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Open AccessJournal ArticleDOI

Incidence of Gonorrhea and Chlamydia Following Human Immunodeficiency Virus Preexposure Prophylaxis Among Men Who Have Sex With Men: A Modeling Study

TLDR
In this paper, a network-based mathematical model of HIV, Neisseria gonorrhoeae (NG), and Chlamydia trachomatis (CT) transmission dynamics among MSM in the United States is presented.
Abstract
Background Preexposure prophylaxis (PrEP) is highly effective for preventing human immunodeficiency virus (HIV) infection, but risk compensation (RC) in men who have sex with men (MSM) raises concerns about increased sexually transmitted infections (STIs). The Center for Disease Control and Prevention's (CDC's) PrEP guidelines recommend biannual STI screening, which may reduce incidence by treating STIs that would otherwise remain undiagnosed. We investigated these two counteracting phenomena. Methods With a network-based mathematical model of HIV, Neisseria gonorrhoeae (NG), and Chlamydia trachomatis (CT) transmission dynamics among MSM in the United States, we simulated PrEP uptake following the prescription indications and HIV/STI screening recommendations in the CDC guidelines. Scenarios varied PrEP coverage (the proportion of MSM indicated for PrEP who received it), RC (a reduction in the per-act probability of condom use), and the STI screening interval. Results In our reference scenario (40% coverage, 40% RC), 42% of NG and 40% of CT infections would be averted over the next decade. A doubling of RC would still result in net STI prevention relative to no PrEP. STIs declined because PrEP-related STI screening resulted in a 17% and 16% absolute increase in the treatment of asymptomatic and rectal STIs, respectively. Screening and timely treatment at quarterly vs biannual intervals would reduce STI incidence an additional 50%. Conclusions Implementation of the CDC PrEP guidelines while scaling up PrEP coverage could result in a significant decline in STI incidence among MSM. Our study highlights the design of PrEP not only as antiretroviral medication but as combination HIV/STI prevention incorporating STI screening.

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Sexually Transmitted Infections Treatment Guidelines,2021

TL;DR: These guidelines for the treatment of persons who have or are at risk for sexually transmitted infections (STIs) were updated by CDC after consultation with professionals knowledgeable in the field of STIs who met in Atlanta, Georgia, June 11-14, 2019.
Journal Article

A separable model for dynamic networks

TL;DR: A discrete time generative model for social network evolution that inherits the richness and flexibility of the class of exponential family random‐graph models and facilitates separable modelling of the tie duration distributions and the structural dynamics of tie formation is developed.
Journal ArticleDOI

Epidemiology and prevention of sexually transmitted infections in men who have sex with men at risk of HIV.

TL;DR: If control of STIs is to be improved, then a far greater emphasis on increased use of existing effective STI control strategies will be required, in addition to the investigation of new interventions.
Journal ArticleDOI

Global Epidemiologic Characteristics of Sexually Transmitted Infections Among Individuals Using Preexposure Prophylaxis for the Prevention of HIV Infection: A Systematic Review and Meta-analysis.

TL;DR: Estimates indicate a high burden of sexually transmitted infections among individuals initiating preexposure prophylaxis and persistent users of preex exposures for the prevention of HIV infection, highlighting the opportunities for active integration of services for sexual transmitted infections and HIV preex Exposure Prophylactic.
References
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Journal ArticleDOI

Prevention of HIV-1 infection with early antiretroviral therapy

TL;DR: The exciting evidence generated by this paper – that antiretroviral treatment of HIV-1 infection definitively reduces the risk of onward transmission of the virus by 96% – was rightly dubbed Science magazine's ‘Breakthrough of the Year’ in 2011.
Journal ArticleDOI

Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems

TL;DR: This paper discusses and applies an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models and develops ABC SMC as a tool for model selection; given a range of different mathematical descriptions, it is able to choose the best model using the standard Bayesian model selection apparatus.
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