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. 2025 Nov 20;25:1622. doi: 10.1186/s12879-025-11813-6

Prevalence of genital and anorectal chlamydia trachomatis in Kenya by risk groups: a systematic review and meta-analysis

Aarman Sohaili 1,#, Zoïe Alexiou 1,2,#, Felix Mogaka 3, Victor Ocholla Omollo 3, Servaas A Morré 1,4,5, Pierre P M Thomas 1,✉
PMCID: PMC12632032  PMID: 41266987

Abstract

The epidemiology of Chlamydia trachomatis (CT) in Kenya is not well understood. We conducted a systematic review and meta-analysis of CT prevalence using PubMed, Embase, and Kenyan databases (Jan 2000–June 2024). Included studies had laboratory-confirmed CT and were peer-reviewed. Populations were categorized by sex/gender and STI vulnerability. A random-effects model was used to account for heterogeneity. Of 198 records, 51 studies (32,559 participants) were included. CT prevalence was reported for 18 studies on males, 36 on females, and four on the general population. Pooled prevalence was 5.8% (95% CI 4.6–7.4) with high heterogeneity. The highest prevalence was among general population females > 25 years (14.8%), while at risk males > 25 had the lowest (0.1%). Studies spanned 13 regions, with Nairobi, Kisumu, and Mombasa most represented. CT prevalence in Kenya aligns with WHO estimates for Africa. High prevalence among general population women > 25 challenges traditional STI risk assumptions. Importantly, the association between HIV and CT was not uniform across populations, suggesting that relying solely on HIV-focused platforms may overlook groups with a substantial CT burden. Addressing diagnostic gaps, urban–rural disparities, and links with HIV care is critical.

Trial registration CRD42024567235

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-025-11813-6.

Keywords: Chlamydia trachomatis, HIV, Systematic review, Kenya, Diagnostics, Sexually transmitted infection, Prevalence

Background

Chlamydia trachomatis (CT) is one of the most prevalent treatable sexually transmitted infections (STIs) globally, with over 128.5 million new cases occurring in 2020 [1]. Despite being curable, effective control and early detection of CT infections are often hampered by their predominantly asymptomatic nature and, in many settings, by limited resources for testing [2]. Untreated infections can lead to serious reproductive health complications, including pelvic inflammatory disease, ectopic pregnancy, and infertility in women, as well as epididymitis in men [3]. These health consequences underscore the urgent need for effective tools to enable timely identification and treatment of CT infections, particularly in resource-limited settings like Kenya.

Historically, STI control has been sidelined in health policy agendas, but the 2030 Agenda [4] for Sustainable Development seeks to rectify this by fostering integrated approaches to STI prevention and control. The WHO’s Global Health Sector Strategy on STIs [5] advocates for universal access to sexual and reproductive health services and rights, emphasizing the importance of understanding the STI epidemic to drive advocacy, political commitment, and effective resource mobilization [5].

The Kenya Ministry of Health National Reproductive Health Policy (2022–2032) emphasizes the goal of reducing the burden of Reproductive Tract Infections (RTIs) and increasing access to high-quality sexual and reproductive health services (SRHS) needs [6]. However, the policy only broadly addresses RTIs without specifying diseases like CT. Additionally, the policy predominantly focuses on human immunodeficiency virus (HIV) [7], while other STIs receive significantly less attention and funding. Socio-cultural sensitivities and limited research compound the lack of robust epidemiological data on CT in Kenya [8]. Currently, no systematic reviews or meta-analyses assess the prevalence of CT in the country [9]. Existing studies in Sub-Saharan Africa (SSA) primarily focus on females and do not differentiate between risk groups, limiting our understanding of the true disease burden.

Our systematic review and meta-analysis aimed to assess the prevalence of genital and anorectal CT infections across various population groups in Kenya. By evaluating epidemiological data, the study seeks to fill knowledge gaps and inform policy on SRHR, guiding effective public health strategies. This paper marks the first comprehensive attempt to systematically review the literature on CT and risk groups in the Kenyan context.

Methods

The protocol for this study was registered in PROSPERO, the International Prospective Register of Systematic Reviews (CRD42024567235). The current study was carried out as per the protocol, with some minor deviations in stratifications due to the lack of necessary detailed information from publications for the planned stratified analyses.

This study followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist in writing and reporting this systematic review [10].

This study conducted a systematic review and meta-analysis to assess the prevalence of genital and anorectal CT in Kenya by population sub-groups.

Populations were defined prior by sex/gender (males, females, and general) and vulnerability to STI (At risk vs. general). The definitions for at risk are shown below and based on Smolak et al. (2019) [3] and adapted to the local setting;

General populations (at low risk): these are individuals with a lower vulnerability to CT infection, such as sexually active youth and adults, antenatal clinic attendees, and pregnant women.

