2010 Kingdom of Eswatini MICS was to produce statistically reliable estimates of most indicators, at the national level, for urban and rural areas, and for the four regions of the country (Hhohho, Manzini, Shiselweni and Lubombo).

A multi-stage, stratified cluster sampling approach was used for the selection of the survey sample. The 2006/07 Swaziland Demographic Health Survey (SDHS) collected many of the indicators in the MICS. Therefore, the results of the 2006/07 SDHS and the sample design were used as a reference in finalizing the sample design for the 2010 Swaziland MICS. In the survey, most of the indicators will be tabulated at the national level, urban and rural domains, and for the four regions as in the case of the 2006/07 SDHS.

The sampling frame for MICS comes from the recent Kingdom of Eswatini Census of Population and Housing data collected in 2007. The primary sampling units (PSUs) are the census enumeration areas (EAs). The EAs were created for the 2007 Census operations with well-defined boundaries identified on sketch maps. The number of households in an EA is based on the expected workload for one enumerator. According to the 2007 Census, the average number of households per EA is 103 (274 for rural EAs and 34 for urban EAs).

The sample size for a good household survey, such as the 2010 Kingdom of Eswatini MICS, is determined by the accuracy required for the estimates for each domain, as well as by the resource and operational constraints. The allocation of the sample EAs in each region to the rural and urban strata will be proportional to the number of households. Based on these criteria, the proposed allocation of sample EAs and households by region and rural and urban stratum results in a total sample of 365 EAs and 5,475 households.

The sampling procedures are more fully described in "Swaziland Multiple Indicator Cluster Survey 2010 - Final Report" pp.A1-A6.

Mode of data collection

Face-to-face [f2f]

Research instrument

The 2010 Kingdom of Eswatini MICS consists of four main questionnaires including a household questionnaire, women’s and men’s questionnaires and a questionnaire for children under age five. The survey includes information on key indicators on the following topics:

Household questionnaire: age, sex, urban vs. rural residency, household composition, education of household members, household assets, water and sanitation, use of iodized salt, use of insecticidetreated nets (ITNs), orphanhood and vulnerability of children, child labor and child discipline.

Questionnaire for children under five: birth registration, early childhood development, infant and young child feeding, care of illness (including diarrhoea and pneumonia), malaria, immunization and anthropometry.

Women’s questionnaire: child mortality, birth history, desire for last birth, maternal an newborn health, illness symptoms, contraception, unmet need, marriage/union, sexual behaviour, HIV/AIDS, sexually transmitted infections (STIs), and attitudes towards domestic violence.

Men’s questionnaire: marriage/union, attitudes towards contraception, sexual behaviour, HIV/AIDS, STIs, male circumcision and attitudes towards domestic violence.

Cleaning operations

Data entry commenced on 3 September after an initial training and ended on 17 December 2010. Data were entered on 10 computers by 10 data entry operators and two data entry supervisors using the CSPro software. In order to ensure quality control, all questionnaires were double entered and two secondary editors complemented the efforts of entry supervisors to perform internal consistency checks. Procedures and standard programmes developed under the global MICS4 survey were adapted, based on the modified Swaziland MICS questionnaires, and used throughout the processing. Data were analyzed using the Statistical Package for Social Sciences (SPSS) software programme, and syntax and tabulation plans developed for the global MICS4 were customized for this purpose.

Response rate

Of the 5,475 households selected for the sample nationally, 5,074 households were found to be occupied. Of these, 4,834 households were interviewed successfully yielding a household response rate of 95 percent. Among the interviewed households, 4,956 women age 15–49 years and 4,646 men age 15–59 years were identified. Of this number, 4,688 women and 4,179 men were successfully interviewed, yielding a response rate of 95 percent and 90 percent respectively. In addition, 2,711 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 2,647, corresponding to a response rate of 98 percent. Overall response rates of 90, 86 and 93 percent are calculated for under-five’s, women’s and men’s interviews respectively.

Responses varied slightly by residence with higher rates for women and men in rural areas than in urban areas. The situation was the reverse for children under-five where rural areas had higher response rates than urban areas. The overall response rate for women, men and children under five years in rural areas were, however, higher than in urban areas. The main reason for non-response among households and eligible individuals was the failure to find these individuals at home despite several visits to the households. Regional differentials also exist with all the regions having a 90 percent or higher response rate for all the questionnaires with the exception of Hhohho and Shiselweni regions that had 88 and 89 percent response rate, respectively, for the men’s questionnaire.

