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Background Neisseria gonorrhoeae is a major public health problem due to increasing incidence and antimicrobial resistance. Genetic markers of reduced susceptibility have been identified; the extent to which those are representative of global antimicrobial resistance is unknown. We evaluated the performance of whole-genome sequencing (WGS) used to predict susceptibility to ciprofloxacin and other antimicrobials using a global collection of N. gonorrhoeae isolates. Methods Susceptibility testing of common antimicrobials and the recently developed zolifodacin was performed using agar dilution to determine minimum inhibitory concentrations (MICs). We identified resistance alleles at loci known to contribute to antimicrobial resistance in N. gonorrhoeae from WGS data. We tested the ability of each locus to predict antimicrobial susceptibility. Results A total of 481 N. gonorrhoeae isolates, collected between 2004 and 2019 and making up 457 unique genomes, were sourced from 5 countries. All isolates with demonstrated susceptibility to ciprofloxacin (MIC ≤0.06 μg/mL) had a wild-type gyrA codon 91. Multilocus approaches were needed to predict susceptibility to other antimicrobials. All isolates were susceptible to zoliflodacin, defined by an MIC ≤0.25 μg/mL. Conclusions Single marker prediction can be used to inform ciprofloxacin treatment of N. gonorrhoeae infection. A combination of molecular markers may be needed to determine susceptibility for other antimicrobials.

Neisseria gonorrhoeae is an urgent public health threat due to the emergence of antibiotic resistance. As most isolates in the United States are susceptible to at least one antibiotic, rapid molecular antimicrobial susceptibility tests (ASTs) would offer the opportunity to tailor antibiotic therapy, thereby expanding treatment options. With genome sequence and antibiotic resistance phenotype data for nearly 20,000 clinical N. gonorrhoeae isolates now available, there is an opportunity to use statistical methods to develop sequence-based diagnostics that predict antibiotic susceptibility from genotype. N. gonorrhoeae, therefore, provides a useful example illustrating how to apply machine learning models to aid in the design of sequence-based ASTs. We present an overview of this framework, which begins with establishing the assay technology, the performance criteria, the population in which the diagnostic will be used, and the clinical goals, and extends to the choices that must be made to arrive at a set of features with the desired properties for predicting susceptibility phenotype from genotype. While we focus on the example of N. gonorrhoeae, the framework generalizes to other organisms for which large-scale genotype and antibiotic resistance data can be combined to aid in diagnostics development.

Wastewater-based epidemiology is a promising public health tool that can yield a more representative view of the population than case reporting. However, only about 80% of the U.S. population is connected to public sewers, and the characteristics of populations missed by wastewater-based epidemiology are unclear. To address this gap, we used publicly available datasets to assess sewer connectivity in the U.S. by location, demographic groups, and economic groups. Data from the U.S. Census American Housing Survey revealed that sewer connectivity was lower than average for American Indian and Alaskan Native, White, non-Hispanic, older, not in poverty, and larger households, but smaller geographic scales revealed local variations from this national connectivity pattern. For example, data from the U.S. Environmental Protection Agency showed that sewer connectivity was positively correlated with income in Minnesota, Florida, and California. Data from the U.S. Census American Community Survey and Environmental Protection Agency also revealed geographic areas with low sewer connectivity, such as Alaska, the Navajo Nation, Minnesota, Michigan, and Florida. However, with the exception of the U.S. Census data, there were inconsistencies across datasets. Using mathematical modeling to assess the impact of wastewater sampling inequities on inferences about epidemic trajectory at a local scale, we found that in some situations, even weak connections between communities may allow wastewater monitoring in one community to serve as a reliable proxy for an interacting community with no wastewater monitoring, when cases are widespread. A systematic, rigorous assessment of sewer connectivity will be important for ensuring an equitable and informed implementation of wastewater-based epidemiology as a public health monitoring system.

