Malaria Indicator Survey 2010
Kenya, 2010
Created on
Apr 25, 2019
Last modified
Apr 25, 2019
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Identification
Survey ID Number
KEN_2010_KMIS_v01_M
Title
Malaria Indicator Survey 2010
Country
| Name | Country code |
|---|---|
| Kenya | KEN |
Study type
Other Household Health Survey [hh/hea]
Series Information
As a household level survey, a malaria indicator survey (MIS) is particularly useful in countries where malaria is a major public health problem. An MIS provides an opportunity to measure the coverage of interventions that primarily target the household level, such as insecticidetreated nets and behaviour change communication, and also helps to understand patterns of antimalarial use among target populations.
The MIS complements other household surveys such as the Demographic and Health Surveys and Multiple Indicator Cluster Surveys in evaluating progress against malaria control targets.
Unlike other surveys, MIS is conducted during the peak malaria transmission season, thus giving a true picture of malaria prevalence among target populations. This is the second MIS to be conducted in Kenya and there are some differences from the fi rst one, conducted in 2007.
For one thing, the 2010 MIS sampled all districts in Kenya, weighting samples by malaria epidemiology, while in 2007, six districts in areas of low or no malaria risk were not included. Second, the 2007 MIS included only children less than fi ve years of age, but this one covered children up through 14 years.
The MIS complements other household surveys such as the Demographic and Health Surveys and Multiple Indicator Cluster Surveys in evaluating progress against malaria control targets.
Unlike other surveys, MIS is conducted during the peak malaria transmission season, thus giving a true picture of malaria prevalence among target populations. This is the second MIS to be conducted in Kenya and there are some differences from the fi rst one, conducted in 2007.
For one thing, the 2010 MIS sampled all districts in Kenya, weighting samples by malaria epidemiology, while in 2007, six districts in areas of low or no malaria risk were not included. Second, the 2007 MIS included only children less than fi ve years of age, but this one covered children up through 14 years.
Abstract
The main objectives of the 2010 KMIS were to measure progress achieved in key malaria indicators since the 2007 KMIS and to provide a baseline for the NMS 2009–2017. The specifi c objectives were:
1. To determine the status of coverage of various key malaria intervention measures (e.g., bed net coverage and use, preventive measures during pregnancy, etc.).
2. To assess the prevalence of malaria among children 3 months to 14 years.
3. To assess the level of anaemia among children 6 months to 14 years.
1. To determine the status of coverage of various key malaria intervention measures (e.g., bed net coverage and use, preventive measures during pregnancy, etc.).
2. To assess the prevalence of malaria among children 3 months to 14 years.
3. To assess the level of anaemia among children 6 months to 14 years.
Kind of Data
Sample survey data [ssd]
Unit of Analysis
Household, Individual, children age 3 months to 14 years, women age 15 to 49
Version
Version Description
v1.1: Data captured as it was collected from the field.
v1.2: Cleaned data and validated data
v1.2: Cleaned data and validated data
Version Notes
Initially the data was in captured using MS-ACCESS, exported to CSpro 4.1 and then exported to SPSS for Analysis
Scope
Notes
Household characteristics, Assess the prevalence of malaria among children 3 months to 14 years, Assess the level of anaemia among children 6 months to 14 years. Mosquito Net usage by defacto members of the household,The woman's questionnaire targeted women aged 15 - 49 years. It was used to collect information on background characteristics, reproductive history, use of intermittent preventive treatment during pregnancy for recent births, fever prevalence and treatment among children under five, and knowledge and attitudes regarding malaria and child survival.
Topics
| Topic | Vocabulary |
|---|---|
| Health | World Bank |
| Malaria | World Bank |
Keywords
| Keyword |
|---|
| Malaria |
| Children health |
Coverage
Geographic Coverage
National coverage
Universe
The household questionnaire was distributed to households in the sampled area. The woman's questionnaire targeted women aged 15 - 49 years from the households.
