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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.

As of March 31, 2023, more than 30,000 monkeypox (mpox) cases had been reported in the United States in an outbreak that has disproportionately affected gay, bisexual, and other men who have sex with men (MSM) and transgender persons (1). JYNNEOS vaccine (Modified Vaccinia Ankara vaccine, Bavarian Nordic) was approved by the Food and Drug Administration (FDA) in 2019 for the prevention of smallpox and mpox via subcutaneous injection as a 2-dose series (0.5 mL per dose, administered 4 weeks apart) (2). To expand vaccine access, an Emergency Use Authorization was issued by FDA on August 9, 2022, for dose-sparing intradermal injection of JYNNEOS as a 2-dose series (0.1 mL per dose, administered 4 weeks apart) (3). Vaccination was available to persons with known or presumed exposure to a person with mpox (postexposure prophylaxis [PEP]), as well as persons at increased risk for mpox or who might benefit from vaccination (preexposure mpox prophylaxis [PrEP]) (4). Because information on JYNNEOS vaccine effectiveness (VE) is limited, a matched case-control study was conducted in 12 U.S. jurisdictions,† including nine Emerging Infections Program sites and three Epidemiology and Laboratory Capacity sites,§ to evaluate VE against mpox among MSM and transgender adults aged 18-49 years. During August 19, 2022-March 31, 2023, a total of 309 case-patients were matched to 608 control patients. Adjusted VE was 75.2% (95% CI = 61.2% to 84.2%) for partial vaccination (1 dose) and 85.9% (95% CI = 73.8% to 92.4%) for full vaccination (2 doses). Adjusted VE for full vaccination by subcutaneous, intradermal, and heterologous routes of administration was 88.9% (95% CI = 56.0% to 97.2%), 80.3% (95% CI = 22.9% to 95.0%), and 86.9% (95% CI = 69.1% to 94.5%), respectively. Adjusted VE for full vaccination among immunocompromised participants was 70.2% (95% CI = -37.9% to 93.6%) and among immunocompetent participants was 87.8% (95% CI = 57.5% to 96.5%). JYNNEOS is effective at reducing the risk for mpox. Because duration of protection of 1 versus 2 doses remains unknown, persons at increased risk for mpox exposure should receive the 2-dose series as recommended by the Advisory Committee on Immunization Practices (ACIP),¶ regardless of administration route or immunocompromise status.

BACKGROUND: Descriptions of changes in invasive bacterial disease (IBD) epidemiology during the coronavirus disease 2019 (COVID-19) pandemic in the United States are limited. METHODS: We investigated changes in the incidence of IBD due to Streptococcus pneumoniae, Haemophilus influenzae, group A Streptococcus (GAS), and group B Streptococcus (GBS). We defined the COVID-19 pandemic period as 1 March to 31 December 2020. We compared observed IBD incidences during the pandemic to expected incidences, consistent with January 2014 to February 2020 trends. We conducted secondary analysis of a health care database to assess changes in testing by blood and cerebrospinal fluid (CSF) culture during the pandemic. RESULTS: Compared with expected incidences, the observed incidences of IBD due to S. pneumoniae, H. influenzae, GAS, and GBS were 58%, 60%, 28%, and 12% lower during the pandemic period of 2020, respectively. Declines from expected incidences corresponded closely with implementation of COVID-19-associated nonpharmaceutical interventions (NPIs). Significant declines were observed across all age and race groups, and surveillance sites for S. pneumoniae and H. influenzae. Blood and CSF culture testing rates during the pandemic were comparable to previous years. CONCLUSIONS: NPIs likely contributed to the decline in IBD incidence in the United States in 2020; observed declines were unlikely to be driven by reductions in testing.

BackgroundThe COVID-19 pandemic has caused substantial morbidity and mortality.ObjectiveTo describe monthly clinical trends among adults hospitalized with COVID-19.DesignPooled cross-sectional study.Setting99 counties in 14 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET).PatientsU.S. adults (aged ≥18 years) hospitalized with laboratory-confirmed COVID-19 during 1 March to 31 December 2020.MeasurementsMonthly hospitalizations, intensive care unit (ICU) admissions, and in-hospital death rates per 100 000 persons in the population; monthly trends in weighted percentages of interventions, including ICU admission, mechanical ventilation, and vasopressor use, among an age- and site-stratified random sample of hospitalized case patients.ResultsAmong 116 743 hospitalized adults with COVID-19, the median age was 62 years, 50.7% were male, and 40.8% were non-Hispanic White. Monthly rates of hospitalization (105.3 per 100 000 persons), ICU admission (20.2 per 100 000 persons), and death (11.7 per 100 000 persons) peaked during December 2020. Rates of all 3 outcomes were highest among adults aged 65 years or older, males, and Hispanic or non-Hispanic Black persons. Among 18 508 sampled hospitalized adults, use of remdesivir and systemic corticosteroids increased from 1.7% and 18.9%, respectively, in March to 53.8% and 74.2%, respectively, in December. Frequency of ICU admission, mechanical ventilation, and vasopressor use decreased from March (37.8%, 27.8%, and 22.7%, respectively) to December (20.5%, 12.3%, and 12.8%, respectively); use of noninvasive respiratory support increased from March to December.LimitationCOVID-NET covers approximately 10% of the U.S. population; findings may not be generalizable to the entire country.ConclusionRates of COVID-19-associated hospitalization, ICU admission, and death were highest in December 2020, corresponding with the third peak of the U.S. pandemic. The frequency of intensive interventions for management of hospitalized patients decreased over time. These data provide a longitudinal assessment of clinical trends among adults hospitalized with COVID-19 before widespread implementation of COVID-19 vaccines.Primary funding sourceCenters for Disease Control and Prevention.

