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We estimated the fraction of antibiotic prescribing in the United States attributable to gonorrhea. Gonorrhea contributes to an outsized proportion of antibiotic prescriptions in young adults, males, and in the southern and western United States. A gonococcal vaccine could substantially reduce antibiotic prescribing in these populations. [ABSTRACT FROM AUTHOR]

Background: Reducing geographic disparities in antibiotic prescribing is a central public health priority to combat antibiotic resistance, but drivers of this variation have been unclear.Methods: We measured how variation in outpatient visit rates (observed disease) and antibiotic prescribing rates per visit (prescribing practices) contributed to geographic variation in per capita antibiotic prescribing in Massachusetts residents younger than 65 years between 2011 and 2015.Results: Of the difference in per capita antibiotic prescribing between high- and low-prescribing census tracts in Massachusetts, 45.2% was attributable to variation in outpatient visit rates, while 25.8% was explained by prescribing practices. Outpatient visits for sinusitis, pharyngitis, and suppurative otitis media accounted for 30.3% of the gap in prescribing, with most of the variation in visit rates concentrated in children younger than 10 years. Outpatient visits for these conditions were less frequent in census tracts with high social deprivation index.Conclusions: Interventions aimed at reducing geographic disparities in antibiotic prescribing should target the drivers of outpatient visits for respiratory illness and should account for possible underutilization of health services in areas with the lowest antibiotic consumption. Our findings challenge the conventional wisdom that prescribing practices are the main driver of geographic disparities in antibiotic use. [ABSTRACT FROM AUTHOR]

Neisseria gonorrhoeae infections have been increasing globally, with prevalence rising across age groups. In this study, we report a case of disseminated gonococcal infection (DGI) involving a prosthetic joint, and we use whole-genome sequencing to characterize resistance genes, putative virulence factors, and the phylogenetic lineage of the infecting isolate. We review the literature on sequence-based prediction of antibiotic resistance and factors that contribute to risk for DGI. We argue for routine sequencing and reporting of invasive gonococcal infections to aid in determining whether an invasive gonococcal infection is sporadic or part of an outbreak and to accelerate understanding of the genetic features of N gonorrhoeae that contribute to pathogenesis. [ABSTRACT FROM AUTHOR]

Antibiotic use is a key driver of antibiotic resistance. Understanding the quantitative association between antibiotic use and resulting resistance is important for predicting future rates of antibiotic resistance and for designing antibiotic stewardship policy. However, the use-resistance association is complicated by "spillover," in which one population's level of antibiotic use affects another population's level of resistance via the transmission of bacteria between those populations. Spillover is known to have effects at the level of families and hospitals, but it is unclear if spillover is relevant at larger scales. We used mathematical modeling and analysis of observational data to address this question. First, we used dynamical models of antibiotic resistance to predict the effects of spillover. Whereas populations completely isolated from one another do not experience any spillover, we found that if even 1% of interactions are between populations, then spillover may have large consequences: The effect of a change in antibiotic use in one population on antibiotic resistance in that population could be reduced by as much as 50%. Then, we quantified spillover in observational antibiotic use and resistance data from US states and European countries for three pathogen-antibiotic combinations, finding that increased interactions between populations were associated with smaller differences in antibiotic resistance between those populations. Thus, spillover may have an important impact at the level of states and countries, which has ramifications for predicting the future of antibiotic resistance, designing antibiotic resistance stewardship policy, and interpreting stewardship interventions. [ABSTRACT FROM AUTHOR]

Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics. [ABSTRACT FROM AUTHOR]

