PROBLEM/CONDITION: Seasonal influenza accounts for 9.3 million-41 million illnesses, 100,000-710,000 hospitalizations, and 4,900-51,000 deaths annually in the United States. Since 2003, the Influenza Hospitalization Surveillance Network (FluSurv-NET) has been conducting population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in the United States, including weekly rate estimations and descriptions of clinical characteristics and outcomes for hospitalized patients. However, a comprehensive summary of trends in hospitalization rates and clinical data collected from the surveillance platform has not been available. REPORTING PERIOD: 2010-11 through 2022-23 influenza seasons. DESCRIPTION OF SYSTEM: FluSurv-NET conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations among children and adults. During the reporting period, the surveillance network included 13-16 participating sites each influenza season, with prespecified geographic catchment areas that covered 27 million-29 million persons and included an estimated 8.8%-9.5% of the U.S. population. A case was defined as a person residing in the catchment area within one of the participating states who had a positive influenza laboratory test result within 14 days before or at any time during their hospitalization. Each site abstracted case data from hospital medical records into a standardized case report form, with selected variables submitted to CDC on a weekly basis for rate estimations. Weekly and cumulative laboratory-confirmed influenza-associated hospitalization rates per 100,000 population were calculated for each season from 2010-11 through 2022-23 and stratified by patient age (0-4 years, 5-17 years, 18-49 years, 50-64 years, and ≥65 years), sex, race and ethnicity, influenza type, and influenza A subtype. During the 2020-21 season, only the overall influenza hospitalization rate was reported because case counts were insufficient to estimate stratified rates. RESULTS: During the 2010-11 to 2022-23 influenza seasons, laboratory-confirmed influenza-associated hospitalization rates varied significantly across seasons. Before the COVID-19 pandemic, hospitalization rates per 100,000 population ranged from 8.7 (2011-12) to 102.9 (2017-18) and had consistent seasonality. After SARS-CoV-2 emerged, the hospitalization rate for 2020-21 was 0.8, and the rate did not return to recent prepandemic levels until 2022-23. Inconsistent seasonality also was observed during 2020-21 through 2022-23, with influenza activity being very low during 2020-21, extending later than usual during 2021-22, and occurring early during 2022-23. Molecular assays, particularly multiplex standard molecular assays, were the most common influenza test type in recent seasons, increasing from 12% during 2017-18 for both pediatric and adult cases to 43% and 55% during 2022-23 for pediatric and adult cases, respectively. During each season, adults aged ≥65 years consistently had the highest influenza-associated hospitalization rate across all age groups, followed in most seasons by children aged 0-4 years. Black or African American and American Indian or Alaska Native persons had the highest age-adjusted influenza-associated hospitalization rates across these seasons. Among patients hospitalized with influenza, the prevalence of at least one underlying medical condition increased with increasing age, ranging from 36.9% among children aged 0-4 years to 95.4% among adults aged ≥65 years. Consistently across each season, the most common underlying medical conditions among children and adolescents were asthma, neurologic disorders, and obesity. The most common underlying medical conditions among adults were hypertension, obesity, chronic metabolic disease, chronic lung disease, and cardiovascular disease. The proportion of FluSurv-NET patients with acute respiratory signs and symptoms at hospital admission decreased from 90.6% during 2018-19 to 83.2% during 2022-23. Although influenza antiviral use increased during the 2010-11 through the 2017-18 influenza seasons, it decreased from 90.2% during 2018-19 to 79.1% during 2022-23, particularly among children and adolescents. Admission to the intensive care unit, need for invasive mechanical ventilation, and in-hospital death ranged from 14.1% to 22.3%, 4.9% to 11.1%, and 2.2% to 3.5% of patients hospitalized with influenza, respectively, during the reported surveillance period. INTERPRETATIONS: Influenza continues to cause severe morbidity and mortality, particularly in older adults, and disparities have persisted in racial and ethnic minority groups. Persons with underlying medical conditions represented a large proportion of patients hospitalized with influenza. Increased use of multiplex tests and other potential changes in facility-level influenza testing practices (e.g., influenza screening at all hospital admissions) could have implications for the detection of influenza infections among hospitalized patients. Antiviral use decreased in recent seasons, and explanations for the decrease should be further evaluated. PUBLIC HEALTH ACTION: Continued robust influenza surveillance is critical to monitor progress in efforts to encourage antiviral treatment and improve clinical outcomes for persons hospitalized with influenza. In addition, robust influenza surveillance can potentially reduce disparities by informing efforts to increase access to preventive measures for influenza and monitoring any subsequent changes in hospitalization rates.

Understanding whether influenza vaccine promotion strategies produce community-wide indirect effects is important for establishing vaccine coverage targets and optimizing vaccine delivery. Empirical epidemiologic studies and mathematical models have been used to estimate indirect effects of vaccines but rarely for the same estimand in the same dataset. Using these approaches together could be a powerful tool for triangulation in infectious disease epidemiology because each approach is subject to distinct sources of bias. We triangulated evidence about indirect effects from a school-located influenza vaccination program using two approaches: a difference-in-difference (DID) analysis, and an age-structured, deterministic, compartmental model. The estimated indirect effect was substantially lower in the mathematical model than in the DID analysis (2.1% (95% Bayesian credible intervals 0.4 - 4.4%) vs. 22.3% (95% CI 7.6% - 37.1%)). To explore reasons for differing estimates, we used sensitivity analyses and probabilistic bias analyses. When we constrained model parameters such that projections matched the DID analysis, results only aligned with the DID analysis with substantially lower pre-existing immunity among school-age children and older adults. Conversely, DID estimates corrected for potential bias only aligned with mathematical model estimates under differential outcome misclassification. We discuss how triangulation using empirical and mathematical modelling approaches could strengthen future studies.

