Historical dataset of population level and growth rate for the Kigali, Rwanda metro area from 1950 to 2025.

This statistic shows the biggest cities in Rwanda in 2022. In 2022, approximately **** million people lived in Kigali, making it the biggest city in Rwanda.

Abstract

Obtaining reliable size estimates for key populations is crucial for the Rwanda Biomedical Center/Institute of HIV/AIDS, Disease Prevention and Control (RBC/IHDPC) and their partners to design an effective HIV response in line with the national HIV strategy. Estimating the size of key populations at higher risk for HIV not only allows for an understanding of the magnitude of the response that is needed, but also helps in more accurately projecting the future of the epidemic in Rwanda. To be effective, it is important to produce consistent and comparable estimates over time. The following study utilized a single household survey to estimate the size of several key populations, including sex workers, men who have sex with men (MSM), injecting drug users (IDU), and clients of sex workers. These populations include several groups outlined in the National Strategic Plan for HIV and AIDS as most at risk for HIV infection, specifically sex workers and MSM.

Geographic coverage

National

Analysis unit

• Household
• Individuals

Kind of data

Sample survey data [ssd]

Sampling procedure

The ESPHS used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. Each of these households was visited to obtain information using the Household Questionnaire. All women and all men age 15 years and above were eligible to be individually interviewed, if they were either usual residents of the household or visitors present in the household on the night before the survey. A total of 4,669 women and men were successfully interviewed.

The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC) 2012, provided by the National Institute of Statistics of Rwanda (NISR). The sampling frame is a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means “to know” someone.

Mode of data collection

Face-to-face [f2f]

Research instrument

The survey used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Household questionnaire: The Household Questionnaire was a short version of the 2011 Rwanda DHS questionnaire. It was primarily used to list all the usual members and visitors in the selected households and to collect some basic information on the characteristics of each person listed, including age, sex, status of residence, and marital status. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, and ownership of various durable goods. This information was used to create an index representing the wealth of the households. The wealth index is a proxy for long-term standard of living of the households and is used in the following analysis as a background characteristic of the respondents who are members of these households.

Individual questionnaire: The individual questionnaire was organized accordingly and included six sections: - Respondent’s background; - Known population; - Summation; - Target population; - Proxy respondent; and - Stigma.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99%. From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98%. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98%. The response rates do not significantly vary by type of questionnaire or residence.

This statistic shows the total population of Rwanda from 2013 to 2023 by gender. In 2023, Rwanda's female population amounted to approximately 7.15 million, while the male population amounted to approximately 6.8 million inhabitants.

Abstract

The fourth Population and Housing Census (PHC4) was based on the characteristics of persons with disabilities under the following three broad headings: (i) The number, prevalence, types, and causes of disability, (ii) The demographic, social and economic characteristics of persons with disabilities, (iii) The characteristics of household heads with disabilities and the living standards of their households. The disability measure used in the 2012 Census was based on the International Classification of Functioning, Disability and Health (ICF) and used the concept of activity limitations e.g. difficulty seeing, hearing, speaking, walking/climbing and learning/concentrating to identify persons with disabilities.

The 2012 PHC was carried out by the National Institute of Statistics of Rwanda (NISR). Field work was conducted from August 16th to August 30th 2012, financial support was provided by the Government of Rwanda, The World Bank (WBG), UKAID, the European Union (EU), One UN, United Nations Population Fund (UNFPA), United Nations Development Programme (UNDP), United Nations Children's Fund (UNICEF) and UN Women.

The specific objectives of the PHC include: 1. The number of persons with disabilities and the prevalence of the different types of disability. 2. The causes of these disabilities. 3. The background characteristics (profile) of persons with disabilities. 4. The household headship rate among people with disabilities. 5. The characteristics of heads of household with disabilities. 6. The household characteristics and the living conditions of households headed by persons with disabilities compared to those headed by persons without a disability.

Geographic coverage

National

Analysis unit

Individuals

Kind of data

Census/enumeration data [cen]

Sampling procedure

As disability affects only a rather small percentage of the population, Census data were particularly valuable in providing detailed evidence on the demographic and socio-economic characteristics of this population group. Sample surveys, unless specifically targeting the population with disabilities, tend to have insufficient sample sizes to examine types and causes of disabilities as well as detailed cross-tabulations of characteristics of the population with disabilities.

Overall, 446,453 persons with disabilities aged 5 and above live in Rwanda according to the 2012 Census, out of which 221,150 are male and 225,303 are female. The count of persons with disabilities by province reflects the geographical distribution of the population in general, with the largest number being found in the Southern Province (122,319) and the lowest in Kigali City (32,170). For the same reason, the number of persons with disabilities is higher in rural areas than in urban areas.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two different types of questionnaires were administered. One for private households and one for institutional households. The questionnaire for private households contained a person record, a household record and a mortality record. The questionnaire for institutional households contained only a person record.

UNOSAT code FL20230504RWA, GDACS Id: 1101977 This map illustrates satellite-detected surface waters in Kigali City, Southern, Northern, Western, and Eastern Provinces, Rwanda as observed from a Sentinel-1 image acquired on 3 May 2023 at 18:20 local time. Within the analyzed area of about 6,000 km2, about 20 km2 of land appear to be flooded. Based on Worldpop population data and the detected surface waters in the analyzed area, the potentially exposed population is mainly located in Southern Province Zambezia province with ~7,000 people, and Kigali City with ~5,600 people.