Rapid identification of new SARS-CoV-2 variants is a critical component of the public health response to the COVID-19 pandemic. However, we lack a quantitative framework to assess the expected performance of sampling strategies in varying epidemic contexts. To address this gap, we used a multi-patch stochastic model of SARS-CoV-2 spread in New York City to evaluate the impact of the volume of testing and sequencing, geographic representativeness of sampling, location and timing of variant emergence, and relative variant transmissibility on the time to first detection of a new variant. The strategy of targeted sampling of likely emergence locations offered the most improvement in detection speed. Increasing sequencing capacity reduced detection time more than increasing testing volumes. The relative transmissibility of the new variant and the epidemic context of variant emergence also influenced detection times, showing that individual surveillance strategies can result in a wide range of detection outcomes, depending on the underlying dynamics of the circulating variants. These findings help contextualize the design, interpretation, and trade-offs of genomic surveillance strategies.

BackgroundDoxycycline post-exposure prophylaxis (DoxyPEP) has demonstrated efficacy for prevention of bacterial sexually transmitted infections. To inform policy decisions on the use of DoxyPEP for gonorrhea prevention, we used a mathematical model to investigate its impact on resistance dynamics and the burden of infection in men who have sex with men (MSM).Methods and FindingsUsing a deterministic compartmental model of gonorrhea transmission in an MSM population, we introduced DoxyPEP at various uptake levels (10-75%) and compared 20-year prevalence and resistance dynamics relative to those at baseline (i.e., no DoxyPEP introduction). Uptake of DoxyPEP resulted in initial drops in the prevalence and incidence of gonorrhea infection, but also accelerated the spread of doxycycline resistance, with increasing DoxyPEP use driving steeper initial declines followed by faster spread of resistance. This resulted in the total loss of DoxyPEP’s clinical efficacy within 1-2 decades in almost all scenarios explored. The magnitude by which DoxyPEP initially reduced the prevalence of infection was constrained by the extent of pre-existing doxycycline resistant strains in the population.De novoemergence of doxycycline resistance did not influence these dynamics. Additionally, the implementation of DoxyPEP had minimal impact on extending the clinically useful lifespan of ceftriaxone monotherapy.ConclusionsModel findings suggest DoxyPEP can be an effective but short-term solution for reducing the burden of gonorrhea infection, as its selection for doxycycline-resistant strains results in loss of its prophylaxis benefit. Increasing levels of DoxyPEP uptake and higher starting prevalence of doxycycline resistance resulted in faster loss of its efficacy and had little change on extending the clinical lifespan of ceftriaxone for treatment ofN. gonorrhoeaeinfections.

Objective:To describe the genomic analysis and epidemiologic response related to a slow and prolonged methicillin-resistant Staphylococcus aureus (MRSA) outbreak.Design:Prospective observational study.Setting:Neonatal intensive care unit (NICU).Methods:We conducted an epidemiologic investigation of a NICU MRSA outbreak involving serial baby and staff screening to identify opportunities for decolonization. Whole-genome sequencing was performed on MRSA isolates.Results:A NICU with excellent hand hygiene compliance and longstanding minimal healthcare-associated infections experienced an MRSA outbreak involving 15 babies and 6 healthcare personnel (HCP). In total, 12 cases occurred slowly over a 1-year period (mean, 30.7 days apart) followed by 3 additional cases 7 months later. Multiple progressive infection prevention interventions were implemented, including contact precautions and cohorting of MRSA-positive babies, hand hygiene observers, enhanced environmental cleaning, screening of babies and staff, and decolonization of carriers. Only decolonization of HCP found to be persistent carriers of MRSA was successful in stopping transmission and ending the outbreak. Genomic analyses identified bidirectional transmission between babies and HCP during the outbreak.Conclusions:In comparison to fast outbreaks, outbreaks that are “slow and sustained” may be more common to units with strong existing infection prevention practices such that a series of breaches have to align to result in a case. We identified a slow outbreak that persisted among staff and babies and was only stopped by identifying and decolonizing persistent MRSA carriage among staff. A repeated decolonization regimen was successful in allowing previously persistent carriers to safely continue work duties.

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.

