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Background Since common diagnostic tests for gonorrhea do not provide information about susceptibility to antibiotics, treatment of gonorrhea remains empiric. Antibiotics used for empiric therapy are usually changed once resistance prevalence exceeds a certain threshold (e.g., 5%). A low switch threshold is intended to increase the probability that an infection is successfully treated with the first-line antibiotic, but it could also increase the pace at which recommendations are switched to newer antibiotics. Little is known about the impact of changing the switch threshold on the incidence of gonorrhea, the rate of treatment failure, and the overall cost and quality-adjusted life-years (QALYs) associated with gonorrhea. Methods and findings We developed a transmission model of gonococcal infection with multiple resistant strains to project gonorrhea-associated costs and loss in QALYs under different switch thresholds among men who have sex with men (MSM) in the United States. We accounted for the costs and disutilities associated with symptoms, diagnosis, treatment, and sequelae, and combined costs and QALYs in a measure of net health benefit (NHB). Our results suggest that under a scenario where 3 antibiotics are available over the next 50 years (2 suitable for the first-line therapy of gonorrhea and 1 suitable only for the retreatment of resistant infections), changing the switch threshold between 1% and 10% does not meaningfully impact the annual number of gonorrhea cases, total costs, or total QALY losses associated with gonorrhea. However, if a new antibiotic is to become available in the future, choosing a lower switch threshold could improve the population NHB. If in addition, drug-susceptibility testing (DST) is available to inform retreatment regimens after unsuccessful first-line therapy, setting the switch threshold at 1% to 2% is expected to maximize the population NHB. A limitation of our study is that our analysis only focuses on the MSM population and does not consider the influence of interventions such as vaccine and common use of rapid drugs susceptibility tests to inform first-line therapy. Conclusions Changing the switch threshold for first-line antibiotics may not substantially change the health and financial outcomes associated with gonorrhea. However, the switch threshold could be reduced when newer antibiotics are expected to become available soon or when in addition to future novel antibiotics, DST is also available to inform retreatment regimens., Author(s): Xuecheng Yin 1,2,3,*, Yunfei Li 4, Minttu M. Rönn 4, Song Li 5, Yue Yuan 6, Thomas L. Gift 7, Katherine Hsu 8, Joshua A. Salomon 9, Yonatan H. [...]

Surveillance systems that monitor pathogen genome sequences are critical for rapidly detecting the introduction and emergence of pathogen variants. To evaluate how interactions between surveillance capacity, variant properties, and the epidemiological context influence the timeliness of pathogen variant detection, we developed a geographically explicit stochastic compartmental model to simulate the transmission of a novel SARS-CoV-2 variant in New York City. We measured the impact of (1) testing and sequencing volume, (2) geographic targeting of testing, (3) the timing and location of variant emergence, and (4) the relative variant transmissibility on detection speed and on the undetected disease burden. Improvements in detection times and reduction of undetected infections were driven primarily by increases in the number of sequenced samples. 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 of pandemic respiratory pathogens. Author summary: To prevent the spread of infections that are more transmissible, evade immunity, or cause more serious illness, public health agencies must quickly detect changes in pathogens such as the virus responsible for COVID-19, which is done by testing the population to identify infections and then sequencing the positive cases to determine which virus variants caused the infections. However, it is unclear how different factors, such as the volume of testing and sequencing, the timing in the outbreak, or the transmissibility of the new variants affect our ability to quickly detect new variants of concern. In our study, we used mathematical simulations of disease spread in New York City to better understand how these factors influence the time it takes to detect a new variant and how many people have been infected by the time it is detected. In our simulations, the greatest improvement in detection speed was achieved by increasing the number of positive cases that are sampled for sequencing. However, factors beyond policymakers' control also influenced the time it took to detect the new variant, meaning that a wide range of detection outcomes was possible even under an ideal public health strategy. These findings help guide decision making for future outbreaks. [ABSTRACT FROM AUTHOR]

In a retrospective, ecological analysis of US medical claims, visit rates explained more of the geographic variation in outpatient antibiotic prescribing rates than per-visit prescribing. Efforts to reduce antibiotic use may benefit from addressing the factors that drive higher rates of outpatient visits, in addition to continued focus on stewardship. [ABSTRACT FROM AUTHOR]