Antimicrobial resistance in Neisseria gonorrhoeae is a major issue of public health, and there is a critical need for the development of new antigonococcal strategies. In this study, we investigated the effectiveness of antimicrobial blue light (aBL; wavelength, 405 nm), an innovative nonpharmacological approach, for the inactivation of N. gonorrhoeae. Our findings indicated that aBL preferentially inactivated N. gonorrhoeae, including antibiotic-resistant strains, over human vaginal epithelial cells in vitro. Furthermore, no aBL-induced genotoxicity to the vaginal epithelial cells was observed at the radiant exposure used to inactivate N. gonorrhoeae. aBL also effectively inactivated N. gonorrhoeae that had attached to and invaded into the vaginal epithelial cells in their cocultures. No gonococcal resistance to aBL developed after 15 successive cycles of inactivation induced by subtherapeutic exposure to aBL. Endogenous aBL-activatable photosensitizing porphyrins in N. gonorrhoeae were identified and quantified using ultraperformance liquid chromatography, with coproporphyrin being the most abundant species in all N. gonorrhoeae strains studied. Singlet oxygen was involved in aBL inactivation of N. gonorrhoeae. Together, these findings show that aBL represents a potential potent treatment for antibiotic-resistant gonococcal infection. [ABSTRACT FROM AUTHOR]

Rising azithromycin nonsusceptibility among Neisseria gonorrhoeae isolates threatens current treatment recommendations, but the cause of this rise is not well understood. We performed an ecological study of seasonal patterns in macrolide use and azithromycin resistance in N. gonorrhoeae, finding that population-wide macrolide use is associated with increased azithromycin nonsusceptibility. These results, indicative of bystander selection, have implications for antibiotic prescribing guidelines. [ABSTRACT FROM AUTHOR]

Infections with Neisseria gonorrhoeae, a sexually transmitted pathogen that causes urethritis, cervicitis, and more severe complications, are increasing. Gonorrhea is typically treated with antibiotics; however, N. gonorrhoeae has rapidly acquired resistance to many antibiotic classes, and lineages with reduced susceptibility to the currently recommended therapies are emerging worldwide. In this review, we discuss the contributions of whole genome sequencing (WGS) to our understanding of resistant N. gonorrhoeae. Genomics has illuminated the evolutionary origins and population structure of N. gonorrhoeae and the magnitude of horizontal gene transfer within and between Neisseria species. WGS can be used to predict the susceptibility of N. gonorrhoeae based on known resistance determinants, track the spread of these determinants throughout the N. gonorrhoeae population, and identify novel loci contributing to resistance. WGS has also allowed more detailed epidemiological analysis of transmission of N. gonorrhoeae between individuals and populations than previously used typing methods. Ongoing N. gonorrhoeae genomics will complement other laboratory techniques to understand the biology and evolution of the pathogen, improve diagnostics and treatment in the clinic, and inform public health policies to limit the impact of antibiotic resistance. Over the 20 years since the first gonococcal genome was sequenced, 15 finished genomes, 413 draft genome assemblies, and 4795 sequencing runs have been made publicly available. Here, we review the background on gonorrhea, resistant gonococcus, and the ways in which researchers are exploring how to integrate these data to advance clinical care and public health management of gonorrhea. [ABSTRACT FROM AUTHOR]

Background: Treatment of Neisseria gonorrhoeae infection is empirical and based on population-wide susceptibilities. Increasing antimicrobial resistance underscores the potential importance of rapid diagnostic tests, including sequence-based tests, to guide therapy. However, the usefulness of sequence-based diagnostic tests depends on the prevalence and dynamics of the resistance mechanisms.Methods: We define the prevalence and dynamics of resistance markers to extended-spectrum cephalosporins, macrolides, and fluoroquinolones in 1102 resistant and susceptible clinical N. gonorrhoeae isolates collected from 2000 to 2013 via the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project.Results: Reduced extended-spectrum cephalosporin susceptibility is predominantly clonal and associated with the mosaic penA XXXIV allele and derivatives (sensitivity 98% for cefixime and 91% for ceftriaxone), but alternative resistance mechanisms have sporadically emerged. Reduced azithromycin susceptibility has arisen through multiple mechanisms and shows limited clonal spread; the basis for resistance in 36% of isolates with reduced azithromycin susceptibility is unclear. Quinolone-resistant N. gonorrhoeae has arisen multiple times, with extensive clonal spread.Conclusions: Quinolone-resistant N. gonorrhoeae and reduced cefixime susceptibility appear amenable to development of sequence-based diagnostic tests, whereas the undefined mechanisms of resistance to ceftriaxone and azithromycin underscore the importance of phenotypic surveillance. The identification of multidrug-resistant isolates highlights the need for additional measures to respond to the threat of untreatable gonorrhea. [ABSTRACT FROM AUTHOR]

