244 Prevalence and relative risks of sexually transmitted infections among international migrants globally: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract OP 34: Diseases and Interventions 2, B304 (FCSH), September 5, 2025, 10:15 - 11:15 International migrants are often disproportionately affected by HIV and other blood-borne viruses, particularly in high-income countries. However, evidence regarding the prevalence of sexually transmitted infections (STIs) more broadly among migrants is scattered. This study aimed to synthesise the global evidence on the prevalence of STIs among migrants and specific subgroups and summarise the risk of migrants having STIs compared to non-migrants. We conducted a systematic review and meta-analysis of peer-reviewed literature published since 2014. We searched MEDLINE, Embase, and Ovid Global Health without language limitations. The primary outcome was the prevalence of STIs namely chlamydia, gonorrhoea, syphilis, genital warts, genital herpes, trichomoniasis, mpox, lymphogranuloma venereum, chancroid and donovanosis, and associated clinical syndromes. We conducted a narrative synthesis of populations studied, study setting, and barriers and facilitators of migrants’ access to sexual health services; and used meta-analysis to calculate the pooled prevalence by infection and relative risk among migrants compared to non-migrant populations. We identified 2,529 records and included 79 studies from 30 countries covering ten infections/conditions. 74 studies were included in the pooled measures of prevalence and 27 in the pooled risk ratio. Of the 27 studies with a comparison group, two thirds reported a higher prevalence of the studied infection in migrants compared to non-migrants. Compared to non-migrants, migrants were twice as likely to have a current syphilis (4 studies, pooled RR = 2.39, 95% CI = 0.13-4.65) or chlamydia infection (8 studies, pooled RR = 2.02, 95% CI = 1.09-2.96) while the risk for gonorrhoea and HSV-2 was similar between groups. While STI prevalence and relative risk among migrants varies by setting, population, study type and infection, there is a clear need to address migrants’ unmet needs for sexual health information and services. This will not only improve health equity but is crucial to addressing the multiple epidemics of STIs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.016 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.054 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".