The 2019-20 Rwanda Demographic and Health Survey (RDHS) is the sixth Demographic and Health Survey (DHS) conducted in Rwanda, following those implemented in 1992, 2000, 2005, 2010, and 2014-15. The National Institute of Statistics of Rwanda (NISR), in collaboration with the Ministry of Health (MOH), implemented the survey.
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.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
- Children age 0-5
- Woman age 15-49
- Man age 15 to 59
The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http://dhsprogram.com).
The 2019-20 Rwanda Demographic and Health Survey covered the following topics:
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, marital status, educational attainment, birth registration, survivorship and residence of biological parents, insurance, and disability.
• Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, type of fuel used for cooking, number of rooms, ownership of livestock, possessions of durable goods, mosquito nets, and main material for the floor, roof and walls of the dwelling.
• Background characteristics (including age, education, and media exposure)
• Birth history and child mortality
• Knowledge, use, and source of family planning methods
• Antenatal, delivery, and postnatal care
• Vaccinations and childhood illnesses
• Breastfeeding and infant feeding practices
• Women’s minimum dietary diversity
• Marriage and sexual activity
• Fertility preferences (including desire for more children and ideal number of children)
• Women’s work and husbands’ background characteristics
• Knowledge, awareness, and behavior regarding HIV/AIDS and other sexually transmitted infections (STIs)
• Knowledge, attitudes, and behavior related to other health issues (e.g., smoking)
• Early childhood development
• Adult and maternal mortality
• Domestic violence
• Background characteristics
• Marriage and sexual activity
• Fertility preferences
• Employment and gender roles
• Other health issues
• Weight, height and hemoglobin, and malaria testing for children age 0-5 (Capillary blood)
• Weight, height, hemoglobin measurement, and malaria and HIV testing for women age 15-49 (Capillary blood)
• HIV testing for men age 15-59
• Micronutrient, weight, height, hemoglobin, and malaria testing for children age 0-5 (Venous blood)
• Micronutrient, weight, height, hemoglobin, and malaria testing for women age 15-49 (Venous blood)
• Background information on each fieldworkers
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.
Producers and sponsors
National Institute of Statistics of Rwanda (NISR)
Government of Rwanda
Ministry of Health
Government of Rwanda
Collaborated in the implementation of the survey
The DHS Program
Provided technical assistance through The DHS Program
Government of Rwanda
United States Agency for International Development
One United Nations
Centers for Disease Control and Prevention
United Nations Children Fund
United Nations Population Fund
United Nations Entity for Gender Equality and the Empowerment of Women
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.
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%.
Due to the non-proportional allocation of the sample to the different provinces and their districts and the possible differences in response rates, sampling weights will be required for any analysis using 2019-20 RDHS data to ensure the actual representativeness of the survey results at the national level and as well as the domain level. Since the 2019-20 RDHS sample was a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster.
For further details on sampling weights, see Appendix A.4 of the final report.
Dates of Data Collection
Data Collection Mode
Computer Assisted Personal Interview [capi]
Fieldwork monitoring was an integral part of the 2019-20 RDHS, and several rounds of monitoring were carried out by the survey coordinators and supervisors of NISR, RBC and ICF. The coordinators were provided with guidelines for overseeing the fieldwork. Weekly field check tables were generated from the completed interviews sent to the central office to monitor fieldwork progress, and feedback was regularly sent out to the teams.
Data Collection Notes
Data collection was carried out by 17 field teams. Each team was provided a four-wheel-drive truck with a driver. All blood smears and DBS specimens were transferred to the NISR office every 3-4 days by 10 supervisors from the NISR and NRL who also coordinated and supervised fieldwork activities. Venous blood specimens were processed in the field laboratories set up in the district hospitals, and serum aliquots were stored in mobile freezers (-20°C) before being transferred to the regional laboratories and then the NRL. ICF and the CDC provided technical assistance during the entire data collection period.
The fieldwork for the 2019-20 RDHS was carried out under close supervision starting on November 9, 2019, in the clusters in the 17 districts in the North, West, and East provinces. The teams were closely monitored by the field coordinators for quality control. After completion of the fieldwork in these 17 districts, the teams were dispatched to the final 13 districts. However, in the wake of the COVID-19 pandemic, the fieldwork was suspended from April to June 2020. Data collection resumed on June 4 and was completed on July 20, 2020.
National Institute of Statistics of Rwanda
Government of Rwanda
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.
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.
Estimates of Sampling Error
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 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 completed by month, according to province, Rwanda DHS 2019-20
- Completeness of information on siblings
- Sibship size and sex ratio of siblings
- Pregnancy-related mortality
See details of the data quality tables in Appendix C of the final report.
The DHS Program
Information about The DHS Program
The DHS Program
The DHS Program
Data and Data Related Resources
The DHS Program
Request Dataset Access
The following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV).
To request dataset access, you must first be a registered user of the website. You must then create a new research project request. The request must include a project title and a description of the analysis you propose to perform with the data.
The requested data should only be used for the purpose of the research or study. To request the same or different data for another purpose, a new research project request should be submitted. The DHS Program will normally review all data requests within 24 hours (Monday - Friday) and provide notification if access has been granted or additional project information is needed before access can be granted.
DATASET ACCESS APPROVAL PROCESS
Access to DHS, MIS, AIS and SPA survey datasets (Surveys, HIV, and GPS) is requested and granted by country. This means that when approved, full access is granted to all unrestricted survey datasets for that country. Access to HIV and GIS datasets requires an online acknowledgment of the conditions of use.
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
A few datasets are restricted and these are noted. Access to restricted datasets is requested online as with other datasets. An additional consent form is required for some datasets, and the form will be emailed to you upon authorization of your account. For other restricted surveys, permission must be granted by the appropriate implementing organizations, before The DHS Program can grant access. You will be emailed the information for contacting the implementing organizations. A few restricted surveys are authorized directly within The DHS Program, upon receipt of an email request.
When The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP.
GPS/HIV Datasets/Other Biomarkers
Once downloaded, the datasets must not be passed on to other researchers without the written consent of The DHS Program. All reports and publications based on the requested data must be sent to The DHS Program Data Archive in a Portable Document Format (pdf) or a printed hard copy.
Datasets are made available for download by survey. You will be presented with a list of surveys for which you have been granted dataset access. After selecting a survey, a list of all available datasets for that survey will be displayed, including all survey, GPS, and HIV data files. However, only data types for which you have been granted access will be accessible. To download, simply click on the files that you wish to download and a "File Download" prompt will guide you through the remaining steps.
Use of the dataset must be acknowledged using a citation which would include:
- the Identification of the Primary Investigator
- the title of the survey (including country, acronym and year of implementation)
- the survey reference number
- the source and date of download
Disclaimer and copyrights
The user of the data acknowledges that the original collector of the data, the authorized distributor of the data, and the relevant funding agency bear no responsibility for use of the data or for interpretations or inferences based upon such uses.
DDI Document ID
Development Economics Data Group
The World Bank
Documentation of the DDI
Date of Metadata Production
DDI Document version
Version 01 (October 2021). Metadata is excerpted from "Rwanda Demographic and Health Survey 2019-20" Report.