{"type":"survey","doc_desc":{"title":"MWI_2014_MIS_v01_M","idno":"DDI_MWI_2014_MIS_v01_M_WB","producers":[{"name":"Development Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2015-09-02","version_statement":{"version":"Version 01 (September 2015). Metadata is excerpted from \"Malaria Indicator Survey 2014\" Report."}},"study_desc":{"title_statement":{"idno":"MWI_2014_MIS_v01_M","title":"Malaria Indicator Survey 2014","alt_title":"MIS 2014 \/ MMIS 2014"},"authoring_entity":[{"name":"National Malaria Control Programme (NMCP)","affiliation":"Ministry of Health, Government of Malawi"}],"production_statement":{"producers":[{"name":"ICF International","affiliation":"","role":"Provided technical assistance"},{"name":"National Statistical Office","affiliation":"","role":"Assisted in the household listing in the selected enumeration areas"}],"funding_agencies":[{"name":"Government of Malawi","abbreviation":"GovMAI","role":"Financial assistance in terms of in-kind contribution"},{"name":"Global Fund","abbreviation":"GF","role":"Funded the study - supported the local costs of the survey"},{"name":"U.S. President\u2019s Malaria Initiative","abbreviation":"PMI","role":"Funded the study - supported the survey through ICF International"}]},"distribution_statement":{"contact":[{"name":"Information about The DHS Program","affiliation":"The DHS Program","email":"reports@DHSprogram.com","uri":"http:\/\/www.DHSprogram.com"},{"name":"General Inquiries","affiliation":"The DHS Program","email":"info@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"},{"name":"Data and Data Related Resources","affiliation":"The DHS Program","email":"archive@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"}]},"series_statement":{"series_name":"Demographic and Health Survey, Special [hh\/dhs-sp]","series_info":"The 2014 Malawi MIS is the 2nd Malaria Indicator Survey conducted in Malawi as part of The DHS Program. It was designed to provide estimates for the country as a whole, for urban and rural areas separately, and for each of the three regions in Malawi."},"study_info":{"abstract":"The 2014 MIS used a standard set of instruments and protocol developed by RBM Monitoring and Evaluation Reference Group (MERG). These tools are largely based on the collective experience gained from the DHS and MIS surveys and are presented as a package of materials to promote standardised survey management and data collection methodology. The package also includes standardised measurement of malaria parasite and anaemia prevalence among target populations to derive the malariarelated burden at the community level.\n\nThe key objectives of the 2014 MIS were to:\n\u2022 Measure the level of ownership and use of mosquito nets\n\u2022 Assess coverage of intermittent preventive treatment for pregnant women\n\u2022 Identify treatment practises, including the use of specific antimalarial medications to treat malaria among children under 5\n\u2022 Measure the prevalence of malaria and anaemia among children age 6-59 months\n\u2022 Assess knowledge, attitudes, and practises of malaria in the adult population\n\u2022 Measure trends in key malaria indicators since the 2012 MIS\n\nThe 2014 MIS was designed to produce most of the key malaria indicators for the country as a whole, for urban and rural areas separately, and for each of the three regions in Malawi: Northern, Central, and Southern.","coll_dates":[{"start":"2014-05-02","end":"2014-06-10","cycle":""}],"nation":[{"name":"Malawi","abbreviation":"MWI"}],"geog_coverage":"National coverage","analysis_unit":"- Women age 15-49 years\n- Children age 6-59 months","data_kind":"Sample survey data [ssd]","notes":"The scope of 2014 Malawi Malaria Indicators Survey covered the following topics:\n\nHousehold Level\n\u2022 List usual members and visitors \n\u2022 Basic characteristics of each person in the household collected (age, sex, education, etc.) \n\u2022 Housing characteristics (access to water, sanitation facilities, floor\/roof\/wall materials, etc.)\n\u2022 Identify women eligible for interview and children eligible for anemia and malaria testing\n\u2022 Identify ownership and use of mosquito nets\n\nWoman Level\n\u2022 Background characteristics (age, education, literacy, religion, dialect, etc.)\n\u2022 Reproductive history and child mortality for births in the last 6 years\n\u2022 Prenatal care and preventive malaria treatment for most recent birth\n\u2022 Prevalence and treatment of fever among children under 5\n\u2022 Knowledge about malaria (symptoms, causes, and ways to prevent it) and messages on malaria\n\u2022 Cost incurred for the treatment of fever in children under 5","study_scope":"The scope of 2014 Malawi Malaria Indicators Survey covered the following topics:\n\nHousehold Level\n\u2022 List usual members and visitors \n\u2022 Basic characteristics of each person in the household collected (age, sex, education, etc.) \n\u2022 Housing characteristics (access to water, sanitation facilities, floor\/roof\/wall materials, etc.)