BACKGROUND: Patients hospitalised with influenza have heterogeneous clinical presentations and disease severity, which may complicate epidemiologic study design or interpretation. We applied latent class analysis to identify clinically distinct subgroups of adults hospitalised with influenza. METHODS: We analysed cross-sectional study data on adults (≥18 years) hospitalised with laboratory-confirmed influenza from the population-based U.S. Influenza Hospitalization Surveillance Network (FluSurv-NET) including 13 states during 2017-2018 and 2018-2019 influenza seasons (October 1 through April 30). Adults were included if they were residents of the FluSurv-NET catchment area, hospitalised with laboratory-confirmed influenza during these two seasons, and had both the main case report form and the supplemental disease severity case report form completed. We constructed a latent class model to identify subgroups from multiple observed variables including baseline characteristics (age and comorbidities) and clinical course (symptoms at admission, respiratory support requirement, and development of new complications and exacerbations of underlying conditions). FINDINGS: Among the 43,811 influenza-associated hospitalizations reported during the 2017-2018 and 2018-2019 influenza seasons, 15,873 (36.2%) were included in our analytic population: among them, 7069 (44.5%) were male and 8804 (55.5%) were female. We identified five subgroups. Subgroup A included persons of all ages with few comorbidities and 87.9% (255/290) of pregnant women. Subgroup B included older adults with comorbidities (cardiovascular disease (79.7% [3650/4581]) and diabetes (50.6% [2320/4581])). Almost all patients in subgroups C and D had asthma or chronic lung disease and high proportions with exacerbations of underlying conditions (59.7% [889/1489] and 65.1% [2274/3496], respectively). Subgroup E had the highest proportion with new complications (90.3% [1383/1531]). Subgroups D and E had the highest proportions with severe disease indicators: 21.0% (733/3496) and 50.4% (771/1531) required ICU admission, 7.2% (253/3496) and 28.0% (428/1531) required invasive mechanical ventilation, and 3.3% (116/3496) and 11.4% (174/1531) died in-hospital, respectively. INTERPRETATION: The five identified subgroups of adults hospitalised with influenza had varying distributions of age, comorbid conditions, and clinical courses characterized by new complications versus exacerbations of existing conditions. Stratifying by these subgroups may strengthen analyses that assess the impact of influenza vaccination and antiviral treatment on risk of severe disease. Limitations included that results were based on a convenience sample within FluSurv-NET sites and were likely not representative of all adults hospitalised with influenza in the United States. Influenza testing was also clinician-driven, likely leading to under-ascertainment. FUNDING: Centers for Disease Control and Prevention.