Sampling error estimates

The sample of respondents selected in the 2010 Kingdom of Eswatini MICS is only one of the samples that could have been selected from the same population, using the same design and size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. The extent of variability is not known exactly, but can be estimated statistically from the survey results.

The following sampling error measures are presented in this appendix for each of the selected indicators:

Standard error (se): Sampling errors are usually measured in terms of standard errors for particular indicators (means, proportions etc). A standard error is the square root of the variance. The Taylor linearization method is used for the estimation of standard errors. Coefficient of variation (se/r) is the ratio of the standard error to the value of the indicator. Design effect (deff) is the ratio of the actual variance of an indicator, under the sampling method used in the survey, to the variance calculated under the assumption of simple random sampling. The square root of the design effect, called the design factor (deft) is used to show the efficiency of the sample design. A deft value of 1.0 indicates that the sample design is as efficient as a simple random sample, while a deft value above 1.0 indicates the increase in the standard error due to the use of a more complex sample design. Confidence limits are calculated to show the interval within which the true value for the population can be reasonably assumed to fall. For any given statistic calculated from the survey, the value of that statistics will fall within a range of plus or minus two times the standard error (p + 2.se or p – 2.se) of the statistic in 95 percent of all possible samples of identical size and design. For the calculation of sampling errors from the MICS data, the SPSS Complex Samples module has been used. The results are shown in the tables that follow. In addition to the sampling error measures described above, the tables also include weighted and unweighted counts of denominators for each

Abstract

The Swaziland Household Income and Expenditure Survey 1995 (the SHIES 1995) is the second survey of this nature to be carried out by the Central Statistical Office (CSO). The main objectives of the SHIES 95 were in the first place to provide basic data required for policy making at national and regional levels as well as for different sectors. Secondly the survey would facilitate the determination of needs or in the establishing of targets which can be identified as obtaining:

• macro estimates of household consumption and expenditure patterns needed to revise the weighting system for the Consumer Price Index (CPI);
• household consumption and expenditure patterns to make market analysis;
• data of non-expenditure consumption, i.e. consumption of own production and payments in kind, which can only be measured by a survey like the SHIES;
• data on household income by source of income.

Geographic coverage

National

Analysis unit

• Household
• Individual
• Product category

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design is based on the nation-wide Master Sample, covering both urban and rural areas (see references 2 and 3). The institutional population is not included in the survey. These people do not live in private households but in institutions like hospitals, hostels, military or police barracks, prisons etc. A stratified two-stage sampling design is used with the Census 1986 enumeration areas (EAs) as the primary sampling unit and homesteads as secondary sampling unit. The number of sampled EAs were 216 of the total 1079 EAs. They were selected by using PPS (probability proportional to size, i.e. number of homesteads). All together 6350 homesteads were sampled with systematic random sampling within the EA. Urban areas are slightly over sampled.

Mode of data collection

Face-to-face [f2f]

Cleaning operations

Coding and Editing The editors coded occupation, industry and consumption transactions. The rest of the questions in the questionnaires were pre-coded.

Data Entry The software used for data entry was the IMPS Version 3.

Data appraisal

The IMPS data entry program and validation program caused a lot of problems. It created duplicates households and individuals and strangely enough these duplicates seemed to be created at random.

Other problem was a number of batches had disappeared after data entry. To solve this more problem, more than 30% of the FORM B had been re-punched/ re-entered. A lot of effort was used to clean the data, however, all problems could not be solved.

Abstract

The Afrobarometer is a comparative series of public attitude surveys that assess African citizen's attitudes to democracy and governance, markets, and civil society, among other topics. The surveys have been undertaken at periodic intervals since 1999. The Afrobarometer's coverage has increased over time. Round 1 (1999-2001) initially covered 7 countries and was later extended to 12 countries. Round 2 (2002-2004) surveyed citizens in 16 countries. Round 3 (2005-2006) 18 countries, Round 4 (2008) 20 countries, Round 5 (2011-2013) 34 countries, Round 6 (2014-2015) 36 countries, and Round 7 (2016-2018) 34 countries. The survey covered 34 countries in Round 8 (2019-2021).

