PLoS ONE plos plosone PLOS ONE 1932-6203 Public Library of Science San Francisco, CA USA 10.1371/journal.pone.0230105 PONE-D-19-21316 Research Article Research and analysis methodsResearch designSurvey researchSurveys Social sciencesSociologyEducationEducational attainment Biology and life sciencesMicrobiologyMedical microbiologyMicrobial pathogensViral pathogensImmunodeficiency virusesHIV Medicine and health sciencesPathology and laboratory medicinePathogensMicrobial pathogensViral pathogensImmunodeficiency virusesHIV Biology and life sciencesOrganismsVirusesViral pathogensImmunodeficiency virusesHIV Biology and life sciencesOrganismsVirusesImmunodeficiency virusesHIV Biology and life sciencesOrganismsVirusesRNA virusesRetrovirusesLentivirusHIV Biology and life sciencesMicrobiologyMedical microbiologyMicrobial pathogensViral pathogensRetrovirusesLentivirusHIV Medicine and health sciencesPathology and laboratory medicinePathogensMicrobial pathogensViral pathogensRetrovirusesLentivirusHIV Biology and life sciencesOrganismsVirusesViral pathogensRetrovirusesLentivirusHIV Social sciencesEconomicsLabor economicsEmployment People and placesGeographical locationsAfricaSouth Africa Medicine and health sciencesEpidemiologyMedical risk factors Earth sciencesGeographyGeographic areasUrban areas Medicine and health sciencesHealth careSocioeconomic aspects of health Medicine and health sciencesPublic and occupational healthSocioeconomic aspects of health HIV-Prevalence in South Africa by settlement type: A repeat population-based cross-sectional analysis of men and women HIV-Prevalence by settlement type in South Africa http://orcid.org/0000-0003-2812-5377 Gibbs Andrew Conceptualization Project administration Writing – original draft 1 2 * Reddy Tarylee Data curation Formal analysis Writing – review & editing 3 Dunkle Kristin Conceptualization Supervision Writing – review & editing 1 Jewkes Rachel Conceptualization Supervision Writing – review & editing 1 4 5 Gender and Health Research Unit, South African Medical Research Council, Pretoria, South Africa Centre for Rural Health, School of Nursing and Public Health, University of KwaZulu-Natal, Durban, South Africa Biostatistics Unit, South African Medical Research Council, Durban, South Africa Office of the Executive Scientist, South African Medical Research Council, Pretoria, South Africa School of Public Health, University of Witwatersrand, Johannesburg, South Africa Blanch Angel Editor University of Lleida, SPAIN

The authors have declared that no competing interests exist.

 * E-mail: Andrew.gibbs@mrc.ac.za 17 3 2020 2020 15 3 e0230105 29 7 2019 21 2 2020 2020 Gibbs et al This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

To assess i) whether there is an independent association between HIV-prevalence and settlement types (urban formal, urban informal, rural formal, rural informal), and, ii) whether this changes over time, in South Africa. We draw on four (2002; 2005; 2008; 2012) cross-sectional South African household surveys. Data is analysed by sex (male/female), and for women by age categories (15–49; and 15–24; 25–49) at all-time points, for men in 2012 data is analysed by age categories (15–24; 25–49). By settlement type and sex/age combinations, we descriptively assess the association between socio-demographic and HIV-risk factors; HIV-prevalence; and trends in HIV-prevalence by time. Relative risk ratios assess unadjusted and adjusted risk for HIV-prevalence by settlement type. All estimates are weighted, and account for survey design. In all survey years, and combinations of sex/age categorisations, HIV-prevalence is highest in urban informal settlements. For men (15–49) an increasing HIV-prevalence over time in rural informal settlements was seen (p = 0.001). For women (15–49) HIV-prevalence increases over time for urban informal, rural informal, rural formal, and women (15–24) decreases in urban formal and urban informal, and women (25–49) increases urban informal and rural informal settlements. In analyses adjusting for potential socio-demographic and risk factors, compared to urban formal settlements, urban informal settlements had consistently higher relative risk of HIV for women, in all age categorisations, for instance in 2012 this was RR1.89 (1.50, 2.40) for all women (15–49), for 15–24 (RR1.79, 1.17–2.73), and women 25–49 (RR1.91, 1.47–2.48). For men, in the overall age categorization, urban informal settlements had a higher relative risk for HIV in all years. In 2012, when this was disaggregated by age, for men 15–24 rural informal (IRR2.69, 1.28–5.67), and rural formal (RR3.59, 1.49–8.64), and for men 25–49 it was urban informal settlements with the highest (RR1.68, 1.11–2.54). In 2012, rural informal settlements also had higher adjusted relative risk for HIV-prevalence for men (15–49) and women (15–49; 15–24; 25–49). In South Africa, HIV-prevalence is patterned geographically, with urban informal settlements having a particularly high burden. Geographical targeting of responses is critical for the HIV-response.

 This study was funded by the South African Medical Research Council (SAMRC). Data Availability All relevant data are available via unrestricted access off the HSRC website: 2002 dataset: http://dx.doi.org/doi:10.14749/1400830395 2005 dataset: http://dx.doi.org/doi:10.14749/1400830455 2008 dataset: http://dx.doi.org/doi:10.14749/1441969417 2012 dataset: http://dx.doi.org/doi:10.14749/1485430466 Introduction

HIV-incidence and HIV-prevalence is spatially distributed globally, nationally, and sub-nationally. The spatial patterning of HIV across settings reflects inequalities in access to resources, healthcare services, and power differentials, particularly along lines of poverty, sexuality, gender and race [1–3]. Across Africa (excluding South Africa) a limited body of work has looked at this by settlement type. In Kenya, HIV-prevalence was assessed comparing urban slums, with urban-non slum settlements, with the HIV-prevalence 12% and 5% respectively [4]. While in Namibia’s capital city, Windhoek, hotspot mapping identified particularly high HIV-incidence in informal settlement areas [5]. Understanding the spatial patterning of HIV-prevalence globally, and nationally, is critical to ensure limited resources are targeted most effectively, particularly as donor funding is declining [6].

In South Africa, a number of studies have explored the spatial patterning of HIV. Studies have, for instance, sought to highlight HIV ‘hot-spots’. For example, Tanser et al [7] found wide variation in HIV-prevalence (from 6–39%) in a rural demographic health surveillance area in KwaZulu-Natal, with clustering of HIV in homesteads [8], nearer national roads [7], and by transport corridors [9]. Amongst women screened for enrollment in clinical trials, also in KwaZulu-Natal, but in more urban settings, HIV-prevalence clustered in ‘hot spots’ with HIV-prevalence in those ranging from 56.0% to 39.0%; with distinguishing factors including being in peri-urban communities (typically including informal settlements), and reporting more lifetime sexual partners [10]. Finally, one nationally representative youth (15–24) survey, found that HIV-prevalence was pattern by rural/urban status, with higher HIV-prevalence in urban settings, and was highest for young women in urban informal settlements (but not men) [11].

In addition, in South Africa, there have been five nationally representative population based studies of HIV-prevalence and incidence, in 2002, 2005, 2008, 2012, and 2017 [12–16]. In each of these data on settlement type is collected and analysed in the main report. The 2017 data is not yet publicly available, and in the report that has been produced, settlement types have been coded differently to previous studies, combing urban informal and urban formal to create one category of ‘urban’. All four previous (2002; 2005; 2008; 2012) nationally representative studies analysed data by urban formal, urban informal, rural formal and rural informal, and these analyses have described HIV-prevalence being substantially higher in urban informal settlements, compared to other settlement types [13–15].

However these nationally representative data have not be disaggregated settlement type by age and sex, which are important factors in the patterning of the HIV-epidemic, with younger (15–24) women at greater risk of acquiring HIV than younger men, and women of all ages more likely to be living with HIV, compared to men [17]. Additionally, the prior descriptive work provided only prevalence estimates, without adjustment for the distribution of potential socio-demographic differences that might account these spatial differences. Nor have changes in HIV-prevalence and settlement-type been explored by time.

Currently, South Africa spends US$1.9 billion annually on HIV, with a quarter (U$0.5 billion) coming from international donors [18]. And while there are a number of large-scale HIV-prevention, and treatment programmes, including universal test-and-treat, and the Determined, Resilient, Empowered, AIDS-Free, Mentored, and Safe (DREAMS) programme for young women (15–24) [19], donors are reducing their funding [18]. Understanding the HIV-epidemic in more detail, by sex and age, will help focus targeting of limited resources.

Drawing on representative population-based data in South Africa of four surveys (2002; 2005; 2008 and 2012), this paper has three objectives. First, to describe HIV-risk acquisition factors by settlement type and age and sex. Second, to describe HIV-prevalence by settlement-type and assess trends over time by settlement-type. Third, to assess whether settlement-type independently predicts HIV-prevalence after accounting for risk factors.

 Materials and methods Data collection

We used four nationally representative population-based cross-sectional household surveys from 2002, 2005, 2008 and 2012 in South Africa. The National Prevalence Surveys employed a stratified multistage cluster sampling approach. In the first stage 1000 census enumeration areas (EAs) were selected proportional to size and stratified by province, geotype(settlement type) and race; after which a fixed number of households were selected per EA in the second stage. Sampling weights were calculated to correct for unequal probabilities of selection and non-response at the EA, household and individual level. The individual weights for each survey were benchmarked to relevant mid-year population estimates by age, race, sex, and province. This ensured that the sample for each survey was representative of the population distribution in South Africa for sex, age, race, settlement type, and province. Response rates for HIV-testing varied, with lower response rates consistently by men, compared to women (e.g. in 2012, for those older than 15, the testing response rate for females was 57.7%, compared to 42.3% in males) [14]. Detailed information about survey design, sampling methods, refusal rates, and survey administration is available in individual reports [12–15]. The comparability of design makes these four surveys nationally representative data sets, enabling assessment of longitudinal change across them.

All studies received ethical approval from the Human and Social Research Council’s (HSRC) ethics committee before starting, and participants provided informed consent for questionnaires, and separately for HIV-testing. Information on this can be found in the original reports.

 Outcome

The primary outcome for analysis is a binary HIV-status (positive or negative). Testing strategy varied by data collection year. In 2002 and 2005 oral saliva samples were obtained and tested using ELISA kits, with confirmatory testing on positive tests only in 2005 [12, 15]. The sensitivity and specificity of the ELISA test are 99% and 99% respectively [12, 15]. In 2008 and 2012, dried blood spots were collected and tested, and confirmatory tests conducted on all positive samples (and a 10% sub-set of negative samples) using a combination of three HIV-1 enzyme immunoassays, with 99% specificity and sensitivity [13, 14].

