ABSTRACT
Respiratory syncytial virus (RSV) causes substantial morbidity and mortality in older adults. In May 2023, two subunit RSV vaccines (Arexvy [GSK] and Abrysvo [Pfizer]) received approval from the U.S. Food and Drug Administration (FDA). In June 2023, ACIP recommended that adults aged ≥60 years may receive a single dose of RSV vaccine, using shared clinical decision-making. In support of development of this policy, our objective was to assess the cost-effectiveness of RSV vaccination in the general population in this age group. We used a decision-analytical model of RSV over a two-year timeframe using data from published literature, FDA documents, epidemiological databases, and manufacturer data. We tracked RSV-associated outpatient, emergency department, inpatient healthcare utilization, RSV-attributable deaths, quality-adjusted life-years lost (QALYs), and societal costs. The societal cost per QALY saved from RSV vaccination depended on age group and product: adults aged ≥60 years, $196,842 for GSK's vaccine and $176,557 for Pfizer's vaccine; adults ≥65 years, $162,138 for GSK and $146,543 for Pfizer; adults 60- <65 years, $385,829 for GSK and $331,486 for Pfizer. Vaccine efficacy, incidence of RSV hospitalization, and vaccine cost had the greatest influence on cost per QALY. Cost per QALY saved decreased as the age of those vaccinated increased. Inputs such as long-term efficacy are uncertain. RSV vaccination in adults aged ≥60 years may be cost-effective, particularly in those of more advanced age. Lower vaccine acquisition costs and persistent efficacy beyond two RSV seasons would render RSV vaccination more cost-effective for a broader target population. PRIMARY FUNDING SOURCE: US Centers for Disease Control and Prevention.
ABSTRACT
Respiratory syncytial virus (RSV) causes substantial morbidity and mortality in older adults. In May 2023, two RSV vaccines were approved for prevention of RSV lower respiratory tract disease in adults aged ≥60 years. In June 2023, CDC recommended RSV vaccination for adults aged ≥60 years, using shared clinical decision-making. Using data from the Respiratory Syncytial Virus-Associated Hospitalization Surveillance Network, a population-based hospitalization surveillance system operating in 12 states, this analysis examined characteristics (including age, underlying medical conditions, and clinical outcomes) of 3,218 adults aged ≥60 years who were hospitalized with laboratory-confirmed RSV infection during July 2022-June 2023. Among a random sample of 1,634 older adult patients with RSV-associated hospitalization, 54.1% were aged ≥75 years, and the most common underlying medical conditions were obesity, chronic obstructive pulmonary disease, congestive heart failure, and diabetes. Severe outcomes occurred in 18.5% (95% CI = 15.9%-21.2%) of hospitalized patients aged ≥60 years. Overall, 17.0% (95% CI = 14.5%-19.7%) of patients with RSV infection were admitted to an intensive care unit, 4.8% (95% CI = 3.5%-6.3%) required mechanical ventilation, and 4.7% (95% CI = 3.6%-6.1%) died; 17.2% (95% CI = 14.9%-19.8%) of all cases occurred in long-term care facility residents. These data highlight the importance of prioritizing those at highest risk for severe RSV disease and suggest that clinicians and patients consider age (particularly age ≥75 years), long-term care facility residence, and underlying medical conditions, including chronic obstructive pulmonary disease and congestive heart failure, in shared clinical decision-making when offering RSV vaccine to adults aged ≥60 years.
Subject(s)
Heart Failure , Pulmonary Disease, Chronic Obstructive , Respiratory Syncytial Virus Infections , Humans , Aged , Middle Aged , Respiratory Syncytial Viruses , Respiratory Syncytial Virus Infections/epidemiology , Respiratory Syncytial Virus Infections/drug therapy , HospitalizationABSTRACT
Respiratory syncytial virus (RSV) causes substantial morbidity and mortality in older adults. In May 2023, two RSV vaccines were approved for prevention of RSV lower respiratory tract disease in adults aged ≥60 years. In June 2023, CDC recommended RSV vaccination for adults aged ≥60 years, using shared clinical decision-making. Using data from the Respiratory Syncytial Virus-Associated Hospitalization Surveillance Network, a population-based hospitalization surveillance system operating in 12 states, this analysis examined characteristics (including age, underlying medical conditions, and clinical outcomes) of 3,218 adults aged ≥60 years who were hospitalized with laboratory-confirmed RSV infection during July 2022-June 2023. Among a random sample of 1,634 older adult patients with RSV-associated hospitalization, 54.1% were aged ≥75 years, and the most common underlying medical conditions were obesity, chronic obstructive pulmonary disease, congestive heart failure, and diabetes. Severe outcomes occurred in 18.5% (95% CI = 15.9%-21.2%) of hospitalized patients aged ≥60 years. Overall, 17.0% (95% CI = 14.5%-19.7%) of patients with RSV infection were admitted to an intensive care unit, 4.8% (95% CI = 3.5%-6.3%) required mechanical ventilation, and 4.7% (95% CI = 3.6%-6.1%) died; 17.2% (95% CI = 14.9%-19.8%) of all cases occurred in long-term care facility residents. These data highlight the importance of prioritizing those at highest risk for severe RSV disease and suggest that clinicians and patients consider age (particularly age ≥75 years), long-term care facility residence, and underlying medical conditions, including chronic obstructive pulmonary disease and congestive heart failure, in shared clinical decision-making when offering RSV vaccine to adults aged ≥60 years.
