AIDS Indicator Survey 2011
Uganda, 2011
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UGA_2011_AIS_v01_M
AIDS Indicator Survey 2011
| Name | Country code |
|---|---|
| Uganda | UGA |
Demographic and Health Survey, AIS
The AIDS Indicator Survey (AIS) was developed to provide countries with a standardized tool to obtain indicators for effective monitoring of national HIV/AIDS programs.
The design for the AIS was guided by the need to have a survey protocol that will provide, in a timely fashion and at a reasonable cost, the information required for meeting HIV/AIDS program reporting requirements, including the collection of the President’s Emergency Plan For AIDS Relief (PEPFAR), UN General Assembly Special Session on HIV/AIDS (UNGASS), and other indicators while ensuring comparability of findings across countries and over time.
AIS Survey Related Topics
Information on AIS Indicators are available for the following topics:
HIV - Overview of MEASURE DHS research on HIV Prevalence, Indicators, and Services
HIV/AIDS Knowledge, Attitudes, and Behavior - Knowledge of HIV prevention, misconceptions, stigma, higher-risk sexual behavior
HIV Prevalence - Prevalence of HIV by demographic and behavioral characteristics
The 2011 Uganda AIDS Indicator Survey (AIS) is a nationally representative, population-based, HIV serological survey. The survey was designed to obtain national and sub-national estimates of the prevalence of HIV and syphilis infection as well as information about other indicators of programme coverage, such as knowledge, attitudes, and sexual behaviour related to HIV/AIDS. Data collection took place from 8 February to the first few days of September 2011.
The UAIS was implemented by the Ministry of Health. ICF International provided financial and technical assistance for the survey through a contract with USAID/Uganda. Financial and technical assistance was also provided by the U.S. Centers for Disease Control and Prevention (CDC). Financial support was provided by the Government of Uganda, the U.S. Agency for International Development (USAID), the President’s Emergency Fund for AIDS Relief (PEPFAR), the World Health Organisation (WHO), the UK Department for International Development (DFID), and the Danish International Development Agency (DANIDA) through the Partnership Fund. The Uganda Bureau of Statistics also partnered in the implementation of the survey. Central testing was conducted at the Uganda Virus Research Institute, with CDC conducting CD4 counts, polymerase chain reaction (PCR) testing for children, and quality control tests.
The survey provided information on knowledge, attitudes, and behaviour regarding HIV/AIDS and indicators of coverage and access to other programmes, for example, HIV testing, access to antiretroviral therapy, services for treating sexually transmitted infections, and coverage of interventions to prevent motherto-child transmission of HIV. The survey also collected information on the prevalence of HIV and syphilis and their social and demographic variations in the country. The overall goal of the survey was to provide programme managers and policymakers involved in HIV/AIDS programmes with strategic information to effectively plan, implement, and evaluate HIV/AIDS interventions.
The information obtained from the survey will help programme implementers to monitor and evaluate existing programmes and design new strategies for combating the HIV/AIDS epidemic in Uganda. The survey data will in addition be used to make population projections and to calculate indicators developed by the UN General Assembly Special Session (UNGASS), USAID, PEPFAR, the UNAIDS Programme, WHO, the Uganda Health Sector Strategic and Investment Plan, and the Uganda AIDS Commission.
The specific objectives of the 2011 UAIS were to provide information on:
• Prevalence and distribution of HIV and syphilis
• Indicators of knowledge, attitudes, and behaviour related to HIV/AIDS and other sexually transmitted infections
• HIV/AIDS programme coverage indicators
• Levels of CD4 T-lymphocyte counts among HIV-positive adults to quantify HIV treatment needs and to calibrate model-based estimates
• HIV prevalence that can be used to calibrate and improve the sentinel surveillance system
• Risk factors for HIV and syphilis infections in Uganda.
Sample survey data [ssd]
- Household
- Children age 0-4
- Women age 15-59
- Men age 15-59
Scope
Topics covered in the study:
• Alcohol Consumption
• Birth Registration
• CAPI Surveys
• GPS/Georeferenced
• HIV Behavior
• HIV Knowledge
• HIV Testing
• Male circumcision
• Men's Survey
• Syphilis Testing
• Women's Status
The survey questionnaires covered the following topics:
Household Questionnaire
• Identification
• Household schedule
• Household characteristics
• List of persons who have died
• Support at the community level
Womena and Men Questionnaire
• Identification
• Background characteristics (including education, media exposure, occupation, and religion)
• Reproduction
• Antenatal care and breastfeeding for recent births (women only)
• Marriage and sexual activity (including sexual violence)
• Knowledge of and attitudes towards HIV/AIDS
• Prior testing for HIV, results of prior testing, and whether taking medication
• Recent injections received
• Prevalence and attitudes towards male circumcision
• Knowledge and prevalence of other sexually transmitted infections (STIs).
| Topic | Vocabulary |
|---|---|
| HIV/AIDS | World Bank |
Coverage
National coverage
The de facto population includes all residents and nonresidents who stayed in the household the night before the interview.