Isolation of symptomatic infectious persons can reduce influenza transmission. However, virus shedding that occurs without symptoms will be unaffected by such measures. Identifying effective isolation strategies for influenza requires understanding the interplay between individual virus shedding and symptom presentation. From 2017 to 2020, we conducted a case-ascertained household transmission study using influenza real-time RT-qPCR testing of nasal swabs and daily symptom diary reporting for up to 7 days after enrolment (≤14 days after index onset). We assumed real-time RT-qPCR cycle threshold (Ct) values were indicators of quantitative virus shedding and used symptom diaries to create a score that tracked influenza-like illness (ILI) symptoms (fever, cough, or sore throat). We fit phenomenological nonlinear mixed-effects models stratified by age and vaccination status and estimated two quantities influencing isolation effectiveness: shedding before symptom onset and shedding that might occur once isolation ends. We considered different isolation end points (including 24 h after fever resolution or 5 days after symptom onset) and assumptions about the infectiousness of Ct shedding trajectories. Of the 116 household contacts with ≥2 positive tests for longitudinal analyses, 105 (91%) experienced ≥1 ILI symptom. On average, children <5 years experienced greater peak shedding, longer durations of shedding, and elevated ILI symptom scores compared with other age groups. Most individuals (63/105) shed <10% of their total shed virus before symptom onset, and shedding after isolation varied substantially across individuals, isolation end points, and infectiousness assumptions. Our results can inform strategies to reduce transmission from symptomatic individuals infected with influenza.

Persons who work in close contact with dairy cattle and poultry that are infected with highly pathogenic avian influenza (HPAI) A(H5N1) virus are at increased risk for infection. In July 2024, the Colorado Department of Public Health & Environment responded to two poultry facilities with HPAI A(H5N1) virus detections in poultry. Across the two facilities, 663 workers assisting with poultry depopulation (i.e., euthanasia) received screening for illness; 109 (16.4%) reported symptoms and consented to testing. Among those who received testing, nine (8.3%) received a positive influenza A(H5) virus test result, and 19 (17.4%) received a positive SARS-CoV-2 test result. All nine workers who received positive influenza A(H5) test results had conjunctivitis, experienced mild illness, and received oseltamivir. This poultry exposure-associated cluster of human cases of influenza A(H5) is the first reported in the United States. The identification of these cases highlights the ongoing risk to persons who work in close contact with infected animals. Early response to each facility using multidisciplinary, multilingual teams facilitated case-finding, worker screening, and treatment. As the prevalence of HPAI A(H5N1) virus clade 2.3.4.4b genotype B3.13 increases, U.S. public health agencies should prepare to rapidly investigate and respond to illness in agricultural workers, including workers with limited access to health care.

BACKGROUND: Pneumonia is common in adults hospitalized with laboratory-confirmed influenza, but the association between timeliness of influenza antiviral treatment and severe clinical outcomes in patients with influenza-associated pneumonia is not well characterized. METHODS: We included adults aged ≥18 years hospitalized with laboratory-confirmed influenza and a discharge diagnosis of pneumonia over 7 influenza seasons (2012-2019) sampled from a multi-state population-based surveillance network. We evaluated 3 treatment groups based on timing of influenza antiviral initiation relative to admission date (day 0, day 1, days 2-5). Baseline characteristics and clinical outcomes were compared across groups using unweighted counts and weighted percentages accounting for the complex survey design. Logistic regression models were generated to evaluate the association between delayed treatment and 30-day all-cause mortality. RESULTS: 26,233 adults were sampled in the analysis. Median age was 71 years and most (92.2%) had ≥1 non-immunocompromising condition. Overall, 60.9% started antiviral treatment on day 0, 29.5% on day 1, and 9.7% on days 2-5 (median 2 days). Baseline characteristics were similar across groups. Thirty-day mortality occurred in 7.5%, 8.5%, and 10.2% of patients who started treatment on day 0, day 1, and days 2-5, respectively. Compared to those treated on day 0, adjusted OR for death was 1.14 (95%CI: 1.01-1.27) in those starting treatment on day 1 and 1.40 (95%CI: 1.17-1.66) in those starting on days 2-5. DISCUSSION: Delayed initiation of antiviral treatment in patients hospitalized with influenza-associated pneumonia was associated with higher risk of death, highlighting the importance of timely initiation of antiviral treatment at admission.