This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).

Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.

Abstract

The Estimating the Size of Populations through a Household Survey (EPSHS), sought to assess the feasibility of the network scale-up and proxy respondent methods for estimating the sizes of key populations at higher risk of HIV infection and to compare the results to other estimates of the population sizes. The study was undertaken based on the assumption that if these methods proved to be feasible with a reasonable amount of data collection for making adjustments, countries would be able to add this module to their standard household survey to produce size estimates for their key populations at higher risk of HIV infection. This would facilitate better programmatic responses for prevention and caring for people living with HIV and would improve the understanding of how HIV is being transmitted in the country.

The specific objectives of the ESPHS were: 1. To assess the feasibility of the network scale-up method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 2. To assess the feasibility of the proxy respondent method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 3. To estimate the population size of MSM, FSW, IDU, and clients of sex workers in Rwanda at a national level; 4. To compare the estimates of the sizes of key populations at higher risk for HIV produced by the network scale-up and proxy respondent methods with estimates produced using other methods; and 5. To collect data to be used in scientific publications comparing the use of the network scale-up method in different national and cultural environments.

Geographic coverage

National

Analysis unit

• Household
• Individual

Sampling procedure

The Estimating the Size of Populations through a Household Survey (ESPHS) used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC), which was conducted in 2012; it was provided by the National Institute of Statistics of Rwanda (NISR).

The sampling frame was a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means "to know" someone.

For further details on sample design and implementation, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Estimating the Size of Populations through a Household Survey (ESPHS) used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

A total of 2,125 households were selected in the sample, of which 2,120 were actually occupied at the time of the interview. The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99 percent.

From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98 percent. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98 percent. The response rates do not significantly vary by type of questionnaire or residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made to minimize this type of error during the implementation of the Rwanda ESPHS 2011, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ESPHS 2011 is only one of many samples that could have been selected from the same population, using the same design and identical 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. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the ESPHS 2011 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the ESPHS 2011 is a SAS program. This program uses the Taylor linearization method for variance estimation for survey estimates that are means or proportions.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

UNOSAT code FL20230504RWA, GDACS Id: 1101977 This map illustrates satellite-detected surface waters in Kigali City, Southern, Northern, Western, and Eastern Provinces, Rwanda as observed from a Sentinel-1 image acquired on 5 May 2023 at 05:45 local time. Within the analyzed area of about 6,000 km², about 54 km² of land appear to be flooded. Water extent appears to have increased by about 34km² since 3 May 2023. Based on Worldpop population data and the detected surface waters in the analyzed area, about 34,600 people are potentially exposed or living close flooded areas mainly along the Nyabarongo river, the potentially exposed population is mainly located in Southern Province with ~11,000 people, and Eastern Province with ~6,000 people
This is a preliminary analysis and has not yet been validated in the field. Please send ground feedback to United Nations Satellite Centre (UNOSAT).
Important note: Flood analysis from radar images may underestimate the presence of standing waters in built-up areas and densely vegetated areas due to the backscattering properties of the radar signal.

Abstract

The Household Living Conditions Survey, also known as Enquête Intégrale sur les Conditions de Vie des Ménages (EICV) in French, was conducted by the Statistics Department of the Ministry of Finance and Economic Planning. The survey was primarily intended to provide policy planners and decision-makers with basic data on household living standards in Rwanda.

In addition, the survey was to be used to: - calculate weights for the Consumer Price Index and estimate final household consumption, - measure the effect of macro-economic policies and projects on the conditions and living standards of the population, - produce key indicators of household welfare in order to assist policy-makers and development partners to improve the design of their development strategy, - identify policy target groups with a view to ensuring that state interventions are better targeted. - provide information on the socio-economic characteristics of households with a view to setting up a socio-economic data base. - carry out in-depth studies, for example on poverty, nutrition, housing conditions, etc, - improve the national capability to conduct statistical surveys, however complex they may be.

Geographic coverage

National coverage with all 11 former provinces (now 5 major provinces) and the City of Kigali.

Analysis unit

-Household -Individual -Commodity (for GDP computation)

Universe

Household members (institutional and itinerant populations excluded)

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling plan was drawn up with the technical support of the late Christopher Scott, Survey Consultant, during his mission in July 1997.

Constraints

The two main factors considered in designing the sampling plan were: - the objectives of the survey, - the fieldwork methodology given the available logistical resources. For the survey one objective was determinant: the Government wanted statistically reliable results at the level of each province, Kigali city and the "other urban sector". Thus, the objective called for 13 domain of analysis. Experience of conducting this type of survey shows that a minimum sample of 500 households per domain of study is required for sound analyses.

Sample size

The sample size was therefore 6,450 households, with 1,170 households for urban areas and 5,280 households for rural areas. Two stage sampling A two stage stratified sample was used: sampling at area level and at household level.

Sampling base

*At the area level, the chosen sampling base ( or at the enumeration district) was the "cellule"in the rural areas and the zone in urban areas, since they are usually fairly homogeneous in size and are well demarcated.

Knowledge of the size of each cellule enabled the use of the classical method of sampling with probability proportional to size at the first stage. A list of all cellules including estimates of the number of households in each was compiled from information provided by the local authorities.

