📊 epidemiology

PrEP-associated screening reduces N. gonorrhoeae transmission but increases case notifications among MSM: a modeling study

This modeling study demonstrates that while PrEP-associated screening effectively reduces the true transmission and prevalence of *N. gonorrhoeae* among men who have sex with men by shortening infection duration, it paradoxically increases case notifications by detecting previously undiagnosed asymptomatic infections, suggesting that public health focus should shift toward managing the consequences of increased antibiotic use and antimicrobial resistance.

Original authors: Marrec, L., Lehtinen, S.

Published 2026-07-02

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CC BY 4.0

Original authors: Marrec, L., Lehtinen, S.

Original paper licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). ⚕️ This is an AI-generated explanation of a preprint that has not been peer-reviewed. It is not medical advice. Do not make health decisions based on this content. Read full disclaimer

Imagine a busy city where a specific type of "traffic jam" (an infection called gonorrhea) keeps happening among a particular group of drivers. Recently, the city introduced a new safety system (PrEP) to prevent a different, more dangerous type of crash (HIV). While this safety system works wonders for HIV, people noticed that the traffic jams for gonorrhea seemed to be getting worse.

This study asks a crucial question: Is the new safety system actually causing more traffic jams, or is it just making us better at seeing them?

Here is how the researchers broke it down using a digital simulation of the city:

The Two Forces at Play

The researchers imagined two opposing forces fighting over the traffic:

The "Riskier Driving" Effect: Because the new safety system protects against the big crash, some drivers feel safer and take off their seatbelts (stop using condoms). This should cause more traffic jams (more infections).
The "Faster Tow Truck" Effect: To use the new safety system, drivers must visit a mechanic every few months for a check-up. This means if a traffic jam starts, the mechanic finds it immediately and fixes it (treats the infection) before it spreads to other cars. This should clear the jams faster.

The Big Discovery: The Tow Trucks Win

The study ran thousands of simulations to see which force wins. They found that the "Faster Tow Truck" effect is stronger.

Even if drivers take off their seatbelts and drive more recklessly, the fact that they are being checked on every three months means infections are caught and cleared so quickly that the total number of traffic jams actually goes down. The regular check-ups are so effective that they "overcompensate" for the risky behavior.

The Great Illusion: Why It Looks Like Things Are Getting Worse

Here is the tricky part that confuses everyone: The number of reported traffic jams goes UP, even though the actual number of jams is going DOWN.

Think of it like this:

Before: Drivers only reported jams when they were huge and blocked the whole road (symptomatic). Many small jams happened but were never seen.
After: Because drivers are visiting the mechanic every few months, the mechanic finds and reports every single jam, even the tiny ones that would have cleared up on their own.

So, the "Reported Cases" (notifications) skyrocket because we are finally seeing the invisible jams. But the "True Burden" (how many people are actually infected at any given time) is shrinking because the mechanic is fixing them faster than they can spread.

The Real Danger: The "Antibiotic Bill"

The paper warns that while we are winning the battle against the spread of the infection, we might be creating a new problem: The cost of the repairs.

Because we are finding and treating so many more infections (including the tiny ones that might have gone away on their own), we are using a lot more "repair fluid" (antibiotics). The researchers suggest that the real worry isn't that PrEP is spreading the infection, but that this massive increase in antibiotic use might train the bacteria to become "superbugs" that the repair fluid can no longer fix.

Summary

Does PrEP make gonorrhea spread faster? No. The frequent testing required by PrEP actually stops the spread more effectively than the risky behavior it might encourage.
Why are case numbers rising? Because we are finding infections we used to miss. It's a sign of better detection, not a worse epidemic.
What should we worry about? Not the spread of the infection, but the fact that treating so many more people might make the bacteria resistant to our medicines in the long run.

Problem Statement
The rapid scale-up of HIV pre-exposure prophylaxis (PrEP) among men who have sex with men (MSM) has coincided with rising rates of bacterial sexually transmitted infections (STIs), particularly Neisseria gonorrhoeae (NG). This temporal association has sparked debate regarding whether PrEP drives a new STI epidemic through behavioral risk compensation (increased condomless sex) or mitigates transmission through intensified clinical surveillance (regular screening). The epidemiological impact of PrEP is complex because it involves competing mechanisms: risk compensation increases transmission risk, while frequent screening shortens infection duration and interrupts transmission chains. Furthermore, sexual network heterogeneity and the rapid emergence of antimicrobial resistance in NG complicate the interpretation of surveillance data. A critical challenge is distinguishing between true disease burden (prevalence and incidence) and observed case notifications, which may be confounded by increased detection of previously undiagnosed asymptomatic infections.