Asymptomatic influenza virus infection occurs but may vary by factors such as age, influenza vaccination status, or influenza season. We examined the frequency of influenza virus infection and associated symptoms using data from two case-ascertained household transmission studies (conducted from 2017-2023) with prospective, systematic collection of respiratory specimens and symptoms. From the 426 influenza virus infected household contacts that met our inclusion criteria, 8% were asymptomatic, 6% had non-respiratory symptoms, 23% had acute respiratory symptoms, and 62% had influenza-like illness symptoms. Understanding the prevalence of asymptomatic and mildly symptomatic influenza cases is important for implementing effective influenza prevention strategies and enhancing the effectiveness of symptom-based surveillance systems.

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.

Direct-on-Filter (DoF) analysis of respirable crystalline silica (RCS) by Fourier Transform Infrared (FTIR) spectroscopy is a useful tool for assessing exposure risks. With the RCS exposure limits becoming lower, it is important to characterize and reduce measurement uncertainties. This study systematically evaluated two filter types (i.e., polyvinyl chloride [PVC] and polytetrafluoroethylene [PTFE]) for RCS measurements by DoF FTIR spectroscopy, including the filter-to-filter and day-to-day variability of blank filter FTIR reference spectra, particle deposition patterns, filtration efficiencies, and pressure drops. For PVC filters sampled at a flow rate of 2.5 L/min for 8 h, the RCS limit of detection (LOD) was 7.4 μg/m(3) when a designated laboratory reference filter was used to correct the absorption by the filter media. When the spectrum of the pre-sample filter (blank filter before dust sampling) was used for correction, the LOD could be up to 5.9 μg/m(3). The PVC absorption increased linearly with reference filter mass, providing a means to correct the absorption differences between the pre-sample and reference filters. For PTFE, the LODs were 12 and 1.2 μg/m(3) when a designated laboratory blank or the pre-sample filter spectrum was used for blank correction, respectively, indicating that using the pre-sample blank spectrum will reduce RCS quantification uncertainty. Both filter types exhibited a consistent radially symmetric deposition pattern when particles were collected using 3-piece cassettes, indicating that RCS can be quantified from a single measurement at the filter center. The most penetrating aerodynamic diameters were around 0.1 µm with filtration efficiencies ≥ 98.8% across the measured particle size range with low-pressure drops (0.2-0.3 kPa) at a flow rate of 2.5 L/min. This study concludes that either the PVC or the PTFE filters are suitable for RCS analysis by DoF FTIR, but proper methods are needed to account for the variability of blank absorption among different filters.

Background: Understanding how symptoms are associated with SARS-CoV-2 culture positivity is important for isolation and transmission control guidelines. Methods: Individuals acutely infected with SARS-CoV-2 in Tennessee and their household contacts were recruited into a prospective study. All participants self-collected nasal swabs daily for 14 days and completed symptom diaries from the day of illness onset through day 14 postenrollment. Nasal specimens were tested for SARS-CoV-2 using RT-qPCR. Positive specimens with cycle threshold values < 40 were sent to the Centers for Disease Control and Prevention (CDC) for viral culture. First, we modeled the association between symptoms and the risk of culture positivity using an age-adjusted generalized additive model (GAM) accounting for repeated measurements within participants and a symptom-day spline. Next, we investigated how timing of symptom resolution was associated with the timing of culture resolution. Results: In a GAM restricted to follow-up days after symptoms began, the odds of a specimen being culture positive was significantly increased on days when wheezing, loss of taste or smell, runny nose, nasal congestion, sore throat, fever, or any symptom were reported. For all symptoms except sore throat, it was more common for participants to have culture resolution before symptom resolution than for culture to resolve after or on the same day as symptom resolution. Conclusions: Overall, symptomatic individuals were more likely to be SARS-CoV-2 viral culture positive. For most symptoms, culture positivity was more likely to end before symptoms resolved. However, a proportion of individuals remained culture positive after symptom resolved, across all symptoms. © 2024 The Authors. Influenza and Other Respiratory Viruses Published by John Wiley & Sons Ltd.

We present a novel small molecule antiviral chemotype that was identified by an unconventional cell-free protein synthesis and assembly-based phenotypic screen for modulation of viral capsid assembly. Activity of PAV-431, a representative compound from the series, has been validated against infectious viruses in multiple cell culture models for all six families of viruses causing most respiratory diseases in humans. In animals, this chemotype has been demonstrated efficacious for porcine epidemic diarrhoea virus (a coronavirus) and respiratory syncytial virus (a paramyxovirus). PAV-431 is shown to bind to the protein 14-3-3, a known allosteric modulator. However, it only appears to target the small subset of 14-3-3 which is present in a dynamic multi-protein complex whose components include proteins implicated in viral life cycles and in innate immunity. The composition of this target multi-protein complex appears to be modified upon viral infection and largely restored by PAV-431 treatment. An advanced analog, PAV-104, is shown to be selective for the virally modified target, thereby avoiding host toxicity. Our findings suggest a new paradigm for understanding, and drugging, the host-virus interface, which leads to a new clinical therapeutic strategy for treatment of respiratory viral disease.

