Prevalence and Risk Factors of Genital Chlamydia trachomatis Infection in Sub-Saharan Africa: A Systematic Review from 1990 to 2025

Prevalence and Risk Factors of Genital Chlamydia trachomatis Infection in Sub-Saharan Africa: A Systematic Review from 1990 to 2025 | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review Prevalence and Risk Factors of Genital Chlamydia trachomatis Infection in Sub-Saharan Africa: A Systematic Review from 1990 to 2025 Mamadou Dolo, Bourama Keita, Boulaye Sanogo, Modibo Kouyate, Romain Dena, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8530557/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Genital Chlamydia trachomatis ( C. trachomatis ) infection is one of the most common bacterial sexually transmitted infections (STIs) and remains a major cause of tubal infertility, ectopic pregnancy, and neonatal ocular and respiratory complications. In sub-Saharan Africa (SSA), its prevalence is likely underestimated due to limited surveillance, testing, and access to reliable diagnostic tools. This systematic review analysed data on the prevalence and risk factors of genital chlamydia between 1990 and 2025. Methods The literature search was conducted in accordance with PRISMA recommendations using PubMed/MEDLINE, Web of Science, AJOL, and Google Scholar, in English and French. Of the 754 articles identified, 47 met the inclusion criteria. Target populations included the general population, pregnant women, sex workers, people living with HIV, and infertile women. Results Reported prevalence varied widely depending on study setting and diagnostic method, ranging from 0.7% among pregnant women in Nigeria to over 60% in a hospital-based study in Cameroon. Serological tests generally overestimated prior exposure to C. trachomatis , whereas polymerase chain reaction (PCR) and nucleic acid amplification tests (NAATs) more accurately reflected active infection, with prevalences often below 10%. Identified risk factors included age under 25 years, multiple sexual partners, non-use of condoms, low socioeconomic status, and HIV co-infection. Associations between C. trachomatis infection and tubal infertility were particularly documented in Nigeria, Rwanda, and Cameroon. Conclusion This review highlights a high and likely underestimated burden of C. trachomatis infection in SSA, with significant implications for sexual and reproductive health, particularly among young people. Targeted testing of vulnerable populations, integration of screening into antenatal and HIV programs, and expanded use of molecular diagnostics are essential to improve surveillance and inform health policies. Multicentre studies in under-documented regions are needed to better estimate the true burden and guide interventions. Epidemiology Chlamydia trachomatis sub-Saharan Africa sexually transmitted infection prevalence risk factors Figures Figure 1 Figure 2 1. INTRODUCTION Infection with Chlamydia trachomatis ( C. trachomatis ) is one of the most common curable bacterial sexually transmitted infections (STIs) worldwide and represents a major public health concern because of its substantial impact on sexual and reproductive health [ 1 , 2 ]. Transmission occurs primarily through sexual contact - vaginal, anal, or oral - but vertical transmission from mother to child during childbirth is also well documented [ 3 ]. A defining characteristic of genital chlamydia is its frequently asymptomatic course: a large proportion of infected individuals, both men and women, exhibit no clinical symptoms. This silent nature facilitates ongoing transmission and makes diagnosis highly dependent on routine screening rather than symptom-driven healthcare seeking [ 2 , 3 ]. In the absence of early diagnosis and appropriate treatment, C. trachomatis infection can lead to severe and long-term complications. In women, untreated infection is associated with pelvic inflammatory disease, tubal factor infertility, and ectopic pregnancy, as well as adverse pregnancy outcomes such as preterm birth and low birth weight [ 2 , 3 , 5 ]. Perinatal exposure may result in neonatal conjunctivitis or pneumonia, both of which are largely preventable through maternal screening and treatment during pregnancy [ 3 , 5 ]. In addition, bacterial STIs, including C. trachomatis , have been shown to increase susceptibility to human immunodeficiency virus (HIV) acquisition and to enhance HIV transmission, highlighting the importance of integrated STI and HIV prevention strategies, particularly in high-prevalence settings [ 4 , 6 ]. Globally, the burden of C. trachomatis remains substantial. The World Health Organization (WHO) estimated that approximately 128.5 million new C. trachomatis infections occurred worldwide in 2020, with a global prevalence of 4.0% among women and 2.5% among men (3). More broadly, an estimated 374 million new cases of curable STIs (chlamydia, gonorrhea, syphilis, and trichomoniasis) occur annually, underscoring the scale of the problem and the urgent need to strengthen prevention, testing, and treatment efforts [ 4 ]. Low- and middle-income countries (LMIC), many of which are in SSA, bear a disproportionate share of this burden [ 4 , 7 ]. In this region, available epidemiological data reveal marked heterogeneity in reported prevalence across countries, study populations, and diagnostic methods [ 2 ]. A review by Dubbink et al. in 2018, based on 102 prevalence estimates from 24 African countries, found lower prevalence in community-based surveys (3.9%) compared with primary healthcare settings (6.0%), with even higher rates observed in certain high-risk groups such as sex workers (5.5%) [ 2 ]. These variations reflect differences in population characteristics, healthcare access, and - critically - the diagnostic tools used to detect C. trachomatis infection. Pregnant women represent a particularly vulnerable population in SSA and warrant special attention. Data from antenatal care settings indicate that C. trachomatis prevalence can be substantial, especially in the presence of HIV co-infection (8). Early detection and treatment during pregnancy could significantly reduce neonatal complications and prevent vertical transmission [ 5 , 6 ]. In some settings, prevalences exceeding 10% have been reported among pregnant women or in specialized HIV clinics, with even higher levels observed in high-risk populations such as women with infertility or sex workers [ 5 , 7 ]. The epidemiology of C. trachomatis infection in SSA is shaped by a complex interplay of individual and structural determinants. Individual-level risk factors include young age, multiple sexual partners, early sexual debut, inconsistent or non-use of condoms, and low educational attainment. Structural factors - such as poverty, population mobility, rapid urbanization, gender inequalities, socio-cultural norms limiting negotiation of safer sex, and restricted access to quality health services - further exacerbate vulnerability and hinder effective prevention and control [ 5 , 7 , 9 ]. Accurate diagnosis of genital chlamydia relies primarily on nucleic acid amplification tests (NAATs), which offer high sensitivity and specificity. However, the implementation of these diagnostic methods is constrained in many sub-Saharan African countries by limited laboratory infrastructure, shortages of trained personnel, and unreliable supply chains (10,11). As a result, syndromic management and serological testing - both of which have limited utility for detecting active infection - remain widely used. In response, the WHO recommends strengthening people-centered health services, integrating STI testing into primary healthcare, reproductive health and HIV programs, and expanding access to reliable diagnostic tools, including validated rapid tests where appropriate [ 4 , 11 ]. Although several reviews have examined STIs or specific subpopulations in SSA, few provide a comprehensive synthesis of both prevalence estimates and associated risk factors for genital C. trachomatis infection across diverse populations and over an extended time [ 2 , 6 , 9 ]. Given ongoing diagnostic advances, persistent gaps in surveillance, and evolving international recommendations, an updated and integrated review was needed to better characterize the prevalence estimates and risk factors of C. trachomatis in SSA. In this context, the objective of this systematic review was to compile and critically analyze data published between 1990 and 2025 on the prevalence and risk factors of genital C. trachomatis infection in SSA. The review includes data from the general population, pregnant women, sex workers, and people living with HIV. It was aimed to address gaps in the existing literature and to provide evidence to support the development and adaptation of national and regional strategies for the prevention and control of C. trachomatis infection. 2. METHODOLOGY 2.1. Study Design and Reporting Standards This study is a systematic review of published observational studies conducted to synthesize available evidence on the prevalence and risk factors of genital C. trachomatis infection in SSA from 1990 to 2025. The review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. 2.2. Data Sources and Search Strategy 2.2.1. Data Sources We performed a comprehensive literature search using the following electronic databases: PubMed/MEDLINE, Web of Science, African Journals Online (AJOL), and Google Scholar. We conducted searches for articles published between January 1990 and April 2025, without restriction on countries within sub-Saharan Africa. We developed search terms using combinations of Medical Subject Headings (MeSH) and free-text keywords related to Chlamydia trachomatis , prevalence, risk factors, and geographic location. The search strategy included the following Boolean combinations: 2.2.2. English Search Strategy We used the following search terms (“ Chlamydia trachomatis ” OR “chlamydia infection” OR “genital chlamydia” OR “urogenital chlamydia” OR “sexually transmitted chlamydia” OR “silent infection”) AND (“prevalence” OR “risk factors” OR “epidemiology”) AND (“sub-Saharan Africa” OR “Africa south of the Sahara” OR “West Africa” OR “Central Africa” OR “Southern Africa” OR “Francophone sub-Saharan Africa” OR “Anglophone sub-Saharan Africa”). Our search terms included the names of individual countries in each region in SSA. We used equivalent search terms in French. Reference lists of included articles were also manually screened to identify additional relevant studies. 2.3. Eligibility Criteria 2.3.1. Inclusion Criteria We included studies that met the following criteria: Reported data on the prevalence and/or risk factors of genital C. trachomatis infection; Conducted in one or more countries in SSA; Published in English or French between 1990 and 2025; Employed recognized diagnostic methods, including culture, antigen detection assays, polymerase chain reaction (PCR), or other nucleic acid amplification tests (NAATs); Included one or more of the following populations: general population, pregnant women, adolescents or young adults, sex workers, people living with HIV, or infertile women; Observational study designs (cross-sectional, cohort, or case–control studies). 2.3.2. Exclusion Criteria We did not include the following studies: Narrative reviews, systematic reviews, editorials, letters to the editor, and non-scientific reports; Animal or in vitro experimental studies; Studies without extractable prevalence or risk factor data; Conference abstracts without full-text availability. 2.4. Study Selection Process All identified references were imported into Zotero reference management software, and duplicates were removed. Study selection was conducted in three sequential stages: (i) screening of titles, (ii) screening of abstracts, and (iii) full-text review. Each stage was independently performed by at least two (2) reviewers. Discrepancies were resolved through discussion, and when necessary, by consultation with a third reviewer. Only studies meeting all inclusion criteria after full-text assessment were included in the final review. 2.5. Data Extraction We independently extracted data by two (2) reviewers using a standardized data extraction form. Extracted information included: author(s), year of publication, country, study design, study population, sample size, diagnostic method, prevalence estimates, identified risk factors, and key outcomes related to reproductive health (e.g., infertility or pregnancy outcomes). We resolved any discrepancies in data extraction by consensus. 2.6. Quality Assessment We independently assessed the methodological quality and risk of bias of included studies by two (2) reviewers using an appropriate standardized appraisal tool for observational studies (e.g., Joanna Briggs Institute or Newcastle–Ottawa Scale). We did not include studies based on quality assessment, but we did consider study quality during the interpretation of their findings. 3. RESULTS 3.1 Study Selection We conducted the literature search across PubMed/MEDLINE, Web of Science, Google Scholar, and African Journals Online identified a total of 754 records. After removal of duplicates and initial screening of titles according to the inclusion criteria, 57 articles were retained for abstract review. Following abstract screening, four (4) articles were excluded due to the absence of abstracts and three (3) were excluded for failure to meet the inclusion criteria. Consequently, we assessed 50 articles for full-text eligibility. Of these, one (1) article was excluded due to unavailability of the full text and two were excluded because their full content did not meet the inclusion criteria. In total, 47 studies were included in the final systematic review ( Figure 1 ). 3.2. Geographic Distribution of Included Studies Among the 47 included studies, Nigeria contributed the largest number of articles, accounting for nearly half of all publications (22/47; 46.8%). Cameroon and South Africa each contributed five (5) studies (5/47; 10.6%), followed by Kenya with three studies (3/47; 6.4%). Gabon and Ghana each contributed two (2) studies (2/47; 4.3%). The remaining countries - Benin, Chad, Côte d’Ivoire, Guinea Conakry, Rwanda, Senegal, Tanzania, and Zimbabwe - were each represented by one (1) study (1/47; 2.1%) ( Figure 2 ). This distribution highlights substantial geographic disparities in the availability of published data on genital C. trachomatis infection across SSA, with a concentration of studies in a few countries. 3.2 Characteristics of Included Studies Table 1 summarizes the methodological and geographical characteristics of the 47 studies [12-58] included in this systematic review. The studies demonstrate substantial heterogeneity in terms of study design, populations investigated, biological samples collected, and diagnostic methods used to detect C. trachomatis infection across SSA. A wide range of biological specimens were used, including urine, vaginal, cervical, endocervical, urethral, anal, blood, serum, and plasma samples. Earlier studies, particularly those conducted in the 1990s and early 2000s, predominantly relied on conventional diagnostic approaches such as cell culture, direct immunofluorescence, antigen detection assays, and serological methods (ELISA). Over time, there has been a gradual shift towards more sensitive and specific molecular techniques, including polymerase chain reaction (PCR), real-time PCR (RT-PCR), strand displacement amplification (SDA), and other nucleic acid amplification tests (NAATs), especially in studies published after 2010. Women of reproductive age constituted the most frequently studied population, reflecting the public health importance of genital C. trachomatis infection in relation to reproductive outcomes, pregnancy complications, and infertility. Several studies focused specifically on pregnant women, infertile women, sex workers, or people living with HIV. Although men were less frequently included, a growing number of recent studies have investigated C. trachomatis infection in male populations, using urine, urethral, or anal specimens. Geographically, the distribution of studies was uneven. Nigeria (N=22) accounted for nearly half of all included publications, followed by Cameroon (N=5) and South Africa (N=5). Other countries were represented by only one (1) or two (2) studies. This uneven distribution highlights substantial gaps in published epidemiological data on genital C. trachomatis infection across many countries in SSA. Table 1. Characteristics of Studies Included in the Systematic Review of Genital C. trachomatis infection in SSA (1990 - 2025) Country Author(s), Year Study Design Study Period Study Population Specimen Type Diagnostic Method Ref. Benin Azonbakin et al., 2025 Cross-sectional Mar.