*For sampling at the household level, an up-dated list of households was prepared for each of the selected first stage cellule by carrying out a listing in each sampled cellule simultaneously but with a lag in data collection before or while collecting the data. Part of this operation was carried out in collaboration with the National Population Office (ONAPO) and the Food Security Research Project (FSRP) of MINAGRI.

Mode of data collection

Face-to-face [f2f]

Research instrument

The questionnaires are published in French.

Three types of questionnaire were used in the field for data collection: - the household questionnaire comprising of 12 modules divided in two parts, A and B. - the community questionnaire for collecting data on economic and social infrastructures in the sample units in rural areas and - a conversion form for non-standard units used by households.

Household questionnaires

Part A collects data on each member of the household. It covered the following areas: - demographic and migration characteristics, - education and health, - employment and housing.

Part B deals with the economic activity of the household. It comprises of the following five modules: - agro-pastoral activities and own-produce consumption, - household expenditure, - non-agricultural economic activities, - transfers, - durable goods, access to credit and savings.

Cleaning operations

Data Editing (see external resource entilted: Final Data Processing Report)

Questionnaires were reviewd by the controller in the field before they were dispatched for data entry. A control sheet was provided to the contollers to assist in the process of manually editing the questionnaires. Questionnaire structures were verified when the questionnaires were checked in prior to data entry. Three contracted persons reviewed the questionnaire and filled in a form that served as a primary data control sheet. Automated data editing was largely done during the data entry phase (see "Other Data Processing" for details). Some batch edit programs were used to identify inconsistent data.

Data Imputation

Data iimputation was largely done during the analysis phase by analysts. However, a "structural" imputation on the microdata was required for the own consumption data. This was done to adjust for erroneous pricing when the unit for measuring own consumption was buckets. For more information, please refer to the SPSS su=yntax files orthe data processing report.

Primary Data Issues

Coding of products was based on sequential codes for each section.

Response rate

In the course of the survey, some households did not respond, for one reason or the other. Of 6,450 households 6,431 responded, giving a response rate of 99.7%. In the course of processing the data, an additional 11 questionnaires were rejected because they did not contain useable information, in particular in respect to expenditure and consumption. Hence, the analysis was based on 6,420 households, giving a coverage rate of 99.5% of the sample households.

Sampling error estimates

Given that the survey estimates are subject to sampling variability, it is important to calculate the sampling errors for the most important estimates from each survey. The sampling error is measured by the standard error, or square root of the variance of the estimate. The CENVAR software, a component of the Integrated Microcomputer Processing System (IMPS) developed by the U.S. Census Bureau, was used for tabulating the standard errors and other measures of precision, taking into account the stratification and clustering in the sample design. The CENVAR output tables show the value of the estimates, standard errors, coefficients of variation, 95 percent confidence intervals, design effects and number of observations. Given that the confidence intervals provide a user-friendly interpretation of the sampling variability, an annex was produced with tables showing the 95 percent confidence intervals for the most important estimates from the EICV1 and EICV2 data appearing in the preliminary report. These tables provide a quick conservative test to determine whether any difference between the EICV1 and EICV2 estimates is statistically significant.

The INSR was also provided with tables showing the full CENVAR results. The design effect is defined as the variance of an estimate based on the actual sample design divided by the corresponding variance based on a simple random sample of the same size; it is a measure of the relative efficiency of the sample design. In comparing the CENVAR results from EICV1 and EICV2, it was found that the design effects are generally lower for EICV2, indicating that the stratification used for this survey was very effective. Given that the EICV1 was based on an older sampling frame from the 1991 Rwanda Census, this also contributed to the higher design effects for the EICV1 estimates.

Abstract

The objectives of the EICV 2005 are to provide information on poverty and living conditions in Rwanda and to monitor changes over time as part of the ongoing monitoring of the Poverty Reduction Strategy and other Government policies. The results of the EICV 2005 will be compared with the results of the EICV 2001 and the content of the questionnaire will be broadly similar to that of the previous survey. In addition the survey will provide data on household income and expenditures which can be used for updating the weights and market basket for the Consumer Price Index (CPI) and components of the national accounts. Survey data on agricultural activities have also proved to be important for national accounts and will complement information provided by future agricultural and rural sector surveys.

Geographic coverage

National coverage.

Analysis unit

Households

Universe

Household members (institutional and itinerant populations excluded).

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the EICV1 was based on the data and cartographic materials from the 1991 Rwanda Census of Population and Housing, while the EICV2 was based on the 2002 Rwanda Census frame. There were significant changes in the areas considered urban between the two censuses, but these geographic changes are taken into account in the comparative analysis between the EICV1 and EICV2 data. The sample design for EICV1 is described in the report on Enquête Intégrale sur les Conditions de Vie des Ménages (Avec Volet Budget - Consommation) - Plan de Sondage" (Scott, July 1997). A detailed description of the EICV2 sample design is found in the report on Recommendations on Sample Design and Estimation Methodology for the Rwanda Enquête Integrale sur les Conditions de Vie des Ménages 2005. (Megill, June 2004).