Methodology
The authors developed a deterministic compartmental transmission model stratified by sexual activity and PrEP use to evaluate the impact of PrEP on NG dynamics.

Population Structure: The MSM population is divided into a low-activity group ( $L$ ) and a high-activity group ( $H$ ). The high-activity group is further subdivided into PrEP users ( $P$ ) and non-users ( $U$ ).
Transmission Dynamics: The model uses a system of ordinary differential equations (ODEs) to track susceptible, symptomatic infected, and asymptomatic infected individuals. Transmission is governed by partner change rates, per-partnership transmission probabilities, and sexual mixing patterns (assortative vs. proportionate).
Clinical Parameters: The model explicitly incorporates the interplay between behavioral changes (e.g., increased transmission probability $\beta_P$ due to reduced condom use) and clinical interventions (e.g., increased asymptomatic testing rate $\tau_{P,A}$ ). Symptomatic individuals are treated at a fixed rate, while asymptomatic individuals clear infection via natural clearance or testing followed by treatment.
Calibration: Parameters were informed by published demographic literature and calibrated using a rejection-based Approximate Bayesian Computation (ABC) approach. Key parameters include the fraction of high-activity individuals, mixing coefficients, transmission probabilities, and testing rates.
Analytical Derivation: Beyond numerical simulations, the authors derived simple analytical conditions governing changes in endemic prevalence, incidence, and notification rates, particularly under the assumption of fully assortative mixing ( $\epsilon = 1$ ).

Key Contributions

Analytical Framework: The study derives explicit analytical conditions that define when PrEP-associated changes in condom use and screening will amplify or mitigate STI transmission. This provides a simpler alternative to complex network-based models for understanding the balance between behavioral risk and clinical surveillance.
Differentiation of Metrics: The paper explicitly distinguishes the differential sensitivity of prevalence, incidence, and notification rates to screening intensity. It demonstrates that while screening directly reduces prevalence by shortening infection duration, its effect on incidence is dampened by the simultaneous reduction in the infected reservoir.
The Notification Paradox: The authors formalize the mechanism by which notification rates can surge even as true disease burden declines. This occurs because intensified screening increases the probability of detecting infections before natural clearance, outweighing the reduction in the total number of infected individuals.

Results

Prevalence and Incidence Reduction: Under current clinical guidelines recommending quarterly screening ( $\tau_{P,A} \approx 4$ year $^{-1}$ ), the model predicts that PrEP-associated screening is generally sufficient to reduce both the true endemic prevalence and incidence of NG. This holds true even when assuming a plausible 50% increase in transmission probability ( $\beta_P$ ) due to risk compensation. Sensitivity analyses confirm these findings are robust across a wide range of parameter sets.
Differential Sensitivity: Prevalence is more sensitive to increases in screening intensity than incidence. While increased screening reduces both, a higher testing frequency is required to achieve a net reduction in incidence compared to prevalence.
Rise in Notifications: The model confirms that clinical notification rates may increase significantly following PrEP rollout, even when true prevalence and incidence are declining. This is driven by the detection of previously undiagnosed asymptomatic infections. The threshold for an increase in notifications is much lower than the threshold for an increase in true incidence or prevalence.
Parameter Thresholds: The analysis suggests that for quarterly screening to fail in reducing incidence, transmission probability would need to increase by a median of ~61%. Conversely, a relatively small increase in transmission probability (median ~36%) is sufficient to cause a net increase in case notifications.

Significance
The paper argues that the observed rise in NG notifications following PrEP implementation should not be interpreted as evidence that PrEP is driving a new STI epidemic. Instead, under realistic assumptions, PrEP programs are expected to reduce transmission while simultaneously increasing case detection.

The authors conclude that the public health focus should shift from questioning whether PrEP amplifies transmission to addressing the consequences of increased STI diagnoses and treatment. Specifically, they highlight the risk that greater antibiotic consumption, driven by intensified screening and treatment of detected cases, may accelerate the spread of antimicrobial resistance in N. gonorrhoeae. The study emphasizes the importance of distinguishing between observed surveillance data and underlying disease dynamics when evaluating PrEP programs and formulating public health recommendations.

The Two Forces at Play

The Big Discovery: The Tow Trucks Win

The Great Illusion: Why It Looks Like Things Are Getting Worse

The Real Danger: The "Antibiotic Bill"

Summary

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