–Dec. 2023 Men Urine RT-PCR [12] Cameroon Ngandjio et al., 2003 Not specified May–Jul. 2001 Men and women Cervical, urethral Direct immunofluorescence, PCR (Cobas) [13] Cameroon Shalanyuy et al., 2025 Cross-sectional Feb.–Mar. 2025 Men and women Serum Rapid IgM/IgG cassette test [14] Cameroon Bobga et al., 2025 Cross-sectional Not specified Men and women Serum ELISA (IgG/IgM) [15] Cameroon Sama et al., 2021 Cross-sectional Nov. 2016–Jun. 2017 Women Serum ELISA [16] Cameroon Tadongfack et al., 2021 Analytical cross-sectional Jul.–Sep. 2020 Women Serum ELISA [17] Côte d’Ivoire Bankolé et al., 2001 Cross-sectional Not specified Women Endocervical Cell culture [18] Gabon Djoba Siawaya et al., 2014 Cross-sectional 2007–2013 Men and women Serum ELISA [19] Gabon Massolou Makaya et al., 2025 Retrospective cross-sectional Jan. 2022–Dec. 2024 Women (15–49 years old) Serum, plasma RT-PCR [20] Ghana Nyarko et al., 2014 Cross-sectional Oct. 2005–Mar. 2006 Women (15–49 years old) Endocervical swab PCR [21] Ghana Siemer et al., 2008 Case - control Nov. 2002–Feb. 2003 Women Urine, serum PCR, ELISA [22] Guinea Mamadou et al., 2022 Prospective descriptive Jan.–Dec. 2019 Men Serum ELISA [23] Kenya Mass et al., 2013 Cohort Aug. 2006–Dec. 2010 Female sex workers Endocervical swab NAAT (Aptima GC/CT) [24] Kenya Kohli et al., 2013 Cross-sectional Jul.–Nov. 2010 Sexually active women Vaginal swab Rapid test [25] Kenya Nyakambi et al., 2023 Cross-sectional Jun. 2021 Women Vaginal swab Rapid diagnostic test [26] Nigeria Olamijulo & Olaleye, 2018 Case–control Mar.–Sep. 2012 Fertile and infertile women Serum, endocervical ELISA, antigen test [27] Nigeria Crowell et al., 2018 Cohort Apr. 2014–Jul. 2016 Men Anal swab PCR [28] Nigeria Ikeme et al., 2011 Not specified 2010 Women Serum ELISA [29] Nigeria Ige et al., 2018 Not specified Feb.–Jul. 2013 Women (15–49 years old) Endocervical swab PCR [30] Nigeria Ajani et al., 2019 Cross-sectional Nov. 2017–Jul. 2018 Women Serum ELISA [31] Nigeria Ajani et al., 2018 Cross-sectional Jan.–Nov. 2015 Women Serum, endocervical ELISA, PCR [32] Nigeria Okoror et al., 2007 Not specified Not specified Men & women Blood, genital samples CCFA, Giemsa staining [33] Nigeria Bello et al., 2019 Cross-sectional Jun. 2014–Apr. 2015 Women Endocervical Rapid antigen test [34] Nigeria Nwankwo & Magaji, 2014 Not specified Jun.–Dec. 2012 Men & women Urine, genital swabs Rapid test [35] Nigeria Gal et al., 2018 Not specified Jul.–Sep. 2017 Women Serum ELISA [36] Nigeria Jeremiah et al., 2011 Case–control Sep. 2008–Feb. 2009 Women Serum ELISA [37] Nigeria Tukur et al., 2006 Case–control May–Aug. 2002 Women Endocervical Rapid antigen test [38] Nigeria Legal et al., 2021 Cross-sectional Sep. 2018–Feb. 2019 Women Serum Quantitative ELISA [39] Nigeria Abiodun et al., 2025 Cross-sectional May–Sep. 2021 Women Urine, vaginal NAAT [40] Nigeria Ogedengbe et al., 2020 Analytical cross-sectional Feb.–Oct. 2009 Women Blood IgG immunoassay [41] Nigeria Ajani et al., 2017 Cross-sectional Jan.–Nov. 2015 Women Blood, endocervical PCR [42] Nigeria Odelola & Akadri, 2023 Comparative cross-sectional Mar. 2018–Jul. 2020 Women Serum ELISA [43] Nigeria Akinnibosun & Onyemekeihia, 2018 Not specified Jan.–Mar. 2015 Women Serum ELISA [44] Nigeria Adesiji et al., 2020 Not specified Not specified Women Endocervical Rapid test [45] Nigeria Aliyu et al., 2023 Cross-sectional Jan.–Apr. 2018 Women 15-49 years old Serum ELISA [46] Nigeria Ekpiwre et al., 2020 Cross-sectional Not specified Women Endocervical Rapid test [47] Nigeria Morhason-Bello et al., 2014 Observational Not specified Women Blood IgG immunoassay [48] Rwanda Muvunyi et al., 2012 Not specified Nov. 2007–Mar. 2010 Women Serum, vaginal ELISA, PCR [49] Senegal Sturm-Ramirez et al., 2000 Cohort Jun. 1996–Jan. 1997 Female sex workers Endocervical swab PCR [50] South Africa Wessels et al., 1991 Case - control Not specified Women Endocervical Immunofluorescence [51] South Africa Abbai-Shaik et al., 2016 Pilot study Jun.–Jul. 2015 Men Urine Rapid test, PCR [52] South Africa Mafokwane & Samie, 2016 Not specified Apr.–Nov. 2010 Women Urine RT-PCR [53] South Africa Peters et al., 2021 Prospective cohort Not specified Women Vulvovaginal swab NAAT (CT & LGV) [54] South Africa Odendaal et al., 2006 Cross-sectional Pregnancy (16–23 weeks) Pregnant women Endocervical PCR [55] Tanzania Juliana et al., 2020 Retrospective cohort Mar. 2018–Jan. 2019 Pregnant women Vaginal swab RT-PCR [56] Chad Ossoga et al., 2023 Cross-sectional Oct.–Dec. 2021 Women 15-49 years old Serum Rapid IgG test [57] Zimbabwe Stephen et al., 2017 Cross-sectional Jan.–Apr. 2012 Women Endocervical Rapid test, SDA [58] *“Not specified” indicates insufficient methodological detail in the original publication CT: C. Trachomatis ELISA : Enzyme-Linked Immunosorbent Assay GC : Neisseria gonorrhoeae IgG: Immunoglobulin G, LGV: lymphogranuloma venereum NAAT: nucleic acid amplification test PCR: Polymerase Chain Reaction Ref.: Reference, RT-PCR: Real time – PCR, SDA: strand displacement amplification Reproductive age : 15–49 years old Table 2a presents the prevalence estimates of C. Trachomatis infection reported in the included studies between 1990 and 2025. We observed considerable heterogeneity across countries, populations, and diagnostic methods. Prevalence ranged from less than 1% in studies using antigen-based tests to over 60% in serological studies conducted among women in healthcare settings. Higher prevalences were consistently reported among younger age groups, women with infertility, people living with HIV, and key populations such as sex workers and men who have sex with men. Studies employing molecular diagnostics generally reported lower prevalence estimates than those relying on serological assays. Table 2a . Prevalence of Genital C. trachomatis infection in SSA (1990–2025) Country Author(s), Year Age Range Sample Size Prevalence Estimate Reference Benin Azonbakin et al., 2025 24–61 y.o 90 3.3% (RT-PCR) [12] Cameroon Ngandjio et al., 2003 ≤25 y.o, >25 y.o 1,277 3.8% overall (women 4.0%; men 3.6%) [13] Cameroon Shalanyuy et al., 2025 18–35 y.o 100 7.0% (IgM seropositivity) [14] Cameroon Sama et al., 2021 18–55 y.o 204 62.3% seroprevalence (IgG/IgM) [16] Cameroon Tadongfack et al., 2021 17–66 y.o 154 38.3% seroprevalence [17] Côte d’Ivoire Bankolé et al., 2001 Not reported 1,522 10.8% among symptomatic women [18] Gabon Djoba Siawaya et al., 2014 13–85 y.o 14,667 / 9,542 Temporal variation: −24% (2007–2010), +14% (2011) [19] Gabon Massolou Makaya et al., 2025 21–40 y.o 594 15.8% (95% CI) [20] Ghana Nyarko et al., 2014 ≥17 y.o 186 20.4% prevalence [21] Guinea Mamadou et al., 2022 17–67 y.o 469 25.8% prevalence [23] Kenya Kohli et al., 2013 18–45 y.o 300 6.0% (95% CI 3.3–8.7) [25] Kenya Nyakambi et al., 2023 18–49 y.o 385 7.5% (18–25 yrs: 5.7%) [26] Nigeria Ikeme et al., 2011 20–34 y.o 286 29.4% (highest in 20–24 yrs) [29] Nigeria Ige et al., 2018 15–49 y.o 400 3.5% prevalence [30] Nigeria Ajani et al., 2019 15–45 y.o 145 31.7% seroprevalence [31] Nigeria Ajani et al., 2018 20–40 y.o 150 IgG: 38.7%; PCR: 7.3% [32] Nigeria Okoror et al., 2007 6–45 y.o 565 40.7% culture-positive [33] Nigeria Bello et al., 2019 15–49 y.o 400 3.5% prevalence [34] Nigeria Nwankwo & Magaji, 2014 14–55 y.o 125 9.6% prevalence [35] Nigeria Gal et al., 2018 ≤25–45 y.o 200 9.5% prevalence [36] Nigeria Adesiji et al., 2020 20–45 y.o 140 0.7% (antigen test) [45] Nigeria Aliyu et al., 2023 15–44 y.o 150 6.7% prevalence [46] Nigeria Morhason-Bello et al., 2014 20–44 y.o 132 20.5% prevalence [48] Rwanda Muvunyi et al., 2012 21–45 y.o 615 3.5% overall [49] Senegal Sturm-Ramirez et al., 2000 22–58 y.o 722 28.5%; mostly asymptomatic [50] South Africa Abbai-Shaik et al., 2016 ≥18 y.o 100 10.0% (PCR) [52] South Africa Mafokwane & Samie, 2016 19–72 y.o 243 32.1% overall [53] Tanzania Juliana et al., 2020 16–48 y.o 439 4.6% (95% CI 2.8–6.9) [56] Chad Ossoga et al., 2023 14–70 y.o 168 10.7% prevalence [57] Zimbabwe Stephen et al., 2017 ≥18 yrs 242 5.8% (SDA) [58] *“Not reported” indicates insufficient methodological detail in the original publication CI : Confidence Interval IgG: Immunoglobulin G, IgM: Immunoglobulin M, PCR: Polymerase Chain Reaction RT-PCR: Reverse Transcriptase – PCR, SDA: strand displacement amplification y.o : Years old Table 2b summarizes studies reporting associations between C. trachomatis infection and infertility, HIV infection, or adverse reproductive and pregnancy outcomes between 1990 and 2025. Several studies documented significantly higher prevalence or seropositivity rates among infertile women compared with fertile controls, as well as increased odds of tubal pathology. Elevated prevalence was also reported among people living with HIV and among key populations, including sex workers and men who have sex with men, with some studies noting frequent co-infection with other sexually transmitted infections. Additionally, selected studies identified associations between C. trachomatis infection and adverse pregnancy outcomes, including preterm birth. Table 2b. C. trachomatis Infection Associated with Infertility, HIV infection, and Pregnancy Outcomes in SSA Country Author(s), Year Population Sample size Key Outcomes Ref. Ghana Siemer et al., 2008 Infertile vs fertile women 439 PCR: 1.6–2.4%; IgG: 39% infertile vs 19% controls [22] Kenya Mass et al., 2013 Female sex workers 865 Incidence 5.0/100 PY; 5.9% NG co-infection [24] Nigeria Olamijulo & Olaleye, 2018 Infertile vs fertile women 180 OR CT infection = 4.0; OR tubal infertility = 3.52 [27] Nigeria Crowell et al., 2018 MsM 420 15.7% anorectal CT; 5.2% LGV; frequent HIV co-infection [28] Nigeria Jeremiah et al., 2011 Subfertile vs fertile women 100 IgG: 74% vs 51% (p<0.001) [37] Nigeria Tukur et al., 2006 Infertile vs fertile women 120 38.3% vs 13.3% controls [38] Nigeria Legal et al., 2021 HIV-positive women 273 49.8% CT prevalence; tubal pathology [39] Nigeria Abiodun et al., 2025 Infertile vs fertile women 120 10% vs 1.7% (p=0.057) [40] Nigeria Ogedengbe et al., 2020 HIV-positive vs HIV-negative 120 45.0% vs 43.3% [41] Nigeria Odelola & Akadri, 2023 Infertile vs fertile women 147 63.9% vs 25.2% (p=0.001) [43] Nigeria Akinnibosun & Onyemekeihia, 2018 Infertile women 50 24–52% prevalence [44] Nigeria Ekpiwre et al., 2020 HIV-positive vs HIV-negative 100 4.5% vs 0% [47] Rwanda Muvunyi et al., 2012 Infertile vs fertile women 615 3.3% vs 3.8% [49] South Africa Wessels et al., 1991 Cases vs controls 40 35.9% vs 7.3% [51] South Africa Peters et al., 2021 Women 85 LGV biovar detected [54] South Africa Odendaal et al., 2006 Pregnant women 343 22.2% preterm vs 10.4% term (p=0.037) [55] *“Not specified” indicates insufficient methodological detail in the original publication, CT: C. Trachomatis HIV: Human Immunodeficiency Virus, NG : Neisseria gonorrhoeae IgG: Immunoglobulin G, LGV: lymphogranuloma venereum, MsM: Men who have sex with other Men, NAAT: nucleic acid amplification test, OR : odd ratio, PCR: Polymerase Chain Reaction, PY: Person-year, RT-PCR: Reverse Transcriptase – PCR, SDA: strand displacement amplification. 3.3. Regional Prevalence of C. trachomatis in SSA (1990–2025) 3.3.1. West Africa In Nigeria, reported prevalence estimates of C. trachomatis varied widely, from very low (3.5% [30], 3.5% [34], 0.7% [45], 2% [47]) to very high (29.4% [29], 31.7% [31], IgG 38.7% / PCR 7.3% [32], 40.7% [33]). Prevalence was notably higher among women with infertility or tubal pathology (IgG 74% vs. 51% controls [37], 38.3% vs. 13.3% controls [38], 49.8% [39]). Younger age groups (15 - 29 years old) consistently demonstrated higher prevalence. In Benin, a low prevalence of 3.33% was reported among adults aged 24 - 61 years old by RT-PCR [12], while in Côte d’Ivoire, 10.8% of symptomatic women were infected [18]. In Guinea Conakry, prevalence was 25.8% among participants aged 17–67 years [23], and Senegal recorded 28.5%, largely among asymptomatic women [50]. 3.3.2. Central Africa Cameroon displayed substantial heterogeneity in prevalence estimates. Lower rates were reported (3.78%; females 3.96%, males 3.62% among participants ≤25 years old and >25 years old) [13] and 7% IgM seropositivity in 18–35 years old [14]. Higher rates were observed in 45.7% (IgG 42.5%, IgM 15.4%; peak 28.3% among 18–24 years old) [15], 62.25% IgG/IgM in 18–55 years old [16], and 38.3% in 17 – 66 years old [17]. In Gabon, a 24% decrease in prevalence from 2007 - 2010 followed by a 14% increase in 2011 was reported [19], while 15.82% prevalence among 21 – 40 years old was observed [20]. In Ghana, prevalence was 20.4% among adults ≥17 years old [21], whereas PCR-detected prevalence was low (2.4% vs. 1.6%), with higher seroprevalence in infertile women (IgG 39% vs. 19%; IgA 14% vs. 3%) [22]. 3.3.3. East Africa In Tanzania, prevalence was moderate at 4.6%, with 7.3% of participants presenting co-infections with other STIs [56]. In Chad, a prevalence of 10.7% was reported, with the highest burden observed among individuals aged 25 - 35 years old [57]. In Zimbabwe, a relatively low prevalence of 5.8% was detected using strand displacement amplification (SDA) [58]. In Rwanda, prevalence remained low and stable, with no significant difference between infertile and fertile women (3.3 - 3.8%) [49]. 3.3.4. Southern Africa In South Africa, high prevalence levels were reported, particularly among women, with marked variation according to fertility and pregnancy status. A case–control study reported prevalence rates of 35.9% among cases compared with 7.3% among controls [51]. More recent studies reported 10% prevalence using PCR [52] and an overall prevalence of 32.1%, with higher rates in women (39.2%) than in men (15.5%) [53]. A prospective cohort study identified LGV biovars in approximately 20% of infections [54]. Additionally, a significant association between C. trachomatis infection and adverse pregnancy outcomes was observed, with higher prevalence among women who delivered preterm compared with those delivering at term (22.2% vs. 10.4%, p = 0.037) [55]. Across all regions in SSA, C. trachomatis infection was strongly associated with high-risk sexual behaviors, including multiple sexual partners, inconsistent condom use, and coexisting STIs. Odds ratios (OR = 3.89 and OR = 2.62) highlight the impact of insufficient prevention practices. Limited knowledge about the infection was also identified as an important factor contributing to ongoing transmission ( Table 3 ). 