BACKGROUND: Novel influenza viruses pose a potential pandemic risk, and rapid detection of infections in humans is critical to characterizing the virus and facilitating the implementation of public health response measures. METHODS: We use a probabilistic framework to estimate the likelihood that novel influenza virus cases would be detected through testing in different community and healthcare settings (urgent care, emergency department, hospital, and intensive care unit [ICU]) while at low frequencies in the United States. Parameters were informed by data on seasonal influenza virus activity and existing testing practices. RESULTS: In a baseline scenario reflecting the presence of 100 novel virus infections with similar severity to seasonal influenza viruses, the median probability of detecting at least one infection per month was highest in urgent care settings (72%) and when community testing was conducted at random among the general population (77%). However, urgent care testing was over 15 times more efficient (estimated as the number of cases detected per 100,000 tests) due to the larger number of tests required for community testing. In scenarios that assumed increased clinical severity of novel virus infection, median detection probabilities increased across all healthcare settings, particularly in hospitals and ICUs (up to 100%) where testing also became more efficient. CONCLUSIONS: Our results suggest that novel influenza virus circulation is likely to be detected through existing healthcare surveillance, with the most efficient testing setting impacted by the disease severity profile. These analyses can help inform future testing strategies to maximize the likelihood of novel influenza detection.

Control of dust in underground coal mines is critical for mitigating both safety and health hazards. For decades, the National Institute of Occupational Safety and Health (NIOSH) has led research to evaluate the effectiveness of various dust control technologies in coal mines. Recent studies have included the evaluation of auxiliary scrubbers to reduce respirable dust downstream of active mining and the use of canopy air curtains (CACs) to reduce respirable dust in key operator positions. While detailed dust characterization was not a focus of such studies, this is a growing area of interest. Using preserved filter samples from three previous NIOSH studies, the current work aims to explore the effect of two different scrubbers (one wet and one dry) and a roof bolter CAC on respirable dust composition and particle size distribution. For this, the preserved filter samples were analyzed by thermogravimetric analysis and/or scanning electron microscopy with energy dispersive X-ray. Results indicate that dust composition was not appreciably affected by either scrubber or the CAC. However, the wet scrubber and CAC appeared to decrease the overall particle size distribution. Such an effect of the dry scrubber was not consistently observed, but this is probably related to the particular sampling location downstream of the scrubber which allowed for significant mixing of the scrubber exhaust and other return air. Aside from the insights gained with respect to the three specific dust control case studies revisited here, this work demonstrates the value of preserved dust samples for follow-up investigation more broadly. © The Author(s) 2024.

We reviewed the tools that have been developed to characterize and communicate seasonal influenza activity in the United States. Here we focus on systematic surveillance and applied analytics, including seasonal burden and disease severity estimation, short-term forecasting, and longer-term modeling efforts. For each set of activities, we describe the challenges and opportunities that have arisen because of the COVID-19 pandemic. In conclusion, we highlight how collaboration and communication have been and will continue to be key components of reliable and actionable influenza monitoring, forecasting, and modeling activities.

OBJECTIVES: State, local, and federal agencies have expanded efforts to address the root causes of overdoses, including health inequity and related social determinants of health. As an Overdose Data to Action (OD2A) technical assistance provider, the Association of State and Territorial Health Officials (ASTHO) conducted the first national needs assessment to understand capacity and technical assistance needs of OD2A jurisdictions in advancing health equity. METHODS: ASTHO designed and disseminated the OD2A Recipient Health Equity Needs Assessment (RHENA) to 66 OD2A-funded jurisdictions from February to March 2022. OD2A principal investigators and staff were contacted via email and asked to complete the needs assessment within 6 weeks. One coder manually coded open-ended responses, conducted a thematic analysis on the qualitative data, and performed a simple frequency analysis on the quantitative data. RESULTS: Fifty-two jurisdictions (78.8%) responded, including 36 states, 12 cities/counties, and 2 territories. Most jurisdictions (n = 46; 88.5%) reported having a formal or informal health equity lead in place. Common barriers included a lack of access to data sources (n = 37; 71.2%), lack of partnerships (n = 20; 38.5%), and lack of funding (n = 14; 26.9%). Respondents reported needing more information sharing among jurisdictions and partner organizations, coaching on best practices, and routine discussions such as peer-to-peer learning sessions. CONCLUSION: Findings suggest that gaps remain in programmatic policies and principles to address inequities in overdose prevention. Results are being used to identify additional technical assistance opportunities, jurisdictional capacity, and approaches to advance health equity.

In the United States, annual influenza vaccination is recommended for all persons aged ≥6 months. Using data from four vaccine effectiveness (VE) networks during the 2023-24 influenza season, interim influenza VE was estimated among patients aged ≥6 months with acute respiratory illness-associated medical encounters using a test-negative case-control study design. Among children and adolescents aged 6 months-17 years, VE against influenza-associated outpatient visits ranged from 59% to 67% and against influenza-associated hospitalization ranged from 52% to 61%. Among adults aged ≥18 years, VE against influenza-associated outpatient visits ranged from 33% to 49% and against hospitalization from 41% to 44%. VE against influenza A ranged from 46% to 59% for children and adolescents and from 27% to 46% for adults across settings. VE against influenza B ranged from 64% to 89% for pediatric patients in outpatient settings and from 60% to 78% for all adults across settings. These findings demonstrate that the 2023-24 seasonal influenza vaccine is effective at reducing the risk for medically attended influenza virus infection. CDC recommends that all persons aged ≥6 months who have not yet been vaccinated this season get vaccinated while influenza circulates locally.