Classification of households into settlement type was done through coding of Enumeration Areas (EA) using census data and classifications provided by Statistics South Africa. Four options were available: urban formal, urban informal, rural formal (including commercial farms), and rural informal, which included tribal authority areas [12–15]. According to Statistics South Africa, urban areas are continuously built-up areas, and either urban formal–defined as land proclaimed as residential where settlements are structured and organized. In addition, services are provided through local government and development is controlled. Or, urban informal, which are unplanned settlements on land not defined as residential, and comprising of informal dwellings. Rural areas are any area not deemed as urban, and comprises of rural informal, which areas are controlled by tribal authorities and informal settlements outside of urban areas. In earlier surveys this was just termed tribal authority areas. And rural formal settlements, which are formal settlements outside of urban areas, which do not fall under tribal authority areas, including commercial farms [20].

 Covariates

In addition to age and sex, we identified comparable measures across all four surveys as potential co-variates, based on known risk factors for HIV-acquisition. All studies assessed current work status [employed (formal or informal), unemployed, or student]. Education level was assessed as either: none through to secondary not completed, else completed secondary or higher. For people reporting ever having had sex, age of sexual debut, and number of past year sexual partners were assessed.

 Analysis

Analyses were done separately for men and women. For men, because of high refusal rates of HIV-testing and small sample sizes in the 2002, 2005 and 2008 surveys (for instance 31% of men refused to be tested for HIV in 2008) only one age categorization (15–49) was possible. In 2012, the larger sample size enabled age stratification by adolescents (15–24), and adult men (25–49), as well as overall (15–49). For women, we analysed all respondents (aged 15–49), and then stratified by adolescents (15–24), and adult women (25–49).

We first calculated the distribution of weighted proportions of socio-demographic and HIV-acquisition risk factors by settlement type, sex, age, and survey wave, presenting percentages and 95 percent confidence intervals (95%CI). We used chi-square tests to assess variation. We then calculated weighted HIV-prevalence by settlement type for each survey by sex, and age groups. Differences are assessed through chi-squared tests. We also assessed trends in HIV-prevalence by settlement type using chi-square tests.

To assess the potential impact of settlement type on prevalent HIV infection, we used individual level poisson regression reporting relative risk with robust standard errors, taking into account sampling weights, stratification by province, and clustering within EA. We then adjusted for education, employment status, age at first sex, number of partners in past year. We report both the unadjusted and adjusted relative risk ratios. All analyses were performed in STATA15, using the survey commands, and weighted estimations.

 Results Men aged 15–49

In total, 2430, 5047, 4291, and 8510 men participated in 2002, 2005, 2008 and 2012 surveys, respectively. Table 1 presents socio-demographic and HIV-acquisition risk factors for all four surveys for men aged 15–49. In 2002, a greater proportion of young men (15–24) were in rural informal settlements (58.0%), compared to other settlement types (37.4% urban formal; 37.2% urban informal; 27.6% urban formal; p<0.0001). In urban informal (43.2%) and rural informal (46.1%) settlements a significantly greater proportion reported being unemployed, compared to urban formal (24.0%) and rural formal (17.3%). The majority of men in urban informal, rural informal and rural formal had not completed secondary school (83.9%, 86.1%, 85.0% respectively), and this was significantly higher compared to urban formal (42.4%). A significantly greater proportion of men in urban informal settlements (58.1%) and rural formal (54.4%) reported sexual debut ≤18 years, compared to urban formal (47.4%), and rural informal (44.8%). In all other survey years (2005; 2008; 2012), a similar patterning of socio-demographic and sexual behaviours was seen, with little variation between years.

10.1371/journal.pone.0230105.t001 Men 15–49 socio-demographic and risk factors by settlement types for all survey years.
Table 1a: 2002 Survey: Men (15–49), socio-demographic and risk factors, by settlement type
  Urban Formal Urban Informal Rural Informal Rural Formal
  N n Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI p-value
Age 2430                
15–24   1145 37.4 [33.4,41.6] 37.2 [29.2,46.1] 58.0 [51.2,64.5] 27.6 [18.8,38.5] <0.0001
25–49   1285 62.6 [58.4,66.6] 62.8 [53.9,70.8] 42.0 [35.5,48.8] 72.4 [61.5,81.2]  
Employment status 2314                
Employed   1064 52.7 [47.6,57.7] 40.1 [31.6,49.2] 18.1 [13.9,23.4] 79.1 [66.7,87.7] <0.0001
Unemployed   666 24.0 [20.0,28.4] 43.2 [34.5,52.5] 46.1 [39.9,52.3] 17.3 [9.9,28.6]
Student   584 23.4 [19.9,27.2] 16.6 [11.1,24.1] 35.8 [29.9,42.2] 3.6 [1.4,8.8]  
Education level 2424                
Secondary not complete or less   1692 57.6 [51.8,63.2] 83.9 [76.9,89.1] 86.1 [81.1,89.9] 85.0 [70.2,93.2] <0.0001
Secondary complete/higher   732 42.4 [36.8,48.2] 16.1 [10.9,23.1] 13.9 [10.1,18.9] 15.0 [6.8,29.8]  
Past year sex partners 2415                
Never had sex, none, one   2164 91.3 [88.7,93.4] 76.9 [68.0,83.9] 86.2 [80.0,90.7] 85.6 [54.4,96.7] 0.179
Two or more   251 8.7 [6.6,11.3] 23.1 [16.1,32.0] 13.8 [9.3,20.1] 14.4 [3.3,45.5]  
Age sexual debut 2396                
< = 18   1129 47.4 [42.4,52.4] 58.1 [48.3,67.3] 44.8 [38.1,51.8] 54.4 [39.7,68.5] 0.0007
> = 19   734 35.9 [31.9,40.2] 27.0 [18.6,37.4] 25.8 [20.3,32.2] 34.6 [22.7,48.8]
Never had sex   533 16.7 [13.9,19.9] 14.9 [10.0,21.6] 29.3 [24.0,35.3] 11.0 [6.0,19.3]  
Table 1b: 2005 Survey: Men (15–49), socio-demographic and risk factors, by settlement type
Age 5047          
15–24   2537 38.8 [35.8,42.0] 36.8 [30.5,43.6] 58.7 [54.3,62.9] 32.2 [23.8,41.8] <0.0001
25–49   2510 61.2 [58.0,64.2] 63.2 [56.4,69.5] 41.3 [37.1,45.7] 67.8 [58.2,76.2]  
Employment status 4874          
Employed   2143 51.7 [47.2,56.1] 37.6 [32.2,43.3] 18.6 [15.1,22.6] 75 [66.2,82.2] <0.0001
Unemployed   1324 26.3 [22.9,30.1] 40.7 [34.1,47.6] 38.8 [34.4,43.5] 13 [8.7,19.1]  
Student   1407 22 [19.4,25.0] 21.7 [16.7,27.8] 42.6 [38.3,47.0] 11.9 [7.3,18.9]  
Education level 4962          
Secondary not complete or less   3168 53.1 [48.3,57.9] 80.6 [75.1,85.2] 78.4 [74.0,82.3] 87.4 [80.6,92.1] <0.0001
Secondary complete/higher   1794 46.9 [42.1,51.7] 19.4 [14.8,24.9] 21.6 [17.8,26.0] 12.6 [7.9,19.4]  
Past year sex partners 4732          
Never had sex, none, one   4248 87.1 [83.9,89.7] 84.6 [79.5,88.6] 88.6 [85.8,90.9] 92.3 [88.4,95.0] <0.0001
Two or more   484 12.9 [10.3,16.1] 15.4 [11.4,20.5] 11.4 [9.1,14.2] 7.7 [5.0,11.7]  
Age sexual debut 4400          
< = 18   2008 50.6 [46.9,54.4] 58.3 [52.3,64.1] 41.6 [36.7,46.6] 59.3 [46.1,71.2] 0.0001
> = 19   1211 29.7 [26.4,33.2] 24.3 [19.9,29.4] 26.7 [22.8,31.0] 26.3 [18.4,36.0]  
Never had sex   1181 19.7 [17.3,22.3] 17.4 [13.1,22.7] 31.7 [27.6,36.2] 14.4 [9.2,22.1]  
Table 1c: 2008 Survey: Men (15–49), socio-demographic and risk factors, by settlement type
Age 4291          
15–24   2115 40.5 [37.5,43.5] 34.1 [29.4,39.0] 56.1 [51.5,60.6] 30.4 [23.1,38.9] <0.0001
25–49   2176 59.5 [56.5,62.5] 65.9 [61.0,70.6] 43.9 [39.4,48.5] 69.6 [61.1,76.9]  
Employment status 3999          
Employed   1893 51.7 [47.8,55.5] 48.8 [42.3,55.4] 23.1 [19.1,27.6] 78 [71.1,83.6] <0.0001
Unemployed   959 24.1 [20.8,27.6] 33.9 [27.8,40.5] 37.2 [33.0,41.5] 11.4 [7.5,17.0]  
Student   1147 24.2 [21.5,27.3] 17.3 [13.2,22.3] 39.7 [35.4,44.3] 10.6 [6.9,15.9]  
Education level 4050          
Secondary not complete or less   2526 50.9 [47.4,54.5] 78.9 [73.5,83.4] 80.3 [76.7,83.6] 73.4 [64.5,80.7] <0.0001
Secondary complete/higher   1524 49.1 [45.5,52.6] 21.1 [16.6,26.5] 19.7 [16.5,23.3] 26.6 [19.3,35.5]  
Past year sex partners 4013          
Never had sex, none, one   2965 74.3 [71.6,76.9] 75.5 [70.2,80.2] 71.1 [67.0,74.9] 68.8 [59.3,77.0] 0.2951
Two or more   1048 25.7 [23.2,28.4] 24.5 [19.8,29.8] 28.9 [25.1,33.0] 31.2 [23.0,40.7]  
Age sexual debut 4018          
< = 18   2077 56.5 [53.6,60.0] 56.6 [50.3,62.7] 51.8 [47.0,56.5] 47.1 [39.6,54.7] <0.0001
> = 19   1076 28.3 [25.1,31.7] 31 [25.7,36.8] 22.4 [18.8,26.5] 39.4 [31.5,48.0]  
Never had sex   865 15.2 [13.3,17.4] 12.4 [9.3,16.2] 25.8 [21.8,30.3] 13.5 [8.2,21.4]  
Table 1d: 2012 Survey: Men (15–49), socio-demographic and risk factors, by settlement type
Age 8510        
15–24   3486 32.8 [30.3,35.3] 26.7 [23.6,30.0] 43.5 [39.9,47.1] 24.8 [19.8,30.6] <0.0001
25–49   5024 67.2 [64.7,69.7] 73.3 [70.0,76.4] 56.5 [52.9,60.1] 75.2 [69.4,80.2]  
Employment status 8091        
Employed   4103 55.8 [52.8,58.9] 50.3 [44.1,56.4] 26.2 [23.1,29.5] 75.6 [67.4,82.3] <0.0001
Unemployed   2149 25.4 [23.0,28.0] 36.3 [31.4,41.5] 45.6 [42.4,49.0] 14.0 [8.8,21.6]
Student   1839 18.7 [16.6,21.1] 13.4 [10.7,16.7] 28.1 [25.2,31.3] 10.4 [7.5,14.2]  
Education level 7544        
Secondary not complete or less   4446 46.5 [43.1,49.9] 70.4 [65.1,75.3] 74.6 [71.0,77.9] 62.2 [39.4,80.7] <0.0001
Secondary complete/higher   3098 53.9 [50.6,57.1] 29.0 [24.2,34.3] 24.8 [21.5,28.4] 36.1 [19.9,56.2]  
Past year sex partners 8145        
Never had sex, none, one   7076 82.4 [79.8,84.7] 83.7 [79.1,87.4] 83.6 [80.8,86.0] 93.3 [90.4,95.4] 0.0024
Two or more   1069 17.6 [15.3,20.2] 16.3 [12.6,20.9] 16.4 [14.0,19.2] 6.7 [4.6,9.6]  
Age sexual debut 7715        
< = 18   3948 53.9 [51.0,56.8] 63.1 [58.4,67.6] 52.1 [48.6,55.6] 53.3 [48.4,58.3] <0.0001
> = 19   2142 30.7 [28.0,33.5] 25.1 [20.7,30.1] 24.2 [21.1,27.6] 34.0 [29.8,38.5]
Never had sex   1625 15.4 [13.6,17.4] 11.8 [8.9,15.4] 23.7 [21.3,26.2] 12.7 [9.2,17.3]