3.4 Risk Factors of C. trachomatis Infection Across the studies included in this review, several demographical, behavioral, and clinical factors were consistently associated with C. trachomatis infection (Table 3). Age emerged as a key determinant, with young women - particularly those under 25 years old - at the highest risk. A 2- to 5-fold increased risk was reported among women aged 15–24 years old, while being single was associated with nearly a fourfold higher risk (OR = 3.83) [20]. Similarly, a cohort study among female sex workers reported an incidence of 27.6 per 100 person-years in women younger than 25 years old, compared with 8.4 and 2.6 per 100 person-years in older age groups, confirming that sexually active young women constitute the primary risk population [24]. Behavioral factors also played a significant role. Multiple sexual partnerships, early sexual debut, and irregular or non-use of condoms were consistently associated with increased infection risk in studies conducted in Cameroon [13,14] and Nigeria [31,34]. In addition, limited knowledge and awareness of sexually transmitted infections contributed to vulnerability, as demonstrated in Cameroon, where low awareness of chlamydia was significantly associated with infection [16]. Clinical and reproductive factors were particularly prominent in Nigeria, where C. trachomatis infection showed a strong association with tubal infertility. OR of 4.0 and 3.52 indicate a robust relationship between infection and infertility, with prevalence among affected women reaching up to 60% in some studies [27,43]. Marital status - including being divorced, married, or single - also modulated risk across multiple settings [35,39]. Co-infections with other sexually transmitted pathogens were frequently reported. A Tanzanian study documented a co-infection prevalence of 7.3%, underscoring the need for integrated STI screening strategies, as chlamydia often occurs alongside other infections [56]. In Chad, the highest prevalence (5.36%) was observed among individuals aged 25 - 35 years old, suggesting that C. trachomatis infection risk may persist beyond adolescence and early adulthood in certain contexts [57]. Overall, the risk of C. trachomatis infection is shaped by a complex interplay of age, marital status, sexual behavior, reproductive health status, and co-existing infections. These findings highlight the need for targeted prevention strategies, routine screening, and comprehensive sexual health education, particularly among young women and populations at risk of infertility or STI co-infection. Table 3: Risk Factors Associated with C. trachomatis Infection in SSA (1990–2025) Country Author / Year Associated Risk Factors Measure (OR / CI / p-value / Prevalence) Reference Cameroon Ngandjio et al., 2003 Non- or irregular condom use (women); history of STI (men) OR = 3.89 (1.15–13.21), p = 0.026; OR = 2.62 (1.16–6.01), p = 0.023 [13] Cameroon Hubert Shalanyuy, 2025 Multiple sexual partners; early sexual activity; risky sexual practices p = 0.005; p = 0.02 [14] Cameroon Sama et al., 2021 Marital status; low knowledge of Chlamydia p = 0.03; p = 0.001 [16] Gabon Massolou Makaya et al., 2025 Age 15–19 years old; age 20–24 years old; single status OR = 2.32 (1.26–4.18), p = 0.004; OR = 4.74 (2.78–8.1), p ≤ 0.001; OR = 3.83 (2.3–6.55), p ≤ 0.001 [20] Kenya Mass et al., 2013 Age <25 years old Incidence 27.6/100 person-years (<25) vs. 8.4 (25–34) and 2.6 (≥35) [24] Nigeria Olamijulo & Olaleye, 2018 Chlamydia infection & tubal infertility OR = 4.0 (1.47–10.88); OR = 3.52 (1.46–8.49) [27] Nigeria Ajani et al., 2019 Age 15–25 years old; non-use of condoms; ≥2 lifetime partners Prevalence 65.2% in 15–25 years old, p < 0.05 [42] Nigeria Bello et al., 2019 Age <29 years old; early sexual debut; marital status High risk (p not specified) [34] Nigeria Nwankwo & Magaji, 2014 Age 20–29 years old; married/divorced vs. single Prevalence 16.7–17.1% (age); divorced 33.3% [35] Nigeria Legal et al., 2021 Tubal pathology (tubal blockage) 66.2% vs. 33.8%, p < 0.05 [39] Nigeria Odelola & Akadri, 2023 Tubal infertility 63.9% vs. 25.2%, p = 0.001 [43] Tanzania Juliana et al., 2020 Co-infections with other pathogens Co-infection prevalence 7.3% [56] Chad Ossoga et al., 2023 Age 25–35 years old Prevalence 5.36% [57] 4. DISCUSSION This review highlights the heterogeneous epidemiology of Chlamydia trachomatis infections across sub-Saharan Africa (SSA), with prevalence estimates ranging from less than 1% to over 60%, depending on the sub-region, population studied, and diagnostic method (Tables 1 – 3 ). Variability reflects not only geographical differences but also methodological heterogeneity, including the use of culture, serology, rapid tests, and molecular methods such as PCR and NAAT. 4.1 Regional Prevalence Patterns 4.1.1. West Africa In West Africa, prevalence estimates vary widely. In Benin, Azonbakin et al. (2025) report 3.3% by RT-PCR among men, with infections linked to sperm abnormalities such as leukocytospermia and necrozoospermia, potentially leading to epididymitis and obstructive infertility [ 12 ]. Côte d’Ivoire shows a prevalence of 10.8% among symptomatic women (Bankolé et al., 2001), lower than in Senegal and Guinea, reflecting differences in diagnostic sensitivity [ 18 , 59 , 60 ]. In Guinea, Mamadou et al. (2022) report 25.8% seroprevalence among 17–67 years old, with approximately one-third showing subfertility associated with sperm abnormalities [ 23 ]. Senegalese sex workers exhibit a high prevalence of 28.5%, with genotypes D and E predominating and many infections being asymptomatic [ 50 , 60 – 62 ]. In Ghana, hospital-based studies show a 20% prevalence overall, with serology indicating 39% IgG positivity among infertile women, while PCR detection remains low, suggesting that many cases represent prior or persistent infections rather than active infection [ 21 , 22 , 63 , 64 ]. Nigeria is the most extensively studied country, displaying substantial heterogeneity. Seroprevalence among women, especially those with tubal infertility, frequently reaches 30–40%, whereas PCR-based studies generally report lower rates but confirm ongoing active transmission [ 37 , 38 , 39 , 43 ]. Some studies report extremely high rates (up to 49.8% in infertile women), while others show very low prevalences (< 1–3.5%), underscoring regional and methodological differences [ 44 – 47 ]. 4.1.2. Central Africa In Cameroon, prevalence ranges from 3.8% among students to over 40% in certain cohorts of women, with genotype E predominating [ 13 , 15 – 17 ]. Gabonese women of childbearing age show 15.8% seroprevalence, with young age (15–24 years old) and single marital status significantly increasing risk [ 19 , 20 ]. Chad reports a prevalence of 10.7% among sexually active adults, highlighting a substantial burden in young adults [ 57 ]. 4.1.3. East Africa Data were more limited but indicated ongoing transmission. In Tanzania, Juliana et al. (2020) report 4.6% prevalence among pregnant women, often occurring as co-infections with other STIs (~ 7.3%). In Kenya, sex workers have a high incidence of 5/100 person-years, whereas prevalence in the general female population is around 6%, mostly asymptomatic [ 24 – 26 ]. Rwanda shows low and stable prevalence (3.3–3.8%) between fertile and infertile women, with serology poorly predictive of tubal pathologies [ 49 ]. 4.1.4. Southern Africa Southern Africa reports some of the highest prevalence rates. In South Africa, nearly 40% of women are infected compared to approximately 15% of men, with high rates among infertile women [ 51 , 53 ]. LGV strains contribute to disease burden; despite effective single-dose azithromycin therapy, reinfections and untreated partners limit overall cure rates [ 54 ]. In Zimbabwe, prevalence among pregnant women is relatively low at 5.8%, highlighting the need for early detection in this group [ 58 ]. 4.2. Risk Factors Demographical and behavioral factors consistently associated with infection include young age, single marital status, multiple sexual partners, early sexual debut, and inconsistent condom use (Tables 2 – 3 ). Studies in Cameroon, Gabon, and Kenya confirm that sexually active young women (< 25 years old) are at highest risk [ 20 , 24 ]. In Nigeria, tubal infertility strongly correlates with infection, with OR of 4.0 and 3.52, and prevalence reaching 60% in affected women [ 27 , 43 ]. Co-infections with other STIs have occurred in approximately 7% of cases, emphasizing the importance of integrated screening [ 56 ]. While young women are typically the main risk group, Chad shows a peak in prevalence among adults aged 25–35 years old [ 57 ]. Other risk factors include socio-economic determinants (low education, low income) and history of STIs, abortion, or ectopic pregnancy. Evidence regarding hormonal contraception and HIV remains inconsistent [ 16 , 24 , 50 , 53 ]. 4.3. Diagnostic Methods Molecular techniques, including PCR and NAAT, are substantially more sensitive than culture or serology for detecting active infections, making them the preferred tools in both clinical and epidemiological settings [ 17 , 22 , 32 , 49 ]. Serology remains valuable for assessing cumulative exposure and risk of tubal sequelae, particularly in infertile women. Rapid tests offer practical advantages in resource-limited settings, though sensitivity varies [ 25 , 52 , 58 ]. Many studies emphasize an integrated approach combining serology and molecular diagnostics to obtain both reliable prevalence estimates and accurate detection of active cases. 4.4. Study Limitations Despite a rigorous methodology and comprehensive search across multiple databases from 1990–2025, this review has several limitations. Relevant publications, particularly from local or unindexed African journals, may have been missed, and restricting the search to English and French may have introduced language bias. The long study period covers substantial changes in diagnostics, health policies, and risk behaviors, complicating longitudinal comparisons. Variations in study populations, definitions, and diagnostic methods, along with heterogeneous study quality, sampling, and incomplete data, limit comparability. The exclusion of grey literature and the lack of formal meta-analysis further constrain the generalizability and statistical precision of the findings, particularly across underrepresented sub-Saharan African regions. 5. CONCLUSION Available data from SSA confirm that C. trachomatis STIs represent a major reproductive health problem, particularly in the occurrence of tubal infertility and male sperm abnormalities. The reported prevalences vary considerably from region to region, ranging from low rates observed in Ghana and some Nigerian cohorts, to intermediate levels in East Africa, to very high values in Southern Africa. These differences reflect both distinct epidemiological realities and notable methodological limitations, related to the heterogeneity of diagnostic techniques, the small sample size and the frequent lack of confirmation by molecular reference tests. In sum, the results highlight that asymptomatic C . trachomatis infections, often misunderstood and underdiagnosed, contribute significantly to the burden of female infertility. STIs, multiple partners and low condom use appear to be recurrent risk factors. However, the diversity of social and cultural contexts, as well as the scarcity of longitudinal studies, limit the scope of the conclusions. 6. RECOMMENDATIONS AND FUTURE DIRECTION Based on the findings of this systematic review, several research and public health priorities are recommended. First, future studies should include a formal meta-analysis of genital Chlamydia trachomatis prevalence in SSA as a whole or in a specific region in SSA, with particular attention to trends before and after the COVID-19 pandemic, to assess potential disruptions in screening and care. Second, standardized multicenter studies and longitudinal cohort designs are needed to better document the natural history of asymptomatic C. trachomatis infection and its long-term consequences, particularly tubal infertility. From a public health perspective, routine screening for C. trachomatis should be strengthened within gynaecology, reproductive health, antenatal, and premarital care services, especially for young women and other high-risk groups. Diagnostic accuracy should be improved through increased use of molecular tests, such as nucleic acid amplification tests, which better detect active infections. In parallel, targeted awareness and education programs should be expanded to inform adolescents and women of reproductive age i.e. 15–49 years old about the reproductive health consequences of untreated chlamydia infection. Finally, the systematic integration of C. trachomatis screening, treatment, and partner management into national sexual and reproductive health policies is essential to sustainably reduce the burden of infection and protect fertility in SSA. Declarations Conflict of Interest : None Funding Statement : This study was funded as part of the Chlamydia Project entitled " Improving the Early Diagnosis of Chlamydia: An Educational Approach for Better Screening and Diagnosis in Mali, Niger, Burkina Faso and Benin " Pfizer Project #94907631 for the Faculty of Pharmacy (FAPH) of the University of Sciences, of the Bamako Technical and Technical Services (USTTB) from January to December 2025. Available data from SSA confirm that C. trachomatis STIs represent a major reproductive health problem, particularly in the occurrence of tubal infertility and male sperm abnormalities. The reported prevalences vary considerably from region to region, ranging from low rates observed in Ghana and some Nigerian cohorts, to intermediate levels in East Africa, to very high values in Southern Africa. 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Available on: https://www.ajol.info/index.php/gmj/article/view/68852 Orroth KK, Korenromp EL, White RG, Changalucha J, De Vlas SJ, Gray RH et al (2003) Comparison of STI prevalences in the populations of the Mwanza, Rakai and Masaka trials: role of selection bias and diagnostic errors. Sex Transm Infect 79(2):98–105 Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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2","display":"","copyAsset":false,"role":"figure","size":90430,"visible":true,"origin":"","legend":"\u003cp\u003eNumber of Selected Articles by Country in SSA\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8530557/v1/84ce335c972c2de7aeabfcba.png"},{"id":100377169,"identity":"9cbb2db4-d953-415a-a69b-c5a47f8e05f5","added_by":"auto","created_at":"2026-01-16 08:47:19","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1869083,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8530557/v1/466612c2-0ed4-429f-ba9d-63f0cac8627c.