At risk populations: these are individuals with a higher vulnerability to CT due to specific sexual behaviors, limited access to healthcare services or stigma. This category comprises female sex workers, men who have sex with men (MSM), male sex workers and transgender persons.

Search strategy

This study searched electronic databases such as Medline via PubMed, Embase and the Kenya Medical Research Institute (KEMRI) repositories. The following terms and Boolean operators were used: (Chlamydia trachomatis ORc trachomatis OR Chlamydia OR genital Chlamydia OR anal chlamydia OR rectal chlamydia OR anorectal chlamydia [Full-text]) AND Kenya [Title/Abstract] AND (prevalence OR incidence OR occurrence OR fraction OR epidemiology [Full-text]).

Eligibility criteria

This study reviewed the titles and abstracts of all references to efficiently manage the screening process and eliminate duplicates. This initial screening identified articles potentially relevant to our research question for further full-text examination. Each selected article was individually assessed by the authors to determine its alignment with the inclusion criteria. To ensure the comprehensive identification of relevant studies, we employed a 'reverse snowballing' technique.

Studies were included if they met the following criteria:

  1. The population tested and described laboratory techniques for detecting CT or typing confirmed positive samples.

  2. They were original research studies published in peer-reviewed journals, including randomized controlled trials, prospective and retrospective cohort studies, case–control studies, and cross-sectional studies.

  3. Publication of the study from the 1 st of January 2000 until the 1 st of June 2024. The 25-year period was chosen to capture recent trends while ensuring that no records were overlooked due to the scarcity of data.

Exclusion criteria:

  1. Geographical location does not focus on Kenya

  2. Dissertations, conference abstracts, policy papers and laboratory protocols

  3. Serology and microscopy were used to assess prevalence.

  4. Studies with individuals younger than 15 years old

  5. Studies with less than 20 participants

Data extraction and bias assessment

The extracted data was systematically taken from the full-text articles and organized into a chart. This chart included key details such as the study title, evaluation location, study size and population which is further divided into population subgroups, testing methods, types of samples tested, HIV status, age and prevalence rates of CT. These data categories were initially established and then refined throughout the review process to ensure comprehensive data capture.

The quality and potential bias of the included articles were evaluated using the JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data (appendix 1). This checklist consisted of nine questions related to the methodological quality of the studies and how effectively they address bias in their design, conduct, and analysis. Each question can be answered with "yes," "no," or "unclear." To qualify for inclusion, a study must receive at least six "yes" responses. In Table 1, JBI critical checklist score was included for each paper with the following labels indicating the quality of the paper; All "yes" responses (9/9): Excellent, All but one "yes" (8/9): Good, All but two "yes" (7/9): Fair, All but three "yes" (6/9): Moderate.

Table 1.

Overview of articles included in the main analysis. (Attached file in supplementary documents with working references)