Post-exposure prophylaxis with doxycycline (doxyPEP) is being introduced to prevent bacterial sexually transmitted infections (STIs). Pre-existing tetracycline resistance inNeisseria gonorrhoeaelimits doxyPEP effectiveness against gonorrhea, and selection for tetracycline resistant lineages may influence prevalence of resistance to other antimicrobials via selection for multi-drug resistant strains. Using genomic and antimicrobial susceptibility data from 5,644 clinical isolates ofN. gonorrhoeae, we assessed the near-term impact of doxyPEP onN. gonorrhoeaeantimicrobial resistance. We found that the impact on antimicrobial resistance is likely to be influenced by the strength of selection for plasmid-encoded and chromosomally-encoded tetracycline resistance, as isolates with high-level, plasmid-encoded resistance had lower minimum inhibitory concentrations to other antimicrobials compared to isolates with low-level tetracycline resistance. The impact of doxyPEP may differ across demographic groups and geographic regions within the United States due to variation in pre-existing tetracycline resistance.

The impact of a prior SARS-CoV-2 infection on the progression of subsequent infections has been unclear. Using a convenience sample of 94,812 longitudinal RT-qPCR measurements from anterior nares and oropharyngeal swabs, we compared the SARS-CoV-2 viral kinetics of firstvs. second infections, adjusting for viral variant, vaccination status, and age. Relative to first infections, second infections usually featured a lower peak viral concentration and faster clearance time, especially in individuals who received a vaccine dose between their first and second infection. Furthermore, a person’s relative (rank-order) viral clearance time, compared to others infected with the same variant, was similar across first and second infections; that is, individuals who had a relatively fast clearance time in their first infection tended to also have a relatively fast clearance time in their second infection. These findings provide evidence that, like vaccination, immunity from a prior SARS-CoV-2 infection shortens the duration of subsequent acute SARS-CoV-2 infections principally by reducing viral clearance time. Additionally, there appears to be an inherent element of the immune response, or some other host factor, that shapes a person’s relative ability to clear SARS-CoV-2 infection that persists across sequential infections.

SARS-CoV-2 antibody titers may serve as a correlate for immunity and could inform optimal booster timing. The relationship between antibody titer and protection from infection was evaluated in 2,323 vaccinated individuals from the National Basketball Association who had antibody levels measured from 9/12/2021—12/31/2021. Cox-proportional hazards models were used to estimate risk of infection within 90-days of serologic testing by titer level (800 AU/mL) and individuals were censored on date of booster receipt. The cohort was 78.2% male, 68.1% aged ≤ 40 years, and 56.4% vaccinated (primary series) with the Pfizer-BioNTech mRNA vaccine. Among the 2,248 individuals not yet boosted at testing, those with titers 800 AU/mL. Serologic titers could inform individual COVID-19 risk and booster scheduling.

The evolution of the obligate human pathogen Neisseria gonorrhoeae has been shaped by selective pressures from diverse host niche environments as well as antibiotics. The varying prevalence of antibiotic resistance across N. gonorrhoeae lineages suggests that underlying metabolic differences may influence the likelihood of acquisition of specific resistance mutations. We hypothesized that the requirement for supplemental CO(2), present in approximately half of isolates, reflects one such example of metabolic variation. Here, using a genome-wide association study and experimental investigations, we show that CO(2)-dependence is attributable to a single substitution in a β-carbonic anhydrase, CanB. CanB(19E) is necessary and sufficient for growth in the absence of CO(2), and the hypomorphic CanB(19G) variant confers CO(2)-dependence. Furthermore, ciprofloxacin resistance is correlated with CanB(19G) in clinical isolates, and the presence of CanB(19G) increases the likelihood of acquisition of ciprofloxacin resistance. Together, our results suggest that metabolic variation has impacted the acquisition of fluoroquinolone resistance.

The CLEAR Trial recently found that decolonization reduced infections and hospitalizations in MRSA carriers in the year following hospital discharge. In this secondary analysis, we explored whether decolonization had a similar benefit in the subgroup of trial participants who harbored USA300, using two different definitions for the USA300 strain-type.