Background Group A Streptococcus (GAS) causes an estimated 5.2 million outpatient visits for pharyngitis annually in the United States, with incidence peaking in winter, but the annual spatiotemporal pattern of GAS pharyngitis across the United States is poorly characterized. Methods We used outpatient claims data from individuals with private medical insurance between 2010 and 2018 to quantify GAS pharyngitis visit rates across U.S. census regions, subregions, and states. We evaluated seasonal and age-based patterns of geographic spread and the association between school start dates and the summertime upward inflection in GAS visits. Results The South had the most visits per person (yearly average, 39.11 visits per 1000 people; 95% confidence interval, 36.21–42.01) and the West had the fewest (yearly average, 17.63 visits per 1000 people; 95% confidence interval, 16.76–18.49). Visits increased earliest in the South and in school-age children. Differences in visits between the South and other regions were most pronounced in the late summer through early winter. Visits peaked earliest in central southern states, in December to January, and latest on the coasts, in March. The onset of the rise in GAS pharyngitis visits correlated with, but preceded, average school start times. Conclusions The burden and timing of GAS pharyngitis varied across the continental United States, with the South experiencing the highest overall rates and earliest onset and peak in outpatient visits. Understanding the drivers of these regional differences in GAS pharyngitis will help in identifying and targeting prevention measures. [ABSTRACT FROM AUTHOR]

SARS‐CoV‐2 antibody levels may serve as a correlate for immunity and could inform optimal booster timing. The relationship between antibody levels and protection from infection was evaluated in vaccinated individuals from the US National Basketball Association who had antibody levels measured at a single time point from September 12, 2021, to December 31, 2021. Cox proportional hazards models were used to estimate the risk of infection within 90 days of serologic testing by antibody level (<250, 250–800, and >800 AU/mL1), adjusting for age, time since last vaccine dose, and history of SARS‐CoV‐2 infection. Individuals were censored on date of booster receipt. The analytic cohort comprised 2323 individuals and was 78.2% male, 68.1% aged ≤40 years, and 56.4% vaccinated (primary series) with the Pfizer‐BioNTech mRNA vaccine. Among the 2248 (96.8%) individuals not yet boosted at antibody testing, 77% completed their primary vaccine series 4–6 months before testing and the median (interquartile range) antibody level was 293.5 (interquartile range: 121.0–740.5) AU/mL. Those with levels <250 AU/mL (adj hazard ratio [HR]: 2.4; 95% confidence interval [CI]: 1.5–3.7) and 250–800 AU/mL (adj HR: 1.5; 95% CI: 0.98–2.4) had greater infection risk compared to those with levels >800 AU/mL. Antibody levels could inform individual COVID‐19 risk and booster scheduling. [ABSTRACT FROM AUTHOR]

Rapid point-of-care tests that diagnose gonococcal infections and identify susceptibility to antibiotics enable individualized treatment. This could improve patient outcomes and slow the emergence and spread of antibiotic resistance. However, little is known about the long-term impact of such diagnostics on the burden of gonorrhea and the effective life span of antibiotics. We used a mathematical model of gonorrhea transmission among men who have sex with men in the United States to project the annual rate of reported gonorrhea cases and the effective life span of ceftriaxone, the recommended antibiotic for first-line treatment of gonorrhea, as well as 2 previously recommended antibiotics, ciprofloxacin and tetracycline, when a rapid drug susceptibility test that estimates susceptibility to ciprofloxacin and tetracycline is available. The use of a rapid drug susceptibility test with ≥50% sensitivity and ≥95% specificity, defined in terms of correct ascertainment of drug susceptibility and nonsusceptibility status, could increase the combined effective life span of ciprofloxacin, tetracycline, and ceftriaxone by at least 2 years over 25 years of simulation. If test specificity is imperfect, however, the increase in the effective life span of antibiotics is accompanied by an increase in the rate of reported gonorrhea cases even under perfect sensitivity. [ABSTRACT FROM AUTHOR]

