Variations in sexual network connectivity may explain dramatic variations in sexually transmitted infection prevalence between populations and over time: a selected four-country analysis

Data sources

A search was conducted on PubMed and Google Scholar on 15 February 2020 using the following terms: ‘chlamydia’, ‘gonorrhoea’, ‘HIV’, ‘HSV-2’, ‘syphilis’, ‘concurrency’, 'multiple partnering’, ‘Kenya’, ‘South Africa’, ‘UK’, ‘United Kingdom’, ‘USA’, ‘United States’, ‘men who have sex with men’, “MSM”.

Cross sectional STI data. The incidence and prevalence estimates of chlamydia, gonorrhoea, HIV, HSV-2, syphilis, concurrency and multiple partnering in Kenya, South Africa, the UK, and USA were extracted from published studies, as detailed in Table 1 and Table 2. When two or more studies were found, we favoured data from studies based on nationally representative samples. Where this data was not available other sources were used such as detailed in Table 2. In addition, for the cross-sectional analyses, we limited studies to those based on data from after the year 1990 and favoured the most recent data.

Symptomatic STI: In the case of Kenya and South Africa, we could not find high quality data on STI prevalence, or behaviour reported by sexual orientation. In addition, we could not find reasonable quality data reporting the incidence/prevalence of chlamydia or gonorrhoea by ethnic group in these two countries. As a result, we use the proportion of men reporting urethral discharge as a composite proxy for combined chlamydia plus gonorrhoea incidence per ethnic group^29,30.

Longitudinal syphilis data. We chose syphilis for the evaluation of longitudinal changes in STI prevalence for a number of reasons, including the fact that syphilis surveillance programmes from the four countries have provided reasonable quality estimates of syphilis incidence for the last 60 years and longer – a far longer period than that for which reasonable incidence estimates are available for other STIs⁴⁵. To a large extent, this is related to the fact that relatively accurate serological tests have been available for the diagnosis of syphilis for longer than other STIs and these have been extensively used to diagnose antenatal syphilis^45–47. Antenatal syphilis surveys have been shown to produce reasonable estimates of the prevalence of syphilis in the general population^45–47. For Kenya and South Africa, we used large antenatal syphilis prevalence surveys - national in the case of South Africa and limited to the capital in the case of Kenya (Table 1). For the UK and USA, we used incidence estimates based on national case reporting data (Table 1). In the UK, the sexual orientation of individuals with syphilis was not available for much of this period and thus we follow the example of others who compare the ratio of the incidence in men to that in women as a proxy for the incidence in MSM^1,48,49.

Multiple partners and concurrency. Studies use a wide variety of definitions of multiple partnering and concurrency.

Concurrency: In all the comparisons of ethnic groups, excluding the UK, the prevalence of concurrency was defined as the percentage of men (15–49 years old) who reported having two or more sex partners at the time of the survey. In the UK, concurrency referred to the percentage of men who reported any overlapping sexual relationships in the past year³⁹. In the comparisons of sexual orientations, for the USA, concurrency was defined as the respondent reporting two or more sexual partnerships with overlapping dates in the prior year⁵⁰. As far as the UK was concerned, this referred to the proportion reporting overlapping sexual partnerships at any point in the past 5 years⁵¹.

Multiple partners: For the ethnic group comparisons, the prevalence of multiple partners was defined as the percentage of men (15–49 years old) who reported having two or more sex partners in the last year. In the UK, this variable was not reported by ethnic group. As a result, multiple partnering here refers to the percentage of men who reported one or more new heterosexual relationship in the prior year. For the MSM vs. heterosexual comparisons, this variable referred to the mean lifetime number of sexual partners reported by respondents in the UK (aged 16–74) and the USA (aged 35–39).

These variations in definitions between studies mean it would be inappropriate to compare these variables between studies. Since all the studies we used were limited to specific countries, we only compare subpopulations within each study/country.

Regions vs. ethnic group in Kenya. Many of the national STI surveillance surveys in Kenya do not collect data on ethnic group³¹. There is however a high correlation between region of residence and ethnic group, with large differences in STI incidence and sexual behaviour between regions^5,32. We therefore follow the approach used in previous studies and use region of residence as a proxy for ethnic group^32,54.