Authors JBI Quality Publication Year Total Sample CT Prevalence Location Study Design Population subgroup Median Age (Age range) Diagnostics Specimen tested HIV status and Prevalence* PrEP status
Fonck et al. [11] Excellent 2000 621 9% Nairobi Cross-sectional Female general population 24* (15–52) NAAT (Abbott Realtime CT/NG) Endocervical Yes (22%) No
Fonck et al. [12] Excellent 2000 520 4% Nairobi Cross-sectional Female general population 24* (14–49) NAAT (Abbott Realtime CT/NG) Endocervical Yes (29%) No
Kohli et al. [13] Fair 2013 300 6% Nairobi Cross-sectional Female general population 31 (18–45) Rapid POC (Chlamydia Rapid Test®) Vaginal No No
Jesper et al. [14] Good 2014 170 3.5% Mombasa Cross-sectional Female general population 22 (16–35) NAAT (Abbott Realtime CT/NG) Endocervical No No
Kinuthia et al. [15] Excellent 2015 1300 5.6% Western Kenya Cohort Female general population 22 (19–27) NAAT (APTIMA COMBO 2 assay) Vaginal Yes (1.9%) Yes
Unger et al. [16] Fair 2015 51 12% Nyanza Cohort Female general population 22 (20–27) NAAT (APTIMA COMBO2 assay) Endocervical No No
Kerubo et al. [17] Fair 2016 511 3% Siaya Cross-sectional Female general population 15* (14–17) NAAT (In-house) Endocervical No No
Maina et al. [18] Good 2016 249 13% Nairobi Cross-sectional Female general population 37 (18–49) NAAT (GenoQuick CT) Endocervical No No
Masha et al. [19] 2017 202 14.9% Kilifi Cross-sectional Female general population 26 (18–45) NAAT (GeneXpert CT/NG assay) Urine Yes (6.4%) No
Masese et al. [20] Good 2017 451 3.6% Mombasa Cross-sectional Female general population 18 (15–24) NAAT (Hologic Aptima Detection System) Urine No No
Oliver et al. [21] Good 2018 457 4.6% Kisumu Cross-sectional Female general population 25 (18–34) NAAT (COBAS Amplicor) Endocervical Yes (14.7%) No
Warr et al. [22] Good 2018 1218 5% Nyanza Cohort Female general population 22 (19–27) NAAT (APTIMA COMBO2 assay) Vaginal No No
Yuh et al. [9] Good 2020 373 11% Nairobi Cohort Female general population 18 (16–20) NAAT (COBAS Amplicor) Endocervical No No
Mehta et al. [23] Good 2021 436 6.2% Siaya cohort Female general population 17 (16–18) NAAT (GeneXpert CT/NG aasay) Vaginal Yes (1.4%) Yes
Heffron et al. [24] Good 2021 198 18.2% Thika and 51Kisumu Mixed methods Female general population 21 (19–22) NAAT (Aptima Genprobe or GeneXpert) Urine No Yes
Omollo et al. [25] Good 2021 40 22.5% Kisumu Cohort Female general population 20 (19–22) NAAT (APTIMA COMBO2 assay) Urine Yes No
Grabert el al. [26] Good 2022 399 6.7% Mombasa Cohort Female general population 39 (19–66) NAAT (APTIMA COMBO 2 assay) Endocervical Yes (48%) No
Celum et al. [27] Good 2022 1000 17.2% Kisumu Cross-sectional Female general population 21 (18–30) NAAT (In-house) Endocervical Yes (4%) Yes
Oware et al. [28] Excellent 2023 448 14.1% Kisumu RCT Female general population 24 (18–30) NAAT (GeneXpert CT/NG assay) Endocervical and Vaginal No Yes
Omosa-Manyonyi et al. [29] Good 2023 813 12.5% Nairobi Cross-sectional Female general population 29* (18–50) NAAT (Real time Multiplex) Urine No No
Mogaka et al. [30] Excellent 2024 1276 5.5% Baringo Cohort Female general population 22 (19–27) NAAT (APTIMA COMBO 2 assay) Endocervical No No
Mehta et al. [31] Good 2007 2743 4.6% Kisumu Cross-sectional Male general population 20 (18–24) NAAT(Amplicor) Urine No No
Kwena et al. [32] Good 2010 250 3.2% Kisumu Cross-sectional Male general population 27 (18–65) NAAT (APTIMA COMBO2 assay) Urine Yes (26%) No
Smith et al. [33] Excellent 2010 2661 4.7% Kisumu Cohort Male general population 20 (17–28) NAAT (Roche) Urine No No