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003ePrevalence and Risk Factors of Genital \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eChlamydia trachomatis\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e Infection in Sub-Saharan Africa: A Systematic Review from 1990 to 2025\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"1. INTRODUCTION","content":"\u003cp\u003eInfection with \u003cem\u003eChlamydia trachomatis\u003c/em\u003e (\u003cem\u003eC. trachomatis\u003c/em\u003e) is one of the most common curable bacterial sexually transmitted infections (STIs) worldwide and represents a major public health concern because of its substantial impact on sexual and reproductive health [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Transmission occurs primarily through sexual contact - vaginal, anal, or oral - but vertical transmission from mother to child during childbirth is also well documented [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. A defining characteristic of genital chlamydia is its frequently asymptomatic course: a large proportion of infected individuals, both men and women, exhibit no clinical symptoms. This silent nature facilitates ongoing transmission and makes diagnosis highly dependent on routine screening rather than symptom-driven healthcare seeking [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the absence of early diagnosis and appropriate treatment, \u003cem\u003eC. trachomatis\u003c/em\u003e infection can lead to severe and long-term complications. In women, untreated infection is associated with pelvic inflammatory disease, tubal factor infertility, and ectopic pregnancy, as well as adverse pregnancy outcomes such as preterm birth and low birth weight [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Perinatal exposure may result in neonatal conjunctivitis or pneumonia, both of which are largely preventable through maternal screening and treatment during pregnancy [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In addition, bacterial STIs, including \u003cem\u003eC. trachomatis\u003c/em\u003e, have been shown to increase susceptibility to human immunodeficiency virus (HIV) acquisition and to enhance HIV transmission, highlighting the importance of integrated STI and HIV prevention strategies, particularly in high-prevalence settings [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGlobally, the burden of \u003cem\u003eC. trachomatis\u003c/em\u003e remains substantial. The World Health Organization (WHO) estimated that approximately 128.5\u0026nbsp;million new \u003cem\u003eC. trachomatis\u003c/em\u003e infections occurred worldwide in 2020, with a global prevalence of 4.0% among women and 2.5% among men (3). More broadly, an estimated 374\u0026nbsp;million new cases of curable STIs (chlamydia, gonorrhea, syphilis, and trichomoniasis) occur annually, underscoring the scale of the problem and the urgent need to strengthen prevention, testing, and treatment efforts [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eLow- and middle-income countries (LMIC), many of which are in SSA, bear a disproportionate share of this burden [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. In this region, available epidemiological data reveal marked heterogeneity in reported prevalence across countries, study populations, and diagnostic methods [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A review by Dubbink et al. in 2018, based on 102 prevalence estimates from 24 African countries, found lower prevalence in community-based surveys (3.9%) compared with primary healthcare settings (6.0%), with even higher rates observed in certain high-risk groups such as sex workers (5.5%) [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. These variations reflect differences in population characteristics, healthcare access, and - critically - the diagnostic tools used to detect \u003cem\u003eC. trachomatis\u003c/em\u003e infection.\u003c/p\u003e \u003cp\u003ePregnant women represent a particularly vulnerable population in SSA and warrant special attention. Data from antenatal care settings indicate that \u003cem\u003eC. trachomatis\u003c/em\u003e prevalence can be substantial, especially in the presence of HIV co-infection (8). Early detection and treatment during pregnancy could significantly reduce neonatal complications and prevent vertical transmission [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In some settings, prevalences exceeding 10% have been reported among pregnant women or in specialized HIV clinics, with even higher levels observed in high-risk populations such as women with infertility or sex workers [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe epidemiology of \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA is shaped by a complex interplay of individual and structural determinants. Individual-level risk factors include young age, multiple sexual partners, early sexual debut, inconsistent or non-use of condoms, and low educational attainment. Structural factors - such as poverty, population mobility, rapid urbanization, gender inequalities, socio-cultural norms limiting negotiation of safer sex, and restricted access to quality health services - further exacerbate vulnerability and hinder effective prevention and control [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccurate diagnosis of genital chlamydia relies primarily on nucleic acid amplification tests (NAATs), which offer high sensitivity and specificity. However, the implementation of these diagnostic methods is constrained in many sub-Saharan African countries by limited laboratory infrastructure, shortages of trained personnel, and unreliable supply chains (10,11). As a result, syndromic management and serological testing - both of which have limited utility for detecting active infection - remain widely used. In response, the WHO recommends strengthening people-centered health services, integrating STI testing into primary healthcare, reproductive health and HIV programs, and expanding access to reliable diagnostic tools, including validated rapid tests where appropriate [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough several reviews have examined STIs or specific subpopulations in SSA, few provide a comprehensive synthesis of both prevalence estimates and associated risk factors for genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection across diverse populations and over an extended time [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Given ongoing diagnostic advances, persistent gaps in surveillance, and evolving international recommendations, an updated and integrated review was needed to better characterize the prevalence estimates and risk factors of \u003cem\u003eC. trachomatis\u003c/em\u003e in SSA.\u003c/p\u003e \u003cp\u003eIn this context, the objective of this systematic review was to compile and critically analyze data published between 1990 and 2025 on the prevalence and risk factors of genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA. The review includes data from the general population, pregnant women, sex workers, and people living with HIV. It was aimed to address gaps in the existing literature and to provide evidence to support the development and adaptation of national and regional strategies for the prevention and control of \u003cem\u003eC. trachomatis\u003c/em\u003e infection.\u003c/p\u003e"},{"header":"2. METHODOLOGY","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1. Study Design and Reporting Standards\u003c/h2\u003e \u003cp\u003eThis study is a systematic review of published observational studies conducted to synthesize available evidence on the prevalence and risk factors of genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA from 1990 to 2025. The review was conducted and reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data Sources and Search Strategy\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1. Data Sources\u003c/h2\u003e \u003cp\u003eWe performed a comprehensive literature search using the following electronic databases: PubMed/MEDLINE, Web of Science, African Journals Online (AJOL), and Google Scholar. We conducted searches for articles published between January 1990 and April 2025, without restriction on countries within sub-Saharan Africa. We developed search terms using combinations of Medical Subject Headings (MeSH) and free-text keywords related to \u003cem\u003eChlamydia trachomatis\u003c/em\u003e, prevalence, risk factors, and geographic location. The search strategy included the following Boolean combinations:\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2. English Search Strategy\u003c/h2\u003e \u003cp\u003eWe used the following search terms (\u0026ldquo;\u003cem\u003eChlamydia trachomatis\u003c/em\u003e\u0026rdquo; OR \u0026ldquo;chlamydia infection\u0026rdquo; OR \u0026ldquo;genital chlamydia\u0026rdquo; OR \u0026ldquo;urogenital chlamydia\u0026rdquo; OR \u0026ldquo;sexually transmitted chlamydia\u0026rdquo; OR \u0026ldquo;silent infection\u0026rdquo;) AND (\u0026ldquo;prevalence\u0026rdquo; OR \u0026ldquo;risk factors\u0026rdquo; OR \u0026ldquo;epidemiology\u0026rdquo;) AND (\u0026ldquo;sub-Saharan Africa\u0026rdquo; OR \u0026ldquo;Africa south of the Sahara\u0026rdquo; OR \u0026ldquo;West Africa\u0026rdquo; OR \u0026ldquo;Central Africa\u0026rdquo; OR \u0026ldquo;Southern Africa\u0026rdquo; OR \u0026ldquo;Francophone sub-Saharan Africa\u0026rdquo; OR \u0026ldquo;Anglophone sub-Saharan Africa\u0026rdquo;). Our search terms included the names of individual countries in each region in SSA. We used equivalent search terms in French. Reference lists of included articles were also manually screened to identify additional relevant studies.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Eligibility Criteria\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.3.1. Inclusion Criteria\u003c/h2\u003e \u003cp\u003eWe included studies that met the following criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eReported data on the prevalence and/or risk factors of genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eConducted in one or more countries in SSA;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003ePublished in English or French between 1990 and 2025;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eEmployed recognized diagnostic methods, including culture, antigen detection assays, polymerase chain reaction (PCR), or other nucleic acid amplification tests (NAATs);\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncluded one or more of the following populations: general population, pregnant women, adolescents or young adults, sex workers, people living with HIV, or infertile women;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eObservational study designs (cross-sectional, cohort, or case\u0026ndash;control studies).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.3.2. Exclusion Criteria\u003c/h2\u003e \u003cp\u003eWe did not include the following studies:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eNarrative reviews, systematic reviews, editorials, letters to the editor, and non-scientific reports;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAnimal or in vitro experimental studies;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eStudies without extractable prevalence or risk factor data;\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eConference abstracts without full-text availability.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Study Selection Process\u003c/h2\u003e \u003cp\u003eAll identified references were imported into Zotero reference management software, and duplicates were removed. Study selection was conducted in three sequential stages: (i) screening of titles, (ii) screening of abstracts, and (iii) full-text review. Each stage was independently performed by at least two (2) reviewers. Discrepancies were resolved through discussion, and when necessary, by consultation with a third reviewer. Only studies meeting all inclusion criteria after full-text assessment were included in the final review.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e2.5. Data Extraction\u003c/h2\u003e \u003cp\u003eWe independently extracted data by two (2) reviewers using a standardized data extraction form. Extracted information included: author(s), year of publication, country, study design, study population, sample size, diagnostic method, prevalence estimates, identified risk factors, and key outcomes related to reproductive health (e.g., infertility or pregnancy outcomes). We resolved any discrepancies in data extraction by consensus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.6. Quality Assessment\u003c/h2\u003e \u003cp\u003eWe independently assessed the methodological quality and risk of bias of included studies by two (2) reviewers using an appropriate standardized appraisal tool for observational studies (e.g., Joanna Briggs Institute or Newcastle\u0026ndash;Ottawa Scale). We did not include studies based on quality assessment, but we did consider study quality during the interpretation of their findings.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. RESULTS","content":"\u003cp\u003e\u003cstrong\u003e3.1 Study\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSelection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted the literature search across PubMed/MEDLINE, Web of Science, Google Scholar, and African Journals Online identified a total of 754 records. After removal of duplicates and initial screening of titles according to the inclusion criteria, 57 articles were retained for abstract review. Following abstract screening, four (4) articles were excluded due to the absence of abstracts and three (3) were excluded for failure to meet the inclusion criteria. Consequently, we assessed 50 articles for full-text eligibility. Of these, one (1) article was excluded due to unavailability of the full text and two were excluded because their full content did not meet the inclusion criteria. In total, 47 studies were included in the final systematic review (\u003cstrong\u003eFigure 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2. Geographic Distribution of Included Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 47 included studies, Nigeria contributed the largest number of articles, accounting for nearly half of all publications (22/47; 46.8%). Cameroon and South Africa each contributed five (5) studies (5/47; 10.6%), followed by Kenya with three studies (3/47; 6.4%). Gabon and Ghana each contributed two (2) studies (2/47; 4.3%). The remaining countries - Benin, Chad, C\u0026ocirc;te d\u0026rsquo;Ivoire, Guinea Conakry, Rwanda, Senegal, Tanzania, and Zimbabwe - were each represented by one (1) study (1/47; 2.1%) (\u003cstrong\u003eFigure 2\u003c/strong\u003e). This distribution highlights substantial geographic disparities in the availability of published data on genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection across SSA, with a concentration of studies in a few countries.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Characteristics of Included Studies\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e summarizes the methodological and geographical characteristics of the 47 studies [12-58] included in this systematic review. The studies demonstrate substantial heterogeneity in terms of study design, populations investigated, biological samples collected, and diagnostic methods used to detect \u003cem\u003eC. trachomatis\u003c/em\u003e infection across SSA.\u003c/p\u003e\n\u003cp\u003eA wide range of biological specimens were used, including urine, vaginal, cervical, endocervical, urethral, anal, blood, serum, and plasma samples. Earlier studies, particularly those conducted in the 1990s and early 2000s, predominantly relied on conventional diagnostic approaches such as cell culture, direct immunofluorescence, antigen detection assays, and serological methods (ELISA). Over time, there has been a gradual shift towards more sensitive and specific molecular techniques, including polymerase chain reaction (PCR), real-time PCR (RT-PCR), strand displacement amplification (SDA), and other nucleic acid amplification tests (NAATs), especially in studies published after 2010.\u003c/p\u003e\n\u003cp\u003eWomen of reproductive age constituted the most frequently studied population, reflecting the public health importance of genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection in relation to reproductive outcomes, pregnancy complications, and infertility. Several studies focused specifically on pregnant women, infertile women, sex workers, or people living with HIV. Although men were less frequently included, a growing number of recent studies have investigated \u003cem\u003eC. trachomatis\u003c/em\u003e infection in male populations, using urine, urethral, or anal specimens.\u003c/p\u003e\n\u003cp\u003eGeographically, the distribution of studies was uneven. Nigeria (N=22) accounted for nearly half of all included publications, followed by Cameroon (N=5) and South Africa (N=5). Other countries were represented by only one (1) or two (2) studies. This uneven distribution highlights substantial gaps in published epidemiological data on genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection across many countries in SSA.