BACKGROUND: Antiviral post-exposure prophylaxis with neuraminidase inhibitors can reduce the incidence of influenza and the risk of symptomatic influenza, but the efficacy of the other classes of antiviral remains unclear. To support an update of WHO influenza guidelines, this systematic review and network meta-analysis evaluated antiviral drugs for post-exposure prophylaxis of influenza. METHODS: We systematically searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, Global Health, Epistemonikos, and ClinicalTrials.gov for randomised controlled trials published up to Sept 20, 2023 that evaluated the efficacy and safety of antivirals compared with another antiviral or placebo or standard care for prevention of influenza. Pairs of reviewers independently screened studies, extracted data, and assessed the risk of bias. We performed network meta-analyses with frequentist random effects model and assessed the certainty of evidence using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. The outcomes of interest were symptomatic or asymptomatic infection, admission to hospital, all-cause mortality, adverse events related to antivirals, and serious adverse events. This study is registered with PROSPERO, CRD42023466450. FINDINGS: Of 11 845 records identified by our search, 33 trials of six antivirals (zanamivir, oseltamivir, laninamivir, baloxavir, amantadine, and rimantadine) that enrolled 19 096 individuals (mean age 6·75-81·15 years) were included in this systematic review and network meta-analysis. Most of the studies were rated as having a low risk of bias. Zanamivir, oseltamivir, laninamivir, and baloxavir probably achieve important reductions in symptomatic influenza in individuals at high risk of severe disease (zanamivir: risk ratio 0·35, 95% CI 0·25-0·50; oseltamivir: 0·40, 0·26-0·62; laninamivir: 0·43, 0·30-0·63; baloxavir: 0·43, 0·23-0·79; moderate certainty) when given promptly (eg, within 48 h) after exposure to seasonal influenza. These antivirals probably do not achieve important reductions in symptomatic influenza in individuals at low risk of severe disease when given promptly after exposure to seasonal influenza (moderate certainty). Zanamivir, oseltamivir, laninamivir, and baloxavir might achieve important reductions in symptomatic zoonotic influenza in individuals exposed to novel influenza A viruses associated with severe disease in infected humans when given promptly after exposure (low certainty). Oseltamivir, laninamivir, baloxavir, and amantadine probably decrease the risk of all influenza (symptomatic and asymptomatic infection; moderate certainty). Zanamivir, oseltamivir, laninamivir, and baloxavir probably have little or no effect on prevention of asymptomatic influenza virus infection or all-cause mortality (high or moderate certainty). Oseltamivir probably has little or no effect on admission to hospital (moderate certainty). All six antivirals do not significantly increase the incidence of drug-related adverse events or serious adverse events, although the certainty of evidence varies. INTERPRETATION: Post-exposure prophylaxis with zanamivir, oseltamivir, laninamivir, or baloxavir probably decreases the risk of symptomatic seasonal influenza in individuals at high risk for severe disease after exposure to seasonal influenza viruses. Post-exposure prophylaxis with zanamivir, oseltamivir, laninamivir, or baloxavir might reduce the risk of symptomatic zoonotic influenza after exposure to novel influenza A viruses associated with severe disease in infected humans. FUNDING: World Health Organization.

BACKGROUND: The optimal antiviral drug for treatment of severe influenza remains unclear. To support updated WHO influenza clinical guidelines, this systematic review and network meta-analysis evaluated antivirals for treatment of patients with severe influenza. METHODS: We systematically searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Cumulative Index to Nursing and Allied Health Literature, Global Health, Epistemonikos, and ClinicalTrials.gov for randomised controlled trials published up to Sept 20, 2023, that enrolled hospitalised patients with suspected or laboratory-confirmed influenza and compared direct-acting influenza antivirals against placebo, standard care, or another antiviral. Pairs of coauthors independently extracted data on study characteristics, patient characteristics, antiviral characteristics, and outcomes, with discrepancies resolved by discussion or by a third coauthor. Key outcomes of interest were time to alleviation of symptoms, duration of hospitalisation, admission to intensive care unit, progression to invasive mechanical ventilation, duration of mechanical ventilation, mortality, hospital discharge destination, emergence of antiviral resistance, adverse events, adverse events related to treatments, and serious adverse events. We conducted frequentist network meta-analyses to summarise the evidence and evaluated the certainty of evidence using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach. This study is registered with PROSPERO, CRD42023456650. FINDINGS: Of 11 878 records identified by our search, eight trials with 1424 participants (mean age 36-60 years for trials that reported mean or median age; 43-78% male patients) were included in this systematic review, of which six were included in the network meta-analysis. The effects of oseltamivir, peramivir, or zanamivir on mortality compared with placebo or standard care without placebo for seasonal and zoonotic influenza were of very low certainty. Compared with placebo or standard care, we found low certainty evidence that duration of hospitalisation for seasonal influenza was reduced with oseltamivir (mean difference -1·63 days, 95% CI -2·81 to -0·45) and peramivir (-1·73 days, -3·33 to -0·13). Compared with standard care, there was little or no difference in time to alleviation of symptoms with oseltamivir (0·34 days, -0·86 to 1·54; low certainty evidence) or peramivir (-0·05 days, -0·69 to 0·59; low certainty evidence). There were no differences in adverse events or serious adverse events with oseltamivir, peramivir, and zanamivir (very low certainty evidence). Uncertainty remains about the effects of antivirals on other outcomes for patients with severe influenza. Due to the small number of eligible trials, we could not test for publication bias. INTERPRETATION: In hospitalised patients with severe influenza, oseltamivir and peramivir might reduce duration of hospitalisation compared with standard care or placebo, although the certainty of evidence is low. The effects of all antivirals on mortality and other important patient outcomes are very uncertain due to scarce data from randomised controlled trials. FUNDING: World Health Organization.

Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. For the 2021-22 and 2022-23 influenza seasons, 26 forecasting teams provided national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one-to-four weeks ahead. Forecast skill is evaluated using the Weighted Interval Score (WIS), relative WIS, and coverage. Six out of 23 models outperform the baseline model across forecast weeks and locations in 2021-22 and 12 out of 18 models in 2022-23. Averaging across all forecast targets, the FluSight ensemble is the 2(nd) most accurate model measured by WIS in 2021-22 and the 5(th) most accurate in the 2022-23 season. Forecast skill and 95% coverage for the FluSight ensemble and most component models degrade over longer forecast horizons. In this work we demonstrate that while the FluSight ensemble was a robust predictor, even ensembles face challenges during periods of rapid change.

A comprehensive understanding of the spatial distribution and correlates of infection are key for the planning of disease control programs and assessing the feasibility of elimination and/or eradication. In this work, we used species distribution modeling to predict the environmental suitability of the Guinea worm (Dracunculus medinensis) and identify important climatic and sociodemographic risk factors. Using Guinea worm surveillance data collected by the Chad Guinea Worm Eradication Program (CGWEP) from 2010 to 2022 in combination with remotely sensed climate and sociodemographic correlates of infection within an ensemble machine learning framework, we mapped the environmental suitability of Guinea worm infection in Chad. The same analytical framework was also used to ascertain the contribution and influence of the identified climatic risk factors. Spatial distribution maps showed predominant clustering around the southern regions and along the Chari River. We also identified areas predicted to be environmentally suitable for infection. Of note are districts near the western border with Cameroon and southeastern border with Central African Republic. Key environmental correlates of infection as identified by the model were proximity to permanent rivers and inland lakes, farmlands, land surface temperature, and precipitation. This work provides a comprehensive model of the spatial distribution of Guinea worm infections in Chad 2010-2022 and sheds light on potential environmental correlates of infection. As the CGWEP moves toward elimination, the methods and results in this study will inform surveillance activities and help optimize the allocation of intervention resources.

PURPOSE: The Youth Risk Behavior Survey (YRBS) among high school students includes standard questions about sexual identity and sex of sexual contacts, but these questions are not consistently included in every state that conducts the survey. This study aimed to develop and apply a method to predict state-level proportions of high school students identifying as lesbian, gay, or bisexual (LGB) or reporting any same-sex sexual contacts in those states that did not include these questions in their 2017 YRBS. METHODS: We used state-level high school YRBS data from 2013, 2015, and 2017. We defined two primary outcomes relating to self-reported LGB identity and reported same-sex sexual contacts. We developed machine learning models to predict the two outcomes based on other YRBS variables, and comparing different modeling approaches. We used a leave-one-out cross-validation approach and report results from best-performing models. RESULTS: Modern ensemble models outperformed traditional linear models at predicting state-level proportions for the two outcomes, and we identified prediction methods that performed well across different years and prediction tasks. Predicted proportions of respondents reporting LGB identity in states that did not include direct measurement ranged between 9.4% and 12.9%. Predicted proportions of respondents reporting any same-sex contacts, where not directly observed, ranged between 7.0% and 10.4%. CONCLUSION: Comparable population estimates of sexual minority adolescents can raise awareness among state policy makers and the public about what proportion of youth may be exposed to disparate health risks and outcomes associated with sexual minority status. This information can help decision makers in public health and education agencies design, implement and evaluate community and school interventions to improve the health of LGB youth.

Loneliness and lack of social connection are widespread and negatively affect physical and mental health and well-being. Data are limited for persons disproportionately affected by social disconnection, especially those who do not identify as heterosexual and cisgender. Using data from the 2022 Behavioral Risk Factor Surveillance System in 26 U.S. states, CDC examined associations of loneliness and lack of social and emotional support to mental health variables. Prevalence estimates for the mental health variables were significantly higher among adults who reported loneliness and lack of social and emotional support than among those adults who did not. The prevalence of loneliness was highest among respondents who identified as bisexual (56.7%) and transgender (range = 56.4%-63.9%). Prevalence of lack of social and emotional support was highest among those who identified as transgender female (44.8%), transgender gender nonconforming (41.4%), and those with household income below $25,000 (39.8%). Prevalences of stress, frequent mental distress, and history of depression were highest among bisexual (34.3%-54.4%) and transgender adults (36.1%-67.2%). Addressing the threat to mental health among sexual and gender minority groups should include consideration of loneliness and lack of social and emotional support. Providing access to health services that are affirming for sexual and gender minority groups and collecting data to address health inequities might help improve the delivery of culturally competent care.

INTRODUCTION: The risk of diabetes begins at a lower BMI among Asian adults. This study compares the prevalence of diabetes between the U.S. and China by BMI. METHODS: Data from the 2015-2017 China Nutrition and Health Surveillance (n=176,223) and the 2015-2018 U.S. National Health and Nutrition Examination Survey (n=4,464) were used. Diagnosed diabetes was self-reported. Undiagnosed diabetes was no report of diagnosed diabetes and fasting plasma glucose ≥126 mg/dL or HbA1c ≥6.5%. Predicted age-adjusted prevalence estimates by BMI were produced using sex- and country-specific logistic regression models. RESULTS: In China, the age-adjusted prevalence of total diabetes was 7.8% (95% CI=7.4%, 8.3%), lower than the 14.6% (95% CI=13.1%, 16.3%) in the U.S. The prevalence of diagnosed diabetes was also lower in China than in the U.S. There were no statistically significant differences in the prevalence of undiagnosed diabetes between China and the U.S. The distribution of BMI in China was lower than in the U.S., and the predicted prevalence of total diabetes was similar between China and the U.S. when comparing adults with the same BMI. The predicted prevalence of undiagnosed diabetes was higher in China than in the U.S. for both men and women, and this disparity increased with BMI. When comparing adults at the same BMI, there was little difference in the prevalence of total diabetes, but diagnosed diabetes was lower in China than in the U.S., and undiagnosed was higher. CONCLUSIONS: Although differences in BMI appear to explain nearly all of the differences in total diabetes prevalence in the 2 countries, not all factors that are associated with diabetes risk have been investigated.

