Antibiotic-Resistant Neisseria gonorrhoeae Spread Faster with More Treatment, Not More Sexual Partners

Abstract

The sexually transmitted bacterium Neisseria gonorrhoeae has developed resistance to all antibiotic classes that have been used for treatment and strains resistant to multiple antibiotic classes have evolved. In many countries, there is only one antibiotic remaining for empirical N. gonorrhoeae treatment, and antibiotic management to counteract resistance spread is urgently needed. Understanding dynamics and drivers of resistance spread can provide an improved rationale for antibiotic management. In our study, we first used antibiotic resistance surveillance data to estimate the rates at which antibiotic-resistant N. gonorrhoeae spread in two host populations, heterosexual men (HetM) and men who have sex with men (MSM). We found higher rates of spread for MSM (0.86 to 2.38 y-1, mean doubling time: 6 months) compared to HetM (0.24 to 0.86 y-1, mean doubling time: 16 months). We then developed a dynamic transmission model to reproduce the observed dynamics of N. gonorrhoeae transmission in populations of heterosexual men and women (HMW) and MSM. We parameterized the model using sexual behavior data and calibrated it to N. gonorrhoeae prevalence and incidence data. In the model, antibiotic-resistant N. gonorrhoeae spread with a median rate of 0.88 y-1 in HMW and 3.12 y-1 in MSM. These rates correspond to median doubling times of 9 (HMW) and 3 (MSM) months. Assuming no fitness costs, the model shows the difference in the host population's treatment rate rather than the difference in the number of sexual partners explains the differential spread of resistance. As higher treatment rates result in faster spread of antibiotic resistance, treatment recommendations for N. gonorrhoeae should carefully balance prevention of infection and avoidance of resistance spread.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1. Structure of N. gonorrhoeae transmission model.

Ni sexual activity group i, Si susceptible hosts, ISeni hosts infected with antibiotic-sensitive strain, IResi hosts infected with antibiotic-resistant strain, πi partner change rate, βij transmission probability per partnership, ρij mixing between and within sexual activity groups, τ treatment rate, ν spontaneous recovery rate, μ probability of resistance during treatment, α rate of entering and leaving the population, γ redistribution rate, G set of low and high sexual activity groups.

Fig 2. Increase in antibiotic-resistant N.gonorrhoeae.

Points show data from antibiotic resistance surveillance programs (GRASP and GISP). Dashed lines indicate the fit of the logistic growth model to the data. For a given antibiotic and surveillance program, the rates of spread in MSM (green) are consistently higher than those in HetM (blue).

Fig 3. Prior and posterior distributions of the parameters.

Prior distributions (yellow) are shown together with posterior distributions for HMW (blue) and MSM (green) for (a) the sexual mixing coefficient, ϵ, (b) the fraction of diagnosed and treated infections, ϕ, (c) the average duration of infection, D, (d) the transmission probability within the low activity group, βLL, and (e) the transmission probability within the high activity group, βHH.

Fig 4. Spread of antibiotic resistance in the transmission model.

Ranges indicating 50% of all simulations are shown in dark color, and ranges indicating 95% of all simulations are shown in light color. The continuous lines describe the median proportion of antibiotic-resistant N. gonorrhoeae for all simulations. The black dotted line indicates the 5% threshold.

Fig 5. Distribution of treatment rates in HMW and MSM.

Treatment rates closely approximate the rates of resistance spread. The median treatment rate was 0.88 y−1 in HMW and 3.12 y−1 in MSM.