IMPORTANCE: Respiratory syncytial virus (RSV) infection can cause severe illness in adults. However, there is considerable uncertainty in the burden of RSV-associated hospitalizations among adults prior to RSV vaccine introduction. OBJECTIVE: To describe the demographic characteristics of adults hospitalized with laboratory-confirmed RSV and to estimate annual rates and numbers of RSV-associated hospitalizations, intensive care unit (ICU) admissions, and in-hospital deaths. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the RSV Hospitalization Surveillance Network (RSV-NET), a population-based surveillance platform that captures RSV-associated hospitalizations in 58 counties in 12 states, covering approximately 8% of the US population. The study period spanned 7 surveillance seasons from 2016-2017 through 2022-2023. Included cases from RSV-NET were nonpregnant hospitalized adults aged 18 years or older residing in the surveillance catchment area and with a positive RSV test result. EXPOSURE: Laboratory-confirmed RSV-associated hospitalization, defined as a positive RSV test result within 14 days before or during hospitalization. MAIN OUTCOMES AND MEASURES: Hospitalization rates per 100 000 adult population, stratified by age group. After adjusting for test sensitivity and undertesting for RSV in adults hospitalized with acute respiratory illnesses, rates were extrapolated to the US population to estimate annual numbers of RSV-associated hospitalizations. Clinical outcome data were used to estimate RSV-associated ICU admissions and in-hospital deaths. RESULTS: From the 2016 to 2017 through the 2022 to 2023 RSV seasons, there were 16 575 RSV-associated hospitalizations in adults (median [IQR] age, 70 [58-81] years; 9641 females [58.2%]). Excluding the 2020 to 2021 and the 2021 to 2022 seasons, when the COVID-19 pandemic affected RSV circulation, hospitalization rates ranged from 48.9 (95% CI, 33.4-91.5) per 100 000 adults in 2016 to 2017 to 76.2 (95% CI, 55.2-122.7) per 100 000 adults in 2017 to 2018. Rates were lowest among adults aged 18 to 49 years (8.6 [95% CI, 5.7-16.8] per 100 000 adults in 2016-2017 to 13.1 [95% CI, 11.0-16.1] per 100 000 adults in 2022-2023) and highest among adults 75 years or older (244.7 [95% CI, 207.9-297.3] per 100 000 adults in 2022-2023 to 411.4 [95% CI, 292.1-695.4] per 100 000 adults in 2017-2018). Annual hospitalization estimates ranged from 123 000 (95% CI, 84 000-230 000) in 2016 to 2017 to 193 000 (95% CI, 140 000-311 000) in 2017 to 2018. Annual ICU admission estimates ranged from 24 400 (95% CI, 16 700-44 800) to 34 900 (95% CI, 25 500-55 600) for the same seasons. Estimated annual in-hospital deaths ranged from 4680 (95% CI, 3570-6820) in 2018 to 2019 to 8620 (95% CI, 6220-14 090) in 2017 to 2018. Adults 75 years or older accounted for 45.6% (range, 43.1%-48.8%) of all RSV-associated hospitalizations, 38.6% (range, 36.7%-41.0%) of all ICU admissions, and 58.7% (range, 51.9%-67.1%) of all in-hospital deaths. CONCLUSIONS AND RELEVANCE: In this cross-sectional study of adults hospitalized with RSV before the 2023 introduction of RSV vaccines, RSV was associated with substantial burden of hospitalizations, ICU admissions, and in-hospital deaths in adults, with the highest rates occurring in adults 75 years or older. Increasing RSV vaccination of older adults has the potential to reduce associated hospitalizations and severe clinical outcomes.

We compared mpox vaccination access between urban and rural residents who received ≥1 JYNNEOS dose using immunization data in Idaho and New Mexico. Rural residents traveled five times farther and three times longer than urban residents to receive mpox vaccination. Increasing mpox vaccine availability to healthcare facilities might increase uptake.

The percentage of positive SARS-CoV-2 tests has been used with other metrics to reflect community transmission and guide community prevention strategies [1,2]. The Centers for Disease Control and Prevention (CDC) recommends calculating percent positivity as the number of positive nucleic acid amplification tests (NAAT) divided by the total number of NAAT results reported during a specified period (e.g., 7 days).1 | | Individuals may have repeat testing for COVID-19 during or following their infection, which is not reflective of new cases in the community. This analysis assesses the impact on percent positivity of deduplicating and censoring SARS-CoV-2 test results at the person level.

Previous reports of COVID-19 case, hospitalization, and death rates by vaccination status() indicate that vaccine protection against infection, as well as serious COVID-19 illness for some groups, declined with the emergence of the B.1.617.2 (Delta) variant of SARS-CoV-2, the virus that causes COVID-19, and waning of vaccine-induced immunity (1-4). During August-November 2021, CDC recommended() additional primary COVID-19 vaccine doses among immunocompromised persons and booster doses among persons aged 18 years (5). The SARS-CoV-2 B.1.1.529 (Omicron) variant emerged in the United States during December 2021 (6) and by December 25 accounted for 72% of sequenced lineages (7). To assess the impact of full vaccination with additional and booster doses (booster doses),() case and death rates and incidence rate ratios (IRRs) were estimated among unvaccinated and fully vaccinated adults by receipt of booster doses during pre-Delta (April-May 2021), Delta emergence (June 2021), Delta predominance (July-November 2021), and Omicron emergence (December 2021) periods in the United States. During 2021, averaged weekly, age-standardized case IRRs among unvaccinated persons compared with fully vaccinated persons decreased from 13.9 pre-Delta to 8.7 as Delta emerged, and to 5.1 during the period of Delta predominance. During October-November, unvaccinated persons had 13.9 and 53.2 times the risks for infection and COVID-19-associated death, respectively, compared with fully vaccinated persons who received booster doses, and 4.0 and 12.7 times the risks compared with fully vaccinated persons without booster doses. When the Omicron variant emerged during December 2021, case IRRs decreased to 4.9 for fully vaccinated persons with booster doses and 2.8 for those without booster doses, relative to October-November 2021. The highest impact of booster doses against infection and death compared with full vaccination without booster doses was recorded among persons aged 50-64 and 65 years. Eligible persons should stay up to date with COVID-19 vaccinations.