Geographic coverage

National coverage

Analysis unit

Individual

Universe

The sample universe for Afrobarometer surveys includes all citizens of voting age within the country. In other words, we exclude anyone who is not a citizen and anyone who has not attained this age (usually 18 years) on the day of the survey. Also excluded are areas determined to be either inaccessible or not relevant to the study, such as those experiencing armed conflict or natural disasters, as well as national parks and game reserves. As a matter of practice, we have also excluded people living in institutionalized settings, such as students in dormitories and persons in prisons or nursing homes.

Kind of data

Sample survey data [ssd]

Sampling procedure

Afrobarometer uses national probability samples designed to meet the following criteria. Samples are designed to generate a sample that is a representative cross-section of all citizens of voting age in a given country. The goal is to give every adult citizen an equal and known chance of being selected for an interview. They achieve this by:

• using random selection methods at every stage of sampling; • sampling at all stages with probability proportionate to population size wherever possible to ensure that larger (i.e., more populated) geographic units have a proportionally greater probability of being chosen into the sample.

The sampling universe normally includes all citizens age 18 and older. As a standard practice, we exclude people living in institutionalized settings, such as students in dormitories, patients in hospitals, and persons in prisons or nursing homes. Occasionally, we must also exclude people living in areas determined to be inaccessible due to conflict or insecurity. Any such exclusion is noted in the technical information report (TIR) that accompanies each data set.

Sample size and design Samples usually include either 1,200 or 2,400 cases. A randomly selected sample of n=1200 cases allows inferences to national adult populations with a margin of sampling error of no more than +/-2.8% with a confidence level of 95 percent. With a sample size of n=2400, the margin of error decreases to +/-2.0% at 95 percent confidence level.

The sample design is a clustered, stratified, multi-stage, area probability sample. Specifically, we first stratify the sample according to the main sub-national unit of government (state, province, region, etc.) and by urban or rural location.

Area stratification reduces the likelihood that distinctive ethnic or language groups are left out of the sample. Afrobarometer occasionally purposely oversamples certain populations that are politically significant within a country to ensure that the size of the sub-sample is large enough to be analysed. Any oversamples is noted in the TIR.

Sample stages Samples are drawn in either four or five stages:

Stage 1: In rural areas only, the first stage is to draw secondary sampling units (SSUs). SSUs are not used in urban areas, and in some countries they are not used in rural areas. See the TIR that accompanies each data set for specific details on the sample in any given country. Stage 2: We randomly select primary sampling units (PSU). Stage 3: We then randomly select sampling start points. Stage 4: Interviewers then randomly select households. Stage 5: Within the household, the interviewer randomly selects an individual respondent. Each interviewer alternates in each household between interviewing a man and interviewing a woman to ensure gender balance in the sample.

To keep the costs and logistics of fieldwork within manageable limits, eight interviews are clustered within each selected PSU.

Eswatini - Sample size: 1,200 - Sampling Frame: Eswatini Central Statistics Office 2017 Population Census - Sample design: Nationally representative, random, clustered, stratified, multi-stage area probability sample - Stratification: Region, urban-rural distribution - Stages: PSUs (from strata), start points, households, respondents - PSU selection: Probability Proportionate to Population Size (PPPS) - Cluster size: 8 households per PSU - Household selection: Randomly selected start points, followed by walk pattern using 5/10 interval - Respondent selection: Gender quota filled by alternating interviews between men and women; respondents of appropriate gender listed, after which computer randomly selects individual

Mode of data collection

Face-to-face [f2f]

Research instrument

The Round 8 questionnaire has been developed by the Questionnaire Committee after reviewing the findings and feedback obtained in previous Rounds, and securing input on preferred new topics from a host of donors, analysts, and users of the data.

The questionnaire consists of three parts: 1. Part 1 captures the steps for selecting households and respondents, and includes the introduction to the respondent and (pp.1-4). This section should be filled in by the Fieldworker. 2. Part 2 covers the core attitudinal and demographic questions that are asked by the Fieldworker and answered by the Respondent (Q1 – Q100). 3. Part 3 includes contextual questions about the setting and atmosphere of the interview, and collects information on the Fieldworker. This section is completed by the Fieldworker (Q101 – Q123).