Table 2 reports the 2012 survey for men, disaggregated by age groups. Among men 15–24, the largest proportion reporting being unemployed (34.6%) were in urban informal settlement and this was higher than urban formal (25.3%) and rural informal (27.4%) and significantly higher than rural formal (17.0%, p<0.001). Over a third (37.5%) of 15–24 year olds in urban formal settlements reported completed secondary education, compared to a quarter (24.4%) in urban informal, and rural formal (27.3%) and a fifth (17.3%) in rural informal, and this proportion was significantly larger (p<0.001). Age of sexual debut was significantly younger in urban settlements, with 56.5% in urban informal and 52.7% urban formal reporting this, compared to 45.3% in rural informal (p = 0.03).

10.1371/journal.pone.0230105.t002 2012 Survey for men socio-demographic and risk factors, by settlement type and age disaggregation.
Table 2a: 2012 Survey: Men (15–24), socio-demographic and risk factors, by settlement type
  Urban Formal Urban Informal Rural Informal Rural Formal
N n Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI p-value
Employment status 3323        
Employed   704 21.1 [18.0, 24.5] 17.5 [12.3, 24.4] 8.4 [6.5, 10.7] 41.1 [14.6, 18.5] <0.001
Unemployed   834 25.3 [22.0, 29.0] 34.6 [27.0, 43.0] 27.4 [24.0, 31.1] 17.0 [11.4, 24.5]
Student   1785 53.6 [49.5, 57.7] 47.9 [38.2, 57.8] 64.2 [60.3, 60.0] 42.0 [30.4, 54.5]  
Education level 3149        
Secondary not complete or less   2252 62.5 [58.7, 66.2] 75.6 [67.9, 81.9] 82.7 [78.6, 86.2] 72.7 [58.7, 83.3] <0.001
Secondary complete/higher   897 37.5 [33.8, 41.3] 24.4 [18.1, 32.1] 17.3 [13.8, 21.4] 27.3 [16.7, 41.4]  
Past year sex partners 3360        
Never had sex, none, one   2862 78.7 [74.5, 82.4] 77.7 [69.8, 84.0] 85.4 [82.2, 88.1] 83.0 [63.7, 93.1] 0.08
Two or more   498 21.3 [17.6, 25.5] 22.3 [16.0, 30.2] 14.6 [11.9, 17.8] 17.0 [6.9, 36.3]  
Age sexual debut 3291        
< = 18   1539 52.7 [48.8, 56.5] 56.5 [47.7, 64.8] 45.3 [41.4, 49.2] 51.4 [40.2, 62.5] 0.0323
> = 19   303 9.4 [7.4, 12.0] 7.4 [4.9, 11.1] 9.3 [7.2, 11.9] 11.7 [7.8, 17.1]
Never had sex   1449 37.9 [34.3, 41.6] 36.1 [28.1, 45.0] 45.4 [41.7, 49.2] 36.9 [27.4, 47.5]
Table 2b: 2012 Survey: Men (25–49), socio-demographic and risk factors, by settlement type
Employment status 4768        
Employed   3399 72.3 [68.7, 75.7] 63.2 [55.9, 70.0] 40.6 [36.1, 45.2] 87.6 [77.6, 93.5] <0.001
Unemployed   1315 25.2 [22.2, 28.6] 36.1 [29.2, 43.5] 58.7 [54.1, 63.2] 12.3 [6.4, 22.2]
Student   54 2.4 [1.3, 4.4] 0.7 [0.3, 1.6] 0.7 [0.3, 1.6] 0.1 [0.03, 0.7]  
Education level 4395        
Secondary not complete or less   2194 38.4 [34.6, 42.4] 68.4 [61.5, 74.7] 67.8 [63.4, 71.9] 58.7 [34.1, 79.6] <0.001
Secondary complete/higher   2201 61.6 [57.6, 65.4] 31.6 [25.3, 38.5] 32.2 [28.1, 36.6] 41.3 [20.4, 65.9]  
Past year sex partners 4785        
Never had sex, none, one   4214 84,2 [81.4, 86.7] 86.0 [81.4, 89.6] 82.1 [78.3, 85.4] 96.7 [93.9, 98.3] 0.0001
Two or more   571 15.8 [13.3, 18.6] 14.0 [10.4, 18.6] 17.9 [14.6, 21.7] 3.3 [1.7, 6.1]  
Age sexual debut 4424        
< = 18   2409 54.6 [50.8, 58.5] 65.9 [59.8, 71.4] 57.7 [52.4, 62.9] 54.0 [48.0, 60.0] 0.0042
> = 19   1839 42.3 [38.5, 46.2] 32.4 [26.6, 38.7] 36.4 [31.6, 41.5] 42.1 [36.0, 48.5]
Never had sex   176 3.1 [2.0, 4.8] 1.8 [0.9, 3.5] 5.8 [4.1, 8.3] 3.8 [2.4, 6.2]

For men aged 25–49 (Table 2B) the greatest proportion unemployed were in rural informal settlements (58.7%), and then urban informal settlements (36.1%), with significantly lower unemployment rates in urban formal (25.2%) and rural formal (12.3%, p<0.001). A significantly larger proportion of men in urban formal settlements (61.6%) had completed secondary education, compared to all other settlement types (31.6% urban informal; 32.2% rural informal; 41.3% rural formal, p<0.001). Finally, a greater proportion of men (25–49) in urban informal settlements (65.9%) reported sexual debut at 18 or less, compared to other settlement types (54.6% urban formal; 57.7% rural informal; 54.0% rural formal; p = 0.004).

HIV-prevalence by settlement type for men (15–49) showed consistent patterns (Table 3). HIV-prevalence in all surveys was highest in urban informal settlements, where it was almost twice that of urban formal settlements, and for 2005, 2008 and 2012, and these were significantly different. There was no difference between other settlement types, and urban formal settlements. Rural informal settlements showed an increasing HIV-prevalence over time (p = 0.001).

10.1371/journal.pone.0230105.t003 Weighted HIV-prevalence for men over time by settlement type.
Table 3a: Weighted HIV-prevalence for men (15–49) by settlement-type over time
2002 2005 2008 2012 Trend test over time
%(95%CI) %(95%CI) %(95%CI) %(95%CI) p-value
Urban formal 12.8 [9.9,16.3] 10.6 [8.3,13.6] 9.8 [7.4,12.7] 12.6 [10.3,15.5] 0.476
Urban informal 21.4 [14.7,30.0] 20 [15.3,25.8] 20.7 [16.0,26.4] 22.6 [17.3,28.9] 0.427
Rural informal 11.7 [8.4,16.1] 10.4 [7.8,13.7] 12.7 [9.2,17.3] 15.9 [13.6,18.5] 0.001
Rural formal 8 [4.6,13.6] 12.8 [7.3,21.4] 11.9 [7.1,19.2] 14 [8.3,22.5] 0.053
For year, by settlement type: p-value 0.0226 0.0318 0.0065 0.0122
All estimates include adjustment for clustering and weighting of data
Table 3b: Weighted HIV-prevalence for men (15–24) by settlement-type for 2012
Urban formal n/a n/a n/a 2.1 [1.3, 3.5]
Urban informal n/a n/a n/a 3.2 [1.6, 6.4]
Rural informal n/a n/a n/a 3.2 [1.9, 5.3]
Rural formal n/a n/a n/a 8.2 [5.3, 12.5]
All estimates include adjustment for clustering and weighting of data
Table 3c: Weighted HIV-prevalence for men (25–49) by settlement-type for 2012
Urban formal n/a n/a n/a 17.9 [14.2, 22.3]
Urban informal n/a n/a n/a 29.1 [22.2, 37.0]
Rural informal n/a n/a n/a 24.6 [20.6, 29.1]
Rural formal n/a n/a n/a 15.6 [8.8, 26.2]

All estimates include adjustment for clustering and weighting of data

Bolded estimates indicate no overlap of 95% confidence intervals with urban formal settlements

In the age disaggregated tables (Table 3B and 3C) HIV prevalence was highest among 15–24 year olds residing in rural forma areas, followed by urban informal areas and rural informal areas. Among men 25–49 years old, the highest HIV-prevalence was among those in urban informal settlements, and lowest among those in urban formal settlements, though 95%CI did overlap.