A stratified two-stage sample design was used for both the EICV1 and EICV2. The primary sampling units (PSUs) were the enumeration areas or zones de dénombrement (ZDs) defined for the census. The sample of ZDs in each stratum was selected with probability proportional to size, where the measure of size was based on the number of households from the census frame. A new listing of households was conducted in each ZD, and a sample of households was selected at the second sampling stage. The units of analysis are the households and the individual members of the household.

One of the objectives of EICV1 and EICV2 was to provide reliable estimates of household consumption and other characteristics at the level of the 12 old provinces, as well as at the national level, City of Kigali, other urban and rural. Later the country was divided into five new provinces; given the larger size of the new provinces, the corresponding estimates will have better precision than those at the old provincial level.

The stratification of the sampling frame for both EICV1 and EICV2 was designed to improve the efficiency of the sample design and ensure a sufficient sample size for the major geographic domains of analysis. The sampling frame for these surveys was stratified by the 12 old provinces, as well as by urban and rural areas. At the national level three residential strata were defined: (1) City of Kigali, (2) other urban, and (3) rural. In the case of EICV1, the ZDs in the urban and rural strata for each province were ordered geographically to provide a corresponding implicit stratification.

In the case of the City of Kigali, there is a higher variability in socioeconomic characteristics compared to the other domains. Therefore a socioeconomic stratification was defined for the ZDs in the EICV2 sampling frame for the City of Kigali, using an indicator of bien-être (well-being) based on housing characteristics in the 2002 Rwanda Census data. The ZDs were coded by four socioeconomic quartiles, and this was used as a sorting variable to provide a corresponding implicit stratification. A new stratification code for "semi-rural" was introduced into the sampling frame for EICV2 to identify urban ZDs with at least 70 percent of households with agricultural operations (based on the 2002 Rwanda Census data). This "semi-rural" code was used as one of the sorting criteria for the sampling frame of the City of Kigali and the other urban stratum in each province. Within each stratum, the ZDs in the sampling frame were further sorted geographically to provide an additional level of implicit stratification.

Given that the rural economy is primarily agricultural, the socioeconomic characteristics of the rural households are generally correlated with the crop and livestock activities found in the different bio-climatic zones. Therefore the EICV2 sampling frame for rural strata was sorted by the ten bio-climatic zones as well as geographic codes to provide an effective implicit stratification.

The sample size for EICV1 and EICV2 was determined by the precision required for the survey estimates for each domain, as well as by the resource and operational constraints. The total sample size for EICV1 was 570 ZDs and 6,450 households. For EICV2 this sample size was increased to 620 ZDs and 6,900 households, in order to provide a larger sample for the urban strata. One reason for increasing the urban sample for EICV2 was because of the expansion of urban areas following the 2002 Rwanda Census. The effective sample size for EICV1 was actually 6,420 households, since 30 non-interviews were not replaced for this survey.

Given that one of the objectives of these surveys was to produce reliable estimates for each of the 12 old provinces, a total of 40 sample rural ZDs was allocated to each province. A larger sample was allocated to the City of Kigali because of the larger variability of socioeconomic characteristics; 80 sample ZDs were selected in this domain for EICV1 and 100 ZDs for EICV2. In the case of the other urban strata, a sample of 50 ZDs for EICV1 and 80 ZDs for EICV2 were allocated to the 11 other provinces proportionately to their urban population.

For EICV1 the number of households selected per sample ZD was 9 for the City of Kigali and the other urban stratum, and 12 for the rural stratum. This was an effective sampling strategy given that the urban strata generally have more variability between ZDs and homogeneity of households within ZDs. This approach also provided a reasonable workload for the enumerators in the urban and rural ZDs based on the data collection procedures each cycle. Therefore this same sampling strategy was used for EICV2.

For both EICV1 and EICV2 the ZDs within each stratum were selected systematically with probability proportional to size, where the measure of size was based on the number of households in the ZD from the corresponding census frame (1991 for EICV1 and 2002 for EICV2). Following a new listing of households in the sample ZDs, at the second stage 9 sample households were selected systematically in each sample urban ZD and 12 sample households were selected in each rural ZD. This sampling strategy provided an approximately self-weighting sample (that is, the sampling weights were similar) within each stratum. A sample of possible replacement households was also selected systematically within each sample ZD. Whenever an original sample household could not be interviewed for any reason, it was substituted by one of the random replacement households.

Sampling deviation

As indicated, any household that was not interviewed as per the original listing and selection was replaced with a reserve household. Each EA had 4 households on reserve. A total of 522 households were replaced over the course of the survey. In addition, several EAs were swapped from their scheduled cyclic visit due to seasonal accessibility problems.

Mode of data collection

Face-to-face paper [f2f]

Research instrument

The questionnaires that were used for the survey were largely adapted from the EICV-1. However there were some substantial changes in structure particularly for the employment section. The questionnaire was subject to revision through a series of consultative meetings held in October 2004. The questionnaires remain predominantly structured with pre-coded responses. It should be noted that some of the response categories have changed between the EICV-1 and EICV-2 requiring a series of recodes for comparability.