\n\u2022 Identify women eligible for interview and children eligible for anemia and malaria testing\n\u2022 Identify ownership and use of mosquito nets\n\nWoman Level\n\u2022 Background characteristics (age, education, literacy, religion, dialect, etc.)\n\u2022 Reproductive history and child mortality for births in the last 6 years\n\u2022 Prenatal care and preventive malaria treatment for most recent birth\n\u2022 Prevalence and treatment of fever among children under 5\n\u2022 Knowledge about malaria (symptoms, causes, and ways to prevent it) and messages on malaria\n\u2022 Cost incurred for the treatment of fever in children under 5"},"method":{"data_collection":{"sampling_procedure":"Sample Design\nThe 2014 MIS sample was designed to produce most of the key indicators for the country as a whole, for urban and rural areas separately, and for each of the three regions.\n\nThe survey utilised a two-stage sample design. The first stage involved selecting 140 clusters with probability proportional to size from the list of approximately 12,474 EAs covered in the 2008 National Population and Housing Census. The EA size was the number of residential households in the EA recorded in the census. Among the 140 clusters selected, 50 were in urban areas and 90 were in rural areas. Urban areas were over-sampled within regions in order to produce robust estimates for that domain. Therefore, the MIS sample was not proportional to the population for urbanrural residence and required a final weighting adjustment to provide valid estimates for every domain of the survey. In the second stage, in each of the selected EAs, 25 households were selected, using systematic sampling, from a list of households in the EA.\n\nAll women age 15-49 who were either permanent residents of the selected households or visitors present in the household on the night before the survey were eligible to be interviewed. In addition, all children age 6-59 months who were listed in the household were eligible for anaemia and malaria testing.\n\nNote: The sample design is described in details in Appendix A.","coll_mode":"Face-to-face [f2f]","research_instrument":"Three questionnaires were used in the 2014 Malawi MIS: a Household Questionnaire, a Biomarker Questionnaire, and a Woman\u2019s Questionnaire. The Household and Woman\u2019s questionnaires were based on the model MIS questionnaires developed by the RBM and DHS programmes, as well as the 2010 and 2012 MIS. The model questionnaires were modified to reflect relevant issues of malaria in Malawi in consultation with the Steering Committee, the NMCP, and staff from ICF International. The questionnaires were translated into the two main local languages of Malawi\u2014Chichewa and Tumbuka.\n\nThe 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, and relationship to the head of the household. The main purpose of the Household Questionnaire was to identify women who were eligible for the individual interview and children age 6-59 months who were eligible for anaemia and malaria testing. The Household Questionnaire also collected information on characteristics of the household\u2019s dwelling unit, such as the source of water, type of toilet facilities, materials used for the floor, roof, and walls of the house, ownership of various durable goods, and ownership and use of mosquito nets.\n\nThe Biomarker Questionnaire was used to record haemoglobin measurements for children age 6-59 months and results of malaria testing for children under age 5 years. The questionnaire was filled in by the health technician and transcribed into the tablet computer by the team supervisor.\n\nThe Woman\u2019s Questionnaire was used to collect information from all women age 15-49 years and covered the following topics:\n\u2022 Background characteristics (age, residential history, education, literacy, religion, dialect)\n\u2022 Reproductive history and child mortality for births in the last six years\n\u2022 Prenatal care and preventive malaria treatment for most recent birth\n\u2022 Prevalence and treatment of fever among children under 5 years\n\u2022 Knowledge about malaria (symptoms, causes, and ways to prevent it) and messages on malaria\n\u2022 Cost incurred for the treatment of fever in children under 5 years\n\nNo formal field pre-test was done for the survey questionnaires because most of the 2014 MIS questions were included in previous surveys in Malawi and the field staff were experienced in anaemia and malaria testing in the field and in the use of PDAs for data collection.","coll_situation":"Training\nThe NMCP in collaboration with the DHOs identified 22 interviewers 22 laboratory technicians and 11 field team supervisors. In addition, 7 national supervisors from the NMCP, the Public Health Laboratory, and other stakeholders were identified for overall supervision.