Producers and sponsors
| Name | Affiliation |
|---|---|
| Ministry of Health | Government of Uganda |
| Name | Affiliation | Role |
|---|---|---|
| Uganda Bureau of Statistics | Government of Uganda | Partnered in the implementation of the survey |
| ICF International | MEASURE DHS | Technical assistance |
| U.S. Centers for Disease Control and Prevention | United States Government | Technical assistance |
| Name | Role |
|---|---|
| Government of Uganda | Financial support |
| U.S. Centers for Disease Control and Prevention | Financial assistance |
| U.S. Agency for International Development | Financial assistance |
| President’s Emergency Fund for AIDS Relief | Financial assistance |
| World Health Organisation | Financial assistance |
| UK Department for International Development | Financial assistance |
| Danish International Development Agency | Financial assistance |
| Name | Role |
|---|---|
| Uganda Virus Research Institute | Conducting tests |
Sampling
The sample for the 2011 UAIS covered the population residing in households. A representative probability sample of 11,750 households was selected for the survey. The sample was constructed to allow for separate estimates for HIV/AIDS indicators for each of 10 geographic regions. The regions were created for the survey and do not represent administrative units of the country. Other than Kampala, each region comprised between 8 and 15 contiguous administrative districts of Uganda that share similar languages and cultural characteristics. Because of its unique character as an entirely urban district and capital city of Uganda,
Kampala comprised a separate region. The 10 regions were comprised of the following districts1:
• Central 1: Bukomansimbi, Gomba, Lwengo, Lyantonde, Kalangala, Kalungu, Masaka, Mpigi, Rakai, Ssembabule, and Wakiso.
• Central 2: Buikwe, Buvuma, Kayunga, Kiboga, Kyankwanzi, Luwero, Mityana, Mubende, Mukono, Nakaseke, and Nakasongola.
• Kampala: Kampala district.
• East-Central: Bugiri, Buyende, Iganga, Jinja, Kaliro, Kamuli, Luuka, Mayuge, and Namutumba
• Mid Eastern: Budaka, Bududa, Bukwa, Bulambuli, Busia, Butaleja, Kapchorwa, Kibuku, Kween, Manafwa, Mbale, Pallisa, Sironko, and Tororo.
• North East: Abim, Amudat, Amuria, Bukedea, Kaabong, Kaberamaido, Katakwi, Kotido, Kumi, Moroto, Nakapiripirit, Napak, Nora, Serere, and Soroti.
• West Nile: Arua, Adjumani, Koboko, Moyo, Nebbi, Maracha, Yumbe, and Zombo.
• Mid Northern: Agago, Alebtong, Amolatar, Amuru, Apac, Dokolo, Gulu, Kitgum, Kole, Lamwo, Lira, Otuke, Oyam, and Pader.
• South Western: Buhweju, Bushenyi, Ibanda, Isingiro, Kabale, Kanungu, Kiruhura, Kisoro, Mbarara, Mitooma, Ntungamo, Rubirizi, Rukungiri, and Sheema.
• Mid Western: Buliisa, Bundibugyo, Hoima, Kabarole, Kamwenge, Kasese, Kibaale, Kiryandongo, Kyegegwa, Kyenjojo and Masindi.
The sample was allocated equally across all 10 regions, so as to allow a sufficient size to produce reliable estimates in each region. Since the sample was not allocated in proportion to the size of each region, the UAIS sample is not self-weighting at the national level. Consequently, weighting factors have been applied to the data to produce nationally representative estimates.
The survey utilised a two-stage sample design. The first stage involved selecting sample points or clusters from a list of enumeration areas (EAs) covered in the 2002 Population Census. A total of 470 clusters was selected (47 in each region), comprised of 79 urban and 391 rural points. The second stage of selection involved the systematic sampling of 25 households per cluster from a list of households in each cluster that was produced by the Uganda Bureau of Statistics prior to the UAIS data collection.