PART A: General - Section 0: Introductory Section - Section 1: Demographics (eng_eicv2_s1_demo). - Section 2: Education (eng_eicv2_s2_education).
- Section 3: Health (eng_eicv2_s3_health). - Section 4: Migration (eng_eicv2_s4_migration).
- Section 5: Household characteristic (eng_eicv2_s5_housing). - Section 5E: Access to services (eng_eicv2_s5e_services).
- Section 6ABC: Employment Parts A,B,C (eng_eicv2_s6abc_employment). - Section 6D: Employment listing (eng_eicv2_s6d_employ_roster). - Section 6E: Salaried employment (eng_eicv2_s6e_employ_wages). - Section 6F: Non-remunerated work (eng_eicv2_s6f_noremuner).
- Section 7: Non-farm Enterprise (eng_eicv2_s7_emterprise).

PART B: Agriculture and Expenditure - Section 8A1: Livestock ownership (eng_eicv2_s8a1_livestock). - Section 8A2: Livestock products (eng_eicv2_s8a2_livestock_products). - Section 8A3: Expenditures related to livestock ownership (eng_eicv2_s8a3_livestock_expenditures). - Section 8B: Assets related to agriculture activity (eng_eicv2_s8b_ag_assets). - Section 8C: Individual plots of land (eng_eicv2_s8c_ag_plots). - Section 8D: Large scale or bulk agricultural production (eng_eicv2_s8d_ag_production1). - Section 8E: Small scale or piecemeal agricultural production (eng_eicv2_s8e_ag_production2). - Section 8F: Other

Abstract

The 2019-20 Rwanda Demographic and Health Survey (2019-20 RDHS) follows those implemented in 1992, 2000, 2005, 2010, and 2014-15. A nationally representative sample of 500 clusters and 13,000 households were selected. All women age 15-49 who were usual residents of the selected households or who slept in the households the night before the survey were eligible for the survey.

The primary objective of the 2019-20 RDHS is to provide up-to-date estimates of basic demographic and health indicators. Specifically, the 2019-20 RDHS: • collected data on fertility levels and preferences; contraceptive use; maternal and child health; infant, child, and neonatal mortality levels; maternal mortality; gender; nutrition; awareness about HIV/AIDS; self-reported sexually transmitted infections (STIs); and other health issues relevant to the achievement of the Sustainable Development Goals (SDGs) • obtained information on the availability of, access to, and use of mosquito nets as part of the National Malaria Control Program • gathered information on other health issues such as injections, tobacco use, and health insurance • collected data on women’s empowerment and domestic violence • tested household salt for iodine levels • obtained data on child feeding practices, including breastfeeding, and conducted anthropometric measurements to assess the nutritional status of children under age 5 and women age 15-49 • conducted anemia testing of women age 15-49 and children age 6-59 months • conducted malaria testing of women age 15-49 and children age 6-59 months • conducted HIV testing of women age 15-49 and men age 15-59 • conducted micronutrient testing of women age 15-49 and children age 6-59 months

The information collected through the 2019-20 RDHS is intended to assist policymakers and program managers in evaluating and designing programs and strategies for improving the health of the country’s population.

Geographic coverage

National coverage

Analysis unit

• Household
• Individual
• Children age 0-5
• Woman age 15-49
• Man age 15 to 59

Universe

The survey covered all de jure household members (usual residents), all women aged 15-49, all men age 15-59, and all children aged 0-5 resident in the household.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame used for the 2019-20 RDHS is the fourth Rwanda Population and Housing Census (RPHC), which was conducted in 2012 by the National Institute of Statistics of Rwanda (NISR). The sampling frame is a complete list of enumeration areas (EAs) covering the whole country provided by the National Institute of Statistics, the implementing agency for the RDHS. An EA is a natural village or part of a village created for the 2012 RPHC; these areas served as the counting units for the census.

The 2019-20 RDHS followed a two-stage sample design and was intended to allow estimates of key indicators at the national level as well as for urban and rural areas, five provinces, and each of Rwanda’s 30 districts for some limited indicators. The first stage involved selecting sample points (clusters) consisting of EAs delineated for the 2012 RPHC. A total of 500 clusters were selected, 112 in urban areas and 388 in rural areas.

The second stage involved systematic sampling of households. A household listing operation was undertaken in all selected EAs from June to August 2019, and households to be included in the survey were randomly selected from these lists. Twenty-six households were selected from each sample point, for a total sample size of 13,000 households. Because of the approximately equal sample sizes in each district, the sample is not self-weighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

For further details on sample selection, see Appendix A of the final report.

Mode of data collection

Computer Assisted Personal Interview [capi]

Research instrument

Five questionnaires were used for the 2019-20 RDHS: the Household Questionnaire, the Woman’s Questionnaire, the Man’s Questionnaire, the Biomarker Questionnaires, and the Fieldworker Questionnaire. These questionnaires, based on The DHS Program’s standard Demographic and Health Survey (DHS-7) questionnaires, were adapted to reflect the population and health issues relevant to Rwanda.

Cleaning operations

The processing of the 2019-20 RDHS data began almost as soon as the fieldwork started. As data collection was completed in each cluster, all electronic data files were transferred via the Internet File Streaming System (IFSS) to the NISR central office in City of Kigali. These data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted to any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding the open-ended questions. The NISR data processor coordinated the exercise at the central office. The biomarker paper questionnaires were compared with electronic data files to check for any inconsistencies in data entry. Data entry and editing were carried out using the CSPro software package. The concurrent processing of the data offered a distinct advantage because it maximized the likelihood of the data being error-free and accurate. Timely generation of field check tables allowed for effective monitoring. The secondary editing of the data was completed in the second week of September 2020.