Response rate

Outcome rates: - Contact rate: 97.53% - Cooperation rate: 91.95% - Refusal rate: 1.27% - Response rate: 89.69%

Sampling error estimates

+/-3 percentage points at 95% confidence level

Kingdom of Eswatini 2007 administrative level 0-2 boundaries

Vetting and live service provision by Information Technology Outreach Services (ITOS) with funding from USAID.

These boundaries are suitable for database or GIS linkage to the Kingdom of Eswatini - Subnational Population Statistics.

Swaziland SZ: Death Rate: Crude: per 1000 People data was reported at 9.585 Ratio in 2016. This records a decrease from the previous number of 9.861 Ratio for 2015. Swaziland SZ: Death Rate: Crude: per 1000 People data is updated yearly, averaging 13.547 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 20.165 Ratio in 1960 and a record low of 9.092 Ratio in 1991. Swaziland SZ: Death Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eswatini – Table SZ.World Bank.WDI: Population and Urbanization Statistics. Crude death rate indicates the number of deaths occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

The 2000 Swaziland Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Swaziland at the end of the decade and for looking forward to the next decade; - To furnish data needed for monitoring progress toward goals established at the World Summit for Children and a basis for future action; - To contribute to the improvement of data and monitoring systems in Swaziland and to strengthen technical expertise in the design, implementation, and analysis of such systems.

Geographic coverage

The 2000 Swaziland Multiple Indicator Cluster Survey (MICS) is a nationally representative survey of households, women, and children.

Analysis unit

Household, Women, Children.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the Swaziland Multiple Indicator Cluster Survey (MICS) 2000 was designed to provide estimates of health indicators at the national level, urban, rural and company town areas and for the four regions: Hhohho, Manzini, Shiselweni and Lubombo. The sample was selected in two stages. At the first stage , 300 clusters were selected with probability proportional to size. After a household listing was carried out within the selected clusters, a systematic sample of 4500 households was drawn. Because the sample was stratified by region, it is not self-weighting. For reporting national level results, sample weights are used.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires for the Swaziland MICS were based on the MICS Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, literacy, marital status, and orphanhood status. The household questionnaire also includes education, child labor, water and sanitation, and salt iodization modules. In addition to a household questionnaire, questionnaires were administered in each household for women age 15- 49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.

The questionnaire for women contains the following modules: Child mortality Tetanus toxoid Maternal and newborn health Contraceptive use HIV/AIDS.

The questionnaire for children under age five includes modules on: Birth registration and early learning Vitamin A Breastfeeding Care of Illness Malaria Immunization Anthropometry.

Information on Vitamin A and Malaria have not been analysed . Reasons for not incuding Vitamin A is that there is no current programme in place on Vit A supplement in the country. Reasons for living malaria module out is that data collection was conducted in the off season for malaria in the country.

Cleaning operations

Data were entered on four microcomputers using the IMPS software. In order to ensure quality control, all questionnaires were double entered and internal consistency checks were performed. Procedures and standard programs developed under MICS and adapted to the Swaziland questionnaire were used throughout. Data processing began in October 2000 and finished in December 2000.

Response rate

Although 4500 households were selected, 4192 were successfully interviewed for a household response rate of 90 percent. In the interviewed households 5320 eligible women (age 15-49) were identified. Of these, 5271 were successfully interviewed, yielding a response rate of 99 percent. In addition, 3525 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 3509 for a response rate of 99 percent.

