RWA_2013_MIS_v01_M
Malaria Indicator Survey 2013
Name | Country code |
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Rwanda | RWA |
Demographic and Health Survey, Special [hh/dhs-sp]
The Rwanda Malaria Indicator Survey (2013 RMIS) is the first survey of its kind in Rwanda. It selects a nationally representative sample of 4,770 households from 159 sample clusters. The survey is designed to provide information on the following key malaria control indictors: (1) the proportion of households having at least one mosquito net and at least one insecticide-treated net (ITN); (2) the proportion of children under age 5 who slept under a mosquito net and under an ITN the night before the survey; (3) and the proportion of pregnant women who slept under a mosquito net and under an ITN the night before the survey.
The 2013 Rwanda Malaria Indicator Survey (RMIS) is a nationally representative, household-based survey that provides data on malaria indicators, which are used to assess the progress of a malaria control program. The control program is geared toward meeting Millennium Development Goals.
The objectives of the 2013 Rwanda Malaria Indicator Survey (RMIS) were to collect data on (1) ownership and utilization of treated mosquito nets and (2) knowledge of symptoms, causes, treatments, and prevention of malaria.
A related objective was to produce survey results in a timely manner and to ensure that the data were disseminated to a wide audience of potential users in government and nongovernmental organizations within and outside of Rwanda. Most survey indicators were produced separately for each of the five provinces.
Key indicators were malaria-specific and general.
Malaria indicators:
• Ownership of insecticide-treated mosquito nets
• Usage of insecticide-treated mosquito nets among persons in the household, children under age 5, and pregnant women
• Proportion of children under age 5 with recent fever who were treated with timely, appropriate antimalarial drugs
• Proportions of mothers who know the symptoms, treatments, and prevention of malaria
General indicators:
• Source of household drinking water; type of toilet facility
• Household socioeconomic status (wealth quintile)
Sample survey data [ssd]
The survey covered the following topics:
HOUSEHOLD:
WOMEN:
National coverage
Name | Affiliation |
---|---|
Malaria and Other Parasitic Diseases Division of the Rwanda Biomedical Center | Ministry of Health |
Name | Affiliation | Role |
---|---|---|
National Institute of Statistics | Government of Rwanda | Collaborated in the implementation of the survey |
ICF International | MEASURE DHS | Provided technical assistance |
Name | Role |
---|---|
Government of Rwanda | Funding the study |
United States Agency for International Development | Funding the study |
Global Fund to Fight AIDS, Tuberculosis and Malaria | Funding the study |
Sample Design
The sample for the 2013 RMIS was designed to provide malaria indicator estimates for the country as a whole and for separate urban and rural areas. Survey estimates are also be reported for the provinces (South, West, North, and East provinces) and Kigali City.
A representative sample of 4,772 households was selected for the 2013 RMIS. The sample was selected in two stages. In the first stage, 159 villages (also known as clusters or enumeration areas) were selected with probability proportional to village size. Village size is determined by the number of households residing in the village. Then, a complete mapping and listing of all households in the selected villages was conducted. The resulting lists of households served as the sampling frame for the second stage of sample selection. Households were systematically selected from those lists for participation in the survey.
All women age 15-49 who were either permanent residents of the households or visitors present in the household on the night before the survey were eligible for interviews.
Note: Detailed description of the sample design is presented in Appendix A of the final report.
A total of 4,772 households was selected, of which 4,769 households were identified and occupied at the time of the survey. Among these households, 4,766 completed the Household Questionnaire, yielding a response rate of nearly 100 percent.
In the 4,766 households surveyed, 5,164 women age 15-49 were identified as being eligible for the individual interview. Interviews were completed with 5,135 of these women, yielding a response rate of 99.4 percent. The response rates were slightly higher in rural areas than in urban areas.
Because of the non-proportional allocation of the sample to the different reporting domains, sampling weights will be required for any analysis using RMIS 2013 data to ensure the sample is representative. Because the RMIS 2013 sample was a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities that were calculated separately for each sampling stage and for each cluster.
Details of sampling weight calculation is available in Appendix A.4 of the final report.
The 2013 RMIS involved two questionnaires: a Household Questionnaire and a Woman’s Questionnaire for all women age 15-49 in the selected households. Both of these instruments were based on the model Demographic and Health Survey Phase III and the model Roll Back Malaria (RBM) Malaria Indicator Survey (MIS) questionnaires developed by the MEASURE DHS program, as well as on previous surveys conducted in Rwanda, including the 2007-08 Rwanda Interim DHS (RIDHS) and the 2010 Rwanda Demographic and Health Survey (RDHS). The MAL & OPD Division reviewed the draft questionnaires with potential stakeholders, including government health agencies and interested donor groups.