Response rate

A total of 13,005 households were selected for the sample, of which 12,951 were occupied. All but two occupied households (12,949) were successfully interviewed, yielding a response rate of 100.0%. In the interviewed households, 14,675 women age 15-49 were identified for individual interviews; interviews were completed with 14,634 women, yielding a response rate of 99.7%. In the subsample selected for the male survey, 6,503 households were selected, of which 6,472 were occupied. All but one occupied household (6,471) were successfully interviewed, yielding a response rate of 100.0%. In this subsample, 6,544 men age 15-59 were identified and 6,513 were successfully interviewed, yielding a response rate of 99.5%. In the subsample selected for the micronutrient survey, 3,501 households were selected, of which 3,492 were occupied. All but one of the occupied households (3,491) were successfully interviewed, yielding a response rate of 100.0%.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: nonsampling errors and sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2019-20 Rwanda Demographic and Health Survey (2019-20 RDHS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2019-20 RDHS is only one of many samples that could have been selected from the same population, using the same design and sample 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 among all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

Sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. The standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

If the sample of respondents had been selected by simple random sampling, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2019-20 RDHS sample was the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed using SAS programs developed by ICF. These programs use the Taylor linearization method to estimate variances for survey estimates that are means, proportions, or ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.

Note: A more detailed description of estimates of sampling errors are presented in APPENDIX B of the survey report.

Data appraisal

Data Quality Tables

• Household age distribution
• Age distribution of eligible and interviewed women
• Age distribution of eligible and interviewed men
• Completeness of reporting
• Births by calendar years
• Reporting of age at death in days
• Reporting of age at death in months
• Standardization exercise results from anthropometry training
• Height and weight data completeness and quality for children
• Height measurements from random sub-sample of measured children
• Number of enumeration areas

Abstract

La deuxième Enquête Démographique et de Santé au Rwanda (EDSR-II) est une enquête par sondage, représentative au niveau national. Elle a été exécutée par l'Office National de Population (ONAPO), avec l'assistance technique de ORC Macro, à l'aide de financements de l'USAID, du FNUAP et de l'UNICEF. L'EDSR-II fournit des informations détaillées sur la fécondité, la planification familiale, la santé maternelle et infantile, l'état nutritionnel des enfants et des mères, la mortalité infantojuvénile, les Infections Sexuellement Transmissibles (IST) et le sida. Au cours de l'enquête, réalisée sur le terrain de juin à novembre 2000, 9 696 ménages, 10 421 femmes âgées de 15-49 ans et 2 717 hommes de 15-59 ans ont été interviewés avec succès.

Les informations recueillies sont significatives au niveau national, au niveau du milieu de résidence (Kigali Ville, Autres Villes et rural) et au niveau des préfectures pour un nombre non négligeable d'indicateurs.

L'EDSR-II a pour objectif d'estimer de nombreux indicateurs socio-économiques, démographiques et sanitaires au niveau de l'ensemble de la population et au niveau des souspopulations des femmes de 15-49 ans, des enfants de moins de 5 ans et des hommes de 15-59 ans.

Geographic coverage

Les informations recueillies sont significatives au niveau national, au niveau du milieu de résidence (Kigali Ville, Autres Villes et rural) et au niveau des préfectures pour un nombre non négligeable d'indicateurs.

Analysis unit

• Household
• Women age 15-49
• Men age 15-59
• Children under five years

Universe

L'univers de l'enquête est l'ensemble de la population et au niveau des sous-populations des femmes de 15 à 49 ans, des hommes 15-59 du ménage, des enfants de moins de 5 ans.

Kind of data

Sample survey data

Sampling procedure

L'Enquête Démographique et de Santé du Rwanda (EDSR-II) a prévu un échantillon national d'environ 9500 femmes âgées de 15 à 49 ans et 3000 hommes âgés de 15 à 59 ans. Les résultats de l'enquête sont présentés pour l'ensemble du Rwanda, le milieu urbain, le milieu rural et pour chacune des 12 préfectures, la ville de Kigali considérée comme une préfecture.

BASE DE SONDAGE

Un échantillon-maître, préparé en 1999 par la Direction des Statistiques sur la base de celui de l'Enquête Intégrale sur les Conditions de Vie (EICV) des ménages de la Banque Mondiale de 1997, a servi de base de sondage pour l'EDSR-II. L'échantillon maître est un échantillon stratifié de 570 unités aréolaires appelées sections d'énumération (SDE); la stratification utilisant le type de résidence (urbain/rural). Les domaines d'étude de l'EDSR-II correspondent à l'ensemble du Rwanda, le milieu urbain, le milieu rural et pour chacune des 12 préfectures.

En milieu urbain, 130 SDE issues du recensement de 1997 ont été tirées, et 440 en milieu rural, avec une probabilité proportionnelle au nombre de ménages en 1997.