Background: The National Basketball Association (NBA) suspended operations in response to the COVID-19 pandemic in March 2020. To safely complete the 2019–20 season, the NBA created a closed campus in Orlando, Florida, known as the NBA "Bubble." More than 5000 individuals lived, worked, and played basketball at a time of high local prevalence of SARS-CoV-2. Methods: Stringent protocols governed campus life to protect NBA and support personnel from contracting COVID-19. Participants quarantined before departure and upon arrival. Medical and social protocols required that participants remain on campus, test regularly, physically distance, mask, use hand hygiene, and more. Cleaning, disinfection, and air filtration was enhanced. Campus residents were screened daily and confirmed cases of COVID-19 were investigated. Results: In the Bubble population, 148 043 COVID-19 reverse transcriptase PCR (RT-PCR) tests were performed across approximately 5000 individuals; Orlando had a 4% to 15% test positivity rate in this timeframe. There were 44 COVID-19 cases diagnosed either among persons during arrival quarantine or in non-team personnel while working on campus after testing but before receipt of a positive result. No cases of COVID-19 were identified among NBA players or NBA team staff living in the Bubble once cleared from quarantine. Conclusions: Drivers of success included the requirement for players and team staff to reside and remain on campus, well-trained compliance monitors, unified communication, layers of protection between teams and the outside, activation of high-quality laboratory diagnostics, and available mental health services. An emphasis on data management, evidence-based decision-making, and the willingness to evolve protocols were instrumental to successful operations. These lessons hold broad applicability for future pandemic preparedness efforts. [ABSTRACT FROM AUTHOR]

Methicillin-resistant Staphylococcus aureus (MRSA) is a major cause of morbidity and mortality. Colonization by MRSA increases the risk of infection and transmission, underscoring the importance of decolonization efforts. However, success of these decolonization protocols varies, raising the possibility that some MRSA strains may be more persistent than others. Here, we studied how the persistence of MRSA colonization correlates with genomic presence of antibiotic resistance genes. Our analysis using a Bayesian mixed effects survival model found that genetic determinants of high-level resistance to mupirocin was strongly associated with failure of the decolonization protocol. However, we did not see a similar effect with genetic resistance to chlorhexidine or other antibiotics. Including strain-specific random effects improved the predictive performance, indicating that some strain characteristics other than resistance also contributed to persistence. Study subject-specific random effects did not improve the model. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol. Author summary: Methicillin-resistant Staphylococcus aureus (MRSA) is responsible for a high burden of morbidity and mortality. MRSA colonization incurs risk of MRSA infection and transmission, highlighting the need for highly effective decolonization protocols. However, decolonization protocols have had mixed success. The extent to which this mixed success is attributable to MRSA strain variations and their resistance to antibiotics, including those like mupirocin that are commonly used for decolonization, versus study subject factors, has been unclear. Here, we characterized the effect of antibiotic resistance genes on the efficiency of an MRSA decolonization protocol. We found that mupirocin resistance and strain-specific effects were associated with reduced effectiveness of an MRSA decolonization protocol, but that resistance to other antibiotics, including purported chlorhexidine resistance genes, and subject-specific effects had no discernible impact on protocol success. Our results highlight the need to consider the properties of the colonizing MRSA strain when deciding which treatments to include in the decolonization protocol. [ABSTRACT FROM AUTHOR]

Pre-existing tetracycline resistance in Neisseria gonorrhoeae limits the effectiveness of post-exposure prophylaxis (PEP) with doxycycline against gonorrhea, and selection for tetracycline resistance may influence prevalence of multi-drug resistant strains. Using genomic and antimicrobial susceptibility data from N. gonorrhoeae , we assessed the near-term impact of doxycycline PEP on N. gonorrhoeae resistance. [ABSTRACT FROM AUTHOR]