\n\nThe participants attended a three-week interviewer and supervisor training which took place 14-28 April 2014 at Riverside Hotel in Lilongwe. All the field staff participated in a one-week joint training session, focusing on how to fill out the Household and Woman\u2019s Questionnaires, mock interviews, and interviewing techniques, as well as on how to locate selected households. Two quizzes were administered to assess how well the participants absorbed the training materials.\n\nDuring the second week of training, two parallel sessions were held, one for the interviewers and field supervisors and one for the laboratory technicians. The training of interviewers and field supervisors focused on the use of computer tablets for data collection, assigning of households to interviewers using computer tablets, sharing of data among interviewers and supervisors, and submission of data to the central data processing centre at NMCP.\n\nThe training of laboratory technicians was facilitated by an ICFI consultant. It focused on preparation of blood samples and testing for anaemia using the HemoCue equipment and malaria testing using SD Bioline RDT. The training involved presentations, discussions, and actual testing for anaemia and malaria. The technicians were trained in identifying children eligible for testing, administering informed consent, conducting the anaemia and malaria rapid testing, and making a proper thick blood smear. They were also trained in storing the blood slides, recording test results on the Biomarker Questionnaire, and providing the results to the parent\/guardians of the children tested. The laboratory technicians also received training on how to record children\u2019s anaemia and malaria results on the respective brochures and how to fill in the referral slip for any child who was found to be severely anaemic. They were given specific instructions on how to calculate the correct dose of antimalarial medications for children who tested positive for malaria, using the portable scales to determine the child\u2019s weight. The laboratory technicians received a lecture on the epidemiology of malaria in Malawi and the correct treatment protocols.\n\nAt the completion of classroom practise and instructions, the laboratory technicians visited the under-5 children\u2019s clinic at Kawale Health Centre and Area 18 Health Centre hospitals, where they performed anaemia and malaria testing and collected thick blood smears from children between the ages of 6 and 71 months.\n\nAll participants took part in a field practise exercise in households located close to the training site before being dispatched to their respective area of assignment.\n\nFieldwork\nEleven teams were organised for field data collection. Each team consisted of one field supervisor, two community health nurses as interviewers, two laboratory technicians, and one driver. The national supervisors were paired; one to focus on the interviewing and the other to perform laboratory procedures.\n\nThe NMCP arranged for printing the questionnaires, manuals, consent forms, and other field forms. It was also in charge of fieldwork logistics such as backpacks, identification cards, umbrellas, and other field supplies.\n\nField data collection for the 2014 Malawi MIS began on 2 May 2014. To allow for maximum supervision, all 11 teams were visited by the national supervisors at least once in the first two weeks. Fieldwork was completed by 10 June 2014.","cleaning_operations":"Data for the 2014 Malawi MIS were collected through questionnaires programmed onto computer tablets. ICFI data processing specialists loaded the Household, Biomarker, and Woman\u2019s Questionnaires in English and the two main local languages, Chichewa and Tumbuka, in the computer tablets and installed data entry and processing programmes. The tablets were Bluetooth-enabled to facilitate electronic transfer of files, e.g., data from the Household Questionnaires transferred among survey team members and transfer of completed questionnaires to the team supervisor\u2019s tablet. The field supervisors transferred data on a daily basis to the central data processing unit using the Internet. To facilitate communication and monitoring, each field worker was assigned a unique identification number.