Swaziland SZ: Population: Growth data was reported at 1.783 % in 2017. This records a decrease from the previous number of 1.810 % for 2016. Swaziland SZ: Population: Growth data is updated yearly, averaging 2.311 % from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 4.326 % in 1987 and a record low of 0.596 % in 2003. Swaziland SZ: Population: Growth data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eswatini – Table SZ.World Bank.WDI: Population and Urbanization Statistics. Annual population growth rate for year t is the exponential rate of growth of midyear population from year t-1 to t, expressed as a percentage . Population is based on the de facto definition of population, which counts all residents regardless of legal status or citizenship.; ; Derived from total population. Population source: (1) United Nations Population Division. World Population Prospects: 2017 Revision, (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

Abstract

Since its inception in the mid-1990s, the Multiple Indicator Cluster Surveys programme, known as MICS, has become the largest source of statistically sound and internationally comparable data on children and women worldwide. In countries as diverse as Bangladesh, Thailand, Fiji, Qatar, Cote d’Ivoire, Turkmenistan and Argentina, trained fieldwork teams conduct face-to-face interviews with household members on a variety of topics – focusing mainly on those issues that directly affect the lives of children and women. MICS is an integral part of plans and policies of many governments around the world, and a major data source for more than 30 Sustainable Development Goals (SDGs) indicators. The MICS programme continues to evolve with new methodologies and initiatives, including MICS Plus, MICS Link, MICS GIS and the MICS Tabulator.

Geographic coverage

Eswatini The majority of MICS surveys are designed to be representative at the national level. Sample sizes are sufficient to generate robust data at the regional or provincial levels, and for urban and rural areas. In MICS1, subnational surveys, covering specific geographical areas (such as the Northeast zone of Somalia and West Bank and Gaza Strip of State of Palestine) within countries were also conducted.

Analysis unit

Household, Individual

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample for the MICS1 was designed to provide national estimates of indicators for the Mid-Decade Goals. Additionally, most countries also used the survey to provide subnational estimates – for example, at the level of regions, areas, states, provinces or districts. These data may be used for detecting areas where greater efforts are required, as well as for programming and evaluation purposes.

MICS1 reports routinely disaggregate data by location of residence. More details on particular sampling design can be found in the survey final reports.

Mode of data collection

Face-to-face [f2f]

Research instrument

MICS questionnaires were designed by implementing agencies, typically the National Statistical Offices. In each country, MICS questionnaires were based on an assessment of the country’s data needs. The starting point was the standard MICS1 questionnaire designed under the guidance of the Planning and Coordination Office, all relevant technical clusters within UNICEF and the Evaluation and Research Office, with assistance from the United Nations Statistical Office, with support from UNFPA, and in consultation with other United Nations agencies, especially the World Health Organization and UNESCO. Countries chose from the MICS modules in the standard MICS questionnaires. All survey activities, from sample and survey design, to fieldwork and report writing were carried out by the implementing agencies – with limited technical support from UNICEF regional advisors in monitoring and evaluation.

The MICS1 standard questionnaire was set up as a series of modules:

HOUSEHOLD MODULES: Household Information Panel Mother and Child Listing Form Water and Sanitation Module Salt Iodization Module Education Module

MODULES FOR MOTHERS: Tetanus Toxoid Module Care of Acute Respiratory Illness Module (optional)

MODULES FOR CHILDREN UNDER FIVE YEARS OF AGE: Diarrhoe Module Vitamin A Module Breastfeeding Module (optional) Immunization Module Anthropometry Module

MORTALITY MODULE (alternative)

Abstract

The principal objectives of the Swaziland HIES are to provide detailed data and statistics to assist policy making both for Swaziland overall as well as for specific regional classifications such as administrative, ecological, urban and rural. Moreover, the results of the survey are intended to be used to: - Generate macro figures of household consumption and expenditure patterns which would be required to revise the weighting for the Consumption Price Index (CPI); - Identify current patterns of consumption and to look at the effects of different demographic and social variables on consumption; - To produce household consumption and expenditure patterns to facilitate market analysis; - To obtain data on household consumption and expenditure to be used for poverty analysis and studying the dynamics of changes in welfare and standards of living over time, in particular between successive Swaziland HIESs; - Determine the extent of ownership of household durable goods; - To obtain data on extra-monetary consumption such as consumption of goods and services either form own production, or from payments and gifts in-kind;

The survey is meant to assist in national economic and social planning, and research, and the formulation of policies as well as assessing and monitoring their effectiveness over time.

Geographic coverage

National

Analysis unit

• Households
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The sample design for the 2000-2001 Swaziland HIES was a two-stage stratification cluster sample. Stratification was done on the basis of certain considerations which are mentioned below.