Table 4 presents the unadjusted and adjusted relative risk ratios for all men by settlement type and survey year. In multivariable regressions (Table 4A), for all men (15–49) compared to urban formal settlements, urban informal settlements had a significantly higher relative risk for HIV-prevalence for 2005 (RR1.68, 1.11–2.50), 2008 (RR1.51, 1.04–2.18) and 2012 (RR1.77, 1.19–2.64). In 2002, men in rural formal settlements had a lower relative risk of HIV-prevalence than urban formal settlement (RR0.43, 0.22–0.84), while in 2012 men (15–49) in rural informal settings had a higher relative risk for HIV-prevalence (RR1.44, 1.05–1.97).

10.1371/journal.pone.0230105.t004 Unadjusted and adjusted relative risk ratios for men for all surveys, by settlement type and in 2012 by age.
Table 4a: Unadjusted and adjusted relative risk ratios for men (15–49) for all surveys, by settlement type and in 2012 by age.
2002 Men (15–49) 2005 Men (15–49) 2008 Men (15–49) 2012 Men (15–49)
  Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI)
Urban formal ref ref ref ref ref ref ref ref
Urban informal 1.67(1.08, 2.59) 1.47(0.93, 2.31) 1.88(1.31, 2.70) 1.68(1.11, 2.50) 2.12(1.47, 3.07) 1.51[1.04–2.18] 1.78(1.27, 2.52) 1.77[1.19, 2.64]
Rural informal 0.92(0.61, 1.38) 1.19(0.76, 1.86) 0.98(0.67, 1.43) 1.06(0.67, 1.67) 1.30(0.86, 1.97) 1.29[0.83–2.02] 1.26(0.96, 1.65) 1.44[1.05, 1.97]
Rural formal 0.63(0.34, 1.14) 0.43(0.22, 0.84) 1.20(0.67, 2.18) 1.23(0.56, 2.70) 1.22(0.69, 2.15) 0.88[0.48–1.60] 1.12(0.66, 1.88) 1.13[0.62, 2.08]
n = 2078, df = 768 n = 1933, df = 747 n = 3595, df = 815 n = 3064; df = 786 n = 3283, df = 886 n = 2961, df = 859 n = 6468, df = 880 n = 5109, df = 853
p = 0.01 p<0.001 p = 0.002 p<0.001 p<0.001 p<0.001 p = 0.01 p<0.001
Table 4b: Unadjusted and adjusted relative risk ratios for men in 2012 survey by age categories, and settlement type 2012 Men (15–24)
Urban formal - - - - - - ref ref
Urban informal - - - - - - 1.49(0.62, 3.56) 1.40[0.50–3.87]
Rural informal - - - - - - 1.48(0.72, 3.04) 2.69[1.28–5.67]
Rural formal - - - - - - 3.81(1.96, 7.41) 3.59[1.49–8.64]
- - - - - - n = 2798, df = 757 n = 2347, df = 708
- - - - - - p<0.001 p<0.001
2012 Men (25–49)
Urban formal - - - - - - ref
Urban informal - - - - - - 1.62(1.15, 2.29) 1.68[1.11–2.54]
Rural informal - - - - - - 1.37(1.03, 1.83) 1.30[0.92–1.84]
Rural formal - - - - - - 0.87(0.48, 1.58) 1.00[0.51–1.99]
            n = 3670, df = 830 n = 2762, df = 780
            p = 0.02 p<0.001

All adjusted regressions are adjusted for: age, education, age first sexual debut, past year number of sexual partners.

All analyses include weighting and adjustment for study design

Bolded estimates indicate no overlap of 95% Confidence Intervals with reference category

In 2012, where it was possible to disaggregate men by age (Table 4), for men aged 15–24, compared to urban informal settlements, the relative risk of HIV-prevalence was higher in rural informal (RR2.69, 1.28–5.67) and rural formal (RR3.59, 1.49–8.64), compared to urban formal settlements, however confidence intervals were wide, highlighting lack of precision. And for men 25–49 in 2012, those in urban informal settlements had a higher relative risk of HIV-prevalence (RR1.68, 1.11–2.54) compared to urban formal settlements.

 Women

In total 3137, 7553, 6107 and 10454 women participated in the 2002, 2005, 2008, and 2012 surveys, respectively. In the 2002 survey, there were consistent patterns in distribution of socio-demographic and HIV-acquisition risk factors across both age groups (Table 5). Amongst all women (15–49; Table 5A) a significantly greater proportion of young women were in rural informal (46.6%) and rural formal (43.0%), compared to urban formal (31.0%) and urban informal (30.9%). For women in all age combinations (15–49; 15–24; 25–49) the highest proportion of unemployed were in urban informal settlements (Table 5A, 5B and 5C), and this was significantly higher than urban formal settlements (e.g. in 2002 for women 15–49 it was 68.9% compared to 47.4% for all women, respectively–Table 5A). The largest proportion who had not completed secondary school was in urban informal and rural informal for all age combinations, and the smallest proportion was always in urban formal settlements (Table 5A, 5B and 5C).

10.1371/journal.pone.0230105.t005 Women (15–49) socio-demographic and risk factors, by settlement type for 2002.
Table 5a: 2002 Survey: Women (15–49), socio-demographic and risk factors, by settlement type
  Urban Formal Urban Informal Rural Informal Rural Formal  
  N n Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI p-value
Age 3137                
15–24   1283 31.0 [28.3,33.8] 30.9 [25.6,36.7] 46.6 [42.4,51.0] 43.0 [32.1,54.7] <0.0001
25–49   1854 69.0 [66.2,71.7] 69.1 [63.3,74.4] 53.4 [49.0,57.6] 57.0 [45.3,67.9]  
Employment status 2946          
Employed   846 37.1 [32.7,41.6] 19.1 [13.6,26.1] 10.6 [7.9,14.1] 29.4 [20.0,40.9] <0.0001
Unemployed   1530 47.4 [42.7,52.0] 68.6 [59.3,76.5] 62.9 [57.2,68.2] 59.4 [45.7,71.8]  
Student   570 15.6 [13.4,18.0] 12.3 [8.5,17.6] 26.5 [22.1,31.4] 11.2 [5.2,22.4]  
Education level 3113          
Secondary not complete or less   2157 56.7 [51.5,61.6] 79.4 [71.3,85.7] 82.0 [77.6,85.7] 93.6 [83.6,97.7] <0.0001
Secondary complete/higher   956 43.4 [38.4,48.5] 20.6 [14.3,28.7] 18.0 [14.3,22.4] 6.4 [2.3,16.4]  
Past year sex partners 3114          
Never had sex, none, one   3021 97.3 [95.9,98.2] 95.0 [90.6,97.4] 97.9 [95.5,99.1] 97.8 [94.3,99.2] 0.2749
Two or more   93 2.7 [1.8,4.1] 5.0 [2.6,9.4] 2.1 [0.9,4.5] 2.2 [0.8,5.7]  
Age sexual debut 3089          
< = 18   1374 42.3 [37.9,46.7] 61.9 [52.8,70.1] 50.1 [45.1,55.2] 58.5 [45.2,70.7] <0.0001
> = 19   1134 43.5 [39.4,47.6] 28.2 [21.6,36.0] 27.3 [23.3,31.7] 26.8 [18.1,37.6]  
Never had sex   581 14.3 [12.1,16.8] 9.9 [6.2,15.5] 22.6 [18.8,26.9] 14.7 [6.6,29.6]  
Table 5b: 2002 Survey: Women (15–24), socio-demographic and risk factors, by settlement type
Employment status 1176        
Employed   143 13.7 [8.6,21.2] 6.5 [2.7,14.6] 2.1 [0.9,4.6] 15.4 [8.1,27.3] <0.0001
Unemployed   469 35.8 [29.2,43.0] 54.7 [43.4,65.4] 40.2 [33.2,47.8] 56.6 [38.2,73.3]
Student   564 50.5 [43.6,57.4] 38.9 [28.3,50.6] 57.7 [50.1,64.9] 28.0 [13.3,49.7]  
Education level 1268        
Secondary not complete or less   176 55.9 [49.4,62.1] 74.3 [64.0,82.5] 81.2 [74.8,86.2] 97.0 [91.6,99.0] <0.0001
Secondary complete/higher   400 44.1 [37.9,50.6] 25.7 [17.6,36.0] 18.8 [13.8,25.2] 3.0 [1.0,8.4]  
Past year sex partners 1271        
Never had sex, none, one   1215 94.7 [91.1,96.9] 89.0 [76.5,95.2] 98.3 [96.5,99.2] 97.9 [92.3,99.5] 0.002
Two or more   56 5.3 [3.1,8.9] 11.0 [4.8,23.5] 1.7 [0.8,3.5] 2.1 [0.5,7.7]  
Age sexual debut 1260        
< = 18   541 42.2 [35.7,48.9] 58.7 [44.6,71.5] 43.7 [36.4,51.2] 58.0 [37.1,76.3] 0.225
> = 19   180 15.8 [11.7,21.0] 12.5 [5.3,26.4] 10.9 [7.1,16.4] 8.3 [3.9,16.8]
Never had sex   539 42.0 [35.7,48.7] 28.8 [17.8,43.0] 45.4 [38.6,52.3] 33.7 [16.1,57.5]  
Table 5c: 2002 Survey: Women (25–49), socio-demographic and risk factors, by settlement type
Employment status 1770          
Employed   703 47.3 [41.9,52.8] 24.9 [16.4,35.9] 17.9 [13.0,24.0] 38.7 [23.4,56.6] <0.0001
Unemployed   1061 52.5 [47.0,57.9] 74.9 [63.9,83.5] 82.1 [76.0,87.0] 61.3 [43.4,76.6]  
Student   6 0.2 [0.0,0.8] 0.2 [0.0,1.3] 0   0    
Education level 1845          
Secondary not complete or less   1289 57 [50.8,63.0] 81.7 [71.3,88.9] 82.7 [76.0,87.8] 91 [72.4,97.5] <0.0001
Secondary complete/higher   556 43 [37.0,49.2] 18.3 [11.1,28.7] 17.3 [12.2,24.0] 9 [2.5,27.6]  
Past year sex partners 1843          
Never had sex, none, one   1806 98.4 [96.9,99.2] 97.7 [94.3,99.1] 97.6 [92.4,99.3] 97.7 [91.3,99.4] 0.8176
Two or more   37 1.6 [0.8,3.1] 2.3 [0.9,5.7] 2.4 [0.7,7.6] 2.3 [0.6,8.7]  
Age sexual debut 1829          
< = 18   833 42.3 [37.3,47.5] 63.2 [53.0,72.4] 55.8 [49.3,62.1] 59 [42.6,73.6] 0.0005
> = 19   954 55.9 [50.8,60.9] 35.2 [26.1,45.4] 41.7 [35.5,48.2] 40.6 [26.1,57.0]  
Never had sex   42 1.8 [0.9,3.7] 1.6 [0.7,3.7] 2.5 [1.1,5.9] 0.4 [0.1,3.0]  

Consistently, over the three age categorization the largest proportion reporting sexual debut ≤18 years, was in urban informal settlements, and smallest in urban formal settlements. For the combined group (15–49) and older women (25–49) this was significantly different. For women aged 15–24 (Table 5C), a greater proportion in urban informal settlements reported ≥2 past year sexual partners (11.0%) and this was significantly different to other settlement types, where it was <5.0%.