OBJECTIVES: Describe population-based rates and risk factors for severe coronavirus disease 2019 (COVID-19) (ie, ICU admission, invasive mechanical ventilation, or death) among hospitalized children. METHODS: During March 2020 to May 2021, the COVID-19-Associated Hospitalization Surveillance Network identified 3106 children hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection in 14 states. Among 2293 children primarily admitted for COVID-19, multivariable generalized estimating equations generated adjusted risk ratios (aRRs) and 95% confidence intervals (CIs) of the associations between demographic and medical characteristics abstracted from medical records and severe COVID-19. We calculated age-adjusted cumulative population-based rates of severe COVID-19 among all children. RESULTS: Approximately 30% of hospitalized children had severe COVID-19; 0.5% died during hospitalization. Among hospitalized children aged <2 years, chronic lung disease (aRR: 2.2; 95% CI: 1.1-4.3), neurologic disorders (aRR: 2.0; 95% CI: 1.5‒2.6), cardiovascular disease (aRR: 1.7; 95% CI: 1.2‒2.3), prematurity (aRR: 1.6; 95% CI: 1.1‒2.2), and airway abnormality (aRR: 1.6; 95% CI: 1.1‒2.2) were associated with severe COVID-19. Among hospitalized children aged 2 to 17 years, feeding tube dependence (aRR: 2.0; 95% CI: 1.5‒2.5), diabetes mellitus (aRR: 1.9; 95% CI: 1.6‒2.3) and obesity (aRR: 1.2; 95% CI: 1.0‒1.4) were associated with severe COVID-19. Severe COVID-19 occurred among 12.0 per 100 000 children overall and was highest among infants, Hispanic children, and non-Hispanic Black children. CONCLUSIONS: Results identify children at potentially higher risk of severe COVID-19 who may benefit from prevention efforts, including vaccination. Rates establish a baseline for monitoring changes in pediatric illness severity after increased availability of COVID-19 vaccines and the emergence of new variants.

OBJECTIVES: Describe population-based rates and risk factors for severe coronavirus disease 2019 (COVID-19) (ie, ICU admission, invasive mechanical ventilation, or death) among hospitalized children. METHODS: During March 2020 to May 2021, the COVID-19-Associated Hospitalization Surveillance Network identified 3106 children hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 infection in 14 states. Among 2293 children primarily admitted for COVID-19, multivariable generalized estimating equations generated adjusted risk ratios (aRRs) and 95% confidence intervals (CIs) of the associations between demographic and medical characteristics abstracted from medical records and severe COVID-19. We calculated age-adjusted cumulative population-based rates of severe COVID-19 among all children. RESULTS: Approximately 30% of hospitalized children had severe COVID-19; 0.5% died during hospitalization. Among hospitalized children aged <2 years, chronic lung disease (aRR: 2.2; 95% CI: 1.1-4.3), neurologic disorders (aRR: 2.0; 95% CI: 1.52.6), cardiovascular disease (aRR: 1.7; 95% CI: 1.22.3), prematurity (aRR: 1.6; 95% CI: 1.12.2), and airway abnormality (aRR: 1.6; 95% CI: 1.12.2) were associated with severe COVID-19. Among hospitalized children aged 2 to 17 years, feeding tube dependence (aRR: 2.0; 95% CI: 1.52.5), diabetes mellitus (aRR: 1.9; 95% CI: 1.62.3) and obesity (aRR: 1.2; 95% CI: 1.01.4) were associated with severe COVID-19. Severe COVID-19 occurred among 12.0 per 100 000 children overall and was highest among infants, Hispanic children, and non-Hispanic Black children. CONCLUSIONS: Results identify children at potentially higher risk of severe COVID-19 who may benefit from prevention efforts, including vaccination. Rates establish a baseline for monitoring changes in pediatric illness severity after increased availability of COVID-19 vaccines and the emergence of new variants.