Producers and sponsors
Primary investigators
| Name | Affiliation |
|---|---|
| Kenya National Bureau of Statistics | Ministry of Planning and National Development |
| Division of Malaria Control | Ministry of Public Health and Sanitation |
Producers
| Name | Role |
|---|---|
| World Health Organization | Technical Assistance |
| Center for Disease Control and Prevention | Technical Assistance |
Funding Agency/Sponsor
| Name | Abbreviation | Role |
|---|---|---|
| United Kingdom Department for Internation International Development | DFID | Funding |
| United states President's Malaria Initiative | PMU | Funding |
| United Nations Children's Fund | UNICEF | Funding |
Sampling
Sampling Procedure
Asample of 7,200 households for the 2010 KMIS was selected to be representative of the entire household population in Kenya. The design for the survey used a representative probability sample to produce estimates for the four malaria epidemiological zones with the endemic zones divided into lake endemic and coast endemic to make fi ve zones:
1. Highland epidemic-prone
2. Lake endemic
3. Coast endemic
4. Seasonal risk/Semi-arid
5. Low risk
In addition, in each zone, clusters were categorized into urban and rural areas and provided two implicit domains for analysis at the national level.
The survey used the National Sample Survey and Evaluation Programme (NASSEP) IV sampling frame. The frame is nationally representative and was developed by the KNBS after the 1999 Census to support two-stage cluster sample surveys. The fi rst stage sampling process involved selection of enumeration areas (EAs) and creation of 1,800 clusters with probability proportional to measure of size with the districts as the fi rst level of stratifi cation.
From the frame, a representative sample of 240 clusters was selected for the 2010 KMIS with a uniform sample of 30 households allocated to each cluster. The resulting sample of 7,200 households was designed so as to produce estimates of most of the key malaria indicators including the prevalence of anaemia in children aged 6 months through 14 years for the specified domains.
The sampling of the clusters was done by the KNBS prior to commencement of the fi eldwork and the details loaded into the interviewers' PDAs, which were fi tted with the capability to record the global positioning system (GPS) coordinates. All the selected clusters were mapped using PDAs in a process that involved collecting the basic descriptions of all the households and their geographic coordinates. A simple random sample of 30 households per cluster was selected with the aid of the PDAs.
Further details on the sample design are provided in Appendix A of the final report
1. Highland epidemic-prone
2. Lake endemic
3. Coast endemic
4. Seasonal risk/Semi-arid
5. Low risk
In addition, in each zone, clusters were categorized into urban and rural areas and provided two implicit domains for analysis at the national level.
The survey used the National Sample Survey and Evaluation Programme (NASSEP) IV sampling frame. The frame is nationally representative and was developed by the KNBS after the 1999 Census to support two-stage cluster sample surveys. The fi rst stage sampling process involved selection of enumeration areas (EAs) and creation of 1,800 clusters with probability proportional to measure of size with the districts as the fi rst level of stratifi cation.
From the frame, a representative sample of 240 clusters was selected for the 2010 KMIS with a uniform sample of 30 households allocated to each cluster. The resulting sample of 7,200 households was designed so as to produce estimates of most of the key malaria indicators including the prevalence of anaemia in children aged 6 months through 14 years for the specified domains.
The sampling of the clusters was done by the KNBS prior to commencement of the fi eldwork and the details loaded into the interviewers' PDAs, which were fi tted with the capability to record the global positioning system (GPS) coordinates. All the selected clusters were mapped using PDAs in a process that involved collecting the basic descriptions of all the households and their geographic coordinates. A simple random sample of 30 households per cluster was selected with the aid of the PDAs.
Further details on the sample design are provided in Appendix A of the final report
Response Rate
Ninety-three percent of the targeted households were interviewed. The survey yielded response rates of 93 percent and 94 per cent for eligible children and women, respectively. Response rates for children under five reported by interviewed women were lower (74 percent). Response rates are higher in rural areas than in urban areas.
Weighting
Sample allocation among the domains was not proportional and therefore, the resulting sample was not self-weighting- Weighting adjustments were done to provide comparable estimates for the domains of study weighting was done using the frame design selection probabilities and adjusted to cater for household and individual non-response and the aggregates weights were normalized and then applied to the data.
Data Collection
Dates of Data Collection
| Start | End |
|---|---|
| 2010-07-18 | 2010-09-18 |
Data Collection Mode
Face-to-face [f2f]
Supervision
Fieldwork was closely supervised by a team of national supervisors from the DOMC including the Provincial Malaria Control Coordinators and KNBS who visited the teams in the field to ensure that the survey was conducted according to the protocol and provide solutions to some of the challenges encountered. The teams were facilitated in the field by KNBS district staff; these included District Statistical Officers (DSO) and cluster guides who made sure that the enumeration areas were accurately identified. Village elders were also instrumental in guiding the teams and mobilizing the communities in their respective clusters. Children who tested positive for malaria using the rapid diagnostic test were provided with a full course of artemether-lumefantrine (AL) according to national guidelines for the treatment of malaria in Kenya 10 KMIS.