STRUCTURE DE L'ÉCHANTILLON

L'échantillon de l'EDSR-II est un échantillon stratifié tiré à deux degrés. Comme pour l'échantillon maître, chaque domaine a été séparé en parties urbaine avec 2 strates et rurale avec 11 strates créées. L'échantillon a été tiré indépendamment dans chaque strate. Au premier degré, des SDE ont été tirées dans chaque strate avec la même probabilité car les SDE de l'échantillon maître ont été tirées avec une probabilité proportionnelle au nombre de ménages. Un dénombrement des ménages dans chacune des SDE tirées a fourni une liste de ménages à partir de laquelle des ménages ont été sélectionnés au deuxième degré. Avant le dénombrement des ménages, les grandes SDE ont été divisées en segments dont un seul a été retenu pour l'EDSR-II. Cette dernière étape n'est pas considérée comme un degré de tirage dans la mesure où elle a pour but de limiter le nombre de ménages à dénombrer à l'intérieur d'une SDE. Tous les membres des ménages sélectionnés ont été identifiés à l'aide d'un questionnaire ménage et chaque femme âgée de 15 à 49 ans a été enquêtée avec un questionnaire individuel femme. Dans la moitié des ménages sélectionnés pour l'enquête auprès des femmes, tous les hommes âgés de 15 à 59 ont également été interrogés.

RÉPARTITION DE L'ÉCHANTILLON

Une allocation proportionnelle de l'échantillon cible de femmes aux 12 domaines et à l'intérieur de chaque strate aurait permis d'obtenir un échantillon auto-pondéré. Mais cela ne permettrait pas d'obtenir au niveau des préfectures, le nombre minimal de 800 femmes nécessaires pour mesurer avec fiabilité certains indicateurs de santé.

SEGMENTATION DES GRANDES SDE

Certaines des SDE tirées pour l'EDSR-II étaient de grande taille et auraient exiger un travail énorme si tous leurs ménages devraient être systématiquement dénombrés. Ainsi, toutes les SDE tirées ayant plus de 399 ménages ont été scindées en plusieurs segments dont un seul a été retenu pour l'enquête. La règle de segmentation était la suivante : taille 400 - 599 ménages .......... segmenter en 2 taille 600 - 799 ménages .......... segmenter en 3 taille 800 - 999 ménages .......... segmenter en 4 etc.

La procédure complète sur la segmentation est décrite dans le manuel de cartographie et de dénombrement des ménages.

Mode of data collection

Face-to-face

Research instrument

Afin d'atteindre les objectifs fixés, trois types de questionnaires ont été utilisés :

a) Questionnaire ménage. Il permet de collecter des informations sur le ménage, telles que le nombre de personnes y résidant, par sexe, âge, niveau d'instruction, la survie des parents, etc. Par ailleurs, il permet de collecter des informations sur les caractéristiques du logement (approvisionnement en eau, type de toilettes, etc.), et sur la catégorie de sel utilisé par les ménages : ces informations sont recueillies afin d'évaluer les conditions environnementales et socio-économiques dans lesquelles vivent les personnes enquêtées. De plus, les femmes âgées de 15-49 ans et les enfants âgés de moins de 5 ans sont pesés et mesurés afin d'évaluer leur état nutritionnel. Enfin, le questionnaire ménage permet d'établir l'éligibilité des personnes à interviewer individuellement. Il permet aussi de déterminer les populations de référence pour le calcul de certains taux démographiques.

b) Questionnaire femme. Il comprend les neuf sections suivantes : -caractéristiques socio-démographiques des enquêtées; -reproduction; -planification familiale; -suivi pré/postnatal, allaitement, vaccination et santé des enfants; -mariage et activité sexuelle; -préférences en matière de fécondité; -caractéristiques du conjoint et activité professionnelle de la femme; -VIH/sida et autres Infections Sexuellement Transmissibles; -mortalité maternelle.

b) Questionnaire homme. Il s'agit également d'un questionnaire individuel comprenant les huit sections suivantes : -caractéristiques socio-démographiques des enquêtés; -reproduction; -planification familiale; -mariage et activité sexuelle; -préférences en matière de fécondité; -participation dans les soins de santé; -VIH/sida et autres Infections Sexuellement Transmissibles; -attitude concernant les relations dans le couple.

Ces instruments ont été développés à partir des questionnaires de base du programme DHS, préalablement adaptés au contexte du Rwanda et en tenant compte des objectifs de l'enquête. Par ailleurs, les questionnaires individuels (femme et homme) ont été traduits en Kinyarwanda de manière qu'au cours de l'enquête, les questions soient posées le plus fidèlement possible par les enquêtrices/enquêteurs.

Cleaning operations

La saisie des données sur micro-ordinateur a débuté deux semaines après le démarrage de l'enquête sur le terrain, en utilisant le logiciel ISSA (Integrated System for Survey Analysis), développé par le programme DHS. Un agent de bureau était chargé de la vérification des questionnaires venus du terrain avant de les transmettre à la saisie. Cette saisie a été réalisée par dix opératrices, du 17 juillet au 17 décembre 2000 sous la supervision de deux programmeurs. La moitié des questionnaires ont fait l'objet d'une double saisie pour éliminer du fichier le maximum d'erreurs de saisie. Par ailleurs, un programme de contrôle de qualité permettait de détecter pour chaque équipe et même, le cas échéant, pour chaque enquêtrice/enquêteur, certaines des principales erreurs de collecte. Ces informations étaient immédiatement répercutées sur les équipes de terrain lors des missions de supervision afin d'améliorer la qualité des données.