Mehta et al. [34] Good 2012 526 1.3% Kisumu Cohort Male general population 20 (18–24) NAAT(Amplicor) Urine and Urethral No No
Auvert et al. [35] Good 2001 1378 M = 765, F = 613 M = 2.6%F = 4.6% Kisumu Cross-sectional Mixed general population m = 28* (15–49) f = 28* (17–48) NAAT (Roche Diagnostic system) Urine Yes (21.1%) No
Fonck et al. [36] Good 2002 487 6% Nairobi Cohort Mixed general population 28 (16–75) NAAT (Amplicor) Urine Yes (3.9%) No
Hawken et al. [37] Excellent 2002 1497 m = 748, f = 749 M = 1.1%F = 1.9% Mombasa Cross-sectional Mixed general population m = 28* (15–49) f = 27* (18–32) NAAT (Amplicor) Urine Yes (10.8%) No
Otieno et al. [38] Good 2015 846 m = 422, f = 424 M = 2.8%F = 2.8% Kisumu Cohort Mixed general population m = 22 (18–34) f = 22 (18–34) NAAT (COBAS AMPLICOR) Endocervical and urine No No
Winston et al. [39] Good 2015 200, m = 119, f = 81 M = 3% F = 16% Eldoret Cross-sectional Mixed general population M = 15 (12–21) F = 18 (15–22) NAAT(In-house) Urine, vaginal and anorectal Yes (6%) No
Behling et al. [40] Good 2015 394 1.8% Eldoret Cross-sectional Mixed general population 20 (18–22) NAAT (In-house) Urine Yes (0.5%) No
Maina et al. [41] Good 2021 297, m = 148, f = 149 F = 21.6%M = 12.1% Nairobi Cross-sectional Mixed general population m = 32* (18–49) f = 29* (20–34) NAAT(Multiplex) Endocervical and urine Yes (3%) No
Hawken et al. [42] Excellent 2002 503 4.2% Mombasa Review Female at risk 30 (15–65) NAAT(Amplicor) Urine Yes (30.6%) No
Kaul et al. [43] Excellent 2004 466 9.2% Nairobi Cohort Female at risk 28* (18–50) NAAT(Amplicor) Endocervical Yes (28.2%) No
Cohen et al. [44] Good 2007 296 8% Nairobi Cohort Female at risk 24* (18–35) NAAT (Amplicor) Endocervical Yes (30%) No
Musyoki et al. [45] Excellent 2014 596 2.7% Nairobi Cross-sectional Female at risk 30 (25–32) NAAT (Roche Amplicor CT/NG test) Urine Yes (29.5%) No
Gomih-Alakija at el. [46] Excellent 2014 349 3.7% Nairobi Cohort Female at risk 28 (18–48) NAAT (APTIMA COMBO 2 assay) Endocervical Yes (24%) No
Vielot et al. [47] Excellent 2015 173 6.4% Nairobi Cohort Female at risk 27 (18–49) NAAT (APTIMA COMBO 2 assay) Endocervical No No
Lockhart et al. [48] Excellent 2019 346 3.7% Nairobi Cohort Female at risk 28 (18–50) NAAT (APTIMA COMBO2 assay) Endocervical Yes (23.9%) No
Beksinska et al. [49] Good 2021 1003 5.7% Nairobi Cross-sectional Female at risk 33* (19–45) NAAT (GeneXpert CT/NG assay) Urine Yes (28.0%) No
Sanders et al. [50] Excellent 2013 85 1.4% Mombasa Cohort Males at risk 26 (18–35) NAAT (APTIMA COMBO 2 assay) Rectal Yes (8.6%) No
Sanders et al. [51] Good 2015 43 1.4% coastal Cohort Males at risk 26 (22–32) NAAT (APTIMA COMBO2 assay) Urine Yes (40.1%) No
Ngetsa et al. [52] Fair 2020 104 13.5% Kilifi Cohort Males at risk 36 (18–49) NAAT (GenoXpert CT/NG Assay) Anorectal Yes (34.6%) No
Otieno et al. [38] Good 2020 619 9.9% Kisumu Cohort Males at risk 23 (18–54) NAAT (COBAS Amplicor) Anorectal Yes (10.6%) No
Ravindran et al. [53] Good 2021 1241 5.4% Bondo Cohort Males at risk 22 (19–27) NAAT (APTIMA COMBO2 assay) Endocervical Yes (0.8%) No
Mehta et al. [54] Good 2021 155 7.7% Kisumu Cohort Males at risk 24 (20–51) NAAT (GeneXpert CT/NG assay) Urine and rectal No No
D Smith et al. [55] Good 2021 592 6.4% Nairobi Cross-sectional Males at risk 41 (19–62) NAAT(GeneXpert CT/NG aasay) Urine Yes (30.2%) No
Mwaniki et al. [56] Good 2023 248 58.7% Nairobi Cross-sectional Males at risk 21 (18–30) NAAT (Rotor-Gene Q Thermocycler) Urine and rectal Yes (8.3%) Yes
Buve et al. [57] Good 2001 1496 3.7% Kisumu Cross-sectional Mixed at risk 28* (15–49) NAAT(Amplicor) Urine Yes No
Singa et al. [58] Excellent 2012 1661 F = 1063, M = 598