\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\" width=\"888\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\" style=\"width: 884px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Characteristics of Studies Included in the Systematic Review of Genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA (1990 - 2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor(s), Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Period\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecimen Type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDiagnostic Method\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eRef.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eBenin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAzonbakin et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMar.\u0026ndash;Dec. 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRT-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[12]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eNgandjio et al., 2003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMay\u0026ndash;Jul. 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen and women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eCervical, urethral\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eDirect immunofluorescence, PCR (Cobas)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[13]\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eShalanyuy et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFeb.\u0026ndash;Mar. 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen and women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid IgM/IgG cassette test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[14]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eBobga et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen and women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA (IgG/IgM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[15]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eSama et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNov. 2016\u0026ndash;Jun. 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eTadongfack et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAnalytical cross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJul.\u0026ndash;Sep. 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[17]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eC\u0026ocirc;te d\u0026rsquo;Ivoire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eBankol\u0026eacute; et al., 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eCell culture\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[18]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eDjoba Siawaya et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2007\u0026ndash;2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen and women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMassolou Makaya et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eRetrospective cross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan. 2022\u0026ndash;Dec. 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen (15\u0026ndash;49 years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum, plasma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRT-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[20]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGhana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eNyarko et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eOct. 2005\u0026ndash;Mar. 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen (15\u0026ndash;49 years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[21]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGhana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eSiemer et al., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCase - control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNov. 2002\u0026ndash;Feb. 2003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine, serum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR, ELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[22]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eGuinea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMamadou et al., 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eProspective descriptive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Dec. 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[23]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMass et al., 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAug. 2006\u0026ndash;Dec. 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eFemale sex workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNAAT (Aptima GC/CT)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[24]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eKohli et al., 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJul.\u0026ndash;Nov. 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eSexually active women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVaginal swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[25]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eNyakambi et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJun. 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVaginal swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid diagnostic test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[26]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOlamijulo \u0026amp; Olaleye, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCase\u0026ndash;control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMar.\u0026ndash;Sep. 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eFertile and infertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum, endocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA, antigen test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[27]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eCrowell et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eApr. 2014\u0026ndash;Jul. 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eAnal swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[28]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eIkeme et al., 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003e2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[29]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eIge et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFeb.\u0026ndash;Jul. 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen (15\u0026ndash;49 years old)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e[30]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAjani et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNov. 2017\u0026ndash;Jul. 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[31]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAjani et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Nov. 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum, endocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA, PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[32]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOkoror et al., 2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen \u0026amp; women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eBlood, genital samples\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eCCFA, Giemsa staining\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[33]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eBello et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJun. 2014\u0026ndash;Apr. 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid antigen test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[34]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eNwankwo \u0026amp; Magaji, 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJun.\u0026ndash;Dec. 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen \u0026amp; women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine, genital swabs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[35]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eGal et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJul.\u0026ndash;Sep. 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[36]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eJeremiah et al., 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCase\u0026ndash;control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSep. 2008\u0026ndash;Feb. 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[37]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eTukur et al., 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCase\u0026ndash;control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMay\u0026ndash;Aug. 2002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid antigen test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[38]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eLegal et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eSep. 2018\u0026ndash;Feb. 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eQuantitative ELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[39]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAbiodun et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMay\u0026ndash;Sep. 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine, vaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNAAT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[40]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOgedengbe et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eAnalytical cross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eFeb.\u0026ndash;Oct. 2009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eIgG immunoassay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[41]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAjani et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Nov. 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eBlood, endocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[42]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOdelola \u0026amp; Akadri, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eComparative cross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMar. 2018\u0026ndash;Jul. 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAkinnibosun \u0026amp; Onyemekeihia, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Mar. 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[44]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAdesiji et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[45]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAliyu et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Apr. 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen 15-49 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e[46]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eEkpiwre et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[47]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMorhason-Bello et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eObservational\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eBlood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eIgG immunoassay\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[48]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eRwanda\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMuvunyi et al., 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNov. 2007\u0026ndash;Mar. 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum, vaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eELISA, PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[49]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSenegal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eSturm-Ramirez et al., 2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJun. 1996\u0026ndash;Jan. 1997\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eFemale sex workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[50]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eWessels et al., 1991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCase - control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eImmunofluorescence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[51]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eAbbai-Shaik et al., 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003ePilot study\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJun.\u0026ndash;Jul. 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eMen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test, PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[52]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eMafokwane \u0026amp; Samie, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eApr.\u0026ndash;Nov. 2010\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eUrine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRT-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 63px;\"\u003e\n \u003cp\u003e[53]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003ePeters et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eProspective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eNot specified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVulvovaginal swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eNAAT (CT \u0026amp; LGV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e[54]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOdendaal et al., 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003ePregnancy (16\u0026ndash;23 weeks)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003ePregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e[55]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eTanzania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eJuliana et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eRetrospective cohort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eMar. 2018\u0026ndash;Jan. 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003ePregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eVaginal swab\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRT-PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e[56]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eChad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eOssoga et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eOct.\u0026ndash;Dec. 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen 15-49 years old\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eSerum\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid IgG test\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e[57]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 110px;\"\u003e\n \u003cp\u003eZimbabwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003eStephen et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 111px;\"\u003e\n \u003cp\u003eJan.\u0026ndash;Apr. 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 93px;\"\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 104px;\"\u003e\n \u003cp\u003eEndocervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 138px;\"\u003e\n \u003cp\u003eRapid test, SDA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 63px;\"\u003e\n \u003cp\u003e[58]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u0026ldquo;Not specified\u0026rdquo; indicates insufficient methodological detail in the original publication CT: \u003cem\u003eC. Trachomatis\u003c/em\u003e ELISA : Enzyme-Linked Immunosorbent Assay GC : \u003cem\u003eNeisseria gonorrhoeae\u0026nbsp;\u003c/em\u003eIgG: Immunoglobulin G, LGV: lymphogranuloma venereum NAAT: nucleic acid amplification test PCR: Polymerase Chain Reaction Ref.: Reference, RT-PCR: Real time \u0026ndash; PCR, SDA: strand displacement amplification Reproductive age : 15\u0026ndash;49 years old\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2a\u003c/strong\u003e presents the prevalence estimates of \u003cem\u003eC. Trachomatis\u003c/em\u003e infection reported in the included studies between 1990 and 2025. We observed considerable heterogeneity across countries, populations, and diagnostic methods. Prevalence ranged from less than 1% in studies using antigen-based tests to over 60% in serological studies conducted among women in healthcare settings. Higher prevalences were consistently reported among younger age groups, women with infertility, people living with HIV, and key populations such as sex workers and men who have sex with men. Studies employing molecular diagnostics generally reported lower prevalence estimates than those relying on serological assays.