Increasing levels of antibiotic resistance in many bacterial pathogen populations is a major threat to public health. Resistance to an antibiotic provides a fitness benefit when the bacteria is exposed to this antibiotic, but resistance also often comes at a cost to the resistant pathogen relative to susceptible counterparts. We lack a good understanding of these benefits and costs of resistance for many bacterial pathogens and antibiotics, but estimating them could lead to better use of antibiotics in a way that reduces or prevents the spread of resistance. Here, we propose a new model for the joint epidemiology of susceptible and resistant variants, which includes explicit parameters for the cost and benefit of resistance. We show how Bayesian inference can be performed under this model using phylogenetic data from susceptible and resistant lineages and that by combining data from both we are able to disentangle and estimate the resistance cost and benefit parameters separately. We applied our inferential methodology to several simulated datasets to demonstrate good scalability and accuracy. We analysed a dataset ofNeisseria gonorrhoeaegenomes collected between 2000 and 2013 in the USA. We found that two unrelated lineages resistant to fluoroquinolones shared similar epidemic dynamics and resistance parameters. Fluoroquinolones were abandoned for the treatment of gonorrhoea due to increasing levels of resistance, but our results suggest that they could be used to treat a minority of around 10% of cases without causing resistance to grow again.

Shiga toxin-producingE. coli(STEC) can give rise to a range of clinical outcomes from diarrhea to the life-threatening systemic condition, hemolytic uremic syndrome (HUS). Although STEC O157:H7 is the serotype most frequently associated with HUS, a major outbreak of HUS occurred in 2011 in Germany, and was caused by a rare serotype, STEC O104:H4. Prior to 2011 and since the outbreak, STEC O104:H4 strains have only rarely been associated with human infections. From 2012 to 2020 intensified STEC surveillance was performed in Germany where subtyping of ∼8,000 clinical isolates by molecular methods including whole genome sequencing was carried out. A rare STEC serotype O181:H4 associated with HUS was identified and, like the STEC O104:H4 outbreak strain, this strain belongs to sequence type (ST) 678. Genomic and virulence comparisons revealed that the two strains are phylogenetically related and differ principally in the gene cluster encoding their respective lipopolysaccharide O-antigens but exhibit similar virulence phenotypes. In addition, five other serotypes belonging to ST678 from human clinical infection, such as OX13:H4, O127:H4, OgN-RKI9:H4, O131:H4, and O69:H4, were identified from diverse locations worldwide.ImportanceOur data suggest the high virulence ensemble of the STEC O104:H4 outbreak strain remains a global threat because genomically similar strains cause disease worldwide, but that horizontal acquisition of O-antigen gene clusters has diversified the O-antigens of strains belonging to ST678. Thus, identification of these highly pathogenic strains is masked by diverse and rare O-antigens, thereby confounding the interpretation of their potential risk.

The etiologic agent of gonorrhea, Neisseria gonorrhoeae, has become resistant to each of the first line antibiotics used to treat it. However, most isolates in the US remain susceptible to ciprofloxacin, leading to the hypothesis that a diagnostic that accurately reports susceptibility to ciprofloxacin may allow its reintroduction into clinical use. One diagnostic approach is to identify codon 91 in gyrA, where coding for the wildtype serine is associated with ciprofloxacin susceptibility and phenylalanine with resistance. Here, we found that escape from this diagnostic method can occur through gyrA F91S reversion and expansion of pre-existing ciprofloxacin non-susceptible N. gonorrhoeae lineages with gyrA 91S. Furthermore, we found that mutations conferring ciprofloxacin resistance in gyrA 91S isolates led to cross-resistance with zoliflodacin, an antibiotic in phase 3 trial for treatment of gonorrhea. These findings define N. gonorrhoeae mutations that should be monitored via surveillance systems, particularly in populations and regions deploying gyrA 91-based diagnostics, and demonstrate how diagnostics that guide antibiotic therapy can have unintended consequences.

Background In the United States, children aged Methods We conducted an observational study with a cohort of 124 759 children aged Results Children received a mean of 6.8 (95% confidence interval [CI]: 6.7–6.9) antibiotic courses by age 5, and 91% (95% CI: 90%–92%) of children had received at least 1 antibiotic course by age 5. Most antibiotic courses (71%; 95% CI: 70%–72%) were associated with respiratory infections. Presence of a pulmonary/respiratory, otologic, and/or immunological comorbidity substantially increase a child's odds of being in the top 20% of antibiotic recipients. Children with at least 1 of these conditions received a mean of 10.5 (95% CI: 10.4–10.6) antibiotic courses by age 5. Conclusions Privately insured children in the United States receive many antibiotics early in life, largely due to respiratory infections. Antibiotic dispensing varies widely among children, with more antibiotics dispensed to children with pulmonary/respiratory, otologic, and/or immunological comorbidities.