M = 0%

F = 0.3%

 Multi-site Cohort Mixed at risk m = 40 (18–77) f = 35 (20–56) NAAT (APTIMA COMBO 2 assay) Urine and Vaginal Yes F = (63.9%) M = (100%) No
Tun et al. [59] Excellent 2015 269 4.2% Nairobi Cross-sectional Mixed at risk 31 (15–35) NAAT (Roche Amplicor CT/NG test) Urine and Vaginal Yes (18.7%) No
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Two independent reviewers assessed the articles. Any disagreements were discussed, and if a consensus could not be reached, a third reviewer was consulted. Only studies deemed to be of sufficient quality were included in the systematic review and meta-analysis.

Study characteristics

Characteristics of the studies were described to explore key determinants of CT prevalence, such as age, geographical area, study design and information including year of publication, design, sampling methods, sample size, and diagnostic techniques (e.g., specimen type, assay type). Factors related to bias and study design were described. If a study included more than two anatomical specimen types, overall prevalence was taken for CT. We also extracted available information on HIV prevalence and PrEP (Pre-exposure Prophylaxis) status.

Statistical analysis

Data from the included studies was synthesized using RStudio (Version 1.3.959) and the Meta package. A Freeman-Tukey type arcsine square-root transformation was first applied to stabilize variances of prevalence measures. Measures were then weighted using the inverse-variance method. Due to expected heterogeneity in CT prevalence arising from variations in settings, diagnostic technologies, years of data collection, and behavioral factors, derSimonian-Laird random-effects models were employed for the estimates. This model assumes that the true effect sizes vary between studies and is used to account for this variability, providing more generalizable estimates.

An initial overview of all included studies was provided. Subsequently, a forest plot displayed the prevalence (%) for each study with 95% confidence intervals, the sample size of each study, and overall estimates stratified by key group. A requirement for the subgroup analysis was availability of at least 5 studies per subgroup.

We also explored the relationship between HIV prevalence and chlamydia prevalence across studies using log–log scatter plots. Pearson correlation coefficients (r) were calculated for each population subgroup, and results were visualized with regression lines and subgroup-specific legends.

Heterogeneity was assessed using the I2 statistic, which indicates the percentage of total variation due to heterogeneity rather than chance. Heterogeneity levels were categorized as low (below 25%), medium (25–75%), and high (above 75%). Publication bias was assessed using the Egger test for estimates from over 10 studies, with P < 0.05 indicating significance.

Subgroup analysis

We performed a subgroup analysis by age. The majority of included studies reported the median age of participants. In instances where the median age was unavailable, the mean age was utilized instead, as highlighted in Table 1. Participants were categorized into two age groups: those with a median age below 25 years and those with a median age of 25 years or older.

Geographical mapping and data comparison

To contextualize the need for further research in areas with limited study representation, geographical maps were created to visualize the locations where prevalence estimates are available. These maps also allow for a comparison with existing data on population density (persons per Sq. Km) from the Kenya National Bureau of Statistics [11] and HIV testing (percentage of women or men receiving an HIV test and receiving test results in the last 12 months) from the Demographic and Health Surveys (DHS) [12].

Results

Literature search

The search strategy resulted in the identification of 198 records, which led to 120 articles after removing duplicates (Fig. 1). Following a review of titles and abstracts, 120 articles were fully assessed for eligibility, culminating in 54 articles. Out of the 54 studies included, 51 were deemed to meet quality criteria (Fig. 1), that included aggregated data from a total of 32,559 participants for the systematic review and meta-analysis. For further details on the quality assessment, please refer to the appendix 1.

Fig. 1.

Fig. 1

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PRISMA flow chart presenting the steps for study selection from the databases

Among these studies, 18 reported male prevalence (12,069 participants), 36 female prevalence (17,844 participants), and some included both genders (2,646 participants). Four studies provided general population data (2,646 participants). Additionally, 32 studies distinguished between general risk populations (23,843) and at risk populations (8,716) (Table 1).

The review included studies from different regions in Kenya (Nairobi = 18, Kisumu = 14, Mombasa = 6, Eldoret = 2, Kilifi = 2, Nyanza = 2, Siaya = 2, Baringo = 1, Bondo = 1, Coastal = 1, Thika = 1, multi-site = 1 and Western Kenya = 1).

Study characteristics

Five studies included participants on PrEP and 43 studies included participants with HIV, while eight studies utilized point-of-care diagnostic tests. Specimen types varied significantly across studies, with only 3 studies including anorectal samples. Studies that included participants with and without HIV or PrEP did not provide separate chlamydia prevalence estimates based on HIV or PrEP use status. Subgroup analysis by characteristics beyond gender and at risk was not possible due to small subgroups (Table 1).

CT prevalence estimates

The pooled prevalence of CT (Table 2) in females general population, based on 27 studies, was estimated to be 7.1% (95% CI, 5.5%–9.2%) with an I2 statistic of 94%.The pooled prevalence of CT in females at risk, based on 13 studies, was estimated to be 5.1% (95% CI, 3.2%–8.1%) with an I2 statistic of 91%. The pooled prevalence of CT in the mixed general population, based on 4 studies, was estimated to be 3.6% (95% CI, 2.4%–5.2%) with an I2 statistic of 68%. The pooled prevalence of CT (Fig. 2) in males at risk, based on 9 studies, was estimated to be 8.2% (95% CI, 2.8%–21.8%). The heterogeneity across the studies was high, with an I2 statistic of 98%. Notable outliers include Mwaniki et al., which reported a much higher prevalence of 57.3% (95% CI, 50.3%–63.5%), and Singa et al., which reported no cases of CT, with a prevalence of 0.0% (95% CI, 0.0%–0.6%). These outliers contribute significantly to the observed heterogeneity in the meta-analysis. The pooled prevalence of CT in males in the general population, based on 9 studies, was estimated to be 3.2% (95% CI, 1.7%–5.9%) with an I2 statistic of 93%.