\n\nThe Census Survey Processing Software (CSPro) was used for data editing, weighting, cleaning, and tabulation. In the NMCP central office, data received from the supervisors\u2019 tablets were registered and checked against any inconsistencies and outliers. Data editing and cleaning included range checks and structure and internal consistency checks. Any anomalies were communicated to the respective team through their team supervisor. The corrected results were resent to the central processing unit."},"analysis_info":{"response_rate":"Of the 3,501 households selected for the sample, 3,415 were occupied at the time of fieldwork. Eighty-six dwellings were abandoned and, therefore, were not included in the response rate. Among the occupied households, 3,405 were successfully interviewed, yielding a total household response rate above 99 percent. In the interviewed households, 2,927 eligible women were identified as eligible for the individual interview and 2,897 were successfully interviewed, yielding a response rate of 99 percent.","sampling_error_estimates":"The estimates from a sample survey are affected by two types of errors: non-sampling errors and 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 during the implementation of the 2014 Malawi Malaria Indicator Survey (Malawi MIS) to minimise this type of error, non-sampling errors are impossible to avoid and difficult to evaluate statistically.\n\nSampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2014 Malawi MIS is only one of many samples that could have been selected from the same population, using the same design and expected 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.\n\nSampling 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.\n\nIf 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 2014 Malawi MIS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulas. Sampling errors are computed in either ISSA or SAS, using programs developed by ICF International. These programs use the Taylor linearisation method of variance estimation for survey estimates that are means, proportions, or ratios like the ones in the Malawi MIS survey.\n\nThe Taylor linearisation 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.\n\nNote: A more detailed description of estimate of sampling error is presented in APPENDIX B of the survey report.","data_appraisal":"Data Quality Tables\n- Household age distribution\n- Age distribution of eligible and interviewed women\n- Completeness of reporting\n\nNote: See detailed data quality tables in APPENDIX C of the report."}},"data_access":{"dataset_availability":{"access_place":"The DHS Program","access_place_uri":"http:\/\/dhsprogram.com\/data\/available-datasets.cfm","original_archive":"The DHS Program\nhttp:\/\/dhsprogram.com\/data\/available-datasets.cfm\nCost: None"},"dataset_use":{"contact":[{"name":"The DHS Program","affiliation":"","email":"archive@dhsprogram.com","uri":"http:\/\/www.DHSprogram.com"}],"cit_req":"Use of the dataset must be acknowledged using a citation which would include:\n- the Identification of the Primary Investigator\n- the title of the survey (including country, acronym and year of implementation)\n- the survey reference number\n- the source and date of download","conditions":"Request Dataset Access\nThe following applies to DHS, MIS, AIS and SPA survey datasets (Surveys, GPS, and HIV). \nTo 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. \n\nThe 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. \n\nDATASET ACCESS APPROVAL PROCESS\nAccess 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.\n\nRequired Information\nA dataset request must include contact information, a research project title, and a description of the analysis you propose to perform with the data.\n\nRestricted Datasets\nA 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. \n\nWhen The DHS Program receives authorization from the appropriate organizations, the user will be contacted, and the datasets made available by secure FTP. \n\nGPS\/HIV Datasets\/Other Biomarkers\nBecause 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.\n\nDataset Terms of Use\nOnce 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. \n\nDownload Datasets\nDatasets 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.","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."}}},"data_files":[{"file_id":"F1","file_name":"RECH0","description":"HOUSEHOLD \n- Household's basic data","case_count":"3501","var_count":"38","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F2","file_name":"RECH1","description":"HOUSEHOLD \n- Household Schedule","case_count":"14327","var_count":"31","producer":null,"data_checks":null,"missing_data":null,"version":null,"notes":null},{"file_id":"F3","file_name":"RECH2","description":"HOUSEHOLD \n- Household 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