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Can the prevalence of one STI serve as a predictor for another? A mathematical modeling analysis.

Infect Dis Model

June 2025

Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar.

We aimed to understand to what extent knowledge of the prevalence of one sexually transmitted infection (STI) can predict the prevalence of another STI, with application for men who have sex with men (MSM). An individual-based simulation model was used to study the concurrent transmission of HIV, HSV-2, chlamydia, gonorrhea, and syphilis in MSM sexual networks. Using the model outputs, 15 multiple linear regression models were conducted for each STI prevalence, treating the prevalence of each as the dependent variable and the prevalences of up to four other STIs as independent variables in various combinations.

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Neisseria gonorrhoeae is an on-going public health problem due in part to the lack of success with efforts to develop an efficacious vaccine to prevent this sexually transmitted infection. The gonococcal transferrin binding protein B (TbpB) is an attractive candidate vaccine antigen. However, it exhibits high levels of antigenic variability, posing a significant obstacle in evoking a broadly protective immune response.

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Background: Latin America-amidst its largest mass migration-has seen minimal progress in curbing new HIV infections. Transgender women (TW) in the region are disproportionately affected, but scant data examines HIV vulnerabilities alongside migration.

Methods: Between February-July 2022, 211 young TW ages 16-24 in Lima participated in a cross-sectional quantitative study accompanied by serological testing (HIV, syphilis, chlamydia, gonorrhea, hepatitis B).

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Introduction: The US state of Florida has the third highest rate of HIV as well as high rates of sexually transmitted infections (STIs) indicating critical HIV and STI prevention needs remain unmet. To address gaps in the STI care continuum in people with HIV (PWH), evidence-based interventions were implemented across three Ryan White HIV/AIDS Program (RWHAP) funded clinics in Florida between August 2020-August 2021. Interventions included comprehensive sexual health history (SHH) taking using audio computer-assisted self-interview (ACASI) software, self-collected extragenital gonorrhea and chlamydia testing, and the introduction of a lesbian, gay, bisexual, transgender, and queer (LGBTQ+) welcoming environment.

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Phylogenetic analyses are crucial for understanding microbial evolution and infectious disease transmission. Bacterial phylogenies are often inferred from SNP alignments, with SNPs as the fundamental signal within these data. SNP alignments can be reduced to a 'strict core' by removing those sites that do not have data present in every sample.

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