Subject(s)
Heart Failure , Pulmonary Disease, Chronic Obstructive , Respiratory Syncytial Virus Infections , Respiratory Syncytial Virus, Human , Humans , Aged , Middle Aged , Respiratory Syncytial Virus Infections/epidemiology , Respiratory Syncytial Virus Infections/therapy , HospitalizationABSTRACT
Background: Clinical trials initiated during emerging infectious disease outbreaks must quickly enroll participants to identify treatments to reduce morbidity and mortality. This may be at odds with enrolling a representative study population, especially when the population affected is undefined. Methods: We evaluated the utility of the Centers for Disease Control and Prevention's COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), the COVID-19 Case Surveillance System (CCSS), and 2020 United States (US) Census data to determine demographic representation in the 4 stages of the Adaptive COVID-19 Treatment Trial (ACTT). We compared the cumulative proportion of participants by sex, race, ethnicity, and age enrolled at US ACTT sites, with respective 95% confidence intervals, to the reference data in forest plots. Results: US ACTT sites enrolled 3509 adults hospitalized with COVID-19. When compared with COVID-NET, ACTT enrolled a similar or higher proportion of Hispanic/Latino and White participants depending on the stage, and a similar proportion of African American participants in all stages. In contrast, ACTT enrolled a higher proportion of these groups when compared with US Census and CCSS. The proportion of participants aged ≥65 years was either similar or lower than COVID-NET and higher than CCSS and the US Census. The proportion of females enrolled in ACTT was lower than the proportion of females in the reference datasets. Conclusions: Although surveillance data of hospitalized cases may not be available early in an outbreak, they are a better comparator than US Census data and surveillance of all cases, which may not reflect the population affected and at higher risk of severe disease.
ABSTRACT
Fungal respiratory illnesses caused by endemic mycoses can be nonspecific and are often mistaken for viral or bacterial infections. We performed fungal testing on serum specimens from patients hospitalized with acute respiratory illness (ARI) to assess the possible role of endemic fungi as etiologic agents. Patients hospitalized with ARI at a Veterans Affairs hospital in Houston, Texas, during November 2016-August 2017 were enrolled. Epidemiologic and clinical data, nasopharyngeal and oropharyngeal samples for viral testing (PCR), and serum specimens were collected at admission. We retrospectively tested remnant sera from a subset of patients with negative initial viral testing using immunoassays for the detection of Coccidioides and Histoplasma antibodies (Ab) and Cryptococcus, Aspergillus, and Histoplasma antigens (Ag). Of 224 patient serum specimens tested, 49 (22%) had positive results for fungal pathogens, including 30 (13%) by Coccidioides immunodiagnostic assays, 19 (8%) by Histoplasma immunodiagnostic assays, 2 (1%) by Aspergillus Ag, and none by Cryptococcus Ag testing. A high proportion of veterans hospitalized with ARI had positive serological results for fungal pathogens, primarily endemic mycoses, which cause fungal pneumonia. The high proportion of Coccidioides positivity is unexpected as this fungus is not thought to be common in southeastern Texas or metropolitan Houston, though is known to be endemic in southwestern Texas. Although serological testing suffers from low specificity, these results suggest that these fungi may be more common causes of ARI in southeast Texas than commonly appreciated and more increased clinical evaluation may be warranted.
ABSTRACT
OBJECTIVES: To assess the clinical impact of respiratory virus codetections among children hospitalized with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: During March 2020 to February 2022, the US coronavirus disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET) identified 4372 children hospitalized with SARS-CoV-2 infection admitted primarily for fever, respiratory illness, or presumed COVID-19. We compared demographics, clinical features, and outcomes between those with and without codetections who had any non-SARS-CoV-2 virus testing. Among a subgroup of 1670 children with complete additional viral testing, we described the association between presence of codetections and severe respiratory illness using age-stratified multivariable logistic regression models. RESULTS: Among 4372 children hospitalized, 62% had non-SARS-CoV-2 respiratory virus testing, of which 21% had a codetection. Children with codetections were more likely to be <5 years old (yo), receive increased oxygen support, or be admitted to the ICU (P < .001). Among children <5 yo, having any viral codetection (<2 yo: adjusted odds ratio [aOR] 2.1 [95% confidence interval [CI] 1.5-3.0]; 2-4 yo: aOR 1.9 [95% CI 1.2-3.1]) or rhinovirus/enterovirus codetection (<2 yo: aOR 2.4 [95% CI 1.6-3.7]; 2-4: aOR 2.4 [95% CI 1.2-4.6]) was significantly associated with severe illness. Among children <2 yo, respiratory syncytial virus (RSV) codetections were also significantly associated with severe illness (aOR 1.9 [95% CI 1.3-2.9]). No significant associations were seen among children ≥5 yo. CONCLUSIONS: Respiratory virus codetections, including RSV and rhinovirus/enterovirus, may increase illness severity among children <5 yo hospitalized with SARS-CoV-2 infection.