Phase change material (PCM) has been widely studied for efficient thermal management. This work is the first holistic experimental research on the temperature control performance of PCM-integrated firefighters' gloves. The results showed that the thermal protection time could be extended by 2-5 times in the direct contact to hot object tests and around 1.5 times under the radiant/convective heat source tests when embedding a 1-mm-thick PCM layer in gloves. The PCM of melting point 68 °C showed the best thermal protection performance in all test conditions since it had the most efficient phase change function during the heating process. Considering the PCM location effect, the PCM with lower melting point (68 °C) showed better performance when located close to external environment (heat source) and the PCM with higher melting point (108 °C and 151 °C) showed better performance when located close to hand. The optimum PCM thickness would be in the range of 0.5-1.0 mm for both thermal protection improvement and hand dexterity purposes. In addition, the time for continuous temperature rises on the hand surface at post-heat exposure was longer when embedding PCM in firefighters’ gloves due to the stored latent heat in PCM. © 2024 The Authors

Diesel particulate matter (DPM) is a common and well-known health hazard in the mining environment. The regulatory method for monitoring both the organic and elemental carbon (OC, EC) portions of DPM is a laboratory-based thermal-optical method with a typical turnaround time of one week. In order to evaluate exposure levels and take corrective action prior to overexposure, a portable real-time device capable of quantifying both OC and EC is needed. To that end, researchers from the National Institute for Occupational Safety and Health (NIOSH) designed and tested the feasibility of a device based on bandpass optical filters that target key infrared wavelengths associated with DPM and its spectroscopic baseline. The resulting device, referred to here as a non-dispersive infrared (NDIR) spectrometer could serve as the basis of a cost-effective, field-portable alternative to the laboratory thermal-optical method. The limits of quantification (LOD) indicate that the NDIR spectrometer can quantify EC, OC, and TC provided they are present at 20, 37, and 46 μg/m3 or more, respectively. In the event that the NDIR spectrometer is integrated with a sampler and filter tape the LOD is estimated to be reduced to 13, 7, and 10 μg/m3 for EC, OC, and TC, respectively. These LOD estimates assume a face velocity of 59 cm/s and a sampling time of 30 min. ©, This work was authored as part of the Contributor's official duties as an Employee of the United States Government and is therefore a work of the United States Government. In accordance with 17 USC. 105, no copyright protection is available for such works under US Law.

Social determinants of health (SDOH) are a broad array of social and contextual conditions where persons are born, live, learn, work, play, worship, and age that influence their physical and mental wellbeing and quality of life. Using 2022 Behavioral Risk Factor Surveillance System data, this study assessed measures of adverse SDOH and health-related social needs (HRSN) among U.S. adult populations. Measures included life satisfaction, social and emotional support, social isolation or loneliness, employment stability, food stability/security, housing stability/security, utility stability/security, transportation access, mental well-being, and health care access. Prevalence ratios were adjusted for age, sex, education, marital status, income, and self-rated health. Social isolation or loneliness (31.9%) and lack of social and emotional support (24.8%) were the most commonly reported measures, both of which were more prevalent among non-Hispanic (NH) American Indian or Alaska Native, NH Black or African American, NH Native Hawaiian or other Pacific Islander, NH multiracial, and Hispanic or Latino adults than among NH White adults. The majority of prevalence estimates for other adverse SDOH and HRSN were also higher across all other racial and ethnic groups (except for NH Asian) compared with NH White adults. SDOH and HRSN data can be used to monitor needed social and health resources in the U.S. population and help evaluate population-scale interventions.

OBJECTIVES: To examine the prevalence and trends in severe obesity among 16.6 million children aged 2 to 4 years enrolled in the Special Supplemental Nutrition Program for Women, Infants, and Children (WIC) from 2010 to 2020. METHODS: Severe obesity was defined as a sex-specific BMI for age ≥120% of the 95th percentile on the Centers for Disease Control and Prevention growth charts or BMI ≥35 kg/m2. Joinpoint regression was used to identify when changes occurred in the overall trend. Logistic regression was used to compute the adjusted prevalence differences between years controlling for sex, age, and race and ethnicity. RESULTS: The prevalence of severe obesity significantly decreased from 2.1% in 2010 to 1.8% in 2016 and then increased to 2.0% in 2020. From 2010 to 2016, the prevalence decreased significantly among all sociodemographic subgroups except for American Indian/Alaska Native (AI/AN) children. The largest decreases were among 4-year-olds, Asian/Pacific Islander and Hispanic children, and children from higher-income households. However, from 2016 to 2020, the prevalence increased significantly overall and among sociodemographic subgroups, except for AI/AN and non-Hispanic white children. The largest increases occurred in 4-year-olds and Hispanic children. Among 56 WIC agencies, the prevalence significantly declined in 17 agencies, and 1 agency (Mississippi) showed a significant increase from 2010 to 2016. In contrast, 21 agencies had significant increases, and only Alaska had a significant decrease from 2016 to 2020. CONCLUSIONS: Although severe obesity prevalence in toddlers declined from 2010 to 2016, recent trends are upward. Early identification and access to evidence-based family healthy weight programs for at-risk children can support families and child health.

