South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey (SABSSM) 2012: Visiting point - All provinces


Description: This data file contains household information about the people who usually lived in the household and slept there the previous night as per the time of the interview. Demographic variables were age, sex, marital status, race, language spoken, education status, main source of drinking water, energy for cooking, type of toilet facility. The data set contains 545 variables and 14919 cases.

Number of completed household interviews: 10908 Number of refusals from household head or other resident: 1320 Number of unoccupied households and invalid visiting points: 1155 Number of partly completed questionnaires, no one at home or eligible to complete questionnaire, incapacitated and other: 1371 Abstract: The 2012 population-based survey of HIV prevalence was the fourth among the HIV prevalence surveys that have investigated HIV prevalence and behaviour. The survey incorporated new methodologies, technologies and novel laboratory methodologies that enabled direct estimates of HIV incidence and ART exposure.

The main objectives of the survey were to determine the prevalence and incidence of HIV infection in South Africa in relation to social and behavioural determinants and to determine the proportion of males in South Africa who are circumcised. The secondary objectives were to determine the proportion of people living with HIV (PLHIV) who are on antiretroviral therapy (ART) in South Africa, to determine the extent to which mother-child pairs include HIV-negative mothers and HIV-positive infants and to describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002 to 2012.

A multi-stage stratified cluster sampling design was implemented with everyone in the sampled households invited to participate. People of all ages living in South African households and hostels were eligible to participate.

South African population.

This project used the updated 2007-2011 HSRC's master sample. Aerial photographs drawn from Google Earth were utilised to ensure that the most up-to-date information was available sample. the master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the Master Sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs) and the Secondary Sampling Units (SSUs) were the visiting points (VPs) or households (HHs). The Ultimate Sampling Units (USUs) were the individuals eligible to be selected for the survey. Any member of the household "who slept here last night", including visitors was an eligible household member for the interview. This sampling approach was used in the 2001 census and is a standard demographic household survey procedure.

The sample was designed with two main explicit strata, the provinces and the geography types (geotype) of the EA. In the 2001 census, the four geotypes were urban formal, urban informal, rural formal (including commercial farms) and tribal areas (rural informal) (i.e. the deep rural areas). In the formal urban areas, race was used as a third stratification variable. What this means is that the Master Sample was designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. A maximum of four visits were made to each VP to optimise response. Fieldworkers enumerated household members, using a random number generator to select the respondent and then preceded with the interview.

All people in the households, resident at the visiting point were invited to participate in the study. These individuals constituted the USUs of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 15 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 15 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 15 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. The VP questionnaire was administered by the fieldworker, and in follow-up, participant selection was made by the supervisor. Participants aged 12 years and older who consented were all interviewed and also asked to provide dried blood spots (DBS) specimens for HIV testing. In case of 0-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children.

The sample size estimate for the 2012 survey was guided by the (1) requirement for measuring change over time in order to detect a change in HIV prevalence of 5 percentage points in each of the main reporting domains, namely gender, age-group, race, locality type, and province (5% level of significance, 80% power, two-sided test), and (2) the requirement of an acceptable precision of estimates per reporting domain; that is, to be able to estimate HIV prevalence in each of the main reporting domains with a precision level of less than ± 4%, which is equivalent to the expected width of the 95% confidence interval (z-score at the 95% level for two-sided test). A design effect of 2 was assumed.

Overall, a total of 38 431 interviewed participants composed of 29.7% children (0-14 years), 19.3% youths (15-24 years), 35.6% adults (25-49 years), and 15.4% adults (50+ years ) were interviewed. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group.

The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). More females (70.3%) than males (64.2%) were tested for HIV. The 15-24 year's age group was the most compliant (71.6%), and less than 2 years the least (51.6%). The highest testing response rate was found in rural formal settlements (80.8%) and the least in urban formal areas (59.7%).

Clinical measurements

Face-to-face interview

Focus group


Metadata Access
Creator Rehle, Thomas Michael; Simbayi, Leickness Chisamu; Shisana, Olive; Human Sciences Research Council
Publisher HSRC - Human Science Research Council SA
Contributor Human Sciences Research Council; Centers for Disease Control and Prevention
Publication Year 2017
Rights Other; By accessing the data, you give assurance that The data and documentation will not be duplicated, redistributed or sold without prior approval from the rights holder. The data will be used for scientific research or educational purposes only. The data will only be used for the specified purpose. If it is used for another purpose the additional purpose will be registered. Redundant data files will be destroyed. The confidentiality of individuals/organisations in the data will be preserved at all times. No attempt will be made to obtain or derive information from the data to identify individuals/organisations. The HSRC will be acknowledged in all published and unpublished works based on the data according to the provided citation. The HSRC will be informed of any books, articles, conference papers, theses, dissertations, reports or other publications resulting from work based in whole or in part on the data and documentation. For archiving and bibliographic purposes an electronic copy of all reports and publications based on the requested data will be sent to the HSRC. To offer for deposit into the HSRC Data Collection any new data sets which have been derived from or which have been created by the combination of the data supplied with other data. The data team bears no responsibility for use of the data or for interpretations or inferences based upon such uses. Failure to comply with the End User License may result in sanctions being imposed.; Download
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Contact HSRC - Human Science Research Council SA
Resource Type Dataset
Discipline Social Sciences