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Meta-Analysis
. 2018 Feb 27;15(2):e1002511.
doi: 10.1371/journal.pmed.1002511. eCollection 2018 Feb.

Prevalence of sexually transmitted infections and bacterial vaginosis among women in sub-Saharan Africa: An individual participant data meta-analysis of 18 HIV prevention studies

Elizabeth A Torrone  1 , Charles S Morrison  2 , Pai-Lien Chen  2 , Cynthia Kwok  2 , Suzanna C Francis  3 , Richard J Hayes  3 , Katharine J Looker  4 , Sheena McCormack  5 , Nuala McGrath  6   7   8   9 , Janneke H H M van de Wijgert  10 , Deborah Watson-Jones  11   12 , Nicola Low  13 , Sami L Gottlieb  14 ; STIMA Working Group
Affiliations
Meta-Analysis

Prevalence of sexually transmitted infections and bacterial vaginosis among women in sub-Saharan Africa: An individual participant data meta-analysis of 18 HIV prevention studies

Elizabeth A Torrone et al. PLoS Med. .

Erratum in

Abstract

Background: Estimates of sexually transmitted infection (STI) prevalence are essential for efforts to prevent and control STIs. Few large STI prevalence studies exist, especially for low- and middle-income countries (LMICs). Our primary objective was to estimate the prevalence of chlamydia, gonorrhea, trichomoniasis, syphilis, herpes simplex virus type 2 (HSV-2), and bacterial vaginosis (BV) among women in sub-Saharan Africa by age, region, and population type.

Methods and findings: We analyzed individual-level data from 18 HIV prevention studies (cohort studies and randomized controlled trials; conducted during 1993-2011), representing >37,000 women, that tested participants for ≥1 selected STIs or BV at baseline. We used a 2-stage meta-analysis to combine data. After calculating the proportion of participants with each infection and standard error by study, we used a random-effects model to obtain a summary mean prevalence of each infection and 95% confidence interval (CI) across ages, regions, and population types. Despite substantial study heterogeneity for some STIs/populations, several patterns emerged. Across the three primary region/population groups (South Africa community-based, Southern/Eastern Africa community-based, and Eastern Africa higher-risk), prevalence was higher among 15-24-year-old than 25-49-year-old women for all STIs except HSV-2. In general, higher-risk populations had greater prevalence of gonorrhea and syphilis than clinic/community-based populations. For chlamydia, prevalence among 15-24-year-olds was 10.3% (95% CI: 7.4%, 14.1%; I2 = 75.7%) among women specifically recruited from higher-risk settings for HIV in Eastern Africa and was 15.1% (95% CI: 12.7%, 17.8%; I2 = 82.3%) in South African clinic/community-based populations. Among clinic/community-based populations, prevalence was generally greater in South Africa than in Southern/Eastern Africa for most STIs; for gonorrhea, prevalence among 15-24-year-olds was 4.6% (95% CI: 3.3%, 6.4%; I2 = 82.8%) in South Africa and was 1.7% (95% CI: 1.2%, 2.6%; I2 = 55.2%) in Southern/Eastern Africa. Across the three primary region/population groups, HSV-2 and BV prevalence was high among 25-49-year-olds (ranging from 70% to 83% and 33% to 44%, respectively). The main study limitation is that the data are not from random samples of the target populations.

Conclusions: Combining data from 18 HIV prevention studies, our findings highlight important features of STI/BV epidemiology among sub-Saharan African women. This methodology can be used where routine STI surveillance is limited and offers a new approach to obtaining critical information on STI and BV prevalence in LMICs.

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Conflict of interest statement

I have read the journal's policy and the authors of this manuscript have the following competing interests: RH receives royalties for textbook from Chapman and Hall and occasional attendance fees for serving on the MRC funding committee. KJL received funding from the World Health Organization during the course of this study. NL receives a stipend as a Specialty Consulting Editor for PLOS Medicine, serves on the journal’s editorial board, and served as a Guest Editor on PLOS Medicine's Collection on the Prevention, Diagnosis, and Treatment of Sexually Transmitted Infections. SM reports grants, non-financial support, and other from Gilead Sciences PLC.

Figures

Fig 1
Fig 1. Chlamydia prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 2
Fig 2. Chlamydia prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 3
Fig 3. Gonorrhea prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 4
Fig 4. Gonorrhea prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 5
Fig 5. Syphilis overall prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 6
Fig 6. Syphilis overall prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 7
Fig 7. High-titer syphilis prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 8
Fig 8. High-titer syphilis prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 9
Fig 9. Trichomoniasis prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 10
Fig 10. Trichomoniasis prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 11
Fig 11. Herpes simplex virus type 2 prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 12
Fig 12. Herpes simplex virus type 2 prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 13
Fig 13. Bacterial vaginosis prevalence among 15–24-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples. E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
Fig 14
Fig 14. Bacterial vaginosis prevalence among 25–49-year-olds.
The area of the marker is proportional to the square root of the sample size. Studies with no estimate presented did not meet the inclusion criteria for this infection and age group. Year presented is the median year that baseline data were collected during the study. *Includes studies of HIV-discordant couples.E Africa, Eastern Africa; SA, South Africa; S/E Africa, Southern and Eastern Africa.
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