Subject(s)
COVID-19 , Respiratory Tract Infections , SARS-CoV-2 , Humans , Male , Female , Child, Preschool , Child , COVID-19/diagnosis , COVID-19/epidemiology , Respiratory Tract Infections/diagnosis , Respiratory Tract Infections/epidemiology , Hospitalization , Coinfection , SARS-CoV-2/isolation & purification , Viruses , Infant , Adolescent , Cross-Sectional StudiesABSTRACT
BACKGROUND: COVID-19 is associated with cardiac complications. OBJECTIVES: The purpose of this study was to estimate the prevalence, risk factors, and outcomes associated with acute cardiac events during COVID-19-associated hospitalizations among adults. METHODS: During January 2021 to November 2021, medical chart abstraction was conducted on a probability sample of adults hospitalized with laboratory-confirmed SARS-CoV-2 infection identified from 99 U.S. counties in 14 U.S. states in the COVID-19-Associated Hospitalization Surveillance Network. We calculated the prevalence of acute cardiac events (identified by International Classification of Diseases-10th Revision-Clinical Modification codes) by history of underlying cardiac disease and examined associated risk factors and disease outcomes. RESULTS: Among 8,460 adults, 11.4% (95% CI: 10.1%-12.9%) experienced an acute cardiac event during a COVID-19-associated hospitalization. Prevalence was higher among adults who had underlying cardiac disease (23.4%; 95% CI: 20.7%-26.3%) compared with those who did not (6.2%; 95% CI: 5.1%-7.6%). Acute ischemic heart disease (5.5%; 95% CI: 4.5%-6.5%) and acute heart failure (5.4%; 95% CI: 4.4%-6.6%) were the most prevalent events; 0.3% (95% CI: 0.1%-0.5%) experienced acute myocarditis or pericarditis. Risk factors varied by underlying cardiac disease status. Patients with ≥1 acute cardiac event had greater risk of intensive care unit admission (adjusted risk ratio: 1.9; 95% CI: 1.8-2.1) and in-hospital death (adjusted risk ratio: 1.7; 95% CI: 1.3-2.1) compared with those who did not. CONCLUSIONS: Acute cardiac events were common during COVID-19-associated hospitalizations, particularly among patients with underlying cardiac disease, and are associated with severe disease outcomes. Persons at greater risk for experiencing acute cardiac events during COVID-19-associated hospitalizations might benefit from more intensive clinical evaluation and monitoring during hospitalization.
Subject(s)
COVID-19 , Heart Diseases , Adult , Humans , COVID-19/complications , COVID-19/epidemiology , SARS-CoV-2 , Hospital Mortality , Hospitalization , Heart Diseases/epidemiologyABSTRACT
We used smartphone technology to differentiate the gait characteristics of older adults with osteoporosis with falls from those without falls. We assessed gait mannerism and obtained activities of daily living (ADLs) with wearable sensor systems (smartphones and inertial measurement units [IMUs]) to identify fall-risk characteristics. We recruited 49 persons with osteoporosis: 14 who had a fall within a year before recruitment and 35 without falls. IMU sensor signals were sampled at 50 Hz using a customized smartphone app (Lockhart Monitor) attached at the pelvic region. Longitudinal data was collected using MoveMonitor+ (DynaPort) IMU over three consecutive days. Given the close association between serum calcium, albumin, PTH, Vitamin D, and musculoskeletal health, we compared these markers in individuals with history of falls as compared to nonfallers. For the biochemical parameters fall group had significantly lower calcium (P = 0.01*) and albumin (P = 0.05*) and higher parathyroid hormone levels (P = 0.002**) than nonfall group. In addition, persons with falls had higher sway area (P = 0.031*), lower dynamic stability (P < 0.001***), gait velocity (P = 0.012*), and were less able to perform ADLs (P = 0.002**). Thus, persons with osteoporosis with a history of falls can be differentiated by using dynamic real-time measurements that can be easily captured by a smartphone app, thus avoiding traditional postural sway and gait measures that require individuals to be tested in a laboratory setting.
Subject(s)
Osteoporosis , Wearable Electronic Devices , Humans , Aged , Smartphone , Calcium , Activities of Daily Living , Gait , Posture , AlbuminsABSTRACT
BACKGROUND: The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) required a sampling methodology that allowed for production of timely population-based clinical estimates to inform the ongoing US COVID-19 pandemic response. METHODS: We developed a flexible sampling approach that considered reporting delays, differential hospitalized case burden across surveillance sites, and changing geographic and demographic trends over time. We incorporated weighting methods to adjust for the probability of selection and non-response, and to calibrate the sampled case distribution to the population distribution on demographics. We additionally developed procedures for variance estimation. RESULTS: Between March 2020 and June 2021, 19,293 (10.4%) of all adult hospitalized cases were sampled for chart abstraction. Variance estimates for select variables of interest were within desired ranges. CONCLUSIONS: COVID-NET's sampling methodology allowed for reporting of robust and timely, population-based data on the clinical epidemiology of COVID-19-associated hospitalizations and evolving trends over time, while attempting to reduce data collection burden on surveillance sites. Such methods may provide a general framework for other surveillance systems needing to quickly and efficiently collect and disseminate data for public health action.