In 2021, the Association for Diagnostics & Laboratory Medicine (ADLM) (formerly the American Association for Clinical Chemistry [AACC]) developed a scientific study that aimed to contribute to the understanding of SARS-CoV-2 immunity during the evolving course of the pandemic. This study was led by a group of expert member volunteers and resulted in survey data from 975 individuals and blood collection from 698 of those participants. This paper describes the formulation and execution of this large-scale scientific study, encompassing best practices and insights gained throughout the endeavor.

BACKGROUND: The National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) has amassed a vast reservoir of genetic data since its inception in 2007. These public data hold immense potential for supporting pathogen surveillance and control. However, the lack of standardized metadata and inconsistent submission practices in SRA may impede the data's utility in public health. METHODS: To address this issue, we introduce the Search-based Geographic Metadata Curation (SGMC) pipeline. SGMC utilized Python and web scraping to extract geographic data of sequencing institutions from NCBI SRA in the Cloud and its website. It then harnessed ChatGPT to refine the sequencing institution and location assignments. To illustrate the pipeline's utility, we examined the geographic distribution of the sequencing institutions and their countries relevant to polio eradication and categorized them. RESULTS: SGMC successfully identified 7,649 sequencing institutions and their global locations from a random selection of 2,321,044 SRA accessions. These institutions were distributed across 97 countries, with strong representation in the United States, the United Kingdom and China. However, there was a lack of data from African, Central Asian, and Central American countries, indicating potential disparities in sequencing capabilities. Comparison with manually curated data for U.S. institutions reveals SGMC's accuracy rates of 94.8% for institutions, 93.1% for countries, and 74.5% for geographic coordinates. CONCLUSION: SGMC may represent a novel approach using a generative AI model to enhance geographic data (country and institution assignments) for large numbers of samples within SRA datasets. This information can be utilized to bolster public health endeavors.

Macrolides of different ring sizes are critically important antimicrobials for human medicine and veterinary medicine, though the widely used 15-membered ring azithromycin in humans is not approved for use in veterinary medicine. We document here the emergence of azithromycin-resistant Salmonella among the NARMS culture collections between 2011 and 2021 in food animals and retail meats, some with co-resistance to ceftriaxone or decreased susceptibility to ciprofloxacin. We also provide insights into the underlying genetic mechanisms and genomic contexts, including the first report of a novel combination of azithromycin resistance determinants and the characterization of multidrug-resistant plasmids. Further, we highlight the emergence of a multidrug-resistant Salmonella Newport clone in food animals (mainly cattle) with both azithromycin resistance and decreased susceptibility to ciprofloxacin. These findings contribute to a better understating of azithromycin resistance mechanisms in Salmonella and warrant further investigations on the drivers behind the emergence of resistant clones.

INTRODUCTION: Survey breakoff is an important source of total survey error. Most studies of breakoff have been of web surveys-less is known about telephone surveys. In the past decade, the breakoff rate has increased in the Behavioral Risk Factor Surveillance System, the world's largest annual telephone survey. Analysis of breakoff in Behavioral Risk Factor Surveillance System can improve the quality of Behavioral Risk Factor Surveillance System. It will also provide evidence in research of total survey error on telephone surveys. METHODS: We used data recorded as breakoff in the 2018 and 2019 Behavioral Risk Factor Surveillance System. We converted questions and modules to a time variable and applied Kaplan-Meier method and a proportional hazard model to estimate the conditional and cumulative probabilities of breakoff and study the potential risk factors associated with breakoff. RESULTS: Cumulative probability of breakoffs up to the end of the core questionnaire was 7.03% in 2018 and 9.56% in 2019. The highest conditional probability of breakoffs in the core was 2.85% for the physical activity section. Cumulative probability of breakoffs up to the end of the core was higher among those states that inserted their own questions or optional modules than among those that did not in both years. The median risk ratio of breakoff among all states was 5.70 in 2018 and 3.01 in 2019. Survey breakoff was associated with the length of the questionnaire, the extent of expected recollection, and the location of questions. CONCLUSIONS: Breakoff is not an ignorable component of total survey error and should be considered in Behavioral Risk Factor Surveillance System data analyses when variables have higher breakoff rates.

BACKGROUND: China's National Free Antiretroviral Treatment Program began in 2002 and, by August 2008, included over 52,000 patients. OBJECTIVE: To report five year outcomes on adult mortality and immunological treatment failure rates and risk factors. DESIGN: Open cohort analysis of prospectively collected observational database. PATIENTS: All patients in national treatment database from June 2002-August 2008. Patients excluded if not started on triple therapy or had missing treatment regimen information. INTERVENTION: Antiretroviral therapy per Chinese national treatment guidelines. MEASUREMENTS: Mortality rate and immunologic treatment failure rate using World Health Organization criteria. RESULTS: Of 52,191 total patients, 48,785 were included. Median age was 38 years, 58% were male, 53% were infected through plasma/blood, and median baseline CD4 cell count was 118/μL. Mortality was greatest during the first three months of treatment (22.6/100 person-years) but declined to a steady rate of 4-5/100 person-years after six months and maintained over the subsequent 4½ years. Baseline CD4 cell count <50/μL (adjusted hazard ratio [HR] 3.3, 95% confidence interval [CI] 2.9-3.8, compared to ≥200/μL) and having 4-5 baseline symptom categories (adjusted HR 3.4, 95% CI 2.9-4.0, compared to no baseline symptoms) were the strongest mortality risk factors. Treatment failure was determined among 31,070 with ≥1 follow-up CD4 cell count. Overall, 25% (12.0/100 person-years) failed treatment with the cumulative treatment failure rate increasing to 50% at five years. LIMITATION: Immunologic treatment failure does not necessarily correlate well with virologic treatment failure. CONCLUSIONS: The National Free Antiretroviral Treatment Program reduced mortality among adult AIDS patients in China to rates comparable to other low or middle-income countries. A cumulative immunological treatment failure rate of 50% after five years, with limited availability of second-line regimens, is of great concern.