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\" width=\"101%\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" style=\"width: 99px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2a\u003c/strong\u003e. Prevalence of Genital \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA (1990\u0026ndash;2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor(s), Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge Range\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample Size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence Estimate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 12px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eReference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eBenin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAzonbakin et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e24\u0026ndash;61 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e3.3% (RT-PCR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[12]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNgandjio et al., 2003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026le;25 y.o, \u0026gt;25 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,277\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e3.8% overall (women 4.0%; men 3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[13]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eShalanyuy et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e18\u0026ndash;35 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e7.0% (IgM seropositivity)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[14]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eSama et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e18\u0026ndash;55 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e62.3% seroprevalence (IgG/IgM)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eTadongfack et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e17\u0026ndash;66 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e38.3% seroprevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[17]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eC\u0026ocirc;te d\u0026rsquo;Ivoire\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eBankol\u0026eacute; et al., 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNot reported\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e1,522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e10.8% among symptomatic women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[18]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eDjoba Siawaya et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e13\u0026ndash;85 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e14,667 / 9,542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eTemporal variation: \u0026minus;24% (2007\u0026ndash;2010), +14% (2011)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[19]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMassolou Makaya et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e21\u0026ndash;40 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e594\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e15.8% (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[20]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eGhana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNyarko et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026ge;17 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e20.4% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[21]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eGuinea\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMamadou et al., 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e17\u0026ndash;67 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e469\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e25.8% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[23]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eKohli et al., 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e18\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e6.0% (95% CI 3.3\u0026ndash;8.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[25]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNyakambi et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e18\u0026ndash;49 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e385\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e7.5% (18\u0026ndash;25 yrs: 5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[26]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eIkeme et al., 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e20\u0026ndash;34 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e29.4% (highest in 20\u0026ndash;24 yrs)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[29]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eIge et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15\u0026ndash;49 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e3.5% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[30]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAjani et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e145\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e31.7% seroprevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[31]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAjani et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e20\u0026ndash;40 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003eIgG: 38.7%; PCR: 7.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[32]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eOkoror et al., 2007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e6\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e565\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e40.7% culture-positive\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[33]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eBello et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15\u0026ndash;49 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e3.5% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[34]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eNwankwo \u0026amp; Magaji, 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e14\u0026ndash;55 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e9.6% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[35]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eGal et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026le;25\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e9.5% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[36]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAdesiji et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e20\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e0.7% (antigen test)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[45]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAliyu et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e15\u0026ndash;44 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e6.7% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[46]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMorhason-Bello et al., 2014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e20\u0026ndash;44 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e132\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e20.5% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[48]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eRwanda\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMuvunyi et al., 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e21\u0026ndash;45 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e3.5% overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[49]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eSenegal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eSturm-Ramirez et al., 2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e22\u0026ndash;58 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e722\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e28.5%; mostly asymptomatic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[50]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eAbbai-Shaik et al., 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026ge;18 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e10.0% (PCR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[52]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eMafokwane \u0026amp; Samie, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e19\u0026ndash;72 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e243\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e32.1% overall\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[53]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eTanzania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eJuliana et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e16\u0026ndash;48 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e4.6% (95% CI 2.8\u0026ndash;6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[56]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eChad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eOssoga et al., 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e14\u0026ndash;70 y.o\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e10.7% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[57]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003eZimbabwe\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 26px;\"\u003e\n \u003cp\u003eStephen et al., 2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\n \u003cp\u003e\u0026ge;18 yrs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e242\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 27px;\"\u003e\n \u003cp\u003e5.8% (SDA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 12px;\"\u003e\n \u003cp\u003e[58]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u0026ldquo;Not reported\u0026rdquo; indicates insufficient methodological detail in the original publication CI : Confidence Interval IgG: Immunoglobulin G, \u0026nbsp;IgM: Immunoglobulin M, \u0026nbsp;PCR: Polymerase Chain Reaction \u0026nbsp;RT-PCR: Reverse Transcriptase \u0026ndash; PCR, SDA: strand displacement amplification y.o : Years old\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2b\u003c/strong\u003e summarizes studies reporting associations between \u003cem\u003eC. trachomatis\u003c/em\u003e infection and infertility, HIV infection, or adverse reproductive and pregnancy outcomes between 1990 and 2025. Several studies documented significantly higher prevalence or seropositivity rates among infertile women compared with fertile controls, as well as increased odds of tubal pathology. Elevated prevalence was also reported among people living with HIV and among key populations, including sex workers and men who have sex with men, with some studies noting frequent co-infection with other sexually transmitted infections. Additionally, selected studies identified associations between \u003cem\u003eC. trachomatis\u003c/em\u003e infection and adverse pregnancy outcomes, including preterm birth.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\" width=\"634\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" style=\"width: 621px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2b. \u003cem\u003eC. trachomatis\u003c/em\u003e Infection Associated with Infertility, HIV infection, and Pregnancy Outcomes in SSA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 8px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor(s), Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePopulation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e\u003cstrong\u003eKey Outcomes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eRef.\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eGhana\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSiemer et al., 2008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e439\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003ePCR: 1.6\u0026ndash;2.4%; IgG: 39% infertile vs 19% controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[22]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMass et al., 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale sex workers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e865\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eIncidence 5.0/100 PY; 5.9% NG co-infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[24]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOlamijulo \u0026amp; Olaleye, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eOR CT infection = 4.0; OR tubal infertility = 3.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[27]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCrowell et al., 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMsM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e420\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e15.7% anorectal CT; 5.2% LGV; frequent HIV co-infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[28]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eJeremiah et al., 2011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSubfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003eIgG: 74% vs 51% (p\u0026lt;0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[37]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eTukur et al., 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e38.3% vs 13.3% controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[38]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eLegal et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIV-positive women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e49.8% CT prevalence; tubal pathology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[39]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAbiodun et al., 2025\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e10% vs 1.7% (p=0.057)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOgedengbe et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIV-positive vs HIV-negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e45.0% vs 43.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[41]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdelola \u0026amp; Akadri, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e63.9% vs 25.2% (p=0.001)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[43]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eAkinnibosun \u0026amp; Onyemekeihia, 2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e24\u0026ndash;52% prevalence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[44]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEkpiwre et al., 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eHIV-positive vs HIV-negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e4.5% vs 0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRwanda\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMuvunyi et al., 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eInfertile vs fertile women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e3.3% vs 3.