À la suite de la saisie, les données ont été éditées en vue de vérifier la cohérence interne des réponses. La vérification finale a été réalisée par l'équipe technique de l'ONAPO avec l'assistance d'un informaticien et du Résident conseiller, un démographe, appartenant tous deux au programme DHS, en utilisant une technique éprouvée au cours de dizaines d'enquêtes similaires.

Response rate

À l'intérieur des 9 696 ménages enquêtés, 10622 femmes âgées de 15-49 ans ont été identifiées comme étant éligibles pour l'enquête individuelle et pour 10421 d'entre elles, l'enquête a pu être menée à bien. Le taux de réponse s'établit donc à 98,1 % pour les interviews auprès des femmes. L'enquête homme a été réalisée dans un ménage sur trois : au total 2857 hommes de 15-59 ans ont été

Abstract

This research is a survey of unregistered businesses conducted in Rwanda from June to July 2011, simultaneously with Rwanda 2011 Enterprise Survey. Data from 240 informal businesses was analyzed.

The objective of World Bank firm-level surveys is to obtain feedback from enterprises in client countries on the state of the private sector, assess the constraints to private sector growth and create statistically significant business environment indicators that are comparable across countries.

Informal survey questionnaires are a shorter, tailored to unregistered businesses, version of Enterprise Survey questionnaires. The topics include general information about a business, infrastructure and services, sales and supplies, crime, sources and access to finance, business-government relationship, assets, AIDS and sickness (for African region), bribery, workforce composition, obstacles to get registration, reasons for not registering, and benefits that an establishment could get from registration. Business owners or managers are interviewed face-to-face.

The Informal Surveys are conducted using a uniform sampling methodology in order to minimize measurement error and yield data that are comparable across the world's economies.

Geographic coverage

Kigali and Butare

Analysis unit

The primary sampling unit of Informal Surveys is an unregistered establishment. For Rwanda, informal firms were defined as those not registered with the Rwanda Development Board.

Universe

The whole population, or the universe, covered in the survey is the non-agricultural informal economy. It comprises manufacturing and services businesses.

Kind of data

Sample survey data [ssd]

Sampling procedure

In each country, Informal Surveys are conducted in selected urban centers, which are intended to coincide with the locations for the implementation of the main Enterprise Surveys. The overall number of interviews is pre-determined, and these interviews are distributed between the two urban centers, according to criteria such as the level of business activity and each urban center's population, etc.

In Rwanda, the urban centers identified were Kigali and Butare. The target sample was 120 interviews for each urban center.

Sampling is conducted within clearly delineated sampling areas, which are geographically determined divisions within each urban center. Sampling areas are defined at the beginning of fieldwork, and are delineated according to the concentration and geographical dispersion of informal business activity. After the sampling sizes are defined for each location every city is divided into several areas that may or may not correspond to the administrative districts.

In both Kigali and Butare, for a total of 240 interviews, 16 sampling areas were identified: 12 in Kigali (Kimisagara, Muhima, Gitega, Nyamirambo, Remera, Gatsata, Gisozi, Kimironko, Rusororo/Kabuga, Gikondo, Gatenga and Kabeza/Kanombe) and 4 in Butare Mukoni, Rwabuye, Rwabuyanga, Centre Ville de Butare). Each area was divided in several sectors. In total 66 sectors were created.

In order to provide information on diverse aspects of the informal economy, the sample is designed to have equal proportions of services and manufacturing sectors (50:50). These sectors are defined by responses provided by each informal business to a question on the business's main activity included in the screener portion of the questionnaire.

As a general rule, services must constitute an ongoing business enterprise and so exclude the sale of manual labor. Manufacturing activity in the informal sector includes business activity requiring inputs and/or intermediate goods. Thus, for example, the processing of coffee, sugar, oil, dried fruit, or other processed foods is considered manufacturing, while the simple selling of these goods falls under services. If an informal business conducts a mixture of these activities, the business is considered under the manufacturing stratum.

Thus, each sampling area was designed with the goal of obtaining two interviews in services and two interviews in manufacturing. Each sampling area, including its two starting points, were delineated using Google maps, with the GPS coordinates of the starting points being systematically recorded.

The interviewers were instructed to attempt an interview at every address passed until 4 completed interviews were achieved. Once the 4 interviews were completed in each sector (two services and two manufacturing firms), the interviewer moved to the next start point.

Mode of data collection

Face-to-face [f2f]

Research instrument

One version of the questionnaire was used for all interviews.

Cleaning operations

Data entry and quality controls are implemented by the contractor and data is delivered to the World Bank in batches (typically 10%, 50% and 100%). These data deliveries are checked for logical consistency, out of range values, skip patterns, and duplicate entries. Problems are flagged by the World Bank and corrected by the implementing contractor through data checks, callbacks, and revisiting establishments.

All variables are named using, first, the letter of each section and, second, the number of the variable within the section, i.e. a1 denotes section A, question 1 (some exceptions apply due to comparability reasons). Variable names proceeded by a prefix "AF" indicate questions specific to Africa, therefore, they may not be found in the implementation of the rollout in other countries. All other suffixed variables are global and are present in all country surveys over the world. All variables are numeric with the exception of those variables with an "x" at the end of their names. The suffix "x" denotes that the variable is alpha-numeric.