In April 2023, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was amended and emended. The phylum was expanded by one new family, 14 new genera, and 140 new species. Two genera and 538 species were renamed. One species was moved, and four were abolished. This article presents the updated taxonomy of Negarnaviricota as now accepted by the ICTV.

BACKGROUND: Key population HIV programmes in sub-Saharan Africa require epidemiological information to ensure equitable and universal access to effective services. We aimed to consolidate and harmonise survey data among female sex workers, men who have sex with men, people who inject drugs, and transgender people to estimate key population size, HIV prevalence, and antiretroviral therapy (ART) coverage for countries in mainland sub-Saharan Africa. METHODS: Key population size estimates, HIV prevalence, and ART coverage data from 39 sub-Saharan Africa countries between 2010 and 2023 were collated from existing databases and verified against source documents. We used Bayesian mixed-effects spatial regression to model urban key population size estimates as a proportion of the gender-matched, year-matched, and area-matched population aged 15-49 years. We modelled subnational key population HIV prevalence and ART coverage with age-matched, gender-matched, year-matched, and province-matched total population estimates as predictors. FINDINGS: We extracted 2065 key population size data points, 1183 HIV prevalence data points, and 259 ART coverage data points. Across national urban populations, a median of 1·65% (IQR 1·35-1·91) of adult cisgender women were female sex workers, 0·89% (0·77-0·95) were men who have sex with men, 0·32% (0·31-0·34) were men who injected drugs, and 0·10% (0·06-0·12) were women who were transgender. HIV prevalence among key populations was, on average, four to six times higher than matched total population prevalence, and ART coverage was correlated with, but lower than, the total population ART coverage with wide heterogeneity in relative ART coverage across studies. Across sub-Saharan Africa, key populations were estimated as comprising 1·2% (95% credible interval 0·9-1·6) of the total population aged 15-49 years but 6·1% (4·5-8·2) of people living with HIV. INTERPRETATION: Key populations in sub-Saharan Africa experience higher HIV prevalence and lower ART coverage, underscoring the need for focused prevention and treatment services. In 2024, limited data availability and heterogeneity constrain precise estimates for programming and monitoring trends. Strengthening key population surveys and routine data within national HIV strategic information systems would support more precise estimates. FUNDING: UNAIDS, Bill & Melinda Gates Foundation, and US National Institutes of Health.

Orthobunyaviruses have been reported to cause severe diseases in humans or animals, posing a threat to human health and social economy. Ebinur lake virus (EBIV) is a newly classified orthobunyavirus, which needs further intensive study and therapies to cope with its potential infection risk to human and animals. Here, through the reverse genetics system, the recombinant EBIV of wild type (rEBIV/WT) and NP-conjugated-eGFP (rEBIV/eGFP/S) were rescued for the application of the rapid antiviral drug screening. The eGFP fluorescence signal of the rEBIV/eGFP/S was stable in the process of successive passage in BHK-21 cells (over 10 passages) and this recombinant virus could replicate in various cell lines. Compared to the wild type EBIV, the rEBIV/eGFP/S caused the smaller plaques and its peak titers were lower, suggesting attenuation due to the eGFP insertion. Through the high-content screening (HCS) system, ribavirin showed an inhibitory effect on the rEBIV/eGFP/S with an EC50 of 21.91 μM, while favipiravir did not inhibit, even at high concentrations. In addition, five of ninety-six natural compounds had antiviral against EBIV. The robust reverse genetics system for EBIV will facilitate investigation into replication and assembly mechanisms and assist drug and vaccine development.Competing Interest StatementThe authors have declared no competing interest.

