Understanding dynamics and overlapping epidemiologies of HIV, HSV-2, chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men
Bibliographic Data
| ID | 22088028 |
|---|---|
| Authors | Ryosuke Omori (0000-0002-9635-1459, Hokkaido University, corresponding author), HIAM CHEMAITELLY (0000-0002-8756-6968, Cornell University), Laith J Abu‐raddad (0000-0003-0790-0506, Cornell University, corresponding author) |
| Year | 2024 |
| Volume | 12 |
| Pages | 1335693-1335693 |
| Publication date | 2024-04-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2024.1335693 |
| PMID | 38628844 |
| OpenAlex | W4393443573 |
| Language | EN |
| Citations received | 1 |
| References cited | 41 |
Introduction: We aimed to investigate the overlapping epidemiologies of human immunodeficiency virus (HIV), herpes simplex virus type 2 (HSV-2), chlamydia, gonorrhea, and syphilis in sexual networks of men who have sex with men (MSM), and to explore to what extent the epidemiology of one sexually transmitted infection (STI) relates to or differs from that of another STI. Methods: An individual-based Monte Carlo simulation model was employed to simulate the concurrent transmission of STIs within diverse sexual networks of MSM. The model simulated sexual partnering, birth, death, and STI transmission within each specific sexual network. The model parameters were chosen based on the current knowledge and understanding of the natural history, transmission, and epidemiology of each considered STI. Associations were measured using the Spearman's rank correlation coefficient (SRCC) and maximal information coefficient (MIC). Results: A total of 500 sexual networks were simulated by varying the mean and variance of the number of partners for both short-term and all partnerships, degree correlation, and clustering coefficient. HSV-2 had the highest current infection prevalence across the simulations, followed by HIV, chlamydia, syphilis, and gonorrhea. Threshold and saturation effects emerged in the relationship between STIs across the simulated networks, and all STIs demonstrated moderate to strong associations. The strongest current infection prevalence association was between HIV and gonorrhea, with an SRCC of 0.84 (95% CI: 0.80-0.87) and an MIC of 0.81 (95% CI: 0.74-0.88). The weakest association was between HSV-2 and syphilis, with an SRCC of 0.54 (95% CI: 0.48-0.59) and an MIC of 0.57 (95% CI, 0.49-0.65). Gonorrhea exhibited the strongest associations with the other STIs while syphilis had the weakest associations. Across the simulated networks, proportions of the population with zero, one, two, three, four, and five concurrent STI infections were 48.6, 37.7, 11.1, 2.4, 0.3, and < 0.1%, respectively. For lifetime exposure to these infections, these proportions were 13.6, 21.0, 22.9, 24.3, 13.4, and 4.8%, respectively. Conclusion: STI epidemiologies demonstrate substantial overlap and associations, alongside nuanced differences that shape a unique pattern for each STI. Gonorrhea exhibits an "intermediate STI epidemiology," reflected by the highest average correlation coefficient with other STIs
Biology · Chlamydia · Gonorrhea · Men who have sex with men · Neisseria gonorrhoeae · Syphilis · Telecommunications · Adolescent Sexual and Reproductive Health · Computer Science · Demography · HIV/AIDS Research and Interventions · Medicine · Reproductive tract infections research · Epidemiology · Genetics · Immunology · Internal Medicine
| Citations per year | 1 |
|---|---|
| Citation span | 2026 - 2026 (1) |
| Highly cited | No |