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P252 Predictability of prevalence of sexually transmitted infection on complex sexual network
  1. Ryosuke Omori1,
  2. Laith Abu-Raddad2
  1. 1Hokkaido University, Research Center For Zoonosis Control, Sapporo, Japan
  2. 2Weill Cornell Medicine-Qatar, Doha, Qatar


Background Estimation of epidemic potential of a sexually transmitted infection (STI) is difficult due to difficulty in measuring and quantifying the sexual network and implications for infection transmission. We demonstrate an approach for predicting the epidemic potential of an STI using data on another STI for men who have sex with men.

Methods An individual-based mathematical model was constructed to describe sex partnering and STI concurrent transmission, namely HIV, herpes simplex virus type 2 (HSV-2), gonorrhea, chlamydia, and syphilis. The model was parameterized with representative biological and behavioral data. 500 heterogeneous sexual networks were simulated, on each of which STI transmission was also simulated. Correlations were assessed on model simulations (STI prevalences). Regressions were conducted to evaluate the predictability of HIV prevalence from each of the other STI prevalences.

Results Across these simulations, Spearman’s rank correlation coefficient was 0.46 (95% CI: 0.37- 0.55) between HIV and HSV-2, 0.90 (95% CI: 0.88–0.91) between HIV and gonorrhea, 0.82 (95% CI: 0.78–0.86) between HIV and chlamydia, 0.82 (95% CI: 0.78–0.84) between HIV and syphilis, 0.31 (95% CI: 0.21–0.40) between HSV-2 and gonorrhea, 0.82 (95% CI: 0.78–0.86) between HSV-2 and chlamydia, 0.15 (95% CI: 0.05–0.25) between HSV-2 and syphilis, 0.70 (95% CI: 0.65–0.75) between gonorrhea and chlamydia, 0.93 (95% CI: 0.92–0.95) between gonorrhea and syphilis, and 0.56 (95% CI: 0.49–0.61) between chlamydia and syphilis. The adjusted R-squared for predicting HIV prevalence using each individual STI prevalence was 0.40 for HSV-2, 0.77 for gonorrhea, 0.71 for chlamydia, and 0.57 for syphilis. The adjusted R-squared for predicting HIV prevalence in a model that includes all other STI prevalences was 0.92.

Conclusion STI prevalence is a proxy biomarker of HIV prevalence across heterogeneous sexual networks, explaining a considerable fraction of HIV prevalence variation. However, the strength of the association between each pair of STIs varies across STIs.

Disclosure No significant relationships.

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