The 1997 population census identified 1758 enumeration areas (EAs), and these EAs served as primary sampling units (PSUs). Out of the 1758 EAs, a total of 422 were selected. Moreover, within these 422 EAs, 284 (around 67%) were chosen from rural areas while the remaining 138 were drawn from urban regions. Given that the 1997 census estimates overall rural/urban division as 77% and 23%, it is noted that urban areas were oversampled in order to improve their representativeness and to provide accurate estimates. Following the sampling procedure, appropriate weights were used to inflate the sample to Swaziland's overall population.

Ecologically, the country is divided into four well-defined zones: Highveld, Middleveld, Lowveld, and the Lubombo. Urban areas are of three types. First, there are gazetted towns, which are traditional urban or per-urban areas that developed around trading posts; secondly, company towns, which are densely populated areas of habitation, built as living quarters for laborers working at major plantations, sugar factories, etc.; and thirdly, non-gazetted towns, which are simply informal towns.

Prior to the selection process, the EAs were arranged into six economically homogeneous strata that cut across both rural and urban locations. This stratification process was based on the above mentioned ecological and administrative subdivisions of the country, as well as land distribution and tenure features.

The total number of strata was 11, out of which 8 were rural and 3 urban. Table 24 in Appendix A3 (refer 2000-2001 Swaziland Household Income Expenditure Survey Report) provides a more detailed explanation of the stratification coding breakdown.

The aim was to interview around 350 households in each stratum. The exception was the stratum of gazetted towns, in which twice as many i.e. approximately 700 households were to be interviewed, as the economic activities of households in these towns differ more from one another than in the rest of the strata. In practice, a total of 422 PSUs were sampled. Using a probability proportional to size (PPS) technique, and then 10 households in each PSU were randomly selected. As a result the total number of households for which data collected was planned was 4220. However, primarily due to non-response on the part of certain households, the eventual number of households on which data was obtained was 3552. This represents around 2% of the total number of households in Swaziland.

The two-stage process for computing the weights involves taking the probability of selection at either stage, inverting these probabilities, and then multiplying them.

Note: See detailed sampling information is presented in Appendix A2 of the 2000-2001 Swaziland Household Income Expenditure Survey Report.

Mode of data collection

Face-to-face [f2f]

Data appraisal

Various problems were encountered at different levels and different stages in the analysis with regard to data quality and availability. Data on food consumption as recorded in the consumption diary was somewhat lacking. In the case of non-food expenditure, there was no information on the value of durable goods. There were some problems with coding of variables as well, such as missing or incorrect codes. There were also difficulties with periods of reference of expenditure on education and health.

Another area of concern was lack of information on quantities consumed, and by association, prices, as well as unit of weight of quantities consumed. These concerns and issues are discussed in detail in the Appendix A5 of the 2000-2001 Swaziland Household Income and Expenditure Survey report.

Mongolia Imports: Africa: Eswatini data was reported at 0.675 USD th in Mar 2025. This records an increase from the previous number of 0.080 USD th for Feb 2025. Mongolia Imports: Africa: Eswatini data is updated monthly, averaging 1.659 USD th from Sep 2015 (Median) to Mar 2025, with 58 observations. The data reached an all-time high of 247.042 USD th in May 2019 and a record low of 0.000 USD th in Jan 2025. Mongolia Imports: Africa: Eswatini data remains active status in CEIC and is reported by National Statistics Office of Mongolia. The data is categorized under Global Database’s Mongolia – Table MN.JA011: Imports: by Country.

Swaziland SZ: Urban Population data was reported at 323,014.000 Person in 2017. This records an increase from the previous number of 315,077.000 Person for 2016. Swaziland SZ: Urban Population data is updated yearly, averaging 160,132.500 Person from Dec 1960 (Median) to 2017, with 58 observations. The data reached an all-time high of 323,014.000 Person in 2017 and a record low of 13,663.000 Person in 1960. Swaziland SZ: Urban Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Eswatini – Table SZ.World Bank.WDI: Population and Urbanization Statistics. Urban population refers to people living in urban areas as defined by national statistical offices. It is calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects. Aggregation of urban and rural population may not add up to total population because of different country coverages.; ; World Bank staff estimates based on the United Nations Population Division's World Urbanization Prospects: 2018 Revision.; Sum;