All women and men age 15-59 years who were either permanent residents of the households in the sample or visitors present in the household on the night before the survey were eligible for interviews. All women and men who were interviewed were asked to voluntarily give a blood sample for testing. In addition, blood samples were drawn from children under age 5 after obtaining consent from their parents or caretaker.
(Refer Appendix A of the final survey report for detail sample design and implementation)
A total of 11,750 households were selected in the sample, of which 11,434 were found to be occupied at the time of the fieldwork. The shortfall is largely due to structures that were vacant or destroyed. Among the occupied households, 11,340 were interviewed, yielding a household response rate of 99 percent.
In the households interviewed in the survey, a total of 12,374 eligible women age 15-59 were identified, of whom 12,153 were interviewed, yielding a response rate of 98 percent. With regard to the male survey results, 9,983 eligible men age 15-59 were identified, of whom 9,588 were interviewed, yielding a response rate of 96 percent. Response rates were only slightly lower in urban than in rural areas.
Due to the non-proportional allocation of the sample to the various regions and the possible differences in response rates, sampling weights are required for any analysis using UAIS data to ensure the actual representative of the survey results at the national level and at the sub-national level. Since the UAIS sample is a two-stage stratified cluster sample, sampling weights were calculated based on sampling probabilities separately for each sampling stage and for each cluster.
(Refer Appendix A.5 of the final survey report for details of sample weight calculcation)
Survey instrument
Two questionnaires were used to collect data: the Household Questionnaire and the Individual Questionnaire for women and men age 15-59. The contents of the questionnaires were based on the model AIDS Indicator Survey questionnaires developed by the MEASURE DHS programme and on the questionnaires used in the 2004-05 Uganda HIV/AIDS Sero-Behavioural Survey (UHSBS). The two questionnaires were loaded onto personal digital assistants (PDAs) that were used to conduct the interviews.
In consultation with stakeholders from government agencies and local and international organisations, the questionnaires were revised to reflect HIV/AIDS issues relevant to Uganda. The questionnaires were then translated from English into six local languages—Ateso-Karamajong, Luganda, Lugbara, Luo, Runyankole-Rukiga, and Runyoro-Rutoro. They were further refined after the pretest and training of the field staff.
The Household Questionnaire on PDAs 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, relationship to the head of the household, and orphanhood among children under age 18. An important purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire was also used to collect information on characteristics of the household’s dwelling unit, such as the source of water, type of toilet facilities, materials used to construct the house, ownership of various durable goods, and ownership of land and farm animals. Information was also collected on adult chronic illness and deaths in the household during the 12 months before the survey.
The Individual Questionnaire on PDAs was used to collect information from all women and men age 15-59.
In addition to the questionnaires, two paper forms were used to record results of home-based testing: a Field Test Result Form for Adults and a Field Test Result Form for Children. These forms were used by the teams’ laboratory technicians to obtain informed consent and record the results of the home-based testing and any treatment provided to respondents.
All aspects of the UAIS data collection were pretested in October 2010. For this, four teams were formed, each with one supervisor, two female interviewers, two male interviewers, three laboratory technicians, and two HIV/AIDS counsellors. Team members were trained for two weeks and then proceeded to conduct the pretest in four locations: Hoima in the west, Lira in the north, Soroti in the east, and Wakiso, just outside of Kampala city. The four clusters were selected by the Uganda Bureau of Statistics to exclude clusters that had been selected for the main survey and to represent a range of languages. Interviews were conducted using the PDAs. The lessons learned from the pretest were used to finalise the survey instruments and logistical arrangements for the survey.
Data collection
| Start | End |
|---|---|
| 2011-02 | 2011-09 |
| Name | Affiliation |
|---|---|
| Ministry of Health | Government of Uganda |
TRAINING AND DATA COLLECTION
The survey was coordinated by a survey director and two deputy directors based at the Ministry of Health headquarters. In the central office, a field coordinator and laboratory coordinator linked the central level functions with the survey implementation in the field. In addition, four regional supervisory teams—each comprised of a specialist in interviewing and fieldwork management, laboratory techniques, and HIV counselling—coordinated data collection activities in Eastern, Western, Northern, and Central sectors of the country. Two PDA programmers supported data management for the survey. They were based in the central office but visited teams in the field to check on the pace and quality of the data collection and resolve technical problems.