BACKGROUND: Age-mixing (age-disparate [5-9 years difference] and intergenerational [≥ 10 years difference]) partnerships are hypothesized drivers of HIV in adolescent girls and young women (AGYW; 15-24 years). These partnerships are often associated with increased gender inequities which undermine women's agency and assertiveness. We assessed whether age-mixing partnerships were associated with HIV in Malawi and if endorsement of inequitable gender norms modifies this relationship. METHODS: We analyzed data from the Malawi Population-based HIV Impact Assessment, a nationally representative household survey conducted in 2015-2016. Participants underwent HIV testing and completed questionnaires related to actively endorsed gender norms and sexual risk behavior. We used multivariate logistic regression and multiplicative interaction to assess associations among AGYW who reported the age of their primary sex partner from the last year. RESULTS: The analysis included 1,958 AGYW (mean age = 19.9 years, SD = 0.1), 459 (23.4%) and 131 (6.7%) of whom reported age-disparate and intergenerational partnerships, respectively. AGYW in age-mixing partnerships accounted for 13% of all AGYW and were older, more likely to reside in urban areas, to be married or cohabitating with a partner, and to have engaged in riskier sexual behavior compared with AGYW in age-concordant partnerships (p < 0.05). HIV prevalence among AGYW in age-disparate and intergenerational partnerships was 6.1% and 11.9%, respectively, compared with 3.2% in age-concordant partnerships (p < 0.001). After adjusting for residence, age, education, employment, wealth quintile, and ever been married or cohabitated as married, AGYW in age-disparate and intergenerational partnerships had 1.9 (95% CI: 1.1-3.5) and 3.4 (95% CI: 1.6-7.2) greater odds of HIV, respectively, compared with AGYW in age-concordant partnerships. Among the 614 (31% of the study group) who endorsed inequitable gender norms, AGYW in age-disparate and intergenerational partnerships had 3.5 (95% CI: 1.1-11.8) and 6.4 (95% CI: 1.5-27.8) greater odds of HIV, respectively, compared with AGYW in age-concordant partnerships. CONCLUSIONS: In this Malawi general population survey, age-mixing partnerships were associated with increased odds of HIV among AGYW. These findings highlight inequitable gender norms as a potential focus for HIV prevention and could inform interventions targeting structural, cultural, and social constraints of this key group.

Marburg virus (MARV) and Ravn virus (RAVV), collectively called marburgviruses, cause Marburg hemorrhagic fever (MHF) in humans. In July 2007, 4 cases of MHF (1 fatal) occurred in miners at Kitaka Mine in southern Uganda. Later, MHF occurred in 2 tourists who visited Python Cave, ≈50 km from Kitaka Mine. One of the tourists was from the United States (December 2007) and 1 was from the Netherlands (July 2008); 1 case was fatal (1,2,3). The cave and the mine each contained 40,000–100,000 Rousettus aegyptiacus bats (Egyptian fruit bats). | | Longitudinal investigations of the outbreaks at both locations were initiated by the Viral Special Pathogens Branch of the Centers for Disease Control and Prevention (CDC, Atlanta, GA, USA, and Entebbe, Uganda) in collaboration with the Uganda Wildlife Authority (UWA) and the Uganda Virus Research Institute (UVRI). During these studies, genetically diverse MARVs and RAVVs were isolated directly from bat tissues, and infection levels of the 2 viruses were found to increase in juvenile bats on a predictable bi-annual basis (4,5). However, investigations at Kitaka Mine were stopped when the miners exterminated the bat colony by restricting egress from the cave with papyrus reed barriers and then entangling the bats in fishing nets draped over the exits. The trapping continued for weeks, and the entrances were then sealed with sticks and plastic. These depopulation efforts were documented by researchers from UVRI, the CDC, the National Institute of Communicable Diseases (Sandringham, South Africa), and UWA during site visits to Kitaka Mine (Technical Appendix Figure). In August 2008, thousands of dead bats were found piled in the forest, and by November 2008, there was no evidence of bats living in the mine; whether 100% extermination was achieved is unknown. CDC, UVRI, and UWA recommended against extermination, believing that any results would be temporary and that such efforts could exacerbate the problem if bat exclusion methods were not complete and permanent (6,7).

Manual data entry is time-consuming, inefficient, and error prone. In contrast, leveraging two-dimensional (2D) barcodes and barcode scanning tools is a rapid, efficient, and effective practice for automatically entering data accurately and completely during vaccine inventorying and administration. CDC pilots in a variety of healthcare settings documented the clinical and public health impact of 2D barcode scanning practices on data quality and completeness, time savings, workflow efficiencies, and staff experience. A sample of 50 million emergency use authorization (EUA) COVID-19 vaccine records were analyzed for accuracy and completeness across three data fields: lot number, expiration date, and National Drug Code (NDC). These vaccines did not include a 2D barcode containing these data fields, thus necessitating manual entry of vaccine data at administration. During a CDC pilot with clinic sites, comparison was made between automatically scanned and manually entered data for routine vaccines for accuracy and completeness across these data fields. Analysis of 50 million manually entered EUA vaccine administration records indicated significant gaps in data accuracy and completeness across three data fields observed. Over half of the 50 million EUA vaccine NDCs (53%) and one-third of the expiration dates (35%) analyzed had missing or inaccurate data recorded. Pilot data also showed many errors when manually entered. However, when 67,951 (out of 72,979) vaccines were scanned during the pilot, nearly all entries were complete and accurate across all three data fields (ranging from 99.7% to 99.999% accurate). Vaccine 2D barcode scanning practices increased data accuracy and completeness (up to 99.999% accurate) across data fields assessed. When used consistently, vaccine 2D barcode scanning can resolve the issues demonstrated in manually entered data. To realize these benefits, the immunization community should widely adopt scanning practices. To increase use, CDC has developed a Vaccine 2D Barcode National Adoption Strategy and resources to guide implementation.