Subject(s)
COVID-19 , Adult , Humans , United States/epidemiology , COVID-19/epidemiology , Pandemics , Population Surveillance/methods , Public Health , HospitalizationABSTRACT
BACKGROUND: Dual-energy X-ray absorptiometry (DXA) is an exam that measures areal bone mineral density (aBMD) and is regularly used to diagnose and monitor osteoporosis. Except for exam quality issues such as operator error, the quantitative results of an exam are not modified by a radiologist or other physician. DXA cross-calibration errors can shift diagnoses, conceivably leading to alternate intervention decisions and patient outcomes. PURPOSE: After identifying and correcting a cross-calibration bias of 3.8% in our two DXA scanners' aBMD measurements, we investigated misdiagnosis rates for given cross-calibration errors in a single patient cohort to determine the impact on patient care and the value of cross-calibration quality control. METHODS: The studied cohort was 8012 patients of all ages and sexes with femoral neck exams that were scanned on a single DXA unit from October 1, 2018 to March 31, 2021. There were six subcohorts delineated by age and sex, three female groups and three male groups. Data reporting focused on the highest risk subcohort of 2840 females aged 65 or older. The DXA unit had no calibration changes during that time. Only one femoral neck-left or right-was randomly chosen for analysis. Patients with multiple qualifying exams within the time interval had one exam randomly chosen. The proof-of-principle simulation shifted the aBMD values within a range of ±10%, ±8%, ±6%, ±4%, ±3.5%, ±3%, ±2.5%, ±2%, ±1.5%, ±1%, ±0.5%, and 0 (no shift); the cross-calibration shifts were informed by published results and institutional experience. Measurement precision was modeled by randomly sampling a Gaussian distribution characterized by the worst acceptable least significant change (LSC) of 6.9%, with 100 000 samplings for each patient. T-scores were recalculated from the shifted aBMD values, followed by reassigned diagnoses from the World Health Organization's T-score-based scheme. RESULTS: The unshifted original subcohort of women aged 65 and older had 599 normal diagnoses (21.1% of the cohort), 1784 osteopenia diagnoses (62.8%), and 455 osteoporosis diagnoses (16.1%). Osteoporosis diagnosis rates were highly sensitive to aBMD shifts. At the extrema, a -10% aBMD shift led to +161% osteoporosis cases, and a +10% aBMD shift led to -64.5% osteoporosis cases. Within the more plausible ±4% aBMD error range, the osteoporosis diagnosis rate changed -10.5% per +1% aBMD shift as indicated by linear regression (R2 = 0.98). Except for the men aged 49 years and younger subcohort, the total cohort and five subcohorts had fit line slopes ranging between -9.7% and -12.1% with R2 ≥ 0.98. Cross-calibration bias had greater influence for diagnosis count rates compared to measurement precision, that is, LSC. CONCLUSIONS: These results quantify the degree of misdiagnosis that can occur in a clinically relevant cohort due to cross-calibration bias. In medical practices where patients may be scanned on more than one DXA unit, ensuring cross-calibration quality is a critical and high-value quality control task with direct impact on patient diagnosis and treatment course. The clinical impact and incidence of poor DXA quality control practices, and cross-calibration in particular, should be studied further.
Subject(s)
Femur Neck , Osteoporosis , Humans , Female , Male , Absorptiometry, Photon , Femur Neck/diagnostic imaging , Bone Density , Osteoporosis/diagnostic imaging , Osteoporosis/epidemiology , Diagnostic ErrorsABSTRACT
BACKGROUND: Influenza virus and SARS-CoV-2 are significant causes of respiratory illness in children. METHODS: Influenza- and COVID-19-associated hospitalizations among children <18 years old were analyzed from FluSurv-NET and COVID-NET, 2 population-based surveillance systems with similar catchment areas and methodology. The annual COVID-19-associated hospitalization rate per 100 000 during the ongoing COVID-19 pandemic (1 October 2020-30 September 2021) was compared with influenza-associated hospitalization rates during the 2017-2018 through 2019-2020 influenza seasons. In-hospital outcomes, including intensive care unit (ICU) admission and death, were compared. RESULTS: Among children <18 years, the COVID-19-associated hospitalization rate (48.2) was higher than influenza-associated hospitalization rates: 2017-2018 (33.5), 2018-2019 (33.8), and 2019-2020 (41.7). The COVID-19-associated hospitalization rate was higher among adolescents 12-17 years old (COVID-19: 59.9; influenza range: 12.2-14.1), but similar or lower among children 5-11 (COVID-19: 25.0; influenza range: 24.3-31.7) and 0-4 (COVID-19: 66.8; influenza range: 70.9-91.5) years old. Among children <18 years, a higher proportion with COVID-19 required ICU admission compared with influenza (26.4% vs 21.6%; P < .01). Pediatric deaths were uncommon during both COVID-19- and influenza-associated hospitalizations (0.7% vs 0.5%; P = .28). CONCLUSIONS: In the setting of extensive mitigation measures during the COVID-19 pandemic, the annual COVID-19-associated hospitalization rate during 2020-2021 was higher among adolescents and similar or lower among children <12 years compared with influenza during the 3 seasons before the COVID-19 pandemic. COVID-19 adds substantially to the existing burden of pediatric hospitalizations and severe outcomes caused by influenza and other respiratory viruses.
