{"doc_desc":{"idno":"DDI_WBG_UGA_2018_MIS_v01_M","producers":[{"name":"Development Economics Data Group","abbreviation":"DECDG","affiliation":"The World Bank","role":"Documentation of the DDI"}],"prod_date":"2020-04-27","version_statement":{"version":"Version 01 (April 2020). Metadata is excerpted from \"Uganda Malaria Indicator Survey 2018-19\" Report."}},"study_desc":{"title_statement":{"idno":"WBG_UGA_2018_MIS_v01_M","title":"Malaria Indicator Survey 2018 - 2019","alt_title":"MIS \/ UMIS 2018-19"},"authoring_entity":[{"name":"National Malaria Control Division (NMCD)","affiliation":"Government of Uganda"},{"name":"Uganda Bureau of Statistics (UBOS)","affiliation":"Government of Uganda"}],"production_statement":{"producers":[{"name":"ICF","affiliation":"","role":"Provided technical assistance"}],"funding_agencies":[{"name":"Government of Uganda","abbreviation":"GovtUGA","role":"Financial support"},{"name":"United States Agency for International Development","abbreviation":"USAID","role":"Financial support through the President\u2019s Malaria Initiative (PMI)"},{"name":"United Kingdom Department for International Development","abbreviation":"DFID","role":"Financial support"},{"name":"Global Fund","abbreviation":"GF","role":"Financial support"}]},"distribution_statement":{"contact":[{"name":"Information about The DHS Program","affiliation":"The DHS Program","email":"reports@DHSprogram.com","uri":""},{"name":"General Inquiries","affiliation":"The DHS Program","email":"info@dhsprogram.com","uri":""},{"name":"Data and Data Related Resources","affiliation":"The DHS Program","email":"archive@dhsprogram.com","uri":""}]},"series_statement":{"series_name":"Malaria Indicator Survey [hh\/mis]","series_info":"The Malaria Indicator Survey (MIS) was developed by the Monitoring and Evaluation Working Group (MERG) of Roll Back Malaria, an international partnership developed to coordinate global efforts to fight malaria. A stand-alone household survey, the MIS collects national and regional or provincial data from a representative sample of respondents.\n\nThe 2018-19 Uganda Malaria Indicator Survey (UMIS) is the third MIS conducted in Uganda after the 2009 UMIS and 2014-15 UMIS. The 2018-19 UMIS used a nationally representative sample of 320 clusters and about 8,960 households."},"version_statement":{"version_notes":"The data dictionary was generated from hierarchical data that was downloaded from the The DHS Program website (http:\/\/dhsprogram.com)."},"study_info":{"abstract":"The 2018-19 Uganda Malaria Indicator Survey (UMIS) used a nationally representative sample of 320 clusters and about 8,960 households.. The survey is designed to provide estimates of key malaria indicators for the country as a whole, urban and rural areas separately, each of the 15 regions, and refugee settlements.\n\nThe primary objective of the 2018-19 UMIS is to provide up-to-date estimates of basic demographic and health indicators related to malaria. Specifically, the 2018-19 UMIS collected information on vector control interventions such as mosquito nets and indoor residual spraying of insecticides, on intermittent preventive treatment of malaria in pregnant women, on care seeking and treatment of fever in children, and malaria knowledge, behaviour, and practices. Children less than age 5 were tested for anaemia and malaria infection.\n\nThe information collected through the 2018-19 UMIS is intended to assist policy makers and programme managers in evaluating and designing programmes and strategies for improving the health of the country\u2019s population.","coll_dates":[{"start":"2018-12-11","end":"2019-01-31","cycle":""}],"nation":[{"name":"Uganda","abbreviation":"UGA"}],"geog_coverage":"National coverage","analysis_unit":"- Household\n- Individual\n- Children age 0-5\n- Woman age 15-59","data_kind":"Sample survey data [ssd]","notes":"The 2018-19 Uganda Malaria Indicator Survey covered the following topics:\n\nHOUSEHOLD\n\u2022 Identification\n\u2022 Usual members and visitors in the selected households\n\u2022 Basic information was collected on the characteristics of each person listed in the household, including their age, sex, and relationship to the head of the household.\n\u2022 Characteristics of the household's dwelling unit, such as the source of water, type of toilet facilities, number of rooms, type of fuel used for cooking, main material of the floor, roof and walls of the house, possessions of durable goods (including land), ownership of livestock, etc.\n\u2022 Mosquito nets\n\nWOMAN\n\u2022 Identification\n\u2022 Background characteristics (age, residential history, education, literacy, religion, and ethnicity)\n\u2022 Reproductive history for the 6 years before the survey\n\u2022 Prenatal care and preventive malaria treatment for the most recent live birth\n\u2022 Prevalence and treatment of fever among children under age 5\n\u2022 Knowledge and opinions about malaria (symptoms, causes, how to prevent, and types of antimalarial medications)\n\u2022 Exposure to and sources of messages about malaria\n\nBIOMARKER\n\u2022 Identification\n\u2022 Hemoglobin measurement and malaria testing for children age 0-5"},"method":{"data_collection":{"data_collectors":[{"name":"Uganda Bureau of Statistics","abbreviation":"UBOS","affiliation":"Government of Uganda"}],"sampling_procedure":"The 2018-19 UMIS followed a two-stage sample design and was intended to allow estimates of key indicators for the following domains:\n\u25aa National\n\u25aa Urban and rural areas\n\u25aa 15 regions\n\u25aa Although they were not included as separate sampling domains, the overall sample size permitted estimates to be produced for the 14 ongoing indoor residual spraying (IRS) intervention districts: Bugiri, Kaberamaido, Koboko, Lira, Otuke, Serere, Tororo, Alebtong, Amolatar, Budaka, Butaleja, Dokolo, Namutumba, and Paliisa and 11 former IRS intervention districts Oyam, Kole, Nwoya, Amuru, Agago, Gulu, Kitgum, Pader, Omoro, Apac, and Lamwo.\n\u25aa Refugee settlements in Adjumani, Arua, Isingiro, Kamwenge, Kiryandongo, Kyegegwa, Lamwo, Moyo, and Yumbe districts were included as a separate sampling domain.