Projecting the development of antimicrobial resistance in Neisseria gonorrhoeae from antimicrobial surveillance data: a mathematical modelling study.

BACKGROUND: The World Health Organization recommends changing the first-line antimicrobial treatment for gonorrhoea when ≥ 5% of Neisseria gonorrhoeae cases fail treatment or are resistant. Susceptibility to ceftriaxone, the last remaining treatment option has been decreasing in many countries. We used antimicrobial resistance surveillance data and developed mathematical models to project the time to reach the 5% threshold for resistance to first-line antimicrobials used for N. gonorrhoeae. METHODS: We used data from the Gonococcal Resistance to Antimicrobials Surveillance Programme (GRASP) in England and Wales from 2000-2018 about minimum inhibitory concentrations (MIC) for ciprofloxacin, azithromycin, cefixime and ceftriaxone and antimicrobial treatment in two groups, heterosexual men and women (HMW) and men who have sex with men (MSM). We developed two susceptible-infected-susceptible models to fit these data and produce projections of the proportion of resistance until 2030. The single-step model represents the situation in which a single mutation results in antimicrobial resistance. In the multi-step model, the sequential accumulation of resistance mutations is reflected by changes in the MIC distribution. RESULTS: The single-step model described resistance to ciprofloxacin well. Both single-step and multi-step models could describe azithromycin and cefixime resistance, with projected resistance levels higher with the multi-step than the single step model. For ceftriaxone, with very few observed cases of full resistance, the multi-step model was needed to describe long-term dynamics of resistance. Extrapolating from the observed upward drift in MIC values, the multi-step model projected ≥ 5% resistance to ceftriaxone could be reached by 2030, based on treatment pressure alone. Ceftriaxone resistance was projected to rise to 13.2% (95% credible interval [CrI]: 0.7-44.8%) among HMW and 19.6% (95%CrI: 2.6-54.4%) among MSM by 2030. CONCLUSIONS: New first-line antimicrobials for gonorrhoea treatment are needed. In the meantime, public health authorities should strengthen surveillance for AMR in N. gonorrhoeae and implement strategies for continued antimicrobial stewardship. Our models show the utility of long-term representative surveillance of gonococcal antimicrobial susceptibility data and can be adapted for use in, and for comparison with, other countries.

Identifying Sexually Transmitted Infection Risk Groups Based on Behavioral and Psychological Characteristics Among Heterosexuals During the COVID-19 Pandemic.

BACKGROUND: Measures to reduce coronavirus disease (COVID-19) transmission may impact sexual health. We aimed to examine the impact of COVID-19 on sexual behavior and sexually transmitted infection (STI) testing and to characterize individuals who were at high STI risk. METHODS: Dutch heterosexual males and females who participated in a cohort study in 2016 to 2018 were invited to fill out 2 questionnaires again in 2020 (age, 21-28 years). We used behavioral and psychological data from: prelockdown (September 2019 to February 2020), lockdown (March to May 2020), and postlockdown (June to August 2020). Behavior change was compared between subgroups identified with latent class analysis. RESULTS: Four latent classes were identified (n = 238). Individuals in class 1 (48% of study population) and class 2 (36%) were at low STI risk and reported mostly steady partnerships. Individuals in class 3 (9%) and class 4 (7%) reported multiple casual partners prelockdown. Class 4 was characterized by lower condom use and health goals, negative infection prevention attitudes, and higher impulsiveness compared with class 3. Furthermore, same/increased partner numbers during lockdown (class 3, 18%; class 4, 56%) and postlockdown (class 3, 36%; class 4, 42%) compared with prelockdown was often reported. Of individuals who wanted an STI test during the pandemic, 62% in class 3 and 56% in class 4 did not get tested, mainly because they were unable to get an appointment. CONCLUSIONS: A subgroup of individuals, characterized by low health goals, negative infection prevention attitudes, and high impulsiveness, engaged in high-risk behavior during the pandemic. Identifying these individuals may help provide appropriate health care during strict lockdowns and after relaxation of measures.