Subject(s)
COVID-19 , Influenza, Human , Adolescent , Child , Humans , United States/epidemiology , Aged , Aged, 80 and over , Influenza, Human/epidemiology , Influenza, Human/complications , COVID-19/epidemiology , COVID-19/complications , Pandemics , SARS-CoV-2 , HospitalizationABSTRACT
Emerging advanced therapies that include cell and gene therapies and tissue-engineered products offer substantial therapeutic benefits. They also present challenges for health services in their modes of delivery to patients. Funding was made available in the United Kingdom to establish three advanced therapies treatment centers and a network to coordinate their activities, supported by the Cell and Gene Therapy Catapult. The aim of this initiative was to grow the advanced therapies sector in the United Kingdom by enhancing access to the National Health Service for patients and industry through close collaboration between advanced therapy companies and publicly funded services and regulators. In this study, we describe the initiative's antecedents, its collaborative structures and management, and its activities. A guiding concept in shaping and assessing progress has been the idea of institutional readiness, an idea developed in the context of social sciences that defines and so can measure movement toward an organization's full competence in delivering new technologies and approaches. We also report the initiative's outcomes and impacts as assessed by ourselves and by third parties. As the initiative has progressed, it has excited increasing interest from advanced therapy companies who were not aware of or engaged in it at the outset and from health care systems that wished to learn from its practices. It is to further that end that we present our study.
Subject(s)
Delivery of Health Care , State Medicine , Humans , United KingdomABSTRACT
Importance: Understanding risk factors for hospitalization in vaccinated persons and the association of COVID-19 vaccines with hospitalization rates is critical for public health efforts to control COVID-19. Objective: To determine characteristics of COVID-19-associated hospitalizations among vaccinated persons and comparative hospitalization rates in unvaccinated and vaccinated persons. Design, Setting, and Participants: From January 1, 2021, to April 30, 2022, patients 18 years or older with laboratory-confirmed SARS-CoV-2 infection were identified from more than 250 hospitals in the population-based COVID-19-Associated Hospitalization Surveillance Network. State immunization information system data were linked to cases, and the vaccination coverage data of the defined catchment population were used to compare hospitalization rates in unvaccinated and vaccinated individuals. Vaccinated and unvaccinated patient characteristics were compared in a representative sample with detailed medical record review; unweighted case counts and weighted percentages were calculated. Exposures: Laboratory-confirmed COVID-19-associated hospitalization, defined as a positive SARS-CoV-2 test result within 14 days before or during hospitalization. Main Outcomes and Measures: COVID-19-associated hospitalization rates among vaccinated vs unvaccinated persons and factors associated with COVID-19-associated hospitalization in vaccinated persons were assessed. Results: Using representative data from 192â¯509 hospitalizations (see Table 1 for demographic information), monthly COVID-19-associated hospitalization rates ranged from 3.5 times to 17.7 times higher in unvaccinated persons than vaccinated persons regardless of booster dose status. From January to April 2022, when the Omicron variant was predominant, hospitalization rates were 10.5 times higher in unvaccinated persons and 2.5 times higher in vaccinated persons with no booster dose, respectively, compared with those who had received a booster dose. Among sampled cases, vaccinated hospitalized patients with COVID-19 were older than those who were unvaccinated (median [IQR] age, 70 [58-80] years vs 58 [46-70] years, respectively; P < .001) and more likely to have 3 or more underlying medical conditions (1926 [77.8%] vs 4124 [51.6%], respectively; P < .001). Conclusions and Relevance: In this cross-sectional study of US adults hospitalized with COVID-19, unvaccinated adults were more likely to be hospitalized compared with vaccinated adults; hospitalization rates were lowest in those who had received a booster dose. Hospitalized vaccinated persons were older and more likely to have 3 or more underlying medical conditions and be long-term care facility residents compared with hospitalized unvaccinated persons. The study results suggest that clinicians and public health practitioners should continue to promote vaccination with all recommended doses for eligible persons.