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. In 2020, the COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized hundreds of thousands of specific predictions from more than 50 different academic, industry, and independent research groups. This manuscript systematically evaluates 23 models that regularly submitted forecasts of reported weekly incident COVID-19 mortality counts in the US at the state and national level. One of these models was a multi-model ensemble that combined all available forecasts each week. The performance of individual models showed high variability across time, geospatial units, and forecast horizons. Half of the models evaluated showed better accuracy than a naïve baseline model. In combining the forecasts from all teams, the ensemble showed the best overall probabilistic accuracy of any model. Forecast accuracy degraded as models made predictions farther into the future, with probabilistic accuracy at a 20-week horizon more than 5 times worse than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.Competing Interest StatementAV, MC, and APP report grants from Metabiota Inc outside the submitted work.Funding StatementFor teams that reported receiving funding for their work, we report the sources and disclosures below. CMU-TimeSeries: CDC Center of Excellence, gifts from Google and Facebook. CU-select: NSF DMS-2027369 and a gift from the Morris-Singer Foundation. COVIDhub: This work has been supported by the US Centers for Disease Control and Prevention (1U01IP001122) and the National Institutes of General Medical Sciences (R35GM119582). The content is solely the responsibility of the authors and does not necessarily represent the official views of CDC, NIGMS or the National Institutes of Health. Johannes Bracher was supported by the Helmholtz Foundation via the SIMCARD Information&amp; Data Science Pilot Project. Tilmann Gneiting gratefully acknowledges support by the Klaus Tschira Foundation. DDS-NBDS: NSF III-1812699. EPIFORECASTS-ENSEMBLE1: Wellcome Trust (210758/Z/18/Z) GT_CHHS-COVID19: William W. George Endowment, Virginia C. and Joseph C. Mello Endowments, NSF DGE-1650044, NSF MRI 1828187, research cyberinfrastructure resources and services provided by the Partnership for an Advanced Computing Environment (PACE) at Georgia Tech, and the following benefactors at Georgia Tech: Andrea Laliberte, Joseph C. Mello, Richard Rick E. &amp; Charlene Zalesky, and Claudia &amp; Paul Raines GT-DeepCOVID: CDC MInD-Healthcare U01CK000531-Supplement. NSF (Expeditions CCF-1918770, CAREER IIS-2028586, RAPID IIS-2027862, Medium IIS-1955883, NRT DGE-1545362), CDC MInD program, ORNL and funds/computing resources from Georgia Tech and GTRI. IHME: This work was supported by the Bill &amp; Melinda Gates Foundation, as well as funding from the state of Washington and the National Science Foundation (award no. FAIN: 2031096). IowaStateLW-STEM: Iowa State University Plant Sciences Institute Scholars Program, NSF DMS-1916204, NSF CCF-1934884, Laurence H. Baker Center for Bioinformatics and Biological Statistics. JHU_IDD-CovidSP: State of California, US Dept of Health and Human Services, US Dept of Homeland Security, US Office of Foreign Disaster Assistance, Johns Hopkins Health System, Office of the Dean at Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University Modeling and Policy Hub, Centers fo Disease Control and Prevention (5U01CK000538-03), University of Utah Immunology, Inflammation, &amp; Infectious Disease Initiative (26798 Seed Grant). LANL-GrowthRate: LANL LDRD 20200700ER. MOBS-GLEAM_COVID: COVID Supplement CDC-HHS-6U01IP001137-01. NotreDame-mobility and NotreDame-FRED: NSF RAPID DEB 2027718 UA-EpiCovDA: NSF RAPID Grant # 2028401. UCSB-ACTS: NSF RAPID IIS 2029626. UCSD-NEU: Google Faculty Award, DARPA W31P4Q-21-C-0014, COVID Supplement CDC-HHS-6U01IP001137-01. UMass-MechBayes: NIGMS R35GM119582, NSF 1749854. UMich-RidgeTfReg: The University of Michigan Physics Department and the University of Michigan Office of Research.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:UMass-Amherst IRBAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAll data and code referred to in the manuscript are publicly available. https://github.com/reichlab/covid19-forecast-hub/ https://github.com/reichlab/covidEnsembles https://zoltardata.com/project/44

The need for high-affinity, SARS-CoV-2-specific monoclonal antibodies (mAbs) is critical in the face of the global COVID-19 pandemic, as such reagents can have important diagnostic, research, and therapeutic applications. Of greatest interest is the ~300 amino acid receptor binding domain (RBD) within the S1 subunit of the spike protein because of its key interaction with the human angiotensin converting enzyme 2 (hACE2) receptor present on many cell types, especially lung epithelial cells. We report here the development and functional characterization of 29 nanomolar-affinity mouse SARS-CoV-2 mAbs created by an accelerated immunization and hybridoma screening process. Differing functions, including binding of diverse protein epitopes, viral neutralization, impact on RBD-hACE2 binding, and immunohistochemical staining of infected lung tissue, were correlated with variable gene usage and sequence.Competing Interest StatementThe authors have declared no competing interest.

Background The coronavirus disease 2019 (COVID-19) pandemic has resulted in severe shortages of personal protective equipment (PPE) necessary to protect front-line healthcare personnel. These shortages underscore the urgent need for simple, efficient, and inexpensive methods to decontaminate SARS-CoV-2-exposed PPE enabling safe reuse of masks and respirators. Efficient decontamination must be available not only in low-resourced settings, but also in well-resourced settings affected by PPE shortages. Methylene blue (MB) photochemical treatment, hitherto with many clinical applications including those used to inactivate virus in plasma, presents a novel approach for widely applicable PPE decontamination. Dry heat (DH) treatment is another potential low-cost decontamination method.Methods MB and light (MBL) and DH treatments were used to inactivate coronavirus on respirator and mask material. We tested three N95 filtering facepiece respirators (FFRs), two medical masks (MMs), and one cloth community mask (CM). FFR/MM/CM materials were inoculated with SARS-CoV-2 (a Betacoronavirus), murine hepatitis virus (MHV) (a Betacoronavirus), or porcine respiratory coronavirus (PRCV) (an Alphacoronavirus), and treated with 10 µM MB followed by 50,000 lux of broad-spectrum light or 12,500 lux of red light for 30 minutes, or with 75°C DH for 60 minutes. In parallel, we tested respirator and mask integrity using several standard methods and compared to the FDA-authorized vaporized hydrogen peroxide plus ozone (VHP+O3) decontamination method. Intact FFRs/MMs/CM were subjected to five cycles of decontamination (5CD) to assess integrity using International Standardization Organization (ISO), American Society for Testing and Materials (ASTM) International, National Institute for Occupational Safety and Health (NIOSH), and Occupational Safety and Health Administration (OSHA) test methods.Findings Overall, MBL robustly and consistently inactivated all three coronaviruses with at least a 4-log reduction. DH yielded similar results, with the exception of MHV, which was only reduced by 2-log after treatment. FFR/MM integrity was maintained for 5 cycles of MBL or DH treatment, whereas one FFR failed after 5 cycles of VHP+O3. Baseline performance for the CM was variable, but reduction of integrity was minimal.Interpretation Methylene blue with light and DH treatment decontaminated masks and respirators by inactivating three tested coronaviruses without compromising integrity through 5CD. MBL decontamination of masks is effective, low-cost and does not require specialized equipment, making it applicable in all-resource settings. These attractive features support the utilization and continued development of this novel PPE decontamination method.Competing Interest StatementAuthors Thomas S. Lendvay, James Chen are Co-Founders and equity owners of Singletto, Inc. (Seattle, WA, USA) Authors Yi Cui and Steven Chu are Co-Founders and equity owners of 4C Air, Inc. (Sunnyvale, CA)Funding StatementThis study was funded by Open Philanthropy; Amazon Inc./University of Washington Catalyst Award; University of Liege (Belgium) and the Walloon Region, Belgium; Li Ka Shing Institute; Alberta Health Services; and an Anonymous donor to the University of Washington, Department of Urology.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Stanford University and Alberta Health Services/University of Calgary were exempt from IRB as the human fit testing was considered Quality Improvement. ERB for clinical specimen use: A clinical saliva specimen with a SARS-CoV-2 was provided by Dr. John Conly from Calgary, Alberta with Calgary ERB approval (ID# Pro00099761).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective inte ventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData will be freely shared post publication on reasonable request by contacting the corresponding author of the study.