Table 2.

Number of studies, cases and pooled CT prevalence presented by sex/gender (males, females, and mixed) combined with vulnerability for STIs (general population vs. at risk)

Group No. Studies Cases/Population Pooled proportion 95% CI I2 [95%CI]
Overall 62* 2235/36119 0.0583 [0.0459; 0.0738] 95.4% [94.7%; 96.0%]
Female general population 27 1046/14978 0.071 [0.0545; 0.0916] 93.8% [92.1; 95.2]
Female at risk 13 395/6426 0.051 [0.0317; 0.0807] 91.1% [86.7; 94.1]
Mixed general population 4 99/2646 0.036 [0.0245;0.0517] 67.7% [6.0;88.9]
Male general population 9 341/8384 0.032 [0.0175; 0.0589] 93.2% [89.3;95.7]
Male at risk 9 354/3685 0.082 [0.0280;0.2180] 97.9% [97.1;98.5]
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The number of studies reported does not align due to the separation between male and female populations in the analysis. Pooled prevalence estimates were derived using the DerSimonian–Laird random-effects model

CT Chlamydia Trachomatis

Fig. 2.

Fig. 2

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Forest plots for the estimations of CT prevalence in Kenya presented by sex/gender (males, females, and mixed) combined with vulnerability for STIs (general population vs. at risk)

Publication bias

No significant publication bias was detected for females in the general population. However, for females in the at risk, the Egger test yielded a p-value of 0.015, suggesting potential bias (appendix 2). For males and the mixed population this could not be assessed due to the limited number of included studies.

Subgroup analysis

For females, those under 25 in the general population had a prevalence of 5.5% (95% CI, 4.3%–6.9%) from 17 studies. Females over 25 in the at risk group had a prevalence of 4.17% (95% CI, 2.6%–6.3%) from 8 studies, while those over 25 in the general population had a prevalence of 14.9% (95% CI, 10.3%–20.5%) from 9 studies. Among males, those under 25 in at risk had a prevalence of 5.4% (95% CI, 4.2%–6.8%) from 4 studies, and those in the general population had a prevalence of 2.5% (95% CI, 0.5%–7.1%) from 5 studies. Males over 25 in the general population had a prevalence of 2.6% (95% CI, 1.6%–4.0%) from 4 studies, while those in at risk had a prevalence of 0.1% (95% CI, 0.00%–0.6%) from 5 studies (appendix 2) as shown in Table 3.

Table 3.

Pooled prevalence of CT prevalence presented by sex/gender (males, females, and mixed) combined with vulnerability for STIs (general population vs. at risk) and age group (< 25 vs. ≥ 25 years)

Sex/gender Age Group Population Type Number of Studies (N) Prevalence % (95% CI)
Female  < 25 General 17 5.5% (4.3%–6.9%)
Female  ≥ 25 At risk 8 4.17% (2.6%–6.3%)
Female  ≥ 25 General 9 14.9% (10.3%–20.5%)
Male  < 25 At risk 4 5.4% (4.2%–6.8%)
Male  < 25 General 5 2.5% (0.5%–7.1%)
Male  ≥ 25 General 4 2.6% (1.6%–4.0%)
Male  ≥ 25 At risk 5 0.1% (0.00%–0.6%)
Excluded groups (due to fewer than 4 studies):
Female < 25, At risk (1 study)
Mixed < 25, General (1 study)
Mixed ≥ 25, General (3 studies)
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CT Chlamydia Trachomatis

Some groups had fewer than 4 studies and could not be included: females under 25 in at risk group (1 study), mixed general populations under 25 (1 study), and mixed general populations over 25 (3 studies).

Data from 31 studies is shown Fig. 3 with available HIV estimates were included, covering five population subgroups. Correlation between HIV and chlamydia prevalence varied by subgroup: Female general population: r = –0.37, Male general population: r = –0.54, Female at-risk population: r = 0.30, Male at-risk population: r = –0.34, Mixed general population: r = 0.06.

Fig. 3.

Fig. 3

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Association between HIV prevalence and CT prevalence across populations in Kenya. Each color represents a distinct population group. The scatter points show individual study estimates, while the dashed lines illustrate overall trends by group

Geographical mapping and data comparison

Geographical mapping of study locations in relation to HIV testing data and population density are shown in Fig. 4. Studies are concentrated in areas with high population density. For both males and females there is areas with high HIV testing rates without any present studies.

Fig. 4.