OBJECTIVES: Some studies suggested more COVID-19-associated hospitalizations among racial and ethnic minorities. To inform public health practice, the COVID-19-associated Hospitalization Surveillance Network (COVID-NET) quantified associations between race/ethnicity, census tract socioeconomic indicators, and COVID-19-associated hospitalization rates. METHODS: Using data from COVID-NET population-based surveillance reported during March 1-April 30, 2020 along with socioeconomic and denominator data from the US Census Bureau, we calculated COVID-19-associated hospitalization rates by racial/ethnic and census tract-level socioeconomic strata. RESULTS: Among 16,000 COVID-19-associated hospitalizations, 34.8% occurred among non-Hispanic White (White) persons, 36.3% among non-Hispanic Black (Black) persons, and 18.2% among Hispanic or Latino (Hispanic) persons. Age-adjusted COVID-19-associated hospitalization rate were 151.6 (95% Confidence Interval (CI): 147.1-156.1) in census tracts with >15.2%-83.2% of persons living below the federal poverty level (high-poverty census tracts) and 75.5 (95% CI: 72.9-78.1) in census tracts with 0%-4.9% of persons living below the federal poverty level (low-poverty census tracts). Among White, Black, and Hispanic persons living in high-poverty census tracts, age-adjusted hospitalization rates were 120.3 (95% CI: 112.3-128.2), 252.2 (95% CI: 241.4-263.0), and 341.1 (95% CI: 317.3-365.0), respectively, compared with 58.2 (95% CI: 55.4-61.1), 304.0 (95%: 282.4-325.6), and 540.3 (95% CI: 477.0-603.6), respectively, in low-poverty census tracts. CONCLUSIONS: Overall, COVID-19-associated hospitalization rates were highest in high-poverty census tracts, but rates among Black and Hispanic persons were high regardless of poverty level. Public health practitioners must ensure mitigation measures and vaccination campaigns address needs of racial/ethnic minority groups and people living in high-poverty census tracts.

Clinical trials of COVID-19 vaccines currently authorized for emergency use in the United States (Pfizer-BioNTech, Moderna, and Janssen [Johnson & Johnson]) indicate that these vaccines have high efficacy against symptomatic disease, including moderate to severe illness (1-3). In addition to clinical trials, real-world assessments of COVID-19 vaccine effectiveness are critical in guiding vaccine policy and building vaccine confidence, particularly among populations at higher risk for more severe illness from COVID-19, including older adults. To determine the real-world effectiveness of the three currently authorized COVID-19 vaccines among persons aged ≥65 years during February 1-April 30, 2021, data on 7,280 patients from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) were analyzed with vaccination coverage data from state immunization information systems (IISs) for the COVID-NET catchment area (approximately 4.8 million persons). Among adults aged 65-74 years, effectiveness of full vaccination in preventing COVID-19-associated hospitalization was 96% (95% confidence interval [CI] = 94%-98%) for Pfizer-BioNTech, 96% (95% CI = 95%-98%) for Moderna, and 84% (95% CI = 64%-93%) for Janssen vaccine products. Effectiveness of full vaccination in preventing COVID-19-associated hospitalization among adults aged ≥75 years was 91% (95% CI = 87%-94%) for Pfizer-BioNTech, 96% (95% CI = 93%-98%) for Moderna, and 85% (95% CI = 72%-92%) for Janssen vaccine products. COVID-19 vaccines currently authorized in the United States are highly effective in preventing COVID-19-associated hospitalizations in older adults. In light of real-world data demonstrating high effectiveness of COVID-19 vaccines among older adults, efforts to increase vaccination coverage in this age group are critical to reducing the risk for COVID-19-related hospitalization.