Stratification of data by ethnic group:

Each study reported the variables under consideration stratified by ethnic group. We used this data for our analyses.

Statistical analysis

We report the incidence/prevalence of the five STIs, multiple partnering and concurrency by ethnic group (all four countries) and MSM vs. heterosexuals in each country with available data (UK and USA). Where this data is provided, we report 95% confidence intervals. We used the Chi-squared test to assess if there was a difference in incidence/prevalence between the subgroups with the highest and lowest incidence/prevalence values in each country. For continuous variables (lifetime number of partners) the Man-Whitney U test was used. The correlation between the prevalence of the different STIs per subgroup in each country, and between the prevalence of each STI and the two behavioural variables was calculated using Pearson’s correlation. Because of the small sample sizes (between 2 and 8), tests of statistical significance were not performed for these calculations. In the case of UK and USA, the STI data is presented as an estimated incidence per 100 000 per year without reporting the number of cases and the total size of the study populations. As a result, we did not test if the association between the prevalence of each STI and each of the markers of network connectivity is statistically significant. The key differences were however large, which allows substantive inferences to be drawn. Where data was only provided in graphical form, we digitized the data using GetData Graph Digitizer version 2.26. STATA v15.2 was used for all analyses (StataCorp LLC, College Station, TX, USA).

Longitudinal association between network connectivity and syphilis prevalence/incidence

A literature review was performed to evaluate the possible causes of increases and decreases in syphilis incidence in each subpopulation. We used a narrative approach here to evaluate if there was evidence from the literature that increases and decreases in syphilis prevalence were preceded by corresponding changes in markers of network connectivity. The approach adopted was not to perform a systematic review or a quantitative analysis, but rather to assess if there is evidence in the literature that corroborates or refutes the network connectivity hypothesis.

Terminology

Sex, gender, ethnicity and race: Where this was specified, each data source used a slightly different definition of sex, gender, ethnicity and race. Wherever possible, we used the same terms used in these original sources.

Cross sectional analyses

Kenya

Ethnic group

HIV prevalence varied 15-fold between 0.9% (95% confidence interval [CI] 0.3-4%) in the North East and 13.9% (95% CI 11.0-17.9%) in Nyanza (Figure 2; Table 1, Table 4 & Table 7). HSV-2 prevalence varied 5-fold between 15.6% and 76.2% in these same two regions. The prevalence of syphilis varied 5-fold between 0.5% (95% CI 0.2-1.4%) and 2.5% (95% CI 1.8-3.4%) in these same two regions. Likewise, the percentage of men reporting urethral discharge in the prior year varied between 0.0% (95% CI 0.0-0.5%) and 3.5% (95% CI 2.0-5.8%; all P<0.001) in the same two regions. The prevalence/incidence of male urethral discharge, HIV, HSV-2 and syphilis by region were positively correlated with each other (r-0.35 to r-0.77; Figure 2, Table 6).

Figure 2. Incidence/prevalence of HIV, HSV-2, chlamydia, gonorrhoea, syphilis, male urethral discharge (MUD), partner concurrency and multiple partnering (MP) by ethnic group in Kenya, South Africa, the United Kingdom and the United States of America.

For all countries, HIV, HSV-2, male urethral discharge, multiple partners and concurrency prevalence are reported as percentages. The same is true for syphilis in Kenya and South Africa. In the USA and the UK, chlamydia, gonorrhoea and syphilis are reported as cases per 100 000 per year (Point estimates with 95% Confidence Intervals; see Table 1 for sources of data).

The region with the lowest HIV prevalence (the North East) was not included in the behavioural survey that provided our data. Other data sources have however found the rate of multiple partnering in this region to be very low⁵. In our data, the region with the second lowest HIV prevalence (Eastern) had the lowest reported prevalence of multiple partnering (12.2%; 95% CI 7.4-19.5%) and concurrency (6.4%; 95% CI 4.2-9.2%; all P<0.001). Nyanza reported the highest prevalence of multiple partnering (30.6%; 95% CI 23.8-38.3%) and the second highest prevalence of concurrency (18.2%; 95% CI 14.9-21.9%).