The rise in gonococcal antibiotic resistance and the threat of untreatable infection are focusing attention on strategies to limit the spread of drug-resistant gonorrhea. Mathematical models provide a framework to link the natural history of infection and patient behavior to epidemiological outcomes and can be used to guide research and enhance the public health impact of interventions. While limited knowledge of key disease parameters and networks of spread has impeded development of operational models of gonococcal transmission, new tools in gonococcal surveillance may provide useful data to aid tracking and modeling. Here, we highlight critical questions in the management of gonorrhea that can be addressed by mathematical models and identify key data needs. Our overarching aim is to articulate a shared agenda across gonococcus-related fields from microbiology to epidemiology that will catalyze a comprehensive evidence-based clinical and public health strategy for management of gonococcal infections and antimicrobial resistance. [ABSTRACT FROM AUTHOR]

The rate of infection by methicillin-resistant Staphylococcus aureus (MRSA) has declined over the past decade, but it is unclear whether this represents a decline in S. aureus infections overall. To evaluate the trends in the annual rates of infection by S. aureus subtypes and mean antibiotic resistance, we conducted a 15-year retrospective observational study at two tertiary care institutions in Boston, MA, of 31,753 adult inpatients with S. aureus isolated from clinical specimens. We inferred the gain and loss of methicillin resistance through genome sequencing of 180 isolates from 2016. The annual rates of infection by S. aureus declined from 2003 to 2014 by 4.2% (2.7% to 5.6%), attributable to an annual decline in MRSA of 10.9% (9.3% to 12.6%). Penicillin-susceptible S. aureus (PSSA) increased by 6.1% (4.2% to 8.1%) annually, and rates of methicillin-susceptible penicillin-resistant S. aureus (MSSA) did not change. Resistance in S. aureus decreased from 2000 to 2014 by 0.8 antibiotics (0.7 to 0.8). Within common MRSA clonal complexes, 3/14 MSSA and 2/21 PSSA isolates arose from the loss of resistance-conferring genes. Overall, in two tertiary care institutions in Boston, MA, a decline in S. aureus infections has been accompanied by a shift toward increased antibiotic susceptibility. The rise in PSSA makes penicillin an increasingly viable treatment option.

Background: Increasing antibiotic resistance limits treatment options for gonorrhea. We examined the impact of a hypothetical point-of-care (POC) test reporting antibiotic susceptibility profiles on slowing resistance spread. Methods: A mathematical model describing gonorrhea transmission incorporated resistance emergence probabilities and fitness costs associated with resistance based on characteristics of ciprofloxacin (A), azithromycin (B), and ceftriaxone (C). We evaluated time to 1% and 5% prevalence of resistant strains among all isolates with the following: (1) empiric treatment (B and C), and treatment guided by POC tests determining susceptibility to (2) A only and (3) all 3 antibiotics. Results: Continued empiric treatment without POC testing was projected to result in >5% of isolates being resistant to both B and C within 15 years. Use of either POC test in 10% of identified cases delayed this by 5 years. The 3 antibiotic POC test delayed the time to reach 1% prevalence of triply-resistant strains by 6 years, whereas the A-only test resulted in no delay. Results were less sensitive to assumptions about fitness costs and test characteristics with increasing test uptake. Conclusions: Rapid diagnostics reporting antibiotic susceptibility may extend the usefulness of existing antibiotics for gonorrhea treatment, but ongoing monitoring of resistance patterns will be critical.