\n\nThe first stage of sampling involved selecting sample points (clusters) from the sampling frames; the nonrefugee areas and the refugee settlements used separate sampling frames. Enumeration areas (EAs) delineated for the 2014 National Population and Housing Census (NPHC) were used as the sampling frame for the non-refugee areas.A sampling frame developed for the National Refugees\u2019 Survey, conducted by UBOS in collaboration with the World Bank and Office of the Prime Minister in early 2018, was used as the frame for the refugee settlement domain. A total of 320 clusters were selected with probability proportional to size from the EAs covered in the 2014 NPHC. Of these clusters, 84 were in urban areas and 236 in rural areas. Urban areas were oversampled within regions in order to produce robust estimates for that domain. A total of 22 clusters were selected with probability proportional to size from the EAs covered in the refugee frame.\n\nThe second stage of sampling involved systematic selection of households. For the non-refugee areas, a household listing operation was undertaken in all of the selected EAs in November and December 2018, and households to be included in the survey were randomly selected from these lists. In the selected clusters for the refugee settlements domain, listing was undertaken immediately before fieldwork in those clusters. Twenty-eight households were selected from each EA, for a total sample size of 8,878 households. Because of the approximately equal sample sizes in each domain, the sample was not selfweighting at the national level.\n\nNote: See Appendix A of the final survey report for additional details on the sampling procedures.","coll_mode":"Face-to-face [f2f]","research_instrument":"Three questionnaires\u2014the Household Questionnaire, the Woman\u2019s Questionnaire, and the Biomarker Questionnaire\u2014were used for fieldwork in the 2018-19 UMIS. Core questionnaires available from the Roll Back Malaria (RBM) Monitoring and Evaluation Reference Group (MERG) were adapted to reflect the population and health issues relevant to Uganda. The modifications were decided upon at a series of meetings with various stakeholders from the NMCD and other government ministries and agencies, nongovernmental organisations, and international donors. The questionnaires were in English; UBOS arranged for translation into Luganda, Luo, Lugbara, Ateso, Runyankole\/Rukiga, and Runyoro\/Rutoro. The Household and Woman\u2019s Questionnaires were programmed onto tablet computers, enabling use of computer-assisted personal interviewing (CAPI) for the survey. The Biomarker Questionnaire was filled out on hard copy and entered into the CAPI system when complete.\n\nA fourth questionnaire, the Fieldworker Questionnaire, was adapted from The DHS Program\u2019s standard questionnaire. It was completed by all fieldworkers in the 2018-19 UMIS; its purpose was to collect basic background information on the people who collect data in the field.","coll_situation":"Twenty-three teams were organised for field data collection with seven people per team. Each team consisted of one supervisor, two health technicians, one interviewer who was also a nurse, two other interviewers, and one driver. The field staff also included a health technician supervisor and four regional laboratory coordinators who followed up with teams to check on and furnish the supplies needed. They also collected slides from the field teams and delivered them to the laboratory at IDRC.\n\nUBOS arranged for printing of questionnaires, manuals, consent forms, brochures, and other field forms, and organised field supplies, which included backpacks, identification cards, and the health technicians\u2019 supplies. UBOS coordinated the fieldwork logistics.\n\nField data collection for the 2018-19 UMIS started on 11 December 2018 and finished on 31 January 2019. To ensure maximum supervision, the national monitors, largely members of the technical working group, visited all 23 teams over the entire period of data collection.","weight":"A spreadsheet containing all sampling parameters and selection probabilities was constructed to facilitate the calculation of sampling weights. Household sampling weights and individual sampling weights were calculated by adjusting the previous calculated weight to compensate household nonresponse and individual nonresponse, respectively. These weights were further normalised at the national level to produce unweighted cases equal to weighted cases for both households and individuals at the national level. The normalised weights are valid for estimation of proportions and means at any aggregation levels, but not valid for estimation of totals.","cleaning_operations":"All electronic data files for the 2018-19 UMIS were transferred via ICF\u2019s IFSS to the UBOS central office in Kampala, where they were stored on a password-protected computer. The data processing operation included registering and checking for inconsistencies, incompleteness, and outliers. Data editing and cleaning included structure and consistency checks to ensure completeness of work in the field. The central office also conducted secondary editing, which required resolution of computer-identified inconsistencies and coding of open-ended questions. The data were processed by UBOS staff who took part in the main fieldwork training and were supervised by senior staff from UBOS. The Census and Survey Processing (CSPro) System software package was used for data editing. Secondary editing and data processing were completed in February 2019."},"analysis_info":{"response_rate":"A total of 8,878 households selected for the sample in the main survey, 8,448 were occupied at the time of fieldwork. Among the occupied households, 8,351 were successfully interviewed, yielding a total household response rate of 99%. In the interviewed households, 8,389 women were eligible for individual interview, and 8,231 were successfully interviewed, yielding a response rate of 98%. In the refugee settlements, the household response rate was almost 100%, and the response rate among women was 99%."}},"data_access":{"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."}}},"schematype":"survey"}