Among underground coal miners, roof bolter operators are generally considered to have some of the highest risks for hazardous respirable dust exposure. This is because bolting requires drilling into roof strata that can often be a source of silica and silicate dust, which are associated with occupational lung diseases. However, little is known about the variability of dust characteristics (e.g., mineralogy constituents, particle size) in the vicinity of the bolter-or when specific dust controls are applied. As part of a prior NIOSH study, respirable dust samples were collected during several different events in standardized locations around an active roof bolter, and personal samples were also collected from the operator during the cleanout of the bolter's dust collection system when it was equipped with a novel wet dust box versus a traditional dry box. Those samples were made available for follow-up analysis by scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM-EDX), as well as direct-on-filter Fourier transform infrared spectroscopy (FTIR). Results showed variability in dust constituents and particle sizes at locations around the roof bolter, and indicated some event-to-event differences in dust sources. Additionally, compared to the dry dust box, the wet dust box appeared to reduce (by 41-82%) the relative silica and silicate content in the respirable dust to which the operator was exposed during cleanout. Furthermore, an inter-laboratory comparison demonstrated the reproducibility of a standardized direct-on-filter FTIR method for estimating quartz mass (i.e., the predominant form of crystalline silica) in respirable coal mine dust samples. However, for constituent analysis by SEM-EDX, differences observed between results from two independent labs indicate that standardization of the analytical protocol is necessary to enable comparability of results.

BACKGROUND: The ongoing COVID-19 pandemic has led to hundreds of millions of infections worldwide. Although differences in COVID-19 hospitalization rates between males and females have been described, many infections in the general population have been mild, and the severity of symptoms during the course of COVID-19 in non-hospitalized males and females is not well understood. METHODS: We conducted a case-ascertained study to examine household transmission of SARS-CoV-2 infections in Nashville, Tennessee, between April 2020 and April 2021. Among enrolled ambulatory adult participants with laboratory-confirmed SARS-CoV-2 infections, we assessed the presence and severity of symptoms (total, systemic, and respiratory) daily using a symptoms severity questionnaire, from illness onset and throughout the 2-week follow-up period. We compared the mean daily symptom severity scores (0-3: none, mild, moderate, and severe) and change in symptoms between males and females using a multivariable linear mixed effects regression model. RESULTS: The analysis included 223 enrolled adults with SARS-CoV-2 infection (58% females, mostly white, non-Hispanic) from 146 households with 2917 total daily symptom reports. The overall mean severity of total symptoms reported over the illness period was 1.04 and 0.90 for females and males, respectively. Mean systemic and respiratory scores were higher for females than for males (p < 0.001). In multivariable analyses, females reported more severe total and systemic symptoms during the illness period compared with males. However, no significant differences in reported respiratory symptoms were observed. CONCLUSIONS: Our findings indicate that among ambulatory adults with SARS-CoV-2 infections, females reported slightly higher symptom severity during their illness compared with males.

Before the COVID-19 pandemic, the role of asymptomatic influenza virus infections in influenza transmission was uncertain. However, the importance of asymptomatic infection with SARS-CoV-2 for onward transmission of COVID-19 has led experts to question whether the role of asymptomatic influenza virus infections in transmission had been underappreciated. We discuss the existing evidence on the frequency of asymptomatic influenza virus infections, the extent to which they contribute to infection transmission, and remaining knowledge gaps. We propose priority areas for further evaluation, study designs, and case definitions to address existing knowledge gaps.

BACKGROUND: Influenza is a substantial cause of annual morbidity and mortality; however, correctly identifying those patients at increased risk for severe disease is often challenging. Several severity indices have been developed; however, these scores have not been validated for use in patients with influenza. We evaluated the discrimination of three clinical disease severity scores in predicting severe influenza-associated outcomes. METHODS: We used data from the Influenza Hospitalization Surveillance Network to assess outcomes of patients hospitalized with influenza in the United States during the 2017-2018 influenza season. We computed patient scores at admission for three widely used disease severity scores: CURB-65, Quick Sepsis-Related Organ Failure Assessment (qSOFA), and the Pneumonia Severity Index (PSI). We then grouped patients with severe outcomes into four severity tiers, ranging from ICU admission to death, and calculated receiver operating characteristic (ROC) curves for each severity index in predicting these tiers of severe outcomes. RESULTS: Among 8252 patients included in this study, we found that all tested severity scores had higher discrimination for more severe outcomes, including death, and poorer discrimination for less severe outcomes, such as ICU admission. We observed the highest discrimination for PSI against in-hospital mortality, at 0.78. CONCLUSIONS: We observed low to moderate discrimination of all three scores in predicting severe outcomes among adults hospitalized with influenza. Given the substantial annual burden of influenza disease in the United States, identifying a prediction index for severe outcomes in adults requiring hospitalization with influenza would be beneficial for patient triage and clinical decision-making.