Subject(s)
COVID-19 , Influenza Vaccines , Adult , Aged , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Cross-Sectional Studies , Hospitalization , Humans , SARS-CoV-2ABSTRACT
Beginning the week of March 2026, 2022, the Omicron BA.2 variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating variant in the United States, accounting for >50% of sequenced isolates.* Data from the COVID-19Associated Hospitalization Surveillance Network (COVID-NET) were analyzed to describe recent COVID-19associated hospitalization rates among adults aged ≥18 years during the period coinciding with BA.2 predominance (BA.2 period [Omicron BA.2 and BA.2.12.1; March 20May 31, 2022]). Weekly hospitalization rates (hospitalizations per 100,000 population) among adults aged ≥65 years increased threefold, from 6.9 (week ending April 2, 2022) to 27.6 (week ending May 28, 2022); hospitalization rates in adults aged 1849 and 5064 years both increased 1.7-fold during the same time interval. Hospitalization rates among unvaccinated adults were 3.4 times as high as those among vaccinated adults. Among hospitalized nonpregnant patients in this same period, 39.1% had received a primary vaccination series and 1 booster or additional dose; 5.0% had received a primary series and ≥2 boosters or additional doses. All adults should stay up to date with COVID-19 vaccination, and multiple nonpharmaceutical and medical prevention measures should be used to protect those at high risk for severe COVID-19 illness, irrespective of vaccination status§ (1).Beginning the week of March 2026, 2022, the Omicron BA.2 variant of SARS-CoV-2, the virus that causes COVID-19, became the predominant circulating variant in the United States, accounting for >50% of sequenced isolates.* Data from the COVID-19Associated Hospitalization Surveillance Network (COVID-NET) were analyzed to describe recent COVID-19associated hospitalization rates among adults aged ≥18 years during the period coinciding with BA.2 predominance (BA.2 period [Omicron BA.2 and BA.2.12.1; March 20May 31, 2022]). Weekly hospitalization rates (hospitalizations per 100,000 population) among adults aged ≥65 years increased threefold, from 6.9 (week ending April 2, 2022) to 27.6 (week ending May 28, 2022); hospitalization rates in adults aged 1849 and 5064 years both increased 1.7-fold during the same time interval. Hospitalization rates among unvaccinated adults were 3.4 times as high as those among vaccinated adults. Among hospitalized nonpregnant patients in this same period, 39.1% had received a primary vaccination series and 1 booster or additional dose; 5.0% had received a primary series and ≥2 boosters or additional doses. All adults should stay up to date with COVID-19 vaccination, and multiple nonpharmaceutical and medical prevention measures should be used to protect those at high risk for severe COVID-19 illness, irrespective of vaccination status§ (1).
Subject(s)
COVID-19 , SARS-CoV-2 , Adolescent , Adult , COVID-19/epidemiology , COVID-19/therapy , COVID-19 Vaccines , Hospitalization , Humans , United States/epidemiology , VaccinationABSTRACT
BACKGROUND: Pregnant women less frequently receive COVID-19 vaccination and are at increased risk for adverse pregnancy outcomes from COVID-19. OBJECTIVE: This study aimed to first, describe the vaccination status, treatment, and outcomes of hospitalized, symptomatic pregnant women with COVID-19, and second, estimate whether treatment differs by pregnancy status among treatment-eligible (ie, requiring supplemental oxygen per National Institutes of Health guidelines at the time of the study) women. STUDY DESIGN: From January to November 2021, the COVID-19-Associated Hospitalization Surveillance Network completed medical chart abstraction for a probability sample of 2715 hospitalized women aged 15 to 49 years with laboratory-confirmed SARS-CoV-2 infection. Of these, 1950 women had symptoms of COVID-19 on admission, and 336 were pregnant. We calculated weighted prevalence estimates of demographic and clinical characteristics, vaccination status, and outcomes among pregnant women with symptoms of COVID-19 on admission. We used propensity score matching to estimate prevalence ratios and 95% confidence intervals of treatment-eligible patients who received remdesivir or systemic steroids by pregnancy status. RESULTS: Among 336 hospitalized pregnant women with symptomatic COVID-19, 39.6% were non-Hispanic Black, 24.8% were Hispanic or Latino, and 61.9% were aged 25 to 34 years. Among those with known COVID-19 vaccination status, 92.9% were unvaccinated. One-third (32.7%) were treatment-eligible. Among treatment-eligible pregnant women, 74.1% received systemic steroids and 61.4% received remdesivir. Among those that were no longer pregnant at discharge (n=180), 5.4% had spontaneous abortions and 3.5% had stillbirths. Of the 159 live births, 29.0% were preterm. Among a propensity score-matched cohort of treatment-eligible hospitalized women of reproductive age, pregnant women were less likely than nonpregnant women to receive remdesivir (prevalence ratio, 0.82; 95% confidence interval, 0.69-0.97) and systemic steroids (prevalence ratio, 0.80; 95% confidence interval, 0.73-0.87). CONCLUSION: Most hospitalized pregnant patients with symptomatic COVID-19 were unvaccinated. Hospitalized pregnant patients were less likely to receive recommended remdesivir and systemic steroids compared with similar hospitalized nonpregnant women. Our results underscore the need to identify opportunities for improving COVID-19 vaccination, implementation of treatment of pregnant women, and the inclusion of pregnant women in clinical trials.