The other three surveys showed very similar patterns in the distribution of socio-demographics and risk factors as the 2002 survey (Tables 6, 7 and 8). For example the 2012 survey showed very similar patterns for all women (15–49), adolescent women (15–24) and older women (25–49) (Table 8A, 8B and 8C respectively), as the 2002 survey. This included the largest proportion of young (15–24) women being in rural informal settlements (39.3%). The highest proportion of unemployed women was in urban informal and rural informal for all age combinations; for instance amongst 15–24 year olds, half (50.8%) in urban informal reported being unemployed, compared to 29.0% in urban formal settlements. Amongst all women, there were no differences with education levels, but among 15–24 nearly three-quarters in urban informal (73.7%), and rural informal (74.0%) had not completed secondary school, compared to half (53.5%) in urban formal.

10.1371/journal.pone.0230105.t006 Women (15–49) socio-demographic and risk factors, by settlement type for 2005.
Table 6a: 2005 Survey: Women (15–49), socio-demographic and risk factors, by settlement type
  Urban Formal Urban Informal Rural Informal Rural Formal  
  N n Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI p-value
Age 7553          
15–24   3171 31.2 [28.9,33.6] 33.7 [30.1,37.5] 38.5 [35.3,41.7] 35.7 [31.9,39.6] <0.0001
25–49   4382 68.8 [66.4,71.1] 66.3 [62.5,69.9] 61.5 [58.3,64.7] 64.3 [60.4,68.1]  
Employment status 7356          
Employed   2099 36.7 [33.8,39.7] 23 [18.7,28.0] 12.2 [10.3,14.5] 36.3 [29.3,43.9] <0.0001
Unemployed   3693 45.7 [42.4,48.9] 63.3 [57.0,69.1] 66.2 [63.1,69.2] 55.1 [47.8,62.2]  
Student   1564 17.6 [15.5,20.0] 13.7 [10.8,17.2] 21.6 [19.2,24.1] 8.6 [6.3,11.7]  
Education level 7475          
Secondary not complete or less   4800 52.7 [48.9,56.5] 78.1 [73.6,82.1] 74.2 [70.9,77.3] 87.2 [82.7,90.7] <0.0001
Secondary complete/higher   2675 47.3 [43.5,51.1] 21.9 [17.9,26.4] 25.8 [22.7,29.1] 12.8 [9.3,17.3]  
Past year sex partners 7223          
Never had sex, none, one   7090 97.5 [96.6,98.2] 97.4 [95.4,98.6] 98.7 [97.9,99.1] 98.8 [97.4,99.4] 0.0424
Two or more   133 2.5 [1.8,3.4] 2.6 [1.4,4.6] 1.3 [0.9,2.1] 1.2 [0.6,2.6]  
Age sexual debut 6762          
< = 18   3143 43.6 [40.5,46.7] 62.1 [56.7,67.2] 54.2 [50.0,58.3] 63.4 [57.4,69.0] <0.0001
> = 19   2275 40.8 [38.0,43.6] 27 [23.2,31.1] 29.1 [25.5,32.9] 27.5 [22.6,33.0]  
Never had sex   1344 15.7 [13.8,17.8] 11 [7.7,15.3] 16.8 [14.7,19.0] 9.1 [6.7,12.4]  
Table 6b: 2005 Survey: Women (15–24), socio-demographic and risk factors, by settlement type
Employment status 3096          
Employed   384 14.7 [12.0,17.9] 8.7 [5.7,13.1] 1.7 [1.0,2.8] 21.3 [15.1,29.1] <0.0001
Unemployed   1180 31.7 [27.5,36.3] 51.9 [44.0,59.7] 43.7 [39.4,48.0] 55.1 [48.0,62.0]  
Student   1532 53.5 [49.2,57.8] 39.4 [32.4,46.8] 54.6 [50.3,58.9] 23.6 [17.7,30.9]  
Education level 3135          
Secondary not complete or less   2037 58.2 [53.7,62.6] 77.8 [70.5,83.7] 71.8 [67.5,75.7] 86 [79.6,90.6] <0.0001
Secondary complete/higher   1098 41.8 [37.4,46.3] 22.2 [16.3,29.5] 28.2 [24.3,32.5] 14 [9.4,20.4]  
Past year sex partners 3027          
Never had sex, none, one   2948 96.1 [94.5,97.3] 95.1 [89.6,97.7] 98.1 [96.8,98.9] 97.8 [94.3,99.2] 0.0542
Two or more   79 3.9 [2.7,5.5] 4.9 [2.3,10.4] 1.9 [1.1,3.2] 2.2 [0.8,5.8]  
Age sexual debut 2978          
< = 18   1284 39.4 [35.0,44.1] 60.7 [50.9,69.7] 47.5 [42.1,53.0] 60.3 [51.4,68.6] 0.0003
> = 19   434 19 [15.3,23.2] 12.4 [8.6,17.5] 14.2 [10.5,18.9] 15.8 [9.7,24.7]  
Never had sex   1260 41.6 [37.5,45.8] 27 [19.4,36.2] 38.3 [34.6,42.2] 23.9 [18.1,31.0]  
Table 6c: 2005 Survey: Women (25–49), socio-demographic and risk factors, by settlement type
Employment status 4260          
Employed   1715 46.7 [42.9,50.5] 30.4 [24.3,37.3] 19 [15.8,22.5] 44.9 [35.5,54.6] <0.0001
Unemployed   2513 52 [48.1,55.8] 69.1 [62.2,75.2] 80.5 [76.9,83.7] 55.1 [45.4,64.5]  
Student   32 1.3 [0.7,2.5] 0.5 [0.2,1.4] 0.5 [0.3,1.1] 0    
Education level 4340          
Secondary not complete or less   2763 50.2 [45.8,54.6] 78.3 [73.6,82.3] 75.8 [71.2,79.9] 87.9 [82.0,92.1] <0.0001
Secondary complete/higher   1577 49.8 [45.4,54.2] 21.7 [17.7,26.4] 24.2 [20.1,28.8] 12.1 [7.9,18.1]  
Past year sex partners 4196          
Never had sex, none, one   4142 98.2 [96.9,98.9] 98.6 [96.9,99.4] 99 [98.0,99.5] 99.3 [97.999.8] 0.2564
Two or more   54 1.8 [1.1,3.1] 1.4 [0.6,3.1] 1 [0.5,2.0] 0.7 [0.2,2.1]  
Age sexual debut 3784          
< = 18   1859 45.5 [42.1,49.0] 62.8 [57.1,68.2] 59 [53.9,64.0] 65.2 [58.0,71.8] <0.0001
> = 19   1841 51.1 [47.6,54.6] 34.9 [29.6,40.6] 40 [35.1,45.0] 34.6 [28.1,41.8]  
Never had sex   84 3.4 [2.3,5.0] 2.3 [1.0,5.5] 1 [0.4,2.4] 0.2 [0.03,1.3]  
10.1371/journal.pone.0230105.t007 Women (15–49) socio-demographic and risk factors, by settlement type for 2008.
Table 7a: 2008 Survey: Women (15–49), socio-demographic and risk factors, by settlement type
N n Urban Formal Urban Informal Rural Informal Rural Formal  
    Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI  
Age 6107                    
15–24   2465 30.5 [28.2,32.9] 33.1 [29.9,36.5] 41.6 [39.1,44.2] 26.5 [22.7,30.8] <0.0001
25–49   3642 69.5 [67.1,71.8] 66.9 [63.5,70.1] 58.4 [55.8,61.0] 73.5 [69.2,77.3]  
Employment status 5682          
Employed   1933 44.7 [41.4,48.0] 21.3 [17.1,26.0] 12.7 [10.0,16.1] 37.7 [30.3,45.8] <0.0001
Unemployed   2630 40.3 [37.3,43.5] 63.9 [59.2,68.4] 63.8 [60.1,67.4] 53.5 [46.0,60.9]  
Student   1119 15 [13.5,16.7] 14.8 [11.9,18.3] 23.5 [20.9,26.3] 8.7 [5.7,13.2]  
Education level 5770          
Secondary not complete or less   3542 47.4 [44.1,50.7] 73.2 [67.9,78.0] 75.1 [71.2,75.1] 68.5 [61.1,75.1] <0.0001
Secondary complete/higher   2228 52.6 [49.3,55.9] 26.8 [22.1,32.1] 24.9 [21.3,28.8] 31.5 [24.9,38.9]  
Past year sex partners 5730                    
Never had sex, none, one   4524 80 [77.6,82.3] 79.6 [74.8,83.6] 76.4 [73.1,79.4] 81.7 [75.6,86.6] 0.1781
Two or more   1206 20 [17.7,22.4] 20.4 [16.4,25.2] 23.6 [20.6,26.9] 18.3 [13.4,24.4]  
Age sexual debut 5731          
< = 18   2793 46.4 [43.5,49.3] 60.6 [56.2,64.8] 57.3 [53.6,60.8] 53.8 [46.7,60.8] <0.0001
> = 19   2101 41.7 [38.9,44.6] 30.8 [27.3,34.5] 31.4 [28.1,34.8] 40.2 [33.3,47.5]  
Never had sex   837 11.9 [10.4,13.7] 8.7 [6.6,11.4] 11.4 [9.5,13.6] 6 [4.0,8.8]  
Table 7b: 2008 Survey: Women (15–24), socio-demographic and risk factors, by settlement type
Employment status 2236          
Employed   335 15.7 [12.6,19.4] 5.1 [3.0,8.6] 3.6 [2.0,6.7] 19.1 [12.9,27.3] <0.0001
Unemployed   802 34.9 [30.2,40.0] 50 [42.3,57.7] 39.2 [34.2,44.4] 49.3 [38.2,60.5]  
Student   1099 49.4 [44.4,54.5] 44.9 [37.3,52.8] 57.2 [51.9,62.3] 31.6 [22.7,42.2]  
Education level 2254          
Secondary not complete or less   1467 58.6 [53.6,63.5] 71.5 [64.2,77.9] 75.7 [71.1,79.8] 71.7 [61.3,70.1] <0.0001