Antimicrobial resistance (AMR) is a major public health problem that requires publicly available tools for rapid analysis. To identify acquired AMR genes in whole genome sequences, the National Center for Biotechnology Information (NCBI) has produced a high-quality, curated, AMR gene reference database consisting of up-to-date protein and gene nomenclature, a set of hidden Markov models (HMMs), and a curated protein family hierarchy. Currently, the Bacterial Antimicrobial Resistance Reference Gene Database contains 4,579 antimicrobial resistance gene proteins and more than 560 HMMs.Here, we describe AMRFinder, a tool that uses this reference dataset to identify AMR genes. To assess the predictive ability of AMRFinder, we measured the consistency between predicted AMR genotypes from AMRFinder against resistance phenotypes of 6,242 isolates from the National Antimicrobial Resistance Monitoring System (NARMS). This included 5,425 Salmonella enterica, 770 Campylobacter spp., and 47 Escherichia coli phenotypically tested against various antimicrobial agents. Of 87,679 susceptibility tests performed, 98.4% were consistent with predictions.To assess the accuracy of AMRFinder, we compared its gene symbol output with that of a 2017 version of ResFinder, another publicly available resistance gene database. Most gene calls were identical, but there were 1,229 gene symbol differences between them, with differences due to both algorithmic differences and database composition. AMRFinder missed 16 loci that Resfinder found, while Resfinder missed 1,147 loci AMRFinder identified. Two missing drug classes from the 2017 version of ResFinder contributed 81% of missed loci. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system.Importance Antimicrobial resistance is a major public health problem. Traditionally, antimicrobial resistance has been identified using phenotypic assays. With the advent of genome sequencing, we now can identify resistance genes and deduce if an isolate could be resistant to antibiotics. We describe a database of 4,579 acquired antimicrobial resistance genes, the largest publicly available, and a software tool to identify genes in bacterial genomes, AMRFinder. Unlike other tools, AMRFinder uses a gene hierarchy to prevent overpredicting what the correct gene call should be, enabling more accurate assessment. To assess these resources, we determined the resistance gene content of over 6,200 bacterial isolates from the National Antimicrobial Resistance Monitoring System that have been assayed using traditional methods and that also have had their genomes sequenced. We also compared our gene assessments to those of a popularly used tool. We found that AMRFinder has a high overall consistency between genotypes and phenotypes.

Next-generation sequencing is a powerful tool for virological surveillance. While Illumina® and Ion Torrent® sequencing platforms are used extensively for generating viral RNA genome sequences, there is limited data comparing different platforms. We evaluated the Illumina MiSeq, Ion Torrent PGM and Ion Torrent S5 platforms using a panel of sixteen specimens containing picornaviruses and human caliciviruses (noroviruses and sapoviruses). The specimens were processed, using combinations of three library preparation and five sequencing kits, to assess the quality and completeness of assembled viral genomes, and an estimation of cost per sample to generate the data was calculated. The choice of library preparation kit and sequencing platform was found to impact the breadth of genome coverage and accuracy of consensus viral genomes. The Ion Torrent S5 outperformed the older Ion Torrent PGM platform in data quality and cost, and generated the highest proportion of reads for enterovirus D68 samples. However, indels at homopolymer regions impacted the accuracy of consensus genome sequences. For lower throughput sequencing runs (i.e., Ion Torrent 510 or Illumina MiSeq Nano V2), the cost per sample was lower on the MiSeq platform, whereas with higher throughput runs (Ion Torrent 530 or Illumina MiSeq V2) the cost per sample was comparable. These findings suggest that the Ion Torrent S5 and Illumina MiSeq platforms are both viable options for genomic sequencing of RNA viruses, each with specific advantages and tradeoffs.