Objective To analyse the proportions of protein identity between Zika virus and dengue, Japanese encephalitis, yellow fever, West Nile and chikungunya viruses as well as polymorphism between different Zika virus strains. Methods We used published protein sequences for the Zika virus and obtained protein sequences for the other viruses from the National Center for Biotechnology Information (NCBI) protein database or the NCBI virus variation resource. We used BLASTP to find regions of identity between viruses. We quantified the identity between the Zika virus and each of the other viruses, as well as within-Zika virus polymorphism for all amino acid k-mers across the proteome, with k ranging from 6 to 100. We assessed accessibility of protein fragments by calculating the solvent accessible surface area for the envelope and nonstructural-1 (NS1) proteins. Findings In total, we identified 294 Zika virus protein fragments with both low proportion of identity with other viruses and low levels of polymorphisms among Zika virus strains. The list includes protein fragments from all Zika virus proteins, except NS3. NS4A has the highest number (190 k-mers) of protein fragments on the list. Conclusion We provide a candidate list of protein fragments that could be used when developing a sensitive and specific serological test to detect previous Zika virus infections. Objectif Analyser les pourcentages de similarite protelque entre le virus Zika et les virus de la dengue, de l'encephalite japonaise, de la fievre jaune, du Nil occidental et du chikungunya, ainsi que le polymorphisme entre differentes souches du virus Zika. Methodes Nous avons utilise les sequences proteiques publiees du virus Zika et avons obtenu les sequences proteiques des autres virus dans la banque proteique du National Center for Biotechnology Information (NCBI) ou dans la base de donnees Virus Variation du NCBI. Nous avons utilise BLASTP pour identifier les regions de similarite entre les virus. Nous avons quantine la similarite entre le virus Zika et chacun des autres virus ainsi que le polymorphisme du virus Zika pour tous les k-mers d'acldes amines, dans tout le proteome, avec k allant de 6 a 100. Nous avons etudie l'accessibilite des fragments proteiques en calculant la surface accessible au solvant pour les proteines d'enveloppe et non structurale-1 (NS1). Resultats Au total, nous avons identifie 294 fragments proteiques du virus Zika qui presentent a la fois un faible degre de similarite avec les autres virus et un faible degre de polymorphisme entre les souches du virus Zika. Notre liste comprend des fragments proteiques issus de toutes les proteines du virus Zika, a l'exception de la proteine NS3. Le plus grand nombre defragments proteiques de notre liste (190 k-mers) correspond a la proteine NS4A. Conclusion Nous proposons une liste de fragments proteiques candidats, qui pourraient etre utilises pour concevolr un test serologique sensible et specifique pour depister les infections anterieures par le virus Zika. Objective Analizar las proporciones de Identidad proteica entre el virus de Zika y los virus del dengue, la encefalitis japonesa, la fiebre amarilla, el Nilo Occidental y el chikungunya, asi como el polimorfismo entre las distintas cepas del virus de Zika. Metodos Se utilizaron secuencias de proteinas publicadas para el virus de Zika y secuencias de proteinas obtenidas para los otros virus de la base de datos de proteinas del Centro Nacional para la Informacion Biotecnologica (NCBI) o la fuente de informacion sobre la variacion de virus del NCBI. Se utilizo el programa BLASTP para encontrar regiones de identidad entre los virus. Se cuantifico la identidad entre el virus de Zika y cada uno de los otros virus, asi como el polimorfismo del virus de Zika para todos los k-mers de aminoacidos a traves del proteoma, con una variacion de k de 6 a 100. Se evaluo la accesibilidad de los fragmentos proteicos calculando la superficie accesible solvente para las proteinas de envoltura y no estructurales 1 (NS1). Resultados En total, se identificaron 294 fragmentos proteicos del virus de Zika con una proporcion escasa de identidad con otros virus y con niveles bajos de polimorfismos entre las distintas cepas del virus de Zika. En la lista se incluyen fragmentos proteicos de todas las proteinas del virus de Zika, salvo la NS3. La NS4A cuenta con el mayor numero (190 k-mers) de fragmentos proteicos de la lista. Conclusion Se proporciono una lista de posibles fragmentos proteicos que podrian utilizarse para desarrollar una prueba serologica sensible y especifica para detectar infecciones del virus de Zika anteriores., Introduction Monitoring the geographic and the demographic distribution of people infected with Zika virus is important for informing decision-makers and researchers during the ongoing epidemic. Health officials also need further [...]