Secondary complete/higher   787 41.4 [36.5,46.4] 28.5 [22.2,35.8] 24.3 [20.2,28.9] 28.3 [19.8,38.7]  
Past year sex partners 2255          
Never had sex, none, one   1869 85.2 [81.7,88.0] 82.1 [76.3,86.8] 76.8 [72.0,81.0] 80.3 [72.2,86.5] 0.0045
Two or more   386 14.9 [12.0,18.3] 17.9 [13.3,23.7] 23.2 [19.0,28.0] 19.7 [13.5,27.8]  
Age sexual debut 2254          
< = 18   1053 42.8 [38.4,47.3] 56.1 [49.0,63.0] 54.5 [49.4,59.5] 54.1 [44.2,63.7] 0.0005
> = 19   364 17.3 [13.7,21.6] 17.6 [13.1,23.2] 16.8 [13.4,21.0] 21.5 [14.3,31.1]  
Never had sex   837 39.9 [35.2,44.8] 26.3 [20.6,32.9] 28.7 [24.2,33.7] 24.3 [16.7,34.0]  
  Table 7c: 2008 Survey: Women (25–49), socio-demographic and risk factors, by settlement type
Employment status 3446          
Employed   1598 57 [53.0,60.9] 29.2 [23.5,35.6] 18.7 [14.8,23.3] 43.9 [35.0,53.2] <0.0001
Unemployed   1828 42.6 [38.7,46.6] 70.8 [64.4,76.5] 80.1 [75.6,84.0] 54.9 [45.7,63.8]  
Student   20 0.4 [0.2,0.9] 0   1.2 [0.5,2.9] 1.2 [0.2,7.7]  
Education level 3516          
Secondary not complete or less   2075 42.7 [38.7,46.8] 74 [68.1,79.2] 74.8 [69.7,79.2] 67.5 [58.0,75.7] <0.0001
Secondary complete/higher   1441 57.3 [53.3,61.3] 26 [20.8,31.9] 25.2 [20.8,31.9] 32.5 [24.3,42.0]  
Past year sex partners 3457          
Never had sex, none, one   2655 77.8 [74.8,80.5] 78.3 [71.8,83.7] 76.1 [72.0,79.7] 82.2 [74.6,87.9] 0.5178
Two or more   820 22.2 [19.5,25.2] 21.7 [16.3,28.2] 23.9 [20.3,28.0] 17.8 [12.1,25.4]  
Age sexual debut 3477          
< = 18   1740 47.9 [44.3,51.5] 62.7 [57.7,67.5] 59.1 [54.1,63.9] 53.7 [44.8,62.5] <0.0001
> = 19   1737 52.1 [48.5,55.7] 37.3 [32.5,42.3] 40.9 [36.1,45.9] 46.3 [37.5,55.3]  
Never had sex                      
10.1371/journal.pone.0230105.t008 Women (15–49) socio-demographic and risk factors, by settlement type for 2012.
Table 8a: 2012 Survey: Women (15–49), socio-demographic and risk factors, by settlement type
Urban formal Urban informal Rural informal Rural formal
  N n Col % 95% CI Col % 95% CI Col % 95% CI Col % 95% CI  
Age 10454        
15–24   3733 32.5 [30.5,34.4] 29.9 [26.8,33.1] 39.3 [36.8,41.8] 28.5 [22.5,35.3] <0.0001
25–49   6721 67.5 [65.6,69.5] 70.1 [66.9,73.2] 60.7 [58.2,63.2] 71.5 [64.7,77.5]  
Employment status 9988        
Employed   3539 42.9 [39.8,46.0] 31.4 [28.3,34.6] 17.8 [15.1,20.8] 43.1 [37.3,49.0] <0.0001
Unemployed   4540 38.8 [35.5,42.1] 55.7 [52.7,58.7] 57.9 [54.9,60.8] 43.2 [37.5,49.1]
Student   1909 18.4 [16.5,20.4] 12.9 [10.4,16.0] 24.3 [22.4,26.4] 13.7 [8.1,22.4]  
Education level 9223        
Secondary not complete or less   5173 45.4 [41.6,49.2] 69.8 [64.7,74.4] 68.9 [65.5,72.1] 67.2 [59.4,74.1] <0.0001
Secondary complete/higher   4050 54.6 [50.8,58.4] 30.2 [25.6,35.3] 31.1 [27.9,34.5] 32.8 [25.9,40.6]  
Past year sex partners 10054        
Never had sex, none, one   9737 96.0 [95.0,96.8] 95.6 [93.6,97.0] 97.0 [96.1,97.8] 98.2 [96.6,99.1] 0.0607
Two or more   315 4.0 [3.2,5.0] 4.4 [3.0,6.4] 3.0 [2.2,3.9] 1.8 [0.9,3.4]  
Age sexual debut 9692        
< = 18   4531 47.6 [44.6,50.6] 64.0 [59.4,68.4] 51.6 [48.9,54.3] 51.9 [45.9,57.9] <0.0001
> = 19   3540 38.2 [35.5,40.9] 26.6 [22.6,31.0] 31.5 [28.7,34.4] 31.8 [27.6,36.3]
Never had sex 1621 14.3 [12.8, 16.0] 9.3 [7.3, 11.9] 16.9 [15.0, 18.9] 16.3 [11.3, 23.0]
Table 8b: 2012 Survey: Women (15–24), socio-demographic and risk factors, by settlement type
Employment status 3572          
Employed   486 18.1 [14.4,22.5] 9.2 [5.9,14.1] 5.3 [3.7,7.6] 15.6 [9.8,23.9] <0.0001
Unemployed   1261 29 [25.3,33.0] 50.8 [44.1,57.4] 35.3 [32.0,38.7] 36.6 [26.1,48.6]
Student   1825 52.9 [48.3,57.6] 40 [33.4,46.9] 59.4 [55.5,63.2] 47.8 [33.5,62.6]  
Education level 3353          
Secondary not complete or less   2156 53.5 [49.1,57.9] 73.7 [66.5,79.8] 74 [69.4,78.1] 63.2 [47.1,76.7] <0.0001
Secondary complete/higher   1197 46.5 [42.1,50.8] 27.2 [21.0,34.4] 25.2 [21.0,30.0] 38.8 [23.7,56.3]  
Past year sex partners 3596          
Never had sex, none, one   3449 95.2 [93.5,96.5] 91.1 [85.2,94.7] 96.7 [94.9,97.9] 98.8 [96.1,99.6] 0.0078
Two or more   147 4.8 [3.5,6.5] 9 [5.3,14.8] 3.3 [2.1,5.1] 1.2 [0.4,3.9]  
Age sexual debut 3562          
< = 18   1569 45.9 [41.6,50.2] 63 [56.0,69.4] 45 [41.0,49.1] 46.9 [34.4,59.7] 0.008
> = 19   525 16.7 [14.1,19.7] 9.1 [6.3,13.0] 15.7 [12.8,19.0] 10.3 [6.9,15.1]
Never had sex   1468 37.4 [33.5,41.5] 28 [22.5,34.2] 39.3 [35.9,42.9] 42.8 [30.5,56.0]  
Table 8c: 2012 Survey: Women (25–49), socio-demographic and risk factors, by settlement type
Employment status 6416          
Employed   3053 54.8 [50.9,58.6] 40.9 [36.8,45.0] 26 [22.0,30.5] 54.1 [48.6,59.5] <0.0001
Unemployed   3279 43.5 [39.6,47.5] 57.8 [53.3,62.2] 72.7 [68.3,76.8] 45.9 [40.5,51.4]  
Student   84 1.7 [1.2,2.5] 1.3 [0.5,3.3] 1.3 [0.6,2.5] 0    
Education level 5870          
Secondary not complete or less   3017 41.3 [36.9,45.8] 68 [62.7,72.9] 65.3 [61.0,69.3] 68.9 [60.0,76.6] <0.0001
Secondary complete/higher   2853 58.7 [54.2,63.1] 32 [27.1,37.3] 34.7 [30.7,39.0] 31.1 [23.4,40.0]  
Past year sex partners 6456          
Never had sex, none, one   6288 96.4 [95.0,97.4] 97.5 [95.7,98.6] 97.2 [95.9,98.1] 98 [95.7,99.1] 0.3502
Two or more   168 3.6 [2.6,5.0] 2.5 [1.4,4.3] 2.8 [1.9,4.1] 2 [0.9,4.3]  
Age sexual debut 6130          
< = 18   2962 48.5 [45.0,52.0] 64.5 [58.8,69.9] 56.2 [52.3,60.0] 54.1 [46.0,61.9] 0.0015
> = 19   3015 49.4 [45.9,52.9] 34.5 [29.1,40.4] 42.4 [38.6,46.1] 40.8 [35.8,46.1]  
Never had sex   153 2.1 [1.6, 2.9] 1 [0.4, 2.2] 1.5 [0.7, 3.1] 5.1 [1.3, 18.6]  

For HIV-risk factors in the 2012 survey, amongst those 15–24 (Table 8B), the greatest proportion reporting two or more past year sexual partners were those in urban informal settlements (9.0%) and this was significantly different to other settlement types (4.8% urban formal; 3.3% rural informal; 1.2% rural formal; p = 0.008). For all age combinations, the greatest proportion reporting sexual debut of ≤18 years was in urban informal settlements, and lowest proportion in urban formal settlements, and these were all significantly different.

HIV-prevalence by settlement types, over surveys for all age categorisations for women (Table 9) showed consistent patterns. The highest HIV-prevalence was among urban informal settlements. For women 15–49 (Table 9A), compared to urban formal settlements these differences were significant at all-time points, and in 2008 and 2012, compared to urban formal settlements, rural informal settlements were also significantly higher. Similarly for women 15–24 (Table 9B), compared to urban formal settlements, urban informal settlements had a significantly higher HIV-prevalence for 2005, 2008 and 2012. And for women 25–49 (Table 9C), urban informal settlements had a higher proportion of HIV-positive women, in all years, and in 2008 and 2012, in rural informal areas also had a higher proportion of HIV-positive women, compared to urban formal areas.

