Malaria Indicator Survey 2021
Nigeria, 2021
Get MicrodataIdentification
NGA_2021_MIS_v01_M
Malaria Indicator Survey 2021
| Name | Country code |
|---|---|
| Nigeria | NGA |
Malaria Indicator Survey [hh/mis]
The 2021 Nigeria Malaria Indicator Survey (NMIS) was implemented by the NMEP in collaboration with the National Population Commission (NPC) and the National Bureau of Statistics (NBS), with technical assistance from ICF. The first NMIS was conducted in 2010 and the second in 2015. The 2021 NMIS is a follow-up to the 2015 NMIS.
The primary objective of the 2021 NMIS was to provide up-to-date estimates of basic demographic and health indicators related to malaria. Specifically, the NMIS collected information on vector control interventions (such as mosquito nets), intermittent preventive treatment of malaria in pregnant women, exposure to messages on malaria, care-seeking behaviour, treatment of fever in children, and social and behaviour change communication (SBCC). Children age 6–59 months were also tested for anaemia and malaria infection. The information collected through the NMIS is intended to assist policymakers and programme managers in evaluating and designing programmes and strategies for improving the health of the country’s population.
Sample survey data [ssd]
- Household
- Individual
- Woman age 15-49
Scope
The 2021 Nigeria Malaria Indicator Survey covers the following topics:
HOUSEHOLD
• Identification
• Usual members and visitors in the selected households
• Background information on each person listed, such as relationship to head of the household, age, sex, and marital status
• 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
• Mosquito nets
INDIVIDUAL WOMAN
• Identification
• Background characteristics (including age, education, and media exposure)
• Reproduction (birth history and child mortality)
• Pregnancy and intermittent preventive treatment
• Fever in children
• Malaria knowledge and beliefs
BIOMARKER
• Identification
• Hemoglobin measurement and malaria testing for children age 6 months to 4 years
FIELDWORKER
• Background information on each fieldworkers
Coverage
National coverage
Producers and sponsors
| Name | Affiliation |
|---|---|
| National Malaria Elimination Programme (NMEP) | Federal Ministry of Health (FMoH), Nigeria |
| Name | Role |
|---|---|
| National Population Commission, Nigeria | Collaborated in the implementation of the survey |
| National Bureau of Statistics, Nigeria | Collaborated in the implementation of the survey |
| ICF | Provided technical assistance through The DHS Program |
| Name | Role |
|---|---|
| Government of Nigeria | Financial support |
| United States Agency for International Development | Financial support |
| Global Fund to Fight AIDS, Tuberculosis and Malaria | Financial support |
Sampling
The sample for the 2021 NMIS was designed to provide most of the survey indicators for the country as a whole, for urban and rural areas separately, and for each of the country’s six geopolitical zones, which include 36 states and the Federal Capital Territory (FCT). Nigeria’s geopolitical zones are as follows:
• North Central: Benue, Kogi, Kwara, Nasarawa, Niger, Plateau, and FCT
• North East: Adamawa, Bauchi, Borno, Gombe, Taraba, and Yobe
• North West: Jigawa, Kaduna, Kano, Katsina, Kebbi, Sokoto, and Zamfara
• South East: Abia, Anambra, Ebonyi, Enugu, and Imo
• South South: Akwa Ibom, Bayelsa, Cross River, Delta, Edo, and Rivers
• South West: Ekiti, Lagos, Ogun, Osun, Ondo, and Oyo
The 2021 NMIS used the sample frame for the proposed 2023 Population and Housing Census (PHC) of the Federal Republic of Nigeria. Administratively, Nigeria is divided into states. Each state is subdivided into local government areas (LGAs), each LGA is divided into wards, and each ward is divided into localities. Localities are further subdivided into convenient areas called census enumeration areas (EAs). The primary sampling unit (PSU), referred to as a cluster unit for the 2021 NMIS, was defined on the basis of EAs for the proposed 2023 PHC.
A two-stage sampling strategy was adopted for the 2021 NMIS. In the first stage, 568 EAs were selected with probability proportional to the EA size. The EA size is the number of households residing in the EA. The sample selection was done in such a way that it was representative of each state. The result was a total of 568 clusters throughout the country, 195 in urban areas and 373 in rural areas.
For further details on sample design, see Appendix A of the final report.
A total of 14,185 households were selected for the survey, of which 13,887 were occupied and 13,727 were successfully interviewed, yielding a response rate of 99%. In the interviewed households, 14,647 women age 15-49 were identified for individual interviews. Interviews were completed with 14,476 women, yielding a response rate of 99%.
Survey instrument
Three questionnaires were used in the 2021 NMIS: the Household Questionnaire, the Woman’s Questionnaire, and the Biomarker Questionnaire. The questionnaires, based on The DHS Program’s model questionnaires, were adapted to reflect the population and health issues relevant to Nigeria. After the questionnaires were finalised in English, they were translated into Hausa, Yoruba, and Igbo.