The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, education, and relationship to the head of household. The main purpose of the Household Questionnaire was to identify women eligible for individual interview. Questions on ownership and use of mosquito nets were included in the Household Questionnaire as were questions about proxy indicators for wealth such as ownership of various durable goods, dwelling unit characteristics, and land.
The Woman’s Questionnaire was used to collect information from women age 15-49 on the following topics:
• Background characteristics (age, education, media exposure, employment, religion, and so on)
• Reproductive history (number of births, date of last birth, current pregnancy status, and antimalarial treatment for children under age 5 with recent fever)
• Knowledge about malaria symptoms, causes, and prevention
Start | End |
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2013-02-17 | 2013-04-26 |
Name | Affiliation |
---|---|
Malaria and Other Parasitic Diseases Division of the Rwanda Biomedical Center | Ministry of Health |
Training for pretesting occurred from January 9 to January 18, 2013. Fifteen women and men were trained to administer the RMIS survey questionnaire and household listing update. Four days of fieldwork were followed by one day of interviewer debriefing and testing. Pretest fieldwork was conducted in 80 households in two rural and two urban villages outside of Kigali City. All pretest participants attended the main training and served as team leaders/field editors for the main survey.
For the main data collection, the Mal & OPD Division recruited and trained 50 participants from 21 January to 1 February 2013 on how to use the RMIS survey instruments, including the household listing update, questionnaires, and fieldwork practice. The training consisted of instruction regarding interviewing techniques and field procedures, a detailed review of items on the questionnaires, and mock interviews and role plays. Instruction and practice on updating a household listing was also included in the main training. At the end of the training 48 participants were organized into 12 data collection teams consisting of a team leader/field editor, and three interviewers. The National Institute of Statistics of Rwanda (NISR) assisted in training for the household listing update.
Fieldwork was launched immediately upon the conclusion of field staff training. Fieldwork supervision was conducted by the MAL & OPD Division through regular visits to teams to review their work and monitor data quality. Additional contact between the central office and the teams was maintained through cell phones. Fieldwork was conducted from February 17, 2013, through April 26, 2013. Questionnaires were regularly delivered to MAL & OPD Division headquarters.
Processing of the 2013 RMIS data began as soon as questionnaires were received from the field. Completed questionnaires were returned from the field to MAL & OPD Division headquarters, where they were entered and edited by data processing personnel who were specially trained for this task. Processing the data concurrently with data collection allowed for regular monitoring of team performance and data quality. Field check tables were regularly generated during data processing to check various data quality parameters. As a result, feedback was given on a regular basis, encouraging teams to continue their high quality work and to correct areas in need of improvement. Feedback was individually tailored to each team. Data entry, which included 100 percent double entry to minimize errors in keying and data editing, was completed on May 10, 2013. Data cleaning and finalization was completed on June 3, 2013.
The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) 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 2013 Rwanda Malaria Indicator Survey (2013 RMIS) 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 2013 RMIS 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 error is 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 2013 RMIS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. The computer software used to calculate sampling errors for the 2013 RMIS is an SAS program. This program used the Taylor linearization method for variance estimation for survey estimates that are means or proportions.
The Taylor linearization method treats any percentage or average as a ratio estimate, r = y/x, where y represents the total sample value for variable y, and x represents the total number of cases in the group or subgroup under consideration.
Note: Detailed description of estimate of sampling error is presented in APPENDIX B of the final report.
Data quality tables are produced to review the quality of the data:
Note: The tables are presented in APPENDIX C of the final report.
Name | URL | |
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The DHS Program | http://www.DHSprogram.com | archive@dhsprogram.com |
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Name | Affiliation | URL | |
---|---|---|---|
Malaria and Other Parasitic Diseases Division of the Rwanda Biomedical Center | Ministry of Health | info@rwandamalariaforum.org | http://www.rbc.gov.rw |
Malaria and Other Parasitic Diseases Division of the Rwanda Biomedical Center | Ministry of Health | info@rwandamoh.gov.rw | http://www.rbc.gov.rw |
Information about The DHS Program | The DHS Program | reports@DHSprogram.com | http://www.DHSprogram.com |
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