10.1371/journal.pone.0230105.t009 Weighted HIV-prevalence for women by settlement type over time.
Table 9a Weighted HIV-prevalence for women (15–49) by settlement-type over time 
2002 2005 2008 2012 Time-trend
%(95%CI) %(95%CI) %(95%CI) %(95%CI) p-value
Urban formal 18.1 [14.8,22.0] 17.2 [14.5,20.3] 16.8 [14.2,19.7] 16.9 [14.2,19.9] 0.308
Urban informal 33.8 [24.4,44.8] 30.7 [26.8,35.0] 34.6 [30.4,39.0] 38.1 [34.0,42.3] 0.006
Rural informal 12.9 [9.5,17.3] 21.8 [18.4,25.7] 23.9 [20.6,27.6] 29.4 [26.5,32.5] <0.0001
Rural formal 15.2 [7.6,28.3] 15.5 [10.9,21.5] 21.4 [16.4,27.5] 20.0 [15.0,26.2] 0.027
For year, by settlement type: p-value 0.0003 0.0001 <0.0001 <0.0001  
Table 9b: Weighted HIV-prevalence for women (15–24), by settlement-type over time  
Urban formal 13.7 [9.7,19.2] 12.3 [9.4,16.1] 11.3 [8.5,14.9] 9.4 [7.3,12.0] 0.001
Urban informal 28.3 [17.9,41.7] 30.7 [24.9,37.1] 21.0 [16.1,26.8] 18.9 [13.1,26.5] 0.001
Rural informal 7.5 [4.7,11.8] 18.4 [14.2,23.4] 14.0 [10.5,18.4] 12.6 [9.8,16.0] 0.928
Rural formal 10.1 [4.2,22.5] 16.7 [10.6,25.2] 19.2 [12.8,27.9] 10.7 [7.5,15.1] 0.419
For year, by settlement type: p-value 0.0006 0.0002 0.018 0.0174  
Table 9c: Weighted HIV-prevalence for women (25–49), by settlement-type over time  
Urban formal 20.1 [15.9,25.2] 19.4 [16.1,23.2] 19.2 [15.9,23.0] 20.5 [16.9,24.7] 0.565
Urban informal 36.2 [25.5,48.6] 30.8 [25.8,36.2] 41.8 [35.8,48.1] 45.8 [41.1,50.5] <0.0001
Rural informal 17.8 [12.5,24.7] 23.9 [19.8,28.6] 31.7 [26.9,36.9] 40.2 [36.3,44.2] <0.0001
Rural formal 18.5 [8.2,36.5] 14.9 [9.6,22.4] 22.3 [15.8,30.5] 23.4 [16.9,31.4] 0.013
For year, by settlement type: p-value 0.0296 0.0049 <0.0001 <0.0001  

All estimates include adjustment for clustering and weighting of data

Bolded estimates indicate no overlap of 95% confidence intervals with urban informal settlements

In the combined age group for women (15–49; Table 9A) urban informal, rural informal and rural formal, all saw significantly increasing HIV-prevalence trends. In younger (15–24; Table 9B) women, there were decreasing HIV-prevalence trends for urban formal and urban informal. And for older (25–49; Table 9C) women, increasing HIV-prevalence trends for urban informal, rural informal and rural formal settlement types.

In adjusted analyses for women (Table 10), for all survey years, and in all age categorisations (15–49; 15–24; 25–49), compared to urban formal settlements, women in urban informal settlements had significantly higher relative risks of living with HIV. In other settlement types, compared to urban formal settlements, there was no consistent patterning, but in 2012, women in rural informal settlements had a higher relative risk for HIV-prevalence, for all age combinations (15–49; 15–24; 25–49).

10.1371/journal.pone.0230105.t010 Unadjusted and adjusted relative risk ratios for women by settlement type, and survey.
Table 10a: Unadjusted and adjusted relative risk ratios for women (15–49), by settlement type, and survey
  2002 Women (15–49) 2005 Women (15–49) 2008 Women (15–49) 2012 Women (15–49)
Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI) Unadjusted RR (95%CI) Adjusted RR(95%CI)
Urban formal ref ref ref ref ref ref ref ref
Urban informal 1.87(1.30, 2.68) 1.75(1.23, 2.48) 1.79(1.44, 2.22) 1.64(1.25, 2.14) 2.06(1.68, 2.53) 1.64[1.32–2.03] 2.26(1.83, 2.78) 1.89[1.50–2.40]
Rural informal 0.71(0.50, 1.02) 0.74(0.50, 1.10) 1.27(1.00, 1.61) 1.22(0.93, 1.59) 1.43(1.14, 1.78) 1.13[0.89–1.43] 1.72(1.40, 2.11) 1.60[1.27, 1.99]
Rural formal 0.84(0.42, 1.69) 0.98(0.50, 1.91) 0.90(0.62, 1.32) 0.81(0.50, 1.31) 1.28(0.94, 1.74) 1.04[0.77–1.42] 1.14(0.82, 1.60) 0.95[0.65–1.38]
n = 2717; df = 818 n = 2495, df = 808 n = 5650, df = 837 n = 4910, df = 824 n = 4823, df = 923 n = 4363, df = 905 n = 8253, df = 909 n = 6650, df = 883
p<0.001 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001
Table 10b: Unadjusted and adjusted relative risk ratios for women (15–24), by settlement type, and survey
  2002 Women (15–24) 2005 Women (15–24) 2008 Women (15–24) 2012 Women (15–24)
Urban formal ref ref ref ref ref ref ref ref
Urban informal 2.06(1.19, 3.56) 1.86(1.10, 3.14) 2.49(1.78, 3.49) 2.07(1.43, 2.99) 1.85(1.27, 2.70) 1.50[1.02–2.22] 2.07(1.34, 3.19) 1.79[1.17–2.73]
Rural informal 0.55(0.31, 0.97) 0.63(0.33, 1.21) 1.49(1.02, 2.16) 1.41(0.95 2.08) 1.23(0.83, 1.84) 0.92[0.61–1.41] 1.38(0.98, 1.95) 1.45[1.01–2.08]
Rural formal 0.74(0.29, 1.85) 0.88(0.34 2.28) 1.35(0.81, 2.26) 1.13(0.65, 1.95) 1.70(1.04, 2.75) 1.07[0.68–1.68] 1.12(0.71, 1.74) 0.93[0.54–1.60]
n = 1123, df = 599 n = 1004, df = 563 n = 2335, df = 717 n = 2134, df = 695 n = 1986, df = 745 n = 1754, df = 674 n = 3092, df = 782 n = 2586, df = 741
p<0.001 p<0.001 p<0.001 p<0.001 p = 0.01 p<0.001 p<0.001 p<0.001
Table 10c: Unadjusted and adjusted relative risk ratios for women (25–49), by settlement type, and survey
  2002 Women (25–49) 2005 Women (25–49) 2008 Women (25–49) 2012 Women (25–49)
Urban formal ref ref ref ref ref ref ref ref
Urban informal 1.80(1.21, 2.68) 1.68(1.11, 2.53) 1.58(1.24, 2.03) 1.48(1.09, 2.02) 2.18(1.72, 2.77) 1.66[1.31–2.12] 2.23(1.76, 2.82) 1.91[1.47–2.48]
Rural informal 0.88(0.58, 1.34) 0.82(0.51 1.31) 1.23(0.95, 1.60) 1.15(0.85, 1.56) 1.65(1.30, 2.12) 1.20[0.92–1.57] 1.90(1.52, 2.39) 1.67[1.31–2.14]
Rural formal 0.92(0.41, 2.03) 1.12(0.52, 2.40) 0.77(0.48, 1.22) 0.68(0.36, 1.28) 1.16(0.80, 1.70) 1.07[0.73–1.56] 1.10(0.76, 1.60) 1.00[0.67–1.49]
n = 1594, df = 729 n = 1491, df = 716 n = 3315, df = 813 n = 2776, df = 796 n = 2837, df = 882 n = 2609, df = 855 n = 5161, df = 886 n = 4064, df = 850
p = 0.01 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001 p<0.001

All adjusted regressions are adjusted for: age, education, age first sexual debut, past year number of sexual partners.

All analyses include weighting and adjustment for study design

Bolded estimates indicate no overlap of 95% Confidence Intervals with reference category

 Discussion

Our analysis of four representative household surveys in South Africa from 2002 to 2012, show consistent patterning around the distribution of HIV, by settlement types, with urban informal settlements showing the highest prevalence. This finding was consistent in multivariate models accounting for potential socio-demographic cofounders, and in multivariate models for all women and men aged 15–49, and for women across different age stratifications (15–24; 25–49). For men, stratification by age was only possible for the most recent survey (2012), and in adjusted models urban informal settlements had the highest relative risk of HIV-prevalence for older men (25–49), but for younger men (15–24) adjusted relative risk HIV-prevalence was highest among rural formal settlements.

The markedly high HIV-prevalence, and consistent association between urban informal settlements and HIV-prevalence, even in adjusted models may have a number of underlying explanations. HIV-risk behaviour showed clear patterning by settlement type, with early sexual debut more common amongst both women and men residing in urban informal settlements across all surveys (and age categorisations). Similarly, young women (15–24) in all survey waves more often reported two or more past year sexual partners in urban informal settlements compared to other settlement types. Early sexual debut and multiple sexual partners, both of which are often driven by poverty, inequitable gender norms and violence, are key risks for HIV-acquisition [21–23]. Interventions targeting these factors may be important strategies.

Structural factors may also shape the disproportionate burden of HIV in urban informal settlements. Across surveys, women and men in urban informal settlements had lower educational attainment than those in formal settlements. Low education, since the early 2000s, has been recognised as a risk factor for HIV [24]. Similarly, urban informal settlements had high unemployment rates, and unemployment, via increased poverty, may be a risk factor for HIV-acquisition [1]. Structural interventions focused on strengthening educational attainment, and increasing employment/reducing poverty, are potentially important interventions.

Even after adjustment for potential co-founders, informal settlements consistently had higher HIV-prevalence than other settlement types, suggesting there remained unmeasured factors. Housing in informal settlements can be unstable, and studies from North America have highlighted how housing instability is an independent risk factor for HIV and STIs [25]. It may also be that settlement type is a proxy for sexual networks; studies in North America have highlighted how dense sexual networks, shaped by poverty and racism, are crucial for HIV-transmission patterns [26]. Finally, it may also be that people acquiring HIV are transitioning into urban informal settlements as they lose access to work and formal housing, and this explains the high HIV-prevalence. We could not, however, find a consistent measure of mobility across surveys to include this as a potential cofounder.