The training of field staff for the UAIS was held at the Hotel Africana in Kampala from 17-29 January 2011. During the two weeks prior to the start of training, the UAIS management team, along with other senior trainers, interviewed short-listed candidates for the various positions. A total of some 250 trainees were recruited, consisting of 120 supervisor/interviewer candidates, 80 laboratory technicians, and 50 HIV counsellors. Trainers were senior staff from the UAIS project and staff from the Uganda Bureau of Statistics, UVRI, the Ministry of Health, and ICF Macro. After two days of plenary sessions that provided an overview of the survey design and explanations of the administrative issues, participants were divided into six groups—three for supervisors/interviewers, two for laboratory technicians, and one for counsellors. Many of the trainers and trainees had participated in the 2004-05 Uganda HIV/AIDS Sero-Behavioural Survey (UHSBS), the 2006 Uganda Demographic and Health Survey (UDHS), or the 2009 Uganda Malaria Indicator Survey (UMIS).
For supervisors and interviewers, training consisted of an overview of the survey and its objectives, techniques of interviewing, field procedures, a detailed description of the Household Questionnaire and the Individual Questionnaire, use of the personal digital assistants (PDAs), instructions for transferring information between team members, mock interviews, and periodic tests. Trainees were divided into language groups to review the questionnaires in their local languages. Two days were set aside for practice interviewing in sites close to Kampala; the interviewing was interspersed with discussions of the experience. A few days before the end of training, project staff appointed regional and team supervisors. They were provided a halfday of special training on how to supervise and how to receive, store, and transfer data on the tablet computers that were provided to the team supervisors.
The lab technicians were trained on blood draw procedures (for both venous and capillary blood), specimen processing in the field lab, storage and transport of specimens, rapid HIV and syphilis testing, lab safety procedures, labelling of samples, and consent administration. In addition, the nurse-interviewers were trained on how to administer syphilis treatment.
HIV counsellors were trained on how to administer pre- and post-test counselling, how to counsel respondents on their test results, and how to maintain privacy as well as encourage test result disclosure to
partners.
Twenty teams carried out data collection for the survey. Each team consisted of one supervisor, four interviewers (two female and two male), three laboratory technicians, and two HIV counsellors. On each team, at least two of the interviewers were health personnel capable of treatment and referral. The laboratory technicians were responsible for drawing blood samples, carrying out HIV and syphilis testing, and preparing samples for shipment to UVRI. The HIV counsellors were responsible for performing pre-test and post-test
counselling and referral of clients who required further care. Because of their size and the amount of equipment and supplies, each team had two vehicles.
Data collection took place over a seven-month period, from 7 February to very early September 2011.
Data processing
Because all interviews were conducted using PDAs, data entry was minimal. Paper forms were used to record the results of the blood draw and the home-based HIV and syphilis testing. These results were entered in the field by the team supervisor. Interviewers transferred completed household and adult questionnaires to the team supervisor using Bluetooth technology. For the first time in a national survey, a ‘real-time’ web-based data management system developed by the DHS programme at ICF was implemented. The system transferred encrypted data from the field to the central office via the Internet. It also delivered system updates to the field from the central office. The system was completely automated and required little action on the part of team supervisors. Supervisors were equipped with GPRS modems, which were used to access the web. The system required supervisors to connect the modem to their tablets to transmit data to the Central Office.
The CDC office in Entebbe worked with the UVRI to program a system to track blood samples as they were received at the laboratory and were tested. Bar code labels on the samples were scanned upon receipt, and sequential lab numbers were assigned to ease tracking of samples. Final checking of the complete survey dataset and production of tables were done by ICF.
Data appraisal
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 2011 Uganda AIDS Indicator Survey (UAIS) to minimise this type of error, non-sampling 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 2011 UAIS 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 between all possible samples. Although the degree of variability is not known exactly, 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, 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 2011 UAIS sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. Sampling errors were computed in ISSA, using programmes developed by ICF Macro. These programmes use the Taylor linearisation method of variance estimation for survey estimates that are means, proportions or ratios.
(Refer Appendix B of the final survey report for detail sampling error calculation)
Data Quality Table
- Household age distribution
(Refer Appendix C of the final survey report for details of the data quality table)
Data Access
| Name | URL | |
|---|---|---|
| MEASURE DHS | http://www.measuredhs.com | archive@measuredhs.com |
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 | URL | |
|---|---|---|---|
| Ministry of Health | Government of Uganda | http://health.go.ug/mohweb/ | |
| 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 |
| World Bank Microdata Library | microdata@worldbank.org |