Pregnant women might be at increased risk for severe coronavirus disease 2019 (COVID-19) (1,2). The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) (3) collects data on hospitalized pregnant women with laboratory-confirmed SARS-CoV-2, the virus that causes COVID-19; to date, such data have been limited. During March 1-August 22, 2020, approximately one in four hospitalized women aged 15-49 years with COVID-19 was pregnant. Among 598 hospitalized pregnant women with COVID-19, 54.5% were asymptomatic at admission. Among 272 pregnant women with COVID-19 who were symptomatic at hospital admission, 16.2% were admitted to an intensive care unit (ICU), and 8.5% required invasive mechanical ventilation. During COVID-19-associated hospitalizations, 448 of 458 (97.8%) completed pregnancies resulted in a live birth and 10 (2.2%) resulted in a pregnancy loss. Testing policies based on the presence of symptoms might miss COVID-19 infections during pregnancy. Surveillance of pregnant women with COVID-19, including those with asymptomatic infections, is important to understand the short- and long-term consequences of COVID-19 for mothers and newborns. Identifying COVID-19 in women during birth hospitalizations is important to guide preventive measures to protect pregnant women, parents, newborns, other patients, and hospital personnel. Pregnant women and health care providers should be made aware of the potential risks for severe COVID-19 illness, adverse pregnancy outcomes, and ways to prevent infection.

We studied departures from regulatory requirements identified on US Federal Select Agent Program (FSAP) inspections to increase transparency regarding biosafety and security risk at FSAP-regulated entities and identify areas for programmatic improvement. Regulatory departures from inspections led by Centers for Disease Control and Prevention inspectors during 2014-15 were grouped into "biosafety," "security," and "other" observation categories and assigned a risk level and score reflecting perceived severity. The resulting 2,267 biosafety (n = 1,153) and security (n = 1,114) observations from 296 inspections were analyzed by frequency and risk across entity and inspection characteristics. The greatest proportion of biosafety observations involved equipment and facilities (28%), and the greatest proportion of security observations involved access restrictions (33%). The greatest proportion of higher-risk observations for biosafety were containment issues and for security were inventory discrepancies. Commercial entities had the highest median cumulative risk score per inspection (17), followed by private (13), academic (10), federal government (10), and nonfederal government (8). Maximum containment (BSL-4) inspections had higher median biosafety risk per inspection (13) than other inspections (5) and lower security risk (0 vs 4). Unannounced inspections had proportionally more upper risk level observations than announced (biosafety, 21% vs 12%; security, 18% vs 7%). Possessors of select agents had higher median biosafety risk per inspection (6) than nonpossessors (4) and more upper risk level security observations (10% vs 0%). Programmatic changes to balance resources according to entity risk may strengthen FSAP oversight. Varying inspection methods by select agent possession and entity type, and conducting more unannounced inspections, may be beneficial.

OBJECTIVE: To build a tool to assist disaster response planning and estimate the numbers of displaced persons that will require special medical care during a disaster. METHODS: We developed a tool, titled MedCon:PreEvent, which incorporates data from the 2006 National Health Interview Survey, 2005 National Hospital Discharge Survey, and 2004 National Nursing Home Survey to calculate numbers of emergency room/emergency department (ER/ED) visits, surgeries, health care home visits, overnight hospital stays, office visits, and self-rated health status. We then used thresholds of more than 12 office visits or 6 or more ER/ED visits or 6 or more surgeries or more than 4 home visits or more than 6 overnight hospital stays within the past 12 months to calculate rates per million evacuees requiring special medical care, including daily bed hospital and nursing home bed occupancy. RESULTS: We calculated that 79,428 (95% CI = 76,940-81,770) per million evacuees would need special medical care. The daily occupation of hospital beds would be 1710 beds (95% CI = 1328-2160) per million. The occupation of nursing home beds would be 5094 beds (95% CI = 5040-5148) per million. Changing the threshold to just those who self-rated health as "poor," the demand for special medical care would be 24,348 (95% CI = 23,087-25,535) per million. Using threshold utilization values at half the original level would increase the estimate to 226,988 (95% CI = 224,444-229,384) per million. CONCLUSIONS: A substantial number of persons with preexisting conditions will need suitable medical care following a disaster. The MedCon:PreEvent tool can assist disaster planners to prepare for medical care needs of large numbers of evacuees and consider re-evaluating the approach to utilizing and augmenting medical care services.