Subject(s)
Antiviral Agents , COVID-19 , Female , Humans , Infant, Newborn , Pregnancy , COVID-19/diagnosis , COVID-19/prevention & control , COVID-19/therapy , COVID-19 Vaccines , Pregnant Women , SARS-CoV-2 , Steroids , Antiviral Agents/therapeutic useABSTRACT
Importance: The number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated persons, independent of the effect of reduced transmission, is a key measure of vaccine impact. Objective: To estimate the number of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented among vaccinated adults in the US. Design, Setting, and Participants: In this modeling study, a multiplier model was used to extrapolate the number of SARS-CoV-2 infections and COVID-19-associated deaths from data on the number of COVID-19-associated hospitalizations stratified by state, month, and age group (18-49, 50-64, and ≥65 years) in the US from December 1, 2020, to September 30, 2021. These estimates were combined with data on vaccine coverage and effectiveness to estimate the risks of infections, hospitalizations, and deaths. Risks were applied to the US population 18 years or older to estimate the expected burden in that population without vaccination. The estimated burden in the US population 18 years or older given observed levels of vaccination was subtracted from the expected burden in the US population 18 years or older without vaccination (ie, counterfactual) to estimate the impact of vaccination among vaccinated persons. Exposures: Completion of the COVID-19 vaccination course, defined as 2 doses of messenger RNA (BNT162b2 or mRNA-1273) vaccines or 1 dose of JNJ-78436735 vaccine. Main Outcomes and Measures: Monthly numbers and percentages of SARS-CoV-2 infections and COVID-19-associated hospitalizations and deaths prevented were estimated among those who have been vaccinated in the US. Results: COVID-19 vaccination was estimated to prevent approximately 27 million (95% uncertainty interval [UI], 22 million to 34 million) infections, 1.6 million (95% UI, 1.4 million to 1.8 million) hospitalizations, and 235â¯000 (95% UI, 175â¯000-305 000) deaths in the US from December 1, 2020, to September 30, 2021, among vaccinated adults 18 years or older. From September 1 to September 30, 2021, vaccination was estimated to prevent 52% (95% UI, 45%-62%) of expected infections, 56% (95% UI, 52%-62%) of expected hospitalizations, and 58% (95% UI, 53%-63%) of expected deaths in adults 18 years or older. Conclusions and Relevance: These findings indicate that the US COVID-19 vaccination program prevented a substantial burden of morbidity and mortality through direct protection of vaccinated individuals.
Subject(s)
COVID-19 , Influenza Vaccines , Influenza, Human , Ad26COVS1 , Adult , Aged , BNT162 Vaccine , COVID-19/epidemiology , COVID-19/prevention & control , COVID-19 Vaccines , Hospitalization , Humans , Influenza, Human/prevention & control , SARS-CoV-2ABSTRACT
BACKGROUND: In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported by states to the Centers for Disease Control and Prevention (CDC). Identifying and reporting every case from every facility in the United States may not be feasible in the long term. Creating sustainable methods for estimating the burden of COVID-19 from established sentinel surveillance systems is becoming more important. OBJECTIVE: We aimed to provide a method leveraging surveillance data to create a long-term solution to estimate monthly rates of hospitalizations for COVID-19. METHODS: We estimated monthly hospitalization rates for COVID-19 from May 2020 through April 2021 for the 50 states using surveillance data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates were calculated from patients hospitalized with a lab-confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for 6 age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) separately. We identified covariates from multiple data sources that varied by age, state, and month and performed covariate selection for each age group based on 2 methods, Least Absolute Shrinkage and Selection Operator (LASSO) and spike and slab selection methods. We validated our method by checking the sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data. RESULTS: We estimated 3,583,100 (90% credible interval [CrI] 3,250,500-3,945,400) hospitalizations for a cumulative incidence of 1093.9 (992.4-1204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 to 1856 per 100,000 between states. The age group with the highest cumulative incidence was those aged ≥85 years (5575.6; 90% CrI 5066.4-6133.7). The monthly hospitalization rate was highest in December (183.7; 90% CrI 154.3-217.4). Our monthly estimates by state showed variations in magnitudes of peak rates, number of peaks, and timing of peaks between states. CONCLUSIONS: Our novel approach to estimate hospitalizations for COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden as well as a flexible framework leveraging surveillance data.