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[49]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWessels et al., 1991\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCases vs controls\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\"\u003e\n \u003cp\u003e35.9% vs 7.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[51]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePeters et al., 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eWomen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003eLGV biovar detected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\"\u003e\n \u003cp\u003e[54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSouth Africa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eOdendaal et al., 2006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePregnant women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\"\u003e\n \u003cp\u003e22.2% preterm vs 10.4% term (p=0.037)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"5\"\u003e\n \u003cp\u003e[55]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 117px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 92px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 3px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 195px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 9px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 20px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 11px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*\u0026ldquo;Not specified\u0026rdquo; indicates insufficient methodological detail in the original publication, CT: \u003cem\u003eC. Trachomatis\u003c/em\u003e HIV: Human Immunodeficiency Virus, NG : \u003cem\u003eNeisseria gonorrhoeae\u0026nbsp;\u003c/em\u003eIgG: Immunoglobulin G, \u0026nbsp;LGV: lymphogranuloma venereum, \u0026nbsp;MsM: Men who have sex with other Men, NAAT: nucleic acid amplification test, \u0026nbsp;OR : odd ratio, PCR: Polymerase Chain Reaction, \u0026nbsp;PY: Person-year, RT-PCR: Reverse Transcriptase \u0026ndash; PCR, SDA: strand displacement amplification.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3. Regional Prevalence of \u003cem\u003eC. trachomatis\u003c/em\u003e in SSA (1990\u0026ndash;2025)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.1. West\u003c/strong\u003e \u003cstrong\u003eAfrica\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn Nigeria, reported prevalence estimates of \u003cem\u003eC. trachomatis\u003c/em\u003e varied widely, from very low (3.5% [30], 3.5% [34], 0.7% [45], 2% [47]) to very high (29.4% [29], 31.7% [31], IgG 38.7% / PCR 7.3% [32], 40.7% [33]). Prevalence was notably higher among women with infertility or tubal pathology (IgG 74% vs. 51% controls [37], 38.3% vs. 13.3% controls [38], 49.8% [39]). Younger age groups (15 - 29 years old) consistently demonstrated higher prevalence. In Benin, a low prevalence of 3.33% was reported among adults aged 24 - 61 years old by RT-PCR [12], while in C\u0026ocirc;te d\u0026rsquo;Ivoire, 10.8% of symptomatic women were infected [18]. In Guinea Conakry, prevalence was 25.8% among participants aged 17\u0026ndash;67 years [23], and Senegal recorded 28.5%, largely among asymptomatic women [50].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.2. Central Africa\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCameroon displayed substantial heterogeneity in prevalence estimates. Lower rates were reported (3.78%; females 3.96%, males 3.62% among participants \u0026le;25 years old and \u0026gt;25 years old) [13] and 7% IgM seropositivity in 18\u0026ndash;35 years old [14]. Higher rates were observed in 45.7% (IgG 42.5%, IgM 15.4%; peak 28.3% among 18\u0026ndash;24 years old) [15], 62.25% IgG/IgM in 18\u0026ndash;55 years old [16], and 38.3% in 17 \u0026ndash; 66 years old [17]. In Gabon, a 24% decrease in prevalence from 2007 - 2010 followed by a 14% increase in 2011 was reported [19], while 15.82% prevalence among 21 \u0026ndash; 40 years old was observed [20]. In Ghana, prevalence was 20.4% among adults \u0026ge;17 years old [21], whereas PCR-detected prevalence was low (2.4% vs. 1.6%), with higher seroprevalence in infertile women (IgG 39% vs. 19%; IgA 14% vs. 3%) [22].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.3. East Africa\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;In Tanzania, prevalence was moderate at 4.6%, with 7.3% of participants presenting co-infections with other STIs [56]. In Chad, a prevalence of 10.7% was reported, with the highest burden observed among individuals aged 25 - 35 years old [57]. In Zimbabwe, a relatively low prevalence of 5.8% was detected using strand displacement amplification (SDA) [58]. In Rwanda, prevalence remained low and stable, with no significant difference between infertile and fertile women (3.3 - 3.8%) [49].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.4. Southern Africa\u003c/strong\u003e\u003cbr\u003e In South Africa, high prevalence levels were reported, particularly among women, with marked variation according to fertility and pregnancy status. A case\u0026ndash;control study reported prevalence rates of 35.9% among cases compared with 7.3% among controls [51]. More recent studies reported 10% prevalence using PCR [52] and an overall prevalence of 32.1%, with higher rates in women (39.2%) than in men (15.5%) [53]. A prospective cohort study identified LGV biovars in approximately 20% of infections [54]. Additionally, a significant association between \u003cem\u003eC. trachomatis\u003c/em\u003e infection and adverse pregnancy outcomes was observed, with higher prevalence among women who delivered preterm compared with those delivering at term (22.2% vs. 10.4%, p = 0.037) [55].\u003c/p\u003e\n\u003cp\u003eAcross all regions in SSA, \u003cem\u003eC. trachomatis\u003c/em\u003e infection was strongly associated with high-risk sexual behaviors, including multiple sexual partners, inconsistent condom use, and coexisting STIs. Odds ratios (OR = 3.89 and OR = 2.62) highlight the impact of insufficient prevention practices. Limited knowledge about the infection was also identified as an important factor contributing to ongoing transmission (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Risk Factors of \u003cem\u003eC. trachomatis\u003c/em\u003e Infection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAcross the studies included in this review, several demographical, behavioral, and clinical factors were consistently associated with \u003cem\u003eC. trachomatis\u003c/em\u003e infection (Table 3). Age emerged as a key determinant, with young women - particularly those under 25 years old - at the highest risk. A 2- to 5-fold increased risk was reported among women aged 15\u0026ndash;24 years old, while being single was associated with nearly a fourfold higher risk (OR = 3.83) [20]. Similarly, a cohort study among female sex workers reported an incidence of 27.6 per 100 person-years in women younger than 25 years old, compared with 8.4 and 2.6 per 100 person-years in older age groups, confirming that sexually active young women constitute the primary risk population [24].\u003c/p\u003e\n\u003cp\u003eBehavioral factors also played a significant role. Multiple sexual partnerships, early sexual debut, and irregular or non-use of condoms were consistently associated with increased infection risk in studies conducted in Cameroon [13,14] and Nigeria [31,34]. In addition, limited knowledge and awareness of sexually transmitted infections contributed to vulnerability, as demonstrated in Cameroon, where low awareness of chlamydia was significantly associated with infection [16].\u003c/p\u003e\n\u003cp\u003eClinical and reproductive factors were particularly prominent in Nigeria, where \u003cem\u003eC. trachomatis\u003c/em\u003e infection showed a strong association with tubal infertility. OR of 4.0 and 3.52 indicate a robust relationship between infection and infertility, with prevalence among affected women reaching up to 60% in some studies [27,43]. Marital status - including being divorced, married, or single - also modulated risk across multiple settings [35,39].\u003c/p\u003e\n\u003cp\u003eCo-infections with other sexually transmitted pathogens were frequently reported. A Tanzanian study documented a co-infection prevalence of 7.3%, underscoring the need for integrated STI screening strategies, as chlamydia often occurs alongside other infections [56]. In Chad, the highest prevalence (5.36%) was observed among individuals aged 25 - 35 years old, suggesting that \u003cem\u003eC.\u003c/em\u003e \u003cem\u003etrachomatis\u003c/em\u003e infection risk may persist beyond adolescence and early adulthood in certain contexts [57].\u003c/p\u003e\n\u003cp\u003eOverall, the risk of \u003cem\u003eC. trachomatis\u003c/em\u003e infection is shaped by a complex interplay of age, marital status, sexual behavior, reproductive health status, and co-existing infections. These findings highlight the need for targeted prevention strategies, routine screening, and comprehensive sexual health education, particularly among young women and populations at risk of infertility or STI co-infection.\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"3\" cellpadding=\"0\" width=\"951\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" style=\"width: 947px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003eRisk Factors Associated with \u003cem\u003eC. trachomatis\u003c/em\u003e Infection in SSA (1990\u0026ndash;2025)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAuthor / Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAssociated Risk Factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" style=\"width: 410px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasure (OR / CI / p-value / Prevalence) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Reference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eNgandjio et al., 2003\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eNon- or irregular condom use (women);\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ehistory of STI (men)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eOR = 3.89 (1.15\u0026ndash;13.21), p = 0.026; OR = 2.62 (1.16\u0026ndash;6.01), p = 0.023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[13]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eHubert Shalanyuy, 2025\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eMultiple sexual partners; early sexual\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eactivity; risky sexual practices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003ep = 0.005; p = 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[14]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eCameroon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eSama et al., 2021\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eMarital status; low knowledge of Chlamydia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003ep = 0.03; p = 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[16]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eGabon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eMassolou Makaya et al., 2025\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge 15\u0026ndash;19 years old;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eage 20\u0026ndash;24 years old; single status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eOR = 2.32 (1.26\u0026ndash;4.18), p = 0.004; OR = 4.74 (2.78\u0026ndash;8.1), p \u0026le; 0.001; OR = 3.83 (2.3\u0026ndash;6.55), p \u0026le; 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[20]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eKenya\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eMass et al., 2013\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge \u0026lt;25 years old\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eIncidence 27.6/100 person-years (\u0026lt;25) vs. 8.4 (25\u0026ndash;34) and 2.6 (\u0026ge;35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[24]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eOlamijulo \u0026amp; Olaleye, 2018\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eChlamydia infection \u0026amp; tubal infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eOR = 4.0 (1.47\u0026ndash;10.88); OR = 3.52 (1.46\u0026ndash;8.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[27]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eAjani et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge 15\u0026ndash;25 years old; non-use of\u0026nbsp;\u003c/p\u003e\n \u003cp\u003econdoms; \u0026ge;2 lifetime partners\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003ePrevalence 65.2% in 15\u0026ndash;25 years old, p \u0026lt; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[42]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eBello et al., 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge \u0026lt;29 years old; early sexual debut;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003emarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eHigh risk (p not specified)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[34]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eNwankwo \u0026amp; Magaji, 2014\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge 20\u0026ndash;29 years old;\u0026nbsp;\u003c/p\u003e\n \u003cp\u003emarried/divorced vs. single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003ePrevalence 16.7\u0026ndash;17.1% (age); divorced 33.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[35]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eLegal et al., 2021\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eTubal pathology (tubal blockage)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003e66.2% vs. 33.8%, p \u0026lt; 0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[39]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eNigeria\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eOdelola \u0026amp; Akadri, 2023\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eTubal infertility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003e63.9% vs. 25.2%, p = 0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[43]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eTanzania\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eJuliana et al., 2020\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eCo-infections with other pathogens\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003eCo-infection prevalence 7.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[56]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 78px;\"\u003e\n \u003cp\u003eChad\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 201px;\"\u003e\n \u003cp\u003eOssoga et al., 2023\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 253px;\"\u003e\n \u003cp\u003eAge 25\u0026ndash;35 years old\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 316px;\"\u003e\n \u003cp\u003ePrevalence 5.36%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e[57]\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"4. DISCUSSION","content":"\u003cp\u003eThis review highlights the heterogeneous epidemiology of \u003cem\u003eChlamydia trachomatis\u003c/em\u003e infections across sub-Saharan Africa (SSA), with prevalence estimates ranging from less than 1% to over 60%, depending on the sub-region, population studied, and diagnostic method (Tables\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Variability reflects not only geographical differences but also methodological heterogeneity, including the use of culture, serology, rapid tests, and molecular methods such as PCR and NAAT.