Methicillin-resistant

This study compares the incidence of SARS-CoV-2 infection in players and staff of the National Basketball Association (NBA) who did vs those who did not receive a COVID-19 vaccine booster dose.

Protein glycosylation systems are widely recognized in bacteria, including members of the genus

The evolution of the obligate human pathogen Neisseria gonorrhoeae has been shaped by selective pressures from diverse host niche environments1,2 as well as antibiotics3,4. The varying prevalence of antibiotic resistance across N. gonorrhoeae lineages5 suggests that underlying metabolic differences may influence the likelihood of acquisition of specific resistance mutations6,7. We hypothesized that the requirement for supplemental CO2, present in approximately half of isolates8, reflects one such example of metabolic variation. Here, using a genome-wide association study and experimental investigations, we show that CO2-dependence is attributable to a single substitution in a β-carbonic anhydrase, canB. CanB19E is necessary and sufficient for growth in the absence of CO2, and the hypomorphic CanB19G variant confers CO2-dependence. Furthermore, ciprofloxacin resistance is correlated with CanB19G in clinical isolates, and the presence of CanB19G increases the likelihood of acquisition of ciprofloxacin resistance. Together, our results suggest that metabolic variation has impacted the acquisition of fluoroquinolone resistance.

Background:The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.Methods:We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.Results:Among individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.3–53.6%) remained potentially infectious (Ct Conclusions:SARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.Funding:Supported in part by CDC contract #200-2016-91779, a sponsored research agreement to Yale University from the National Basketball Association contract #21-003529, and the National Basketball Players Association.

MRSA colonization is a critical public health concern. Decolonization protocols have been designed for the clearance of MRSA. Successful decolonization protocols reduce disease incidence; however, multiple protocols exist, comprising diverse therapies targeting multiple body sites, and the optimal protocol is unclear. Here, we formulate a machine learning model using data from a randomized controlled trial (RCT) of MRSA decolonization, which estimates interactions between body sites, quantifies the contribution of each therapy to successful decolonization, and enables predictions of the efficacy of therapy combinations. This work shows how a machine learning model can help design and improve complex clinical protocols., Comment: Extended Abstract presented at Machine Learning for Health (ML4H) symposium 2022, November 28th, 2022, New Orleans, United States & Virtual, http://www.ml4h.cc, 12 pages

Low rates of vaccination, emergence of novel variants of SARS-CoV-2, and increasing transmission relating to seasonal changes leave many U.S. communities at risk for surges of COVID-19 during the winter and spring of 2022 that might strain hospital capacity, as in previous waves. The trajectories of COVID-19 hospitalizations during this period are expected to differ across communities depending on their age distributions, vaccination coverage, cumulative incidence, and adoption of risk mitigating behaviors. Yet, existing predictive models of COVID-19 hospitalizations are almost exclusively focused on national- and state-level predictions. This leaves local policymakers in urgent need of tools that can provide early warnings about the possibility that COVID-19 hospitalizations may rise to levels that exceed local capacity. In this work, we develop simple decision rules to predict whether COVID-19 hospitalization will exceed the local hospitalization capacity within a 4- or 8-week period if no additional mitigating strategies are implemented during this time. These decision rules use real-time data related to hospital occupancy and new hospitalizations associated with COVID-19, and when available, genomic surveillance of SARS-CoV-2. We showed that these decision rules present reasonable accuracy, sensitivity, and specificity (all ≥80%) in predicting local surges in hospitalizations under numerous simulated scenarios, which capture substantial uncertainties over the future trajectories of COVID-19 during the winter and spring of 2022. Our proposed decision rules are simple, visual, and straightforward to use in practice by local decision makers without the need to perform numerical computations.Significance StatementIn many U.S. communities, the risk of exceeding local healthcare capacity during the winter and spring of 2022 remains substantial since COVID-19 hospitalizations may rise due to seasonal changes, low vaccination coverage, and the emergence of new variants of SARS-CoV-2, such as the omicron variant. Here, we provide simple and easy-to-communicate decision rules to predict whether local hospital occupancy is expected to exceed capacity within a 4- or 8-week period if no additional mitigating measures are implemented. These decision rules can serve as an alert system for local policymakers to respond proactively to mitigate future surges in the COVID-19 hospitalization and minimize risk of overwhelming local healthcare capacity.