Fig. 4

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Geographical mapping of study locations in relation to HIV testing data and population density. Panel (A) shows the percentage of females who received an HIV test in the last 12 months and received the results, compared to study locations. Panel (B) shows the same data for males, while panel (C) displays the total population density (population/km2) in relation to the study locations. (Footnote: Studies without exact location details could not be included for females: multi-site, multi-site, Thika and Kisumu, Western Kenya; and for males: multi-site, coastal)

Discussion

This meta-analysis provides a comprehensive assessment of CT epidemiology in Kenya. This study reviewed 51 studies with a total population of 32,559. Most of the studies were performed in urban settings, with a majority of studies being performed in Nairobi, Kisumu, Mombasa or Eldoret. The results of this study showed an overall prevalence of CT infection at 5.8% (95% CI: 4.6–7.4%). The prevalence was also in line with WHO estimates for the African region (about 5%) [60].

This study found that general population women over 25 years old have the highest STI prevalence at 14.85% (95% CI: 10.25–20.52%), which is higher than that found among reproductive age women in sub-Saharan Africa (7.8%) [61]. Moreover, this finding was also higher than compared to 4.17% (95% CI: 2.6–6.31%) among traditionally recognized at risk. These findings challenge the assumption that conventional at risk populations fully represent Kenya’s STI burden [62]. Successful interventions, such as the 2018 rollout of PrEP [48], awareness campaigns, and the distribution of male and female condoms, demonstrate progress for these populations [63].

However, the country’s continuing reliance on syndromic management of STIs is burdensome, particularly given the limited sensitivity(42%) and specificity(63%) of the national diagnostic algorithm for detecting Neisseria gonorrhoeae and CT [61]. Although traditional PCR remains the gold standard for CT diagnosis, offering high sensitivity and accuracy, widespread implementation remains constrained by cost, infrastructure demands, and the need for specialized expertise. In a healthcare landscape that is fragmented, heavily donor-dependent, and characterized by limited resources [64]. Cost-effective diagnostic alternatives that can reduce waiting times and treatment delays are urgently needed to prevent severe long-term complications.

Notably, it was found that the association between HIV prevalence and CT prevalence is not uniform across populations. The declining or flat trends in most populations suggest that they may not represent the populations at highest risk for CT. This could reflect the protective effects of ongoing engagement with care, including regular monitoring, prevention counseling, and treatment of co-infections [64]. By contrast, the upward CT trend observed in some cohorts may reflect behavioral risk compensation or increased detection through more frequent testing [41]. These findings support the idea that while integrating STI services into HIV care remains important, relying solely on HIV-focused platforms may overlook other groups where the CT burden is substantial [64, 65]. Broader community-based screening and prevention strategies may therefore be necessary to reach individuals who are not engaged in HIV care but remain at high risk for bacterial STIs [41, 55].

A key finding from this study is the notably high pooled prevalence of STIs among men in the at risk group (8.2%, 95% CI: 2.8–21.8%). For example, Mwaniki et al. (2023) [56] reported that among 248 tertiary student MSM in Nairobi, Kenya, 58.8% were infected with anorectal or urogenital CT. These figures reflect the high prevalence of STIs specifically in men who engage in same-sex behaviors, which is consistent with global trends in MSM populations [66]. In Kenya, their vulnerability is further intensified by criminalization, stigma, and discrimination, barriers that severely restrict access to prevention, screening, and treatment services. Moreover, many MSM maintain relationships with both men and women to preserve social acceptance, effectively acting as a “bridging” population in STI transmission [66]. Targeting MSM populations with tailored interventions is therefore critical not only for improving their health outcomes but also for the overall population health.

Most of the studies and testing efforts were concentrated in Kenya’s major urban centers, nearly 75% took place in Nairobi, Kisumu, and Mombasa. This suggests a strong research focus on these high-density areas and possibly better access to SRHS services in urban settings. Additionally, 38 studies employed true commercial PCR-based testing, indicating that Kenya, especially in urban settings, has diagnostic capacity. However, this concentration of research does not in itself justify allocating a larger share of SRHS resources to these areas. There is no clear evidence that site selection was based on an evidence-driven rationale; rather, it may have been shaped by logistical convenience. As a result, rural and underserved regions—where access to SRHS remains limited or non-existent—are often left out of both research and planning, risking the reinforcement of existing healthcare inequities. This urban–rural divide is further reflected in healthcare delivery across the country, where proximity to major cities and the ability to pay frequently determine access to quality care [64]. Expanding access to affordable STI testing in resource-limited settings is therefore essential to ensure timely, widespread diagnosis which is crucial for initiating early treatment and curbing further transmission within underserved communities [41].