Data Collection Notes
Training
Field staff training for KMIS 2010 was conducted from 7 to 17 July 2010 in Nakuru. A total of 148 participants took part, including 25 team supervisors, 59 research assistants, 56 health workers (28 clinicians and 28 laboratory technologists) and the 8 Provincial Malaria Control Coordinators.
Team supervisors and research assistants were trained on the rationale and methodology of KMIS data collection using PDAs and global positioning system technology. Key concepts in household listing, interviewing skills and filling the questionnaires using PDAs were emphasized.
Health workers were trained on how to conduct informed consent and specimen collection procedures like preparing blood smears and performing rapid diagnostic tests (RDT) for malaria and anaemia testing. Participants also received refresher training on the management of uncomplicated malaria and referral of complicated malaria cases.
As part of the training, the questionnaires were pre-tested in six urban areas in Nakuru that were purposively selected because of their proximity to the training center. The questionnaires were then adapted and finalized for the actual field work.
Fieldwork
Among the 148 trained field staff, only 128 were selected for final data collection, while 12 were kept as reserves in case of attrition. The remaining eight were Provincial Malaria Control Coordinators who acted as national coordinators during the fieldwork. Twenty-five teams, each comprising one supervisor, two research assistants and two health workers (a clinician and a laboratory technician) constituted the field staff. Teams were each allocated clusters in the different districts in accordance to their local language competency. Each team was assigned a driver and supplied with logistics for the survey activity. The fieldwork was conducted for approximately 40 days with a one-week break at the beginning of August to allow for the national constitutional referendum activities.
Prior to the fieldwork, the communities residing in the sampled clusters received information about the KMIS through social mobilization and the mass media. This was necessary to alert the communities about the days of the survey and also that children would be tested for malaria. Taking of blood samples is often a sensitive issue requiring adequate information beforehand to avoid misinformation.
The fieldwork commenced on 18 July and after the one-week break (1-7 August) ended on 2 September. Teams spent an average of three days in a cluster with the first day dedicated to mapping the households while the next two days were used to conduct field interviews.
Field staff training for KMIS 2010 was conducted from 7 to 17 July 2010 in Nakuru. A total of 148 participants took part, including 25 team supervisors, 59 research assistants, 56 health workers (28 clinicians and 28 laboratory technologists) and the 8 Provincial Malaria Control Coordinators.
Team supervisors and research assistants were trained on the rationale and methodology of KMIS data collection using PDAs and global positioning system technology. Key concepts in household listing, interviewing skills and filling the questionnaires using PDAs were emphasized.
Health workers were trained on how to conduct informed consent and specimen collection procedures like preparing blood smears and performing rapid diagnostic tests (RDT) for malaria and anaemia testing. Participants also received refresher training on the management of uncomplicated malaria and referral of complicated malaria cases.
As part of the training, the questionnaires were pre-tested in six urban areas in Nakuru that were purposively selected because of their proximity to the training center. The questionnaires were then adapted and finalized for the actual field work.
Fieldwork
Among the 148 trained field staff, only 128 were selected for final data collection, while 12 were kept as reserves in case of attrition. The remaining eight were Provincial Malaria Control Coordinators who acted as national coordinators during the fieldwork. Twenty-five teams, each comprising one supervisor, two research assistants and two health workers (a clinician and a laboratory technician) constituted the field staff. Teams were each allocated clusters in the different districts in accordance to their local language competency. Each team was assigned a driver and supplied with logistics for the survey activity. The fieldwork was conducted for approximately 40 days with a one-week break at the beginning of August to allow for the national constitutional referendum activities.
Prior to the fieldwork, the communities residing in the sampled clusters received information about the KMIS through social mobilization and the mass media. This was necessary to alert the communities about the days of the survey and also that children would be tested for malaria. Taking of blood samples is often a sensitive issue requiring adequate information beforehand to avoid misinformation.
The fieldwork commenced on 18 July and after the one-week break (1-7 August) ended on 2 September. Teams spent an average of three days in a cluster with the first day dedicated to mapping the households while the next two days were used to conduct field interviews.
Data Collectors
| Name | Abbreviation | Affiliation |
|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Ministry of Planning and National Development |
Questionnaires
Questionnaires
The questionnaires used in the 2010 KMIS were developed by the Roll Back Malaria Monitoring and Evaluation Reference Group (MERG) in collaboration with ICF Macro. The standard questionnaires were adapted to the Kenyan situation and programmed into PDAs by a team from CDC/Atlanta. The questionnaires were fi rst reviewed by the KMIS Technical Working Group and were translated into Kiswahili. All KMIS interviews were done using the PDAs.