Hispanic/Latino persons are disproportionately impacted by HIV in the US, and HIV diagnoses among Hispanic/Latino men in Georgia have increased over the past decade, particularly in metropolitan Atlanta. In 2022, the Georgia Department of Public Health detected five clusters of rapid HIV transmission centered among Hispanic/Latino gay, bisexual, and other men who have sex with men (HLMSM) in metropolitan Atlanta. We conducted in-depth interviews with 65 service providers and 29 HLMSM to identify barriers and facilitators to HIV service access for HLMSM. Interviews were audio recorded, transcribed, and translated, if needed. Initial data analyses were conducted rapidly in the field to inform public health actions. We then conducted additional analyses including line-by-line coding of the interview transcripts using a thematic analytic approach. We identified four main themes. First, inequity in language access was a predominant barrier. Second, multiple social and structural barriers existed. Third, HLMSM encountered intersectional stigma. Finally, the HLMSM community is characterized by its diversity, and there is not a one-size-fits-all approach to providing appropriate care to this population. The collection of qualitative data during an HIV cluster investigation allowed us to quickly identity barriers experienced by HLMSM when accessing HIV and other medical care, to optimize public health response and action. Well-designed program evaluation and implementation research may help elucidate specific strategies and tools to reduce health disparities, ensure equitable service access for HLMSM, and reduce HIV transmission in this population.

Influenza vaccines have been routinely recommended in the United States for some groups since 1960 and for everyone 6 months of age or older for more than a decade. Yet, annual influenza vaccination coverage has rarely exceeded 50% in children and younger adults or 70% in adults aged 65 years or older (1). Long-standing barriers to influenza vaccine uptake include beliefs that influenza illness is mild or inconsequential and vaccines are not effective, concerns about safety and adverse effects, and distrust of the medical system and disparities in access to vaccines (1, 2). | | During the COVID-19 pandemic, influenza vaccination coverage rates remained low overall and declined in some groups (1, 3). Although the first year of the COVID-19 pandemic temporarily interrupted circulation of seasonal respiratory viruses, the United States experienced high levels of influenza virus, SARS-CoV-2, and respiratory syncytial virus co-circulation during the 2022 to 2023 influenza season, putting a strain on health care resources. As the 2023 to 2024 season begins, internal medicine physicians and other health care professionals play an important role in communicating the benefits of vaccinations against influenza and other respiratory viruses. A health care professional’s recommendation and offer of or referral for vaccination have been shown over many seasons to be one of the strongest factors associated with willingness to get vaccinated (2).

Bluetongue virus (BTV) is a segmented, double-stranded RNA virus transmitted by Culicoides biting midges. Infection of domestic and wild ruminants with BTV can result in a devastating disease and significant economic losses. As a virus with a segmented genome, reassortment among the BTV serotypes that have co-infected a host may increase genetic diversity, which can alter BTV transmission dynamics and generate epizootic events. The objective of this study was to determine the extent of dissemination and characterize the tropism of BTV serotypes 10 and 17 in co-infected Culicoides sonorensis. Midges were exposed to both BTV serotypes via blood meal and processed for histologic slides 10 days after infection. An in situ hybridization approach was employed using the RNAscope platform to detect the nucleic acid segment 2 of both serotypes. Observations of the mosaic patterns in which serotypes did not often overlap suggest that co-infection at the cellular level may not be abundant with these two serotypes in C. sonorensis. This could be a consequence of superinfection exclusion. Understanding BTV co-infection and its biological consequences will add an important dimension to the modeling of viral evolution and emergence.

During the 2022-23 influenza season, early increases in influenza activity, co-circulation of influenza with other respiratory viruses, and high influenza-associated hospitalization rates, particularly among children and adolescents, were observed. This report describes the 2022-23 influenza season among children and adolescents aged <18 years, including the seasonal severity assessment; estimates of U.S. influenza-associated medical visits, hospitalizations, and deaths; and characteristics of influenza-associated hospitalizations. The 2022-23 influenza season had high severity among children and adolescents compared with thresholds based on previous seasons' influenza-associated outpatient visits, hospitalization rates, and deaths. Nationally, the incidences of influenza-associated outpatient visits and hospitalization for the 2022-23 season were similar for children aged <5 years and higher for children and adolescents aged 5-17 years compared with previous seasons. Peak influenza-associated outpatient and hospitalization activity occurred in late November and early December. Among children and adolescents hospitalized with influenza during the 2022-23 season in hospitals participating in the Influenza Hospitalization Surveillance Network, a lower proportion were vaccinated (18.3%) compared with previous seasons (35.8%-41.8%). Early influenza circulation, before many children and adolescents had been vaccinated, might have contributed to the high hospitalization rates during the 2022-23 season. Among symptomatic hospitalized patients, receipt of influenza antiviral treatment (64.9%) was lower than during pre-COVID-19 pandemic seasons (80.8%-87.1%). CDC recommends that all persons aged ≥6 months without contraindications should receive the annual influenza vaccine, ideally by the end of October.