With the exception of syphilis, which was negatively associated with concurrency prevalence (r- -0.34), the prevalence of each STI was positively correlated with both the multiple partnering (r-0.38 to r-0.84) and concurrency (r-0.42 to r-0.72) variables.

South Africa

Ethnic group

HIV prevalence varied 40-fold between 0.5% (95% CI 0.3-1.1%) in the White group and 19.9% (95% CI 18.3-21.7%) in the Black group (Figure 2; Table 4). HSV-2 prevalence varied 5-fold from 6.3% to 31.3% between the same groups. The prevalence of syphilis varied 21-fold between 0.4% (95% CI 0.1-0.9%) and 8.3% (95% CI 7.8-8.8%) in these same two groups. Likewise, the percentage of men reporting urethral discharge in the prior year varied 7-fold between 2.0% (95% CI 0.7-3.2%) and 13.2% (95% CI 12.2-14.2%) in the same groups (all P<0.001). The prevalence/incidence of male urethral discharge, HIV, HSV-2 and syphilis by ethnic group were positively correlated with each other (r-0.78 to r-0.98; Figure 2, Table 6).

The Black group reported a 5-fold higher prevalence of concurrency and a 3-fold higher prevalence of multiple partners than the White group (9.2% ,95% CI 7.1-12.0% vs. 2.0%, 95% CI 0.3-12.5% and 16.0%, 95% CI 13.9-18.3% vs. 4.9%, 95% CI 2.1-11.2%, respectively; all P<0.001). The prevalence of each STI was positively correlated with both the multiple partnering (r-0.87 to r-1.00) and concurrency (r-0.85 to r-0.99) variables (Table 6).

USA

Ethnic group

HIV prevalence varied 8-fold between 0.2% (95% CI 0.2-0.2%) in the non-Hispanic White group and 1.7% (95% CI 1.6-1.8%) in the non-Hispanic Black group (Figure 2, Table 4). The incidence of syphilis varied 4-fold between 5 and 24 per 100 000 per year in these same two groups. Likewise, the incidence of chlamydia varied 5-fold and that of gonorrhoea 8-fold between the same groups (all P<0.001). The prevalence/incidence of chlamydia, gonorrhoea, HIV, HSV-2 and syphilis by ethnic group were strongly positively correlated with each other (r-0.97 to r-1.00; Table 6).

The non-Hispanic Black group reported 4-fold higher prevalence of concurrency and a 2-fold higher prevalence of multiple partners than the non-Hispanic Whites group (11.3%, 95% CI 7.5-16.7% vs. 3.1%, 95% CI 2.2-4.3% and 27.1%, 95% CI 23.8-31.4% vs. 15.0%, 95% CI 14.0-16.5%, respectively; all P<0.001). The prevalence of each STI was positively correlated with both the multiple partnering (r-0.94 to r-0.98) and concurrency (r-0.79 to r-0.91) variables.

MSM vs heterosexuals

The prevalence of HIV was 36-fold higher (7.2% vs. 0.2%) and the incidence of syphilis 33-fold higher (233 vs. 7/100 000 per year) in MSM compared to heterosexuals (Table 2 & Table 5, Figure 3). The percent reporting concurrency was 3 times higher in MSM than heterosexuals (31.3% vs. 9.7%). Likewise, the mean number of lifetime partners was 7-times higher (67 vs. 10) in MSM.

Figure 3. Incidence/prevalence of HIV, chlamydia, gonorrhoea, syphilis, partner concurrency and multiple partnering by men who have sex with men (MSM) versus heterosexual men in the United Kingdom and the United States of America.

HIV and partner concurrency prevalence are reported as percentages, multiple partners as the number of lifetime partners and chlamydia, gonorrhoea and syphilis incidence as cases per 100 000 per year (Point estimates with 95% Confidence Intervals; see Table 1 for sources of data).