Two types of questionnaires were used: a Household Questionnaire and a Woman’s Questionnaire. The Household Questionnaire captured information on the usual members and visitors, including age, sex and relationship to the head of the household. One purpose of the Household Questionnaire was to identify women aged 15–49 who were eligible for the individual interviews. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the fl oor, walls and roof of the house, etc. Information on ownership and use of mosquito nets was also collected with the Household Questionnaire. In addition, this questionnaire was used to capture some information on attitudes about malaria and to record the results of the request for doing anaemia and malaria testing on young children.
The Woman’s Questionnaire was administered to consenting women aged 15–49 years to collect data on background characteristics, reproductive history, use of intermittent preventive treatment (IPT) during pregnancy for recent births, fever prevalence and treatment among children under fi ve, and knowledge and attitudes regarding malaria and child survival.
Two types of questionnaires were used: a Household Questionnaire and a Woman’s Questionnaire. The Household Questionnaire captured information on the usual members and visitors, including age, sex and relationship to the head of the household. One purpose of the Household Questionnaire was to identify women aged 15–49 who were eligible for the individual interviews. The questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used for the fl oor, walls and roof of the house, etc. Information on ownership and use of mosquito nets was also collected with the Household Questionnaire. In addition, this questionnaire was used to capture some information on attitudes about malaria and to record the results of the request for doing anaemia and malaria testing on young children.
The Woman’s Questionnaire was administered to consenting women aged 15–49 years to collect data on background characteristics, reproductive history, use of intermittent preventive treatment (IPT) during pregnancy for recent births, fever prevalence and treatment among children under fi ve, and knowledge and attitudes regarding malaria and child survival.
Data Processing
Data Editing
KMIS data were captured using PDAs fitted with GPS. The questionnaires were programmed into the PDAs and tested before the actual field work. They were then periodically transferred to and saved on the supervisor’s PDA in each team and at the end of the data collection were downloaded onto a personal computer for merging and analysis. The data underwent various cleaning processes before analysis. First, the data were corrected for problems in geographic coding by using ArcGIS software to plot the coordinates and identify the misplaced information. The data were further split and merged into various data sets to ease analysis and were converted into SPSS (Statistical Package for Social Science) format. The data sets were then converted into CSPro format and further checks/corrections were made prior to the production of preliminary tabulations.
Data Appraisal
Estimates of Sampling Error
Sampling errors listed in tables in report.
Data Appraisal
The following data quality tables are produced:
- Household age distribution
- Coverage of testing for malaria and anaemia testing in children
- Prevalence of malaria in children aged 3-59 months
- Anaemia prevalence among children aged 6-59 months
See the tables in Appendix D of the final report.
- Household age distribution
- Coverage of testing for malaria and anaemia testing in children
- Prevalence of malaria in children aged 3-59 months
- Anaemia prevalence among children aged 6-59 months
See the tables in Appendix D of the final report.
Access policy
Contacts
| Name | Affiliation | URL | |
|---|---|---|---|
| Director General | KNBS | directorgeneral@knbs.or.ke | http://www.knbs.or.ke |
| General Inquiries | MEASURE DHS | info@measuredhs.com | http://www.measuredhs.com |
| Data and Data Related Resources | MEASURE DHS | archive@measuredhs.com | http://www.measuredhs.com |
Citation requirements
"Kenya National Bureau of Statistics, 2010 Kenya Malaria Indicator Survey (KMIS 2010), Version 1.2, provided by the Kenya National Data Archive. http://statistics.knbs.or.ke/nada/index.php/catalog"
Disclaimer and copyrights
Disclaimer
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.
Metadata production
DDI Document ID
DDI_KEN_2010_KMIS_v02_M
Producers
| Name | Abbreviation | Affiliation | Role |
|---|---|---|---|
| Kenya National Bureau of Statistics | KNBS | Ministry of Planning and National Development | Production |
| Accelerated Data Program | ADP | International Household Survey Network | Review of the metadata |
Date of Metadata Production
2013-05-31
DDI Document version
Version 02 (October 2013). Edited version based on Version 01 DDI that was done by Kenya National Bureau of Statistics and reviewed by Accelerated Data Program, International Household Survey Network.