Most reported cases of coronavirus disease 2019 (COVID-19) in children aged

Electronic medical records (EMRs) are important for rapidly compiling information to determine disease characteristics (eg, symptoms) and risk factors (eg, underlying comorbidities, medications) for disease-related outcomes. To assess EMR data accuracy, agreement between EMR abstractions and patient interviews was evaluated. Symptoms, medical history, and medication use among patients with COVID-19 collected from EMRs and patient interviews were compared using overall agreement (ie, same answer in EMR and interview), reported agreement (yes answer in both EMR and interview among those who reported yes in either), and κ statistics. Overall, patients reported more symptoms in interviews than in EMR abstractions. Overall agreement was high (≥50% for 20 of 23 symptoms), but only subjective fever and dyspnea had reported agreement of ≥50%. The κ statistics for symptoms were generally low. Reported medical conditions had greater agreement with all condition categories (n = 10 of 10) having ≥50% overall agreement and half (n = 5 of 10) having ≥50% reported agreement. More nonprescription medications were reported in interviews than in EMR abstractions, leading to low reported agreement (28%). Discordance was observed for symptoms, medical history, and medication use between EMR abstractions and patient interviews. Investigations using EMRs to describe clinical characteristics and identify risk factors should consider the potential for incomplete data, particularly for symptoms and medications. [ABSTRACT FROM AUTHOR]

Mathematical transmission models are useful tools for predicting the magnitude, duration, and severity of the severe acute respiratory coronavirus 2 (SARS-CoV-2) pandemic. However, widely used national-level models might not capture [...]

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease (COVID-19), was first detected in China in December 2019 (2,2). Within 1 month, COVID-19 cases were reported [...]

Objectives: The number of SARS-CoV-2 infections is underestimated in surveillance data. Various approaches to assess the seroprevalence of antibodies to SARS-CoV-2 have different resource requirements and generalizability. We estimated the seroprevalence of antibodies to SARS-CoV-2 in Denver County, Colorado, via a cluster-sampled community survey. Methods: We estimated the overall seroprevalence of antibodies to SARS-CoV-2 via a community seroprevalence survey in Denver County in July 2020, described patterns associated with seroprevalence, and compared results with cumulative COVID-19 incidence as reported to the health department during the same period. In addition, we compared seroprevalence as assessed with a temporally and geographically concordant convenience sample of residual clinical specimens from a commercial laboratory. Results: Based on 404 specimens collected through the community survey, 8.0% (95% CI, 3.9%-15.7%) of Denver County residents had antibodies to SARS-CoV-2, an infection rate of about 7 times that of the 1.1% cumulative reported COVID-19 incidence during this period. The estimated infection-to-reported case ratio was highest among children (34.7; 95% CI, 11.1-91.2) and males (10.8; 95% CI, 5.7-19.3). Seroprevalence was highest among males of Black race or Hispanic ethnicity and was associated with previous COVID-19–compatible illness, a previous positive SARS-CoV-2 test result, and close contact with someone who had confirmed SARS-CoV-2 infection. Testing of 1598 residual clinical specimens yielded a seroprevalence of 6.8% (95% CI, 5.0%-9.2%); the difference between the 2 estimates was 1.2 percentage points (95% CI, −3.6 to 12.2 percentage points). Conclusions: Testing residual clinical specimens provided a similar seroprevalence estimate yet yielded limited insight into the local epidemiology of COVID-19 and might be less representative of the source population than a cluster-sampled community survey. Awareness of the limitations of various sampling strategies is necessary when interpreting findings from seroprevalence assessments. [ABSTRACT FROM AUTHOR]

Background: Most current evidence on risk factors for hospitalization because of coronavirus disease 2019 (COVID-19) comes from studies using data abstracted primarily from electronic health records, limited to specific populations, or that fail to capture over-the-counter medications and adjust for potential confounding factors. Properly understanding risk factors for hospitalization will help improve clinical management and facilitate targeted prevention messaging and forecasting and prioritization of clinical and public health resource needs. Objectives: To identify risk factors for hospitalization using patient questionnaires and chart abstraction. Methods: We randomly selected 600 of 1,738 laboratory-confirmed Colorado COVID-19 cases with known hospitalization status and illness onset during March 9–31, 2020. In April 2020, we collected demographics, social history, and medications taken in the 30 days before illness onset via telephone questionnaire and collected underlying medical conditions in patient questionnaires and medical record abstraction. Results: Overall, 364 patients participated; 128 were hospitalized and 236 were non-hospitalized. In multivariable analysis, chronic hypoxemic respiratory failure with oxygen requirement (adjusted odds ratio [aOR] 14.64; 95% confidence interval [CI] 1.45–147.93), taking opioids (aOR 8.05; CI 1.16–55.77), metabolic syndrome (aOR 5.71; CI 1.18–27.54), obesity (aOR 3.35; CI 1.58–7.09), age ≥65 years (aOR 3.22; CI 1.20–7.97), hypertension (aOR 3.14; CI 1.47–6.71), arrhythmia (aOR 2.95; CI 1.00–8.68), and male sex (aOR 2.65; CI 1.44–4.88), were significantly associated with hospitalization. Conclusion: We identified patient characteristics, medications, and medical conditions, including some novel ones, associated with hospitalization. These data can be used to inform clinical and public health resource needs. [ABSTRACT FROM AUTHOR]