Point-of-care (PoC) diagnostics will be vital in the future, as they can be implemented with limited resources directly at the site of care. This immediacy is crucial for STIs enabling early treatment and reducing the risk of further transmission [67]. However, the successful implementation of PoC diagnostics hinges on a thorough understanding of the local epidemiological landscape, including disease burden and the characteristics of at risk populations. Therefore, this overview will also provide the foundational data needed to inform and optimize PoC strategies in the region.

This systematic review is the first to systematically analyze data on CT prevalence in Kenya by both population and age group. By examining the burden of CT among general and at risk groups and highlighting data from HIV-focused studies, it challenges long standing assumptions about traditional STI risk groups and the idea of syndemic relationship between HIV and CT. Its robust methodology, large and diverse sample, and alignment with WHO benchmarks bolster its credibility, while the insights generated can inform national policy by revealing diagnostic gaps and demonstrating how STI screening can be integrated into existing health programs.

However, the findings must be interpreted with caution due to several limitations. Data quantity and quality varied across regions and populations, with a notable focus on urban areas and female participants, potentially overlooking other at-risk groups. Additionally, differences in CT rates may be influenced by sampling variation and selection bias, as well as potential publication bias from missing studies reporting lower prevalence or smaller, lower-quality studies with extreme results. Furthermore, the use of diverse diagnostic methods could introduce detection bias. The review also excluded grey literature, potentially limiting the completeness of the data and leading to publication bias by omitting findings that did not reach formal publication.

In conclusion, this analysis reveals a substantial, often underestimated burden of CT in Kenya, one that transcends traditional risk groups and highlights critical gaps in surveillance, diagnosis, and care. Persistent urban biases, the surprising prevalence of older general population women, and the heightened vulnerability of MSM populations call for more inclusive, integrated strategies. Emerging point-of-care (POC) diagnostics [68] offer a promising solution, particularly if tested through dedicated pilot studies to assess their feasibility, cost-effectiveness, and operational viability at the community level. Despite challenges such as infrastructural limitations, fragmented healthcare, and out-of-pocket costs, Kenya’s existing laboratory capacity provides a strong foundation for scaling up affordable, accessible STI testing. By prioritizing equitable access, community-focused interventions, and integrated sexual health frameworks, Kenya can strengthen STI surveillance, reduce infection rates, and improve overall reproductive health outcomes.

Supplementary Information

12879_2025_11813_MOESM1_ESM.docx (156.5KB, docx)

Supplementary Material 1: Appendix 1 JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data.

12879_2025_11813_MOESM2_ESM.docx (269.3KB, docx)

Supplementary Material 2: Appendix 2 Working references. Supplementary Figures.

Acknowledgements

Not applicable.

Clinical trial number

Not applicable

Abbreviations

CT

Chlamydia trachomatis

DHS

Demographic and Health Surveys

HIV

Human immunodeficiency Virus

KEMRI

Kenya Medical Research Institute

MSM

Men who have sex with Men

PoC

Point-of-care

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PrEP

Pre-exposure Prophylaxis

RTIs

Reproductive Tract Infections

SRHS

Sexual and Reproductive Health Services

STIs

Sexually Transmitted Infections

SSA

Sub-Saharan Africa

WHO

World Health Organization

Authors’ contributions

A.S.: conceptualization; methodology; validation; writing—original draft; writing—review and editing; formal analysis. Z.A.: conceptualization; methodology; validation; writing—original draft; writing—review and editing; formal analysis; visualization. F.M.: conceptualization; methodology; supervision; writing—review and editing. V.O.O.: conceptualization; methodology; supervision; writing—review and editing. P.P.M.T.: conceptualization; methodology; supervision; writing—review and editing; formal analysis. S.A.M.: conceptualization; validation; supervision; writing- review and editing. All authors have read and agreed to the published version of the manuscript.

Funding

This study received no external funding.

Data availability

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

This study is a systematic review and meta-analysis of previously published data. As such, it did not involve the collection of primary data from human participants and does not require ethical approval or informed consent. All data analyzed were derived from publicly available peer-reviewed articles that had obtained appropriate ethical clearance from their respective institutional review boards or ethics committees. This study was conducted in accordance with the PRISMA guidelines for systematic reviews.

Consent for publication

Not applicable. This study did not involve individual participant data, images, or any other personal details requiring consent for publication.

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Aarman Sohaili and Zoïe Alexiou are shared first authors.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

12879_2025_11813_MOESM1_ESM.docx (156.5KB, docx)

Supplementary Material 1: Appendix 1 JBI Critical Appraisal Checklist for Studies Reporting Prevalence Data.

12879_2025_11813_MOESM2_ESM.docx (269.3KB, docx)

Supplementary Material 2: Appendix 2 Working references. Supplementary Figures.

Data Availability Statement

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

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