White Americans make more office-based and emergency department visits per capita than other races/ethnicities, but the proportion of visits during which antibiotics are administered or prescribed is similar across races/ethnicities. Racial/ethnic disparities in antibiotic use may be due more to disparities in healthcare access and utilization than to prescriber behavior.

Antimicrobial resistance in Neisseria gonorrhoeae is a global health concern. Strains from two internationally circulating sequence types, ST-7363 and ST-1901, have acquired resistance to treatment with third-generation cephalosporins mainly due to the emergence of mosaic penA alleles. These two STs were first detected in Japan; however, when and how the mosaic penA alleles emerged and spread to other countries remains unknown. Here, we addressed the evolution of penA alleles by obtaining complete genomes from three Japanese ST-1901 clinical isolates harboring mosaic penA allele 34 (penA-34) dating from 2005 and generating a phylogenetic representation of 1,075 strains sampled from 37 countries. We also sequenced the genomes of 103 Japanese ST-7363 N. gonorrhoeae isolates from 1996-2005 and reconstructed a phylogeny including 88 previously sequenced genomes. Based on an estimate of the time of emergence of ST-1901 harboring mosaic penA-34 and ST-7363 harboring mosaic penA-10, and >300 additional genome sequences of Japanese strains representing multiple STs isolated in 1996-2015, we suggest that penA-34 in ST-1901 was generated from penA-10 via recombination with another Neisseria species, followed by a second recombination event with a gonococcal strain harboring wildtype penA-1. Following the acquisition of penA-10 in ST-7363, a dominant sub-lineage rapidly acquired fluoroquinolone resistance mutations at GyrA 95 and ParC 87-88, possibly due to independent mutations rather than horizontal gene transfer. Literature data suggest the emergence of these resistance determinants may reflect selection from the standard treatment regimens in Japan at that time. Our findings highlight how recombination and antibiotic use across and within Neisseria species intersect in driving the emergence and spread of drug-resistant gonorrhea.Author summaryAntimicrobial resistance is recognized as one of the greatest threats to human health, and Neisseria gonorrhoeae resistance is classified as one of the most urgent. The two major internationally spreading lineages resistant. to first line drugs likely originated in Japan, but when and how their genetic resistance determinants emerged remain unknown. In this study, we conducted an evolutionary analysis using clinical N. gonorrhoeae isolates from 37 countries, including a historical collection of Japanese isolates, to investigate the emergence of resistance in each of the two major lineages. We showed that the penA allele responsible for resistance to cephalosporins, the first-line treatment for gonorrhea, was possibly generated by two recombination events, one from another Neisseria species and one from another N. gonorrhoeae lineage. We also showed that mutations responsible for resistance to a previously widely used antibiotic treatment occurred twice independently in one of the two major lineages. The emergence of the genetic resistance determinants potentially reflects selection from the standard treatment regimen at that time. Our findings highlight how recombination (horizontal gene transfer) and antibiotic use across and within a bacterial species intersect in driving the emergence and spread of antimicrobial resistance genes and mutations.

Study of SARS-CoV-2 Dynamics in the NBA A SARS-CoV-2 surveillance program conducted by the National Basketball Association identified 173 newly infected persons. The viral kinetics were systematica...

In 2020, life expectancy in the United States decreased by an estimated 1.5 years. Due to mortality displacement during the COVID-19 pandemic, life expectancy could soon rebound to above its pre-pandemic baseline. We estimated the size and duration of this anticipated rise in life expectancy through 2030. We found that this rebound could persist for years and will likely be most pronounced in minority populations who suffered the highest rates of mortality during the pandemic. Accounting for this artificial rebound will be critical to avoid funneling resources away from populations that still urgently need them.