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BACKGROUND: Neisseria gonorrhoeae poses an urgent public health threat because of increasing antimicrobial resistance; however, much of the circulating population remains susceptible to historical treatment regimens. Point-of-care diagnostics that report susceptibility could allow for reintroduction of these regimens, but development of such diagnostics has been restricted to ciprofloxacin, for which susceptibility can be predicted from a single locus. We aimed to define genetic variants associated with susceptibility to penicillin and tetracycline. METHODS: We collected publicly available global whole-genome sequencing data (n=12 045) from clinical N gonorrhoeae isolates, with phenotypic resistance data for penicillin (n=6935), and tetracycline (n=5727). Using conditional genome-wide association studies, we defined genetic variants associated with susceptibility to penicillin and tetracycline. We excluded isolates that could not be classified as either susceptible or resistant. To validate our results, we assembled 1479 genomes from the US Centers for Disease Control and Prevention (CDC)’s Gonococcal Isolate Surveillance Project, for which urethral specimens are collected at sentinel surveillance sites across the USA. We evaluated the sensitivity and specificity of susceptibility-associated alleles using Clinical & Laboratory Standards Institute breakpoints for susceptibility and non-resistance in both the global and validation datasets. FINDINGS: In our conditional penicillin genome-wide association study, the presence of a genetic variant defined by a non-mosaic penA allele without an insertion at codon 345 was associated with penicillin susceptibility and had the highest negative effect size (β) of significant variants (p=5·0×10(–14), β –2·5). In combination with the absence of bla(TEM), this variant predicted penicillin susceptibility with high specificity (99·8%) and modest sensitivity (36·7%). For tetracycline, the wildtype allele at rpsJ codon 57, encoding valine, was associated with tetracycline susceptibility (p=5·6×10(–16), β –1·6) after conditioning on the presence of tetM. The combination of rpsJ codon 57 allele and tetM absence predicted tetracycline susceptibility with high specificity (97·2%) and sensitivity (88·7%). INTERPRETATION: As few as two genetic loci can predict susceptibility to penicillin and tetracycline in N gonorrhoeae with high specificity. Molecular point-of-care diagnostics targeting these loci have the potential to increase available treatments for gonorrhoea. FUNDING: National Institute of Allergy and Infectious Diseases, the National Science Foundation, and the Smith Family Foundation.

Summary Background Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible and broader mitigation measures must be implemented. Methods To estimate the comparative efficacy of individual quarantine and active monitoring of contacts to control severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit a model to the incubation period distribution (mean 5·2 days) and to two estimates of the serial interval distribution: a shorter one with a mean serial interval of 4·8 days and a longer one with a mean of 7·5 days. To assess variable resource settings, we considered two feasibility settings: a high-feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and a low-feasibility setting with 50% of contacts traced, a 2-day average delay, and 50% effective isolation. Findings Model fitting by sequential Monte Carlo resulted in a mean time of infectiousness onset before symptom onset of 0·77 days (95% CI −1·98 to 0·29) for the shorter serial interval, and for the longer serial interval it resulted in a mean time of infectiousness onset after symptom onset of 0·51 days (95% CI −0·77 to 1·50). Individual quarantine in high-feasibility settings, where at least 75% of infected contacts are individually quarantined, contains an outbreak of SARS-CoV-2 with a short serial interval (4·8 days) 84% of the time. However, in settings where the outbreak continues to grow (eg, low-feasibility settings), so too will the burden of the number of contacts traced for active monitoring or quarantine, particularly uninfected contacts (who never develop symptoms). When resources are prioritised for scalable interventions such as physical distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. Even under the shorter serial interval, if physical distancing reduces the reproductive number to 1·25, active monitoring of 50% of contacts can result in overall outbreak control (ie, effective reproductive number Interpretation Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission to make data-driven policy decisions regarding the cost–benefit comparisons of individual quarantine versus active monitoring of contacts. To the extent that these interventions can be implemented, they can help mitigate the spread of SARS-CoV-2. Funding National Institute of General Medical Sciences, National Institutes of Health.

The sexually transmitted infection gonorrhea, caused by the Gram-negative bacterium Neisseria gonorrhoeae, can cause urethritis, cervicitis, and systemic disease, among other manifestations. N. gonorrhoeae has rapidly rising incidence along with increasing levels of antibiotic resistance to a broad range of drugs including first-line treatments. The rise in resistance has led to fears of untreatable gonorrhea causing substantial disease globally. In this review, we will describe multiple approaches being undertaken to slow and control this spread of resistance. First, a number of old drugs have been repurposed and new drugs are being developed with activity against Neisseria gonorrhoeae. Second, vaccine development, long an important goal, is advancing. Third, new diagnostics promise rapid detection of antibiotic resistance and a shift from empiric to tailored treatment. The deployment of these new tools for addressing the challenge of antibiotic resistance will require careful consideration to provide optimal care for all patients while extending the lifespan of treatment regimens.