BACKGROUND: For surveillance of episodic illness, the emergency department (ED) represents one of the largest interfaces for generalizable data about segments of the US public experiencing a need for unscheduled care. This protocol manuscript describes the development and operation of a national network linking symptom, clinical, laboratory and disposition data that provides a public database dedicated to the surveillance of acute respiratory infections (ARIs) in EDs. METHODS: The Respiratory Virus Laboratory Emergency Department Network Surveillance (RESP-LENS) network includes 26 academic investigators, from 24 sites, with 91 hospitals, and the Centers for Disease Control and Prevention (CDC) to survey viral infections. All data originate from electronic medical records (EMRs) accessed by structured query language (SQL) coding. Each Tuesday, data are imported into the standard data form for ARI visits that occurred the prior week (termed the index file); outcomes at 30 days and ED volume are also recorded. Up to 325 data fields can be populated for each case. Data are transferred from sites into an encrypted Google Cloud Platform, then programmatically checked for compliance, parsed, and aggregated into a central database housed on a second cloud platform prior to transfer to CDC. RESULTS: As of August, 2023, the network has reported data on over 870,000 ARI cases selected from approximately 5.2 million ED encounters. Post-contracting challenges to network execution have included local shifts in testing policies and platforms, delays in ICD-10 coding to detect ARI cases, and site-level personnel turnover. The network is addressing these challenges and is poised to begin streaming weekly data for dissemination. CONCLUSIONS: The RESP-LENS network provides a weekly updated database that is a public health resource to survey the epidemiology, viral causes, and outcomes of ED patients with acute respiratory infections.

BACKGROUND: Influenza burden varies across seasons, partly due to differences in circulating influenza virus types or subtypes. Using data from the US population-based surveillance system, Influenza Hospitalization Surveillance Network (FluSurv-NET), we aimed to assess the severity of influenza-associated outcomes in individuals hospitalised with laboratory-confirmed influenza virus infections during the 2010-11 to 2018-19 influenza seasons. METHODS: To evaluate the association between influenza virus type or subtype causing the infection (influenza A H3N2, A H1N1pdm09, and B viruses) and in-hospital severity outcomes (intensive care unit [ICU] admission, use of mechanical ventilation or extracorporeal membrane oxygenation [ECMO], and death), we used FluSurv-NET to capture data for laboratory-confirmed influenza-associated hospitalisations from the 2010-11 to 2018-19 influenza seasons for individuals of all ages living in select counties in 13 US states. All individuals had to have an influenza virus test within 14 days before or during their hospital stay and an admission date between Oct 1 and April 30 of an influenza season. Exclusion criteria were individuals who did not have a complete chart review; cases from sites that contributed data for three or fewer seasons; hospital-onset cases; cases with unidentified influenza type; cases of multiple influenza virus type or subtype co-infection; or individuals younger than 6 months and ineligible for the influenza vaccine. Logistic regression models adjusted for influenza season, influenza vaccination status, age, and FluSurv-NET site compared odds of in-hospital severity by virus type or subtype. When missing, influenza A subtypes were imputed using chained equations of known subtypes by season. FINDINGS: Data for 122 941 individuals hospitalised with influenza were captured in FluSurv-NET from the 2010-11 to 2018-19 seasons; after exclusions were applied, 107 941 individuals remained and underwent influenza A virus imputation when missing A subtype (43·4%). After imputation, data for 104 969 remained and were included in the final analytic sample. Averaging across imputed datasets, 57·7% (weighted percentage) had influenza A H3N2, 24·6% had influenza A H1N1pdm09, and 17·7% had influenza B virus infections; 16·7% required ICU admission, 6·5% received mechanical ventilation or ECMO, and 3·0% died (95% CIs had a range of less than 0·1% and are not displayed). Individuals with A H1N1pdm09 had higher odds of in-hospital severe outcomes than those with A H3N2: adjusted odds ratios (ORs) for A H1N1pdm09 versus A H3N2 were 1·42 (95% CI 1·32-1·52) for ICU admission; 1·79 (1·60-2·00) for mechanical ventilation or ECMO use; and 1·25 (1·07-1·46) for death. The adjusted ORs for individuals infected with influenza B versus influenza A H3N2 were 1·06 (95% CI 1·01-1·12) for ICU admission, 1·14 (1·05-1·24) for mechanical ventilation or ECMO use, and 1·18 (1·07-1·31) for death. INTERPRETATION: Despite a higher burden of hospitalisations with influenza A H3N2, we found an increased likelihood of in-hospital severe outcomes in individuals hospitalised with influenza A H1N1pdm09 or influenza B virus. Thus, it is important for individuals to receive an annual influenza vaccine and for health-care providers to provide early antiviral treatment for patients with suspected influenza who are at increased risk of severe outcomes, not only when there is high influenza A H3N2 virus circulation but also when influenza A H1N1pdm09 and influenza B viruses are circulating. FUNDING: The US Centers for Disease Control and Prevention.