Data collection
| Start | End |
|---|---|
| 2021-10-12 | 2021-12-04 |
- Face-to-face [f2f]
Fieldworkers were grouped into 37 teams, each team consisting of one supervisor, one medical laboratory scientist/biomarker specialist, one nurse/interviewer, and two interviewers. Overall, 37 supervisors, 74 female interviewers, 37 biomarker specialists, and 37 nurses were deployed (a total of 185 personnel). Five biomarker specialists and five nurses were kept as reserves. Following deployment, each team developed a schedule to visit the various clusters selected. Prior to fieldwork, each team had entry meetings with the respective states’ Ministries of Health and offices of the National Population Commission. Advocacy visits were paid to key community gatekeepers at the community level to enable smooth entrance of the survey team and increase acceptance by community members.
Data collection lasted from 12 October to 4 December 2021. The fieldwork in some states took longer than expected due to the security situation and delays in household listing. During fieldwork, blood from finger pricks (or heel pricks among children age 6–11 months) was collected from eligible children (6–59 months) for rapid diagnostic testing, anaemia testing, and thin and thick film preparation. The slides were counted, recorded in the transmittal sheet, signed, and then sent to staining sites; subsequently, they were transported to the ANDI Centre of Excellence, the primary slide reading laboratory. The teams were closely monitored by the state coordinators, zonal biomarker representatives, quality control officers, and national monitors. The monitors were given orientation and provided with appropriate guidelines and checklists. The IFSS was used for uploading of data from the field in real time while fieldwork and data quality were simultaneously monitored by NMEP, NPC, and ICF. Weekly field check tables generated from the completed interviews sent to the central office were used to monitor fieldwork progress, and regular feedback was sent to the teams.
Data processing
The processing of the 2021 NMIS data began immediately after the start of fieldwork. As data collection was being completed in each cluster, all electronic data files were transferred via the IFSS to the NPC central office in Abuja. Data files were registered and checked for inconsistencies, incompleteness, and outliers. The field teams were alerted on any inconsistencies and errors. Secondary editing, carried out in the central office, involved resolving inconsistencies and coding open-ended questions. 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. Concurrent processing of the data offered a distinct advantage because it maximised the likelihood of the data being error-free and accurate. Timely generation of field check tables also allowed for effective monitoring. Secondary editing of the data was completed in February 2022. The data processing team coordinated this exercise at the central office.
Data appraisal
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 in 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, or incorrect data entry. Although numerous efforts were made during the implementation of the 2021 Nigeria Malaria Indicator Survey (NMIS) to minimise 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 2021 NMIS is only one of many samples that could have been selected from the same population, using the same design and expected sample size. Each of these samples would yield results that differ somewhat from the results of the selected sample. Sampling errors are a measure of the variability among all possible samples. Although the exact degree of variability is unknown, 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, and so on), 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 as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the 2021 NMIS sample was the result of a multistage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed via SAS programmes developed by ICF. These programmes use the Taylor linearisation method to estimate variances for estimated means, proportions, and ratios. The Jackknife repeated replication method is used for variance estimation of more complex statistics such as fertility and mortality rates.
Sampling errors tables are presented in Appendix B of the final report.
Data Quality Tables
- Household age distribution
- Age distribution of eligible and interviewed women
- Age displacement at ages 14/15
- Age displacement at ages 49/50
- Live births by years preceding the survey
- Completeness of reporting
- Observation of mosquito nets
- Number of enumeration areas completed by month of fieldwork and zone
- Positive rapid diagnostic test (RDT) results by month of fieldwork and zone, Nigeria MIS 2021
- Concordance and discordance between RDT and microscopy results
- Concordance and discordance between national and external quality control laboratories
See details of the data quality tables in Appendix C of the final report.
Data Access
| Name | URL |
|---|---|
| The DHS Program | http://dhsprogram.com |
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.
Required Information
A dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.
Restricted Datasets
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
Because of the sensitive nature of GPS, HIV and other biomarkers datasets, permission to access these datasets requires that you accept a Terms of Use Statement. After selecting GPS/HIV/Other Biomarkers datasets, the user is presented with a consent form which should be signed electronically by entering the password for the user's account.
Dataset Terms of Use
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.
Download Datasets
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.
Contacts
| Name | Affiliation | |
|---|---|---|
| Information about The DHS Program | The DHS Program | reports@DHSprogram.com |
| General Inquiries | The DHS Program | info@dhsprogram.com |
| Data and Data Related Resources | The DHS Program | archive@dhsprogram.com |
Metadata production
DDI_NGA_2021_MIS_v01_M_WB
| Name | Affiliation | Role |
|---|---|---|
| Development Economics Data Group | The World Bank | Documentation of the DDI |
2023-03-01
Metadata version
Version 01 (March 2023). Metadata in this DDI is excerpted from "Nigeria Malaria Indicator Survey 2021" report.
2023-03-01