Emergence of a novel pathogen drives the urgent need for diagnostic tests that can aid in defining disease prevalence. The limitations associated with rapid development and deployment of these tests result in a dilemma: In efforts to optimize prevalence estimates, would tests be better used in the lab to reduce uncertainty in test characteristics or to increase sample size in field studies? Here, we provide a framework to address this question through a joint Bayesian model that simultaneously analyzes lab validation and field survey data, and we define the impact of test allocation on inferences of sensitivity, specificity, and prevalence. In many scenarios, prevalence estimates can be most improved by apportioning additional effort towards validation rather than to the field. The joint model provides superior estimation of prevalence, sensitivity, and specificity, compared with typical analyses that model lab and field data separately, and it can be used to inform sample allocation when testing is limited.

Background: Despite 'best effort' public health measures, the incidence of gonorrhoea is increasing in many countries. Recently, whole genome sequencing (WGS) has been used to investigate transmission of Neisseria gonorrhoeae, including antimicrobial-resistant (AMR) lineages, but to date, most studies have not combined genomic data with detailed patient-level information on sexual behaviour to define the extent of transmission across population subgroups ('bridging'). Methods: We performed an observational study and undertook WGS and bioinformatic analysis on all cultured clinical isolates of N. gonorrhoeae in the state of Victoria, Australia, from January to December 2017. Antimicrobial susceptibility testing was performed on all isolates, and detailed epidemiological data was obtained, including data on sexual orientation, HIV status, use of HIV pre-exposure prophylaxis (PrEP), sex work, and overseas travel. Epidemiological associations were made with dominant genetic clusters of N. gonorrhoeae. Findings: A total of 2,186 isolates were sequenced from 2,055 patients, 86·3% of whom were male. We identified eleven dominant genetic clusters, containing thirty or more patients, with the largest cluster comprising 181 patients. There was extensive bridging of clusters between men who have sex with men (MSM) and heterosexuals, with bisexual males identified in seven of the major clusters. Eight major clusters contained HIV-positive and HIV-negative patients (including individuals receiving PrEP). We also identified transmission of a novel azithromycin-resistant clone, associated with a mosaic mtr locus. Interpretation: To our knowledge, our study is the first to combine WGS with comprehensive individual-level behavioural risk data, providing verification for transmission of multiple gonococcal lineages within and across distinct sexual networks. Application of these methods in real-time will allow gonorrhoea transmission and antimicrobial resistance to be tracked, with 'hotspots' identified for interventions aimed at improving gonorrhoea control. Funding Statement: The National Health and Medical Research Council of Australia, and the Victorian Department of Health and Human Services. DAW (GNT1123854), EPFC (GNT1091226), and JCK (GNT1142613) are supported by Early Career Fellowships from the National Health and Medical Research Council (NHMRC) of Australia. BPH is supported by a Practitioner Fellowship from the NHMRC (GNT1105905). DJI is supported by the European Union’s Horizon 2020 research and innovation programme under grant agreement 643476. Work in this study was supported by a Project Grant from the NHMRC (GNT1147735) and a Partnership grant from the NHMRC (GNT1149991). MDU PHL is funded by the Victorian Department of Health and Human Services. Declaration of Interests: The authors declare no competing interests. Ethics Approval Statement: Data were collected in accordance with the Victorian Public Health and Wellbeing Act 2008. Ethical approval was obtained from the Alfred Hospital Ethics Committee (Project 625/17).

Summary Background The emergence of Neisseria gonorrhoeae with decreased susceptibility to extended spectrum cephalosporins raises the prospect of untreatable gonorrhoea. In the absence of new treatments, efforts to slow the increasing incidence of resistant gonococcus require insight into the factors that contribute to its emergence and spread. We assessed the relatedness between isolates in the USA and reconstructed likely spread of lineages through different sexual networks. Methods We sequenced the genomes of 236 isolates of N gonorrhoeae collected by the Centers for Disease Control and Prevention's Gonococcal Isolate Surveillance Project (GISP) from sentinel public sexually transmitted disease clinics in the USA, including 118 (97%) of the isolates from 2009–10 in GISP with reduced susceptibility to cefixime (cef RS ) and 118 cefixime-susceptible isolates from GISP matched as closely as possible by location, collection date, and sexual orientation. We assessed the association between antimicrobial resistance genotype and phenotype and correlated phylogenetic clustering with location and sexual orientation. Findings Mosaic penA XXXIV had a high positive predictive value for cef RS . We found that two of the 118 cef RS isolates lacked a mosaic penA allele, and rechecking showed that these two were susceptible to cefixime. Of the 116 remaining cef RS isolates, 114 (98%) fell into two distinct lineages that have independently acquired mosaic penA allele XXXIV. A major lineage of cef RS strains spread eastward, predominantly through a sexual network of men who have sex with men. Eight of nine inferred transitions between sexual networks were introductions from men who have sex with men into the heterosexual population. Interpretation Genomic methods might aid efforts to slow the spread of antibiotic-resistant N gonorrhoeae through augmentation of gonococcal outbreak surveillance and identification of populations that could benefit from increased screening for aymptomatic infections. Funding American Sexually Transmitted Disease Association, Wellcome Trust, National Institute of General Medical Sciences, and National Institute of Allergy and Infectious Diseases, National Institutes of Health.