Our analysis also highlighted two trends in HIV-prevalence by settlement type. First, increasing HIV-prevalence amongst older (24–49) women in urban informal, rural informal and rural formal, and men (15–49) in rural informal. These changes may be indicative of the rollout of ARVs, with people surviving for longer, and HIV becoming a chronic disease [27]. The changing distribution of HIV also suggests that there may be important migration patterns as people age, with movement from urban to rural areas. The decreasing HIV-prevalence amongst younger (15–24) women in urban formal and urban informal settlements is likely indicative of the impact of improved prevention of mother-to-child transmission in South Africa [28], and also potentially the impact of HIV-prevention programming, reducing HIV-incidence [16]. The lack of similar trends in rural formal and informal settings highlights important gaps in impact for both programmes.

For men in 2012 the age stratified adjusted analysis showed that among young men those residing in rural formal areas had significantly higher HIV-prevalence than urban formal. Given that men typically acquire HIV at a later age [29], it may be the failure of prevention of mother-to-child transmission interventions in rural formal areas that leads to this patterning, paralleling what is seen among young women. For older men the sustained high HIV-prevalence in urban informal settlements, similarly parallels that seen among women of all ages, and is likely due to the rollout of ART. Importantly, given that one important pathway for HIV-transmission is often intergenerational [29], the high HIV-prevalence in older men in urban informal settlements could explain the continued high HIV-prevalence among young women in urban informal settings.

Limitations

This study has a number of limitations. In all surveys, there was relatively high refusal rates for the main survey and for HIV-testing, particularly amongst men, and while data were weighted to account for this, there may be bias. In addition, the low levels of HIV-testing prevented age-disaggregated analysis of the men’s data, apart from for the 2012 data, and even in 2012 the large confidence intervals in adjusted analyses highlight the lack of precision. South Africa has high levels of mobility and internal migration, and the assumption that all participants were regular residents of the settlement type where data were collected cannot be tested. Similarly, there was variation in the timing of studies, and seasonal migration may have played a greater, or lesser role in depending on the months of data collection. In addition, only a few potential cofounders were consistently assessed in all four surveys, and key risk factors such as intimate partner violence, condom use, and migration were not included. We were unable to include the 2017 survey data as the data set had not been made public, and the categorization of settlement type was changed, with urban formal and urban informal combined into one category, ‘urban’, limiting comparability across time. Finally, only HIV-prevalence rather than incidence was assessed, and as such, we cannot determine whether the pattern of HIV-incidence is the same as prevalence. Nonetheless, analysis is nationally generalizable, as the surveys were all population based samples, and analyses were weighted to census data and to account for response refusal.

 Conclusions

The analyses presented have a number of implications for programming in South Africa. First, in terms of ensuring ARV coverage, and achieving 90-90-90, settlement types with the highest, and increasing HIV-prevalence (urban informal settlements, and rural informal and formal settlements) remain most poorly served. The historical legacies in South Africa remain around access to healthcare, despite attempts to address these via government. Spatially targeted access to ARVs is therefore an important priority. Second, given the concentration of urban informal settlements, in relatively geographically bounded, and dense situations, a significant effort is required around HIV-prevention programming. Current programmes such as DREAMS and She-Conquers, do recognize and target urban informal settlements [19], however, the specific challenges of interventions in these settings, and lack of well evaluated interventions delivered here, remains a major challenge to intervention programming.

More widely, this analysis suggests that settlement type may be important in understanding the spatial distribution of HIV in South Africa, and elsewhere. Such spatial patterning of HIV reflects patterns of wider marginalization of those who live there, including race, gender and poverty [1, 25, 26]. Further investigation into how these factors intersect to shape high HIV-incidence and prevalence is critical to understand how best to prevent HIV, and ensure HIV-treatment is available to all.

The four surveys were managed and made available by the HSRC team and we thank them and their staff for this, and recognize the huge investment in this process. We thank the participants who provided their time and information.

 References Magadi M. The Disproportionate High Risk of HIV Infection Among the Urban Poor in Sub-Saharan Africa. AIDS and Behaviour. 2013;17:1645–54. Dunkle K, Jewkes R, Murdock D, Sikweyiya Y, Morrell R. Prevalence of Consensual Male–Male Sex and Sexual Violence, and Associations with HIV in South Africa: A Population-Based Cross-Sectional Study. PLoS Med. 2013;10(6):e1001472. doi: 10.1371/journal.pmed.1001472 23853554 Altman D. Globalization, political economy, and HIV/AIDS. Theory and Society. 1999;28(4):559–84. Madise NJ, Ziraba AK, Inungu J, Khamadi SA, Ezeh A, Zulu EM, et al. Are slum dwellers at heightened risk of HIV infection than other urban residents? Evidence from population-based HIV prevalence surveys in Kenya. Health Place. 2012;18(5):1144–52. doi: 10.1016/j.healthplace.2012.04.003 22591621 UNAIDS. Identifying Populations at Greatest Risk of Infection–Geographic Hotspots and Key Populations. Geneva: UNAIDS, 2013. Kates J, Wexler A, Lief E, UNAIDS. Donor Government Funding for HIV in Low- and Middle-Income Countries in 2017. Geneva: Kaiser Foundation and UNAIDS, 2018. Tanser F, Bärnighausen T, Cooke GS, Newell M-L. Localized spatial clustering of HIV infections in a widely disseminated rural South African epidemic. International journal of epidemiology. 2009;38(4):1008–16. doi: 10.1093/ije/dyp148 19261659 Tanser F, LeSueur D, Solarsh G, Wilkinson D. HIV heterogeneity and proximity of homestead to roads in rural South Africa: an exploration using a geographical information system. Trop Med Int Health. 2000;5(1):40–6. doi: 10.1046/j.1365-3156.2000.00513.x 10672204 Tanser F, Bärnighausen T, Dobra A, Sartorius B. Identifying ‘corridors of HIV transmission’in a severely affected rural South African population: a case for a shift toward targeted prevention strategies. International journal of epidemiology. 2017;47(2):537–49. Wand H, Ramjee G. Targeting the hotspots: investigating spatial and demographic variations in HIV infection in small communities in South Africa. Journal of the International AIDS Society. 2010;13(1):41. Kleinschmidt I, Pettifor A, Morris N, MacPhail C, Rees H. Geographic distribution of human immunodeficiency virus in South Africa. The American journal of tropical medicine and hygiene. 2007;77(6):1163–9. 18165541 Rehle T, Shisana O, Pillay V, Zuma K, Puren A, Parker W. National HIV incidence measures—new insights into the South African epidemic. Samj S Afr Med J. 2007;97(3):194–9. 17440667 Shisana O, Rehle T, Simbayi L, Zuma K. South African National HIV Prevalence, Incidence, Behaviour and Communication Survey, 2008. Cape Town: HSRC, 2009. Shisana O, Rehle T, Simbayi LC, Zuma K, Jooste S, Zungu N, et al. South African National HIV Prevalence, Incidence and Behaviour Survey, 2012. Cape Town: HSRC Press, 2014. Connolly C, Colvin M, Shishana O, Stoker D. Epidemiology of HIV in South Africa-results of a national, community-based survey. South African Medical Journal. 2004;94(9). HSRC. South African National HIV Prevalence, Incidence, Behaviour and Communication Survey, 2017. Pretoria, South Africa: HSRC, 2018. UNICEF. Opportunity in crisis: Preventing HIV from early adolescence to young adulthood. Geneva: UNICEF, 2011. Editors L. Commitment needed from South Africa’s new president. Lancet HIV. 2018;5(4):PE155. Saul J, Bachman G, Allen S, Toiv NF, Cooney C. The DREAMS core package of interventions: A comprehensive approach to preventing HIV among adolescent girls and young women. Plos One. 2018;13(12):e0208167. doi: 10.1371/journal.pone.0208167 30532210 Statistics SA. Census 2011: Metadata. Pretoria: Statistics South Africa, 2012 Contract No.: Report No. 03-01-47 Jewkes R, Dunkle K, Nduna M, Shai N. Intimate partner violence, relationship power inequity, and incidence of HIV infection in young women in South Africa: a cohort study. Lancet. 2010;376(9734):41–8. doi: 10.1016/S0140-6736(10)60548-X 20557928 Krishnan S, Dunbar MS, Minnis AM, Medlin CA, Gerdts CE, Padian NS. Poverty, gender inequities, and women's risk of human immunodeficiency virus/AIDS. Annals of the New York Academy of Sciences. 2008;1136(1):101–10. Stöckl H, Kalra N, Jacobi J, Watts C. Is early sexual debut a risk factor for HIV infection among women in sub‐saharan Africa? A systematic review. American Journal of Reproductive Immunology. 2013;69:27–40. doi: 10.1111/aji.12043 23176109 Hargreaves JR, Bonell CP, Boler T, Boccia D, Birdthistle I, Fletcher A, et al. Systematic review exploring time trends in the association between educational attainment and risk of HIV infection in sub-Saharan Africa. Aids. 2008;22(3):403–14. doi: 10.1097/QAD.0b013e3282f2aac3 18195567 Linton SL, Cooper HL, Luo R, Karnes C, Renneker K, Haley DF, et al. Changing places and partners: associations of neighborhood conditions with sexual network turnover among African American adults relocated from public housing. Archives of sexual behavior. 2017;46(4):925–36. doi: 10.1007/s10508-015-0687-x 26927277 Adimora AA, Schoenbach VJ, Taylor EM, Khan MR, Schwartz RJ, Miller WC. Sex ratio, poverty, and concurrent partnerships among men and women in the United States: a multilevel analysis. Annals of epidemiology. 2013;23(11):716–9. doi: 10.1016/j.annepidem.2013.08.002 24099690 Johnson LF, May MT, Dorrington RE, Cornell M, Boulle A, Egger M, et al. Estimating the impact of antiretroviral treatment on adult mortality trends in South Africa: A mathematical modelling study. PLoS medicine. 2017;14(12):e1002468. doi: 10.1371/journal.pmed.1002468 29232366 Barron P, Pillay Y, Doherty T, Sherman G, Jackson D, Bhardwaj S, et al. Eliminating mother-to-child HIV transmission in South Africa. B World Health Organ. 2013;91:70–4. De Oliveira T, Kharsany AB, Gräf T, Cawood C, Khanyile D, Grobler A, et al. Transmission networks and risk of HIV infection in KwaZulu-Natal, South Africa: a community-wide phylogenetic study. The Lancet HIV. 2017;4(1):e41–e50. doi: 10.1016/S2352-3018(16)30186-2 27914874