\u003c/p\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Regional Prevalence Patterns\u003c/h2\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003e4.1.1. West Africa\u003c/h2\u003e \u003cp\u003eIn West Africa, prevalence estimates vary widely. In Benin, Azonbakin et al. (2025) report 3.3% by RT-PCR among men, with infections linked to sperm abnormalities such as leukocytospermia and necrozoospermia, potentially leading to epididymitis and obstructive infertility [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. C\u0026ocirc;te d\u0026rsquo;Ivoire shows a prevalence of 10.8% among symptomatic women (Bankol\u0026eacute; et al., 2001), lower than in Senegal and Guinea, reflecting differences in diagnostic sensitivity [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]. In Guinea, Mamadou et al. (2022) report 25.8% seroprevalence among 17\u0026ndash;67 years old, with approximately one-third showing subfertility associated with sperm abnormalities [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Senegalese sex workers exhibit a high prevalence of 28.5%, with genotypes D and E predominating and many infections being asymptomatic [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. In Ghana, hospital-based studies show a 20% prevalence overall, with serology indicating 39% IgG positivity among infertile women, while PCR detection remains low, suggesting that many cases represent prior or persistent infections rather than active infection [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNigeria is the most extensively studied country, displaying substantial heterogeneity. Seroprevalence among women, especially those with tubal infertility, frequently reaches 30\u0026ndash;40%, whereas PCR-based studies generally report lower rates but confirm ongoing active transmission [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Some studies report extremely high rates (up to 49.8% in infertile women), while others show very low prevalences (\u0026lt;\u0026thinsp;1\u0026ndash;3.5%), underscoring regional and methodological differences [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section3\"\u003e \u003ch2\u003e4.1.2. Central Africa\u003c/h2\u003e \u003cp\u003eIn Cameroon, prevalence ranges from 3.8% among students to over 40% in certain cohorts of women, with genotype E predominating [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Gabonese women of childbearing age show 15.8% seroprevalence, with young age (15\u0026ndash;24 years old) and single marital status significantly increasing risk [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Chad reports a prevalence of 10.7% among sexually active adults, highlighting a substantial burden in young adults [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003e4.1.3. East Africa\u003c/h2\u003e \u003cp\u003eData were more limited but indicated ongoing transmission. In Tanzania, Juliana et al. (2020) report 4.6% prevalence among pregnant women, often occurring as co-infections with other STIs (~\u0026thinsp;7.3%). In Kenya, sex workers have a high incidence of 5/100 person-years, whereas prevalence in the general female population is around 6%, mostly asymptomatic [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Rwanda shows low and stable prevalence (3.3\u0026ndash;3.8%) between fertile and infertile women, with serology poorly predictive of tubal pathologies [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003e4.1.4. Southern Africa\u003c/h2\u003e \u003cp\u003eSouthern Africa reports some of the highest prevalence rates. In South Africa, nearly 40% of women are infected compared to approximately 15% of men, with high rates among infertile women [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. LGV strains contribute to disease burden; despite effective single-dose azithromycin therapy, reinfections and untreated partners limit overall cure rates [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. In Zimbabwe, prevalence among pregnant women is relatively low at 5.8%, highlighting the need for early detection in this group [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Risk Factors\u003c/h2\u003e \u003cp\u003eDemographical and behavioral factors consistently associated with infection include young age, single marital status, multiple sexual partners, early sexual debut, and inconsistent condom use (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Studies in Cameroon, Gabon, and Kenya confirm that sexually active young women (\u0026lt;\u0026thinsp;25 years old) are at highest risk [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. In Nigeria, tubal infertility strongly correlates with infection, with OR of 4.0 and 3.52, and prevalence reaching 60% in affected women [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Co-infections with other STIs have occurred in approximately 7% of cases, emphasizing the importance of integrated screening [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]. While young women are typically the main risk group, Chad shows a peak in prevalence among adults aged 25\u0026ndash;35 years old [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. Other risk factors include socio-economic determinants (low education, low income) and history of STIs, abortion, or ectopic pregnancy. Evidence regarding hormonal contraception and HIV remains inconsistent [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Diagnostic Methods\u003c/h2\u003e \u003cp\u003eMolecular techniques, including PCR and NAAT, are substantially more sensitive than culture or serology for detecting active infections, making them the preferred tools in both clinical and epidemiological settings [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Serology remains valuable for assessing cumulative exposure and risk of tubal sequelae, particularly in infertile women. Rapid tests offer practical advantages in resource-limited settings, though sensitivity varies [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Many studies emphasize an integrated approach combining serology and molecular diagnostics to obtain both reliable prevalence estimates and accurate detection of active cases.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.4. Study Limitations\u003c/h2\u003e \u003cp\u003eDespite a rigorous methodology and comprehensive search across multiple databases from 1990\u0026ndash;2025, this review has several limitations. Relevant publications, particularly from local or unindexed African journals, may have been missed, and restricting the search to English and French may have introduced language bias. The long study period covers substantial changes in diagnostics, health policies, and risk behaviors, complicating longitudinal comparisons. Variations in study populations, definitions, and diagnostic methods, along with heterogeneous study quality, sampling, and incomplete data, limit comparability. The exclusion of grey literature and the lack of formal meta-analysis further constrain the generalizability and statistical precision of the findings, particularly across underrepresented sub-Saharan African regions.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. CONCLUSION","content":"\u003cp\u003eAvailable data from SSA confirm that \u003cem\u003eC. trachomatis\u0026nbsp;\u003c/em\u003eSTIs represent a major reproductive health problem, particularly in the occurrence of tubal infertility and male sperm abnormalities. The reported prevalences vary considerably from region to region, ranging from low rates observed in Ghana and some Nigerian cohorts, to intermediate levels in East Africa, to very high values in Southern Africa. These differences reflect both distinct epidemiological realities and notable methodological limitations, related to the heterogeneity of diagnostic techniques, the small sample size and the frequent lack of confirmation by molecular reference tests. In sum, the results highlight that asymptomatic C\u003cem\u003e. trachomatis\u0026nbsp;\u003c/em\u003einfections, often misunderstood and underdiagnosed, contribute significantly to the burden of female infertility. STIs, multiple partners and low condom use appear to be recurrent risk factors. However, the diversity of social and cultural contexts, as well as the scarcity of longitudinal studies, limit the scope of the conclusions.\u003c/p\u003e"},{"header":"6. RECOMMENDATIONS AND FUTURE DIRECTION","content":"\u003cp\u003eBased on the findings of this systematic review, several research and public health priorities are recommended. First, future studies should include a formal meta-analysis of genital Chlamydia trachomatis prevalence in SSA as a whole or in a specific region in SSA, with particular attention to trends before and after the COVID-19 pandemic, to assess potential disruptions in screening and care. Second, standardized multicenter studies and longitudinal cohort designs are needed to better document the natural history of asymptomatic C. trachomatis infection and its long-term consequences, particularly tubal infertility.\u003c/p\u003e \u003cp\u003eFrom a public health perspective, routine screening for C. trachomatis should be strengthened within gynaecology, reproductive health, antenatal, and premarital care services, especially for young women and other high-risk groups. Diagnostic accuracy should be improved through increased use of molecular tests, such as nucleic acid amplification tests, which better detect active infections. In parallel, targeted awareness and education programs should be expanded to inform adolescents and women of reproductive age i.e. 15\u0026ndash;49 years old about the reproductive health consequences of untreated chlamydia infection. Finally, the systematic integration of \u003cem\u003eC. trachomatis\u003c/em\u003e screening, treatment, and partner management into national sexual and reproductive health policies is essential to sustainably reduce the burden of infection and protect fertility in SSA.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003e \u003cb\u003eConflict of Interest\u003c/b\u003e :\u003c/h2\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding Statement :\u003c/h2\u003e \u003cp\u003eThis study was funded as part of the Chlamydia Project entitled \" \u003cem\u003eImproving the Early Diagnosis of Chlamydia: An Educational Approach for Better Screening and Diagnosis in Mali, Niger, Burkina Faso and Benin\u003c/em\u003e \" Pfizer Project #94907631 for the Faculty of Pharmacy (FAPH) of the University of Sciences, of the Bamako Technical and Technical Services (USTTB) from January to December 2025.\u003c/p\u003e\u003ch2\u003eAvailable data\u003c/h2\u003e \u003cp\u003efrom SSA confirm that \u003cem\u003eC. trachomatis\u003c/em\u003e STIs represent a major reproductive health problem, particularly in the occurrence of tubal infertility and male sperm abnormalities. The reported prevalences vary considerably from region to region, ranging from low rates observed in Ghana and some Nigerian cohorts, to intermediate levels in East Africa, to very high values in Southern Africa. These differences reflect both distinct epidemiological realities and notable methodological limitations, related to the heterogeneity of diagnostic techniques, the small sample size and the frequent lack of confirmation by molecular reference tests. In sum, the results highlight that asymptomatic C. \u003cem\u003etrachomatis\u003c/em\u003e infections, often misunderstood and underdiagnosed, contribute significantly to the burden of female infertility. STIs, multiple partners and low condom use appear to be recurrent risk factors. However, the diversity of social and cultural contexts, as well as the scarcity of longitudinal studies, limit the scope of the conclusions.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdachi K, Nielsen-Saines K, Klausner JD (2016) Chlamydia Infection in Pregnancy: The Global Challenge of Preventing Adverse Pregnancy and Infant Outcomes in Sub-Saharan Africa and Asia. Biomed Res Int 2016(1):9315757\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHussen S, Wachamo D, Yohannes Z, Tadesse E Prevalence of Chlamydia trachomatis infection among women of reproductive age in sub-Saharan Africa: a systematic review and meta-analysis. BMC InfectDis [Internet]. 2018 Dec [cited 2025 Jul 16]; 18(1). 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Sex Transm Infect 79(2):98\u0026ndash;105\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"547c9b06-ca69-4348-a472-8e639862d912","identifier":"10.13039/100004319","name":"Pfizer","awardNumber":"Pfizer Project #94907631","order_by":0}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Pfizer (United States)","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Chlamydia trachomatis, sub-Saharan Africa, sexually transmitted infection, prevalence, risk factors","lastPublishedDoi":"10.21203/rs.3.rs-8530557/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8530557/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGenital \u003cem\u003eChlamydia trachomatis\u003c/em\u003e (\u003cem\u003eC. trachomatis\u003c/em\u003e) infection is one of the most common bacterial sexually transmitted infections (STIs) and remains a major cause of tubal infertility, ectopic pregnancy, and neonatal ocular and respiratory complications. In sub-Saharan Africa (SSA), its prevalence is likely underestimated due to limited surveillance, testing, and access to reliable diagnostic tools. This systematic review analysed data on the prevalence and risk factors of genital chlamydia between 1990 and 2025.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThe literature search was conducted in accordance with PRISMA recommendations using PubMed/MEDLINE, Web of Science, AJOL, and Google Scholar, in English and French. Of the 754 articles identified, 47 met the inclusion criteria. Target populations included the general population, pregnant women, sex workers, people living with HIV, and infertile women.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eReported prevalence varied widely depending on study setting and diagnostic method, ranging from 0.7% among pregnant women in Nigeria to over 60% in a hospital-based study in Cameroon. Serological tests generally overestimated prior exposure to \u003cem\u003eC. trachomatis\u003c/em\u003e, whereas polymerase chain reaction (PCR) and nucleic acid amplification tests (NAATs) more accurately reflected active infection, with prevalences often below 10%. Identified risk factors included age under 25 years, multiple sexual partners, non-use of condoms, low socioeconomic status, and HIV co-infection. Associations between \u003cem\u003eC. trachomatis\u003c/em\u003e infection and tubal infertility were particularly documented in Nigeria, Rwanda, and Cameroon.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis review highlights a high and likely underestimated burden of \u003cem\u003eC. trachomatis\u003c/em\u003e infection in SSA, with significant implications for sexual and reproductive health, particularly among young people. Targeted testing of vulnerable populations, integration of screening into antenatal and HIV programs, and expanded use of molecular diagnostics are essential to improve surveillance and inform health policies. Multicentre studies in under-documented regions are needed to better estimate the true burden and guide interventions.\u003c/p\u003e","manuscriptTitle":"Prevalence and Risk Factors of Genital Chlamydia trachomatis Infection in Sub-Saharan Africa: A Systematic Review from 1990 to 2025","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 06:37:47","doi":"10.21203/rs.3.rs-8530557/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"bee95138-aa38-4adf-9cb2-bf280407640f","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":60675933,"name":"Epidemiology"}],"tags":[],"updatedAt":"2026-01-09T06:37:47+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 06:37:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8530557","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8530557","identity":"rs-8530557","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}