United Kingdom

Ethnic group

HIV prevalence varied between 2.8% in the Black Caribbean and Black African groups and 0% in the White and Asian groups (Table 4, Figure 2). The incidence of chlamydia varied 11-fold between the Black Caribbean (1540/100 000/year) and Asian (136/100 000/year) groups. Gonorrhoea incidence varied 8-fold between these same groups (840 and 109/100 000/year, respectively). Likewise, the incidence of syphilis varied 4-fold between 71 and 18 per 100 000 per year in these same two groups. The prevalence/incidence of chlamydia, gonorrhoea, HIV and syphilis by ethnic group were positively correlated with each other (r-0.71 to r-0.98; Table 6).

The prevalence of concurrency and multiple partnering were approximately 1.5 to 2.5-fold higher in the Black African and Black Caribbean groups than the Asian and White groups. The prevalence of each STI was positively correlated with both the multiple partnering (r-0.63 to r-0.96) and concurrency (r-0.37 to r-0.91) variables.

MSM vs heterosexuals

The prevalence of HIV was 39-fold higher in MSM outside of London (7.2%) than heterosexual men (0.16%; Table 5, Figure 3). Likewise, the incidence of chlamydia was 12-fold higher (24 vs. 2/100 000/year), gonorrhoea was 68-fold higher (41 vs. 0.6/100 000/year) and syphilis 185-fold higher (74. vs. 0.04/100 000/year) in MSM outside of London than MSW. The incidence of each of these STIs was higher in MSM residing in London. The percentage reporting concurrency was 14 times higher in MSM than heterosexuals (52% vs. 3.8%). Likewise, the mean number of lifetime partners was 8-times higher (111.1 vs. 14.3) in MSM.

Longitudinal analyses

UK and USA. In both the UK and the USA, the incidence of syphilis increased in the 1960s and 1970s but this increase was largely limited to MSM (Figure 1)^1,7,49. The incidence remained fairly stable in heterosexuals. Although quantitative data is very limited from this period, a number of analyses attributed this increased incidence in MSM to behavioural factors, such as increases in rates of partner change^7,49,55,56.

In the early 1980s, incidence plummeted in MSM in both countries^1,7. The AIDS epidemic played a large role in this decline. Individuals most centrally placed in sexual networks were more likely to die from AIDs, which resulted in a fragmentation of sexual networks^7,57. So too reductions in multiple partnering and increases in condom use both served to reduce effective network connectivity^49,58. From around 2000, the incidence of syphilis has been increasing in both countries and this increase has been largely limited to MSM^1,7. A very similar trend has been evident for MSM in the UK for chlamydia and gonorrhoea where reasonable surveillance data is available and is likely the case in the USA where surveillance data is less detailed as regards sexual orientation^1,44. In both countries, numerous lines of evidence suggest that the introduction of effective antiretroviral therapy from 1996 onwards together with other factors resulted in increases in sexual network connectivity, which was in turn responsible for these increases in STI incidence^1,48. Reduced deaths from AIDS, increases in rates of partner change and reductions in condom usage all played a role in this reconstitution of network connectivity^{7,48,58,59–61}.

Kenya and South Africa. The prevalence of antenatal syphilis in both Kenya and South Africa was between 5 and 12% in the pre-HIV period (Figure 4; Table 3 and Table 4). A number of analyses attributed this high prevalence of syphilis to a number of factors that included behaviours that translate into dense sexual networks^45,62,63. Syphilis prevalence declined rapidly following the AIDS epidemic to below 1% in both countries⁶². Similar, contemporaneous declines in diagnoses of cases of syphilis took place in these countries^45,64. Using a range of data sources and study methodologies, a number of analyses have concluded that a combination of connectivity-reducing factors was responsible: reductions in multiple partnering (number of partners and concurrency), delayed sexual debut, increased condom usage and the effect of AIDS mortality removing more centrally placed transmission nodes^{45,62,65–67}.

Figure 4. Prevalence of antenatal syphilis (red circles) and HIV (black squares) in South Africa and Kenya between 1990 and 2012.

Underlying data

All data underlying the results are available as part of the article and no additional source data are required (see Table 1–Table 3 and Table 7).