Subject(s)
COVID-19 , Bayes Theorem , COVID-19/epidemiology , Hospitalization , Humans , Incidence , Infant, Newborn , SARS-CoV-2 , United States/epidemiologyABSTRACT
On October 29, 2021, the Food and Drug Administration expanded the Emergency Use Authorization for Pfizer-BioNTech COVID-19 vaccine to children aged 5-11 years; CDC's Advisory Committee on Immunization Practices' recommendation followed on November 2, 2021.* In late December 2021, the B.1.1.529 (Omicron) variant of SARS-CoV-2 (the virus that causes COVID-19) became the predominant strain in the United States, coinciding with a rapid increase in COVID-19-associated hospitalizations among all age groups, including children aged 5-11 years (1). COVID-19-Associated Hospitalization Surveillance Network (COVID-NET)§ data were analyzed to describe characteristics of COVID-19-associated hospitalizations among 1,475 U.S. children aged 5-11 years throughout the pandemic, focusing on the period of early Omicron predominance (December 19, 2021-February 28, 2022). Among 397 children hospitalized during the Omicron-predominant period, 87% were unvaccinated, 30% had no underlying medical conditions, and 19% were admitted to an intensive care unit (ICU). The cumulative hospitalization rate during the Omicron-predominant period was 2.1 times as high among unvaccinated children (19.1 per 100,000 population) as among vaccinated¶ children (9.2).** Non-Hispanic Black (Black) children accounted for the largest proportion of unvaccinated children (34%) and represented approximately one third of COVID-19-associated hospitalizations in this age group. Children with diabetes and obesity were more likely to experience severe COVID-19. The potential for serious illness among children aged 5-11 years, including those with no underlying health conditions, highlights the importance of vaccination among this age group. Increasing vaccination coverage among children, particularly among racial and ethnic minority groups disproportionately affected by COVID-19, is critical to preventing COVID-19-associated hospitalization and severe outcomes.
Subject(s)
COVID-19 , BNT162 Vaccine , COVID-19/epidemiology , Child , Ethnicity , Hospitalization , Humans , Minority Groups , SARS-CoV-2 , United States/epidemiologyABSTRACT
Beginning the week of December 19-25, 2021, the B.1.1.529 (Omicron) variant of SARS-CoV-2 (the virus that causes COVID-19) became the predominant circulating variant in the United States (i.e., accounted for >50% of sequenced isolates).* Information on the impact that booster or additional doses of COVID-19 vaccines have on preventing hospitalizations during Omicron predominance is limited. Data from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) were analyzed to compare COVID-19-associated hospitalization rates among adults aged ≥18 years during B.1.617.2 (Delta; July 1-December 18, 2021) and Omicron (December 19, 2021-January 31, 2022) variant predominance, overall and by race/ethnicity and vaccination status. During the Omicron-predominant period, weekly COVID-19-associated hospitalization rates (hospitalizations per 100,000 adults) peaked at 38.4, compared with 15.5 during Delta predominance. Hospitalizations rates increased among all adults irrespective of vaccination status (unvaccinated, primary series only, or primary series plus a booster or additional dose). Hospitalization rates during peak Omicron circulation (January 2022) among unvaccinated adults remained 12 times the rates among vaccinated adults who received booster or additional doses and four times the rates among adults who received a primary series, but no booster or additional dose. The rate among adults who received a primary series, but no booster or additional dose, was three times the rate among adults who received a booster or additional dose. During the Omicron-predominant period, peak hospitalization rates among non-Hispanic Black (Black) adults were nearly four times the rate of non-Hispanic White (White) adults and was the highest rate observed among any racial and ethnic group during the pandemic. Compared with the Delta-predominant period, the proportion of unvaccinated hospitalized Black adults increased during the Omicron-predominant period. All adults should stay up to date (1) with COVID-19 vaccination to reduce their risk for COVID-19-associated hospitalization. Implementing strategies that result in the equitable receipt of COVID-19 vaccinations, through building vaccine confidence, raising awareness of the benefits of vaccination, and removing barriers to vaccination access among persons with disproportionately higher hospitalizations rates from COVID-19, including Black adults, is an urgent public health priority.
Subject(s)
COVID-19 Vaccines , COVID-19/ethnology , Hospitalization/statistics & numerical data , SARS-CoV-2 , Vaccination/statistics & numerical data , Adult , Humans , Immunization, Secondary , United States/epidemiologyABSTRACT
The B.1.1.529 (Omicron) variant of SARS-CoV-2, the virus that causes COVID-19, has been the predominant circulating variant in the United States since late December 2021.* Coinciding with increased Omicron circulation, COVID-19-associated hospitalization rates increased rapidly among infants and children aged 0-4 years, a group not yet eligible for vaccination (1). Coronavirus Disease 19-Associated Hospitalization Surveillance Network (COVID-NET) data were analyzed to describe COVID-19-associated hospitalizations among U.S. infants and children aged 0-4 years since March 2020. During the period of Omicron predominance (December 19, 2021-February 19, 2022), weekly COVID-19-associated hospitalization rates per 100,000 infants and children aged 0-4 years peaked at 14.5 (week ending January 8, 2022); this Omicron-predominant period peak was approximately five times that during the period of SARS-CoV-2 B.1.617.2 (Delta) predominance (June 27-December 18, 2021, which peaked the week ending September 11, 2021).§ During Omicron predominance, 63% of hospitalized infants and children had no underlying medical conditions; infants aged <6 months accounted for 44% of hospitalizations, although no differences were observed in indicators of severity by age. Strategies to prevent COVID-19 among infants and young children are important and include vaccination among currently eligible populations (2) such as pregnant women (3), family members, and caregivers of infants and young children (4).