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Monkeypox is a viral zoonotic disease endemic in Central and West Africa. In May 2022, dozens of non-endemic countries reported hundreds of monkeypox cases, most with no epidemiological link to Africa. We identified two lineages of Monkeypox virus (MPXV) among nine 2021 and 2022 U.S. monkeypox cases. A 2021 case was highly similar to the 2022 MPXV outbreak variant, suggesting a common ancestor. Analysis of mutations among these two lineages revealed an extreme preference for GA-to-AA mutations indicative of APOBEC3 cytosine deaminase activity that was shared among West African MPXV since 2017 but absent from Congo Basin lineages. Poxviruses are not thought to be subject to APOBEC3 editing; however, these findings suggest APOBEC3 activity has been recurrent and dominant in recent West African MPXV evolution. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the emergence of many new variant lineages that have exacerbated the COVID-19 pandemic. Some of those variants were designated as variants of concern/interest (VOC/VOI) by national or international authorities based on many factors including their potential impact on vaccines. To ascertain and rank the risk of VOCs and VOIs, we analyzed their ability to escape from vaccine-induced antibodies. The variants showed differential reductions in neutralization and replication titers by post-vaccination sera. Although the Omicron variant showed the most escape from neutralization, sera collected after a third dose of vaccine (booster sera) retained moderate neutralizing activity against that variant. Therefore, vaccination remains the most effective strategy to combat the COVID-19 pandemic.

Background: We have previously shown that the time of Chlamydia infection was crucial in determining the chlamydial infectivity and pathogenesis. This study aims to determine whether the time of Chlamydia infection affects the genital tract microbiome. This study analyzed mice vaginal, uterine, and ovary/oviduct microbiome with and without Chlamydia infection. The mice were infected with Chlamydia at either 10:00 am (ZT3) or 10:00 pm (ZT15). Result(s): The results showed that mice infected at ZT3 had higher Chlamydia infectivity than those infected at ZT15. There was more variation in the compositional complexity of the vaginal microbiome (alpha diversity) of mice infected at ZT3 than those mice infected at ZT15 throughout the infection within each treatment group, with both Shannon and Simpson diversity index values decreased over time. The analysis of samples collected four weeks post-infection showed that there were significant taxonomical differences (beta diversity) between different parts of the genital tract-vagina, uterus, and ovary/oviduct-and this difference was associated with the time of infection. Firmicutes and Proteobacteria were the most abundant phyla within the microbiome in all three genital tract regions for all the samples collected during this experiment. Additionally, Firmicutes was the dominant phylum in the uterine microbiome of ZT3 Chlamydia infected mice. Conclusion(s): The results show that the time of infection is associated with the microbial dynamics in the genital tract. And this association is more robust in the upper genital tract than in the vagina. This result implies that more emphasis should be placed on understanding the changes in the microbial dynamics of the upper genital tract over the course of infection. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.

Genomic surveillance of monkeypox virus (MPXV) during the 2022 outbreak has been mainly focused on single nucleotide polymorphism (SNP) changes. DNA viruses, including MPXV, have a lower SNP mutation rate than RNA viruses due to higher fidelity replication machinery. We identified a large genomic rearrangement in a MPXV sequence from a 2022 case in the state of Minnesota (MN), USA, from an abnormal, uneven MPXV read mapping coverage profile in whole-genome sequencing (WGS) data. We further screened WGS data of 206 U.S. MPXV samples and found seven (3.4 percent) sequenced genomes contained similar abnormal read coverage profiles that suggested putative large deletions or genomic rearrangements. Here, we present three MPXV genomes containing deletions ranging from 2.3 to 15 kb and four genomes containing more complex rearrangements. Five genomic changes were each only seen in one sample, but two sequences from linked cases shared an identical 2.3 kb deletion in the 3' terminal region. All samples were positive using VAC1 and Clade II (formerly West African)-specific MPXV diagnostic tests; however, large deletions and genomic rearrangements like the ones reported here have the potential to result in viruses in which the target of a PCR diagnostic test is deleted. The emergence of genomic rearrangements during the outbreak may have public health implications and highlight the importance of continued genomic surveillance. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. This article is a US Government work. It is not subject to copyright under 17 USC 105 and is also made available for use under a CC0 license.

Background: HIV programmes in sub-Saharan Africa (SSA) require information about HIV among key populations to ensure equitable and equal access to HIV prevention and treatment. Surveillance has been conducted among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender populations, but is not systematically included in national HIV estimates. We consolidated existing KP surveys to create national-level estimates of key population size, HIV prevalence, and ART coverage for mainland SSA. Method(s): Key population size estimates (KPSE), HIV prevalence, and ART coverage data from 38 countries from 2010-2021 were collated from existing databases, deduplicated, and verified against primary sources. We used Bayesian mixed-effects regression to spatially smooth KPSE, and regressed subnational key population HIV prevalence and ART coverage against age/sex/year/province-matched total population estimates. Finding(s): We extracted 1449 unique KPSE datapoints, 1181 HIV prevalence datapoints, and 242 ART coverage datapoints. Countries had data for a median of five of the twelve population/outcome stratifications. Across countries, a median of 1.44% of urban women were FSW (interquartile range [IQR] 0.83-1.89%); 0.60% of urban men were MSM; and 0.16% of urban adults injected drugs (IQR 0.14-0.24%). HIV prevalence in all key populations was higher than matched total population prevalence. ART coverage was correlated with, but lower than, total population ART coverage. Across SSA, key populations were estimated as 1.1% (95%CI 0.7-1.9%) of the population but 5.1% (95%CI 3.2-10.3%) of all PLHIV aged 15-49 years. Interpretation(s): Key populations in sub-Saharan experience disproportionate HIV burden and somewhat lower ART coverage, underscoring need for focused prevention and treatment services. However, large heterogeneity and incomplete data availability limit precise estimates for programming and monitoring trends. Future efforts should focus on integrating and strengthening key population surveys and routine data within national HIV strategic information systems. Copyright The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.