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.

Severe outcomes were common among adults hospitalized for COVID-19 or influenza, while the percentage of COVID-19 hospitalizations involving critical care decreased from October 2021 to September 2022. During the Omicron BA.5 period, intensive care unit admission frequency was similar for COVID-19 and influenza, although patients with COVID-19 had a higher frequency of in-hospital death.

Background Identification of risk factors for COVID-19-associated hospitalization is needed to guide prevention and clinical care.Objective To examine if age, sex, race/ethnicity, and underlying medical conditions is independently associated with COVID-19-associated hospitalizations.Design Cross-sectional.Setting 70 counties within 12 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET) and a population-based sample of non-hospitalized adults residing in the COVID-NET catchment area from the Behavioral Risk Factor Surveillance System.Participants U.S. community-dwelling adults (≥18 years) with laboratory-confirmed COVID-19-associated hospitalizations, March 1- June 23, 2020.Measurements Adjusted rate ratios (aRR) of hospitalization by age, sex, race/ethnicity and underlying medical conditions (hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m2], severe obesity [BMI≥40 kg/m2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease).Results Our sample included 5,416 adults with COVID-19-associated hospitalizations. Adults with (versus without) severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7) had higher rates of hospitalization, after adjusting for age, sex, and race/ethnicity. In models adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults ≥65 years, 45-64 years (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites).Limitations Interim analysis limited to hospitalizations with underlying medical condition data.Conclusion Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.Competing Interest StatementDr. Anderson reports personal fees from AbbVie, personal fees from Pfizer, grants from Pfizer, grants from Merck, grants from Micron, grants from Paxvax, grants from Sanofi Pasteur, grants from Novavax, grants from MedImmune, grants from Regeneron, grants from GSK, outside the submitted work. Mr. Henderson, Ms. Kim, Ms. George, and Ms. Hill report grants from Council of State and Territorial Epidemiologists (CSTE), during the conduct of the study. Dr. Lynfield reports grants from CDC- Emerging Infections Program, during the conduct of the study; and Royalties from a book on infectious disease surveillance and compensation for AAP Red Book (Report from Committee on Infectious Disease) donated to Minnesota Dept of Health. Dr. Schaffner reports grants from CDC, during the conduct of the study; personal fees from VBI Vaccines, outside the submitted work. Dr. Talbot reports other from Seqirus, outside the submitted work.Funding StatementThis work was supported by the Centers of Disease Control and Prevention through an Emerging Infections Program cooperative agreement (grant CK17-1701) and through a Council of State and Territorial Epidemiologists cooperative agreement (grant NU38OT000297-02-00).Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:This analysis was exempt from CDC's Institutional Review Board, as it was considered part of public health surveillance and emergency response. Participating sites obtained approval for the COVID-NET surveillance protocol from their respective state and local IRBs, as required.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved regi try, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesData is not publically available at this time.

BACKGROUND: Diabetes mellitus (DM) is common among older adults hospitalized with influenza, yet data are limited on the impact of DM on risk of severe influenza-associated outcomes. METHODS: We included adults aged ≥65 years hospitalized with influenza during 2012-2013 through 2016-2017 from the Influenza Hospitalization Surveillance Network (FluSurv-NET), a population-based surveillance system for laboratory-confirmed influenza-associated hospitalizations conducted in defined counties within 13 states. We calculated population denominators using the Centers for Medicare and Medicaid Services county-specific DM prevalence estimates and National Center for Health Statistics population data. We present pooled rates and rate ratios (RRs) of intensive care unit (ICU) admission, pneumonia diagnosis, mechanical ventilation, and in-hospital death for persons with and without DM. We estimated RRs and 95% confidence intervals (CIs) using meta-analysis with site as a random effect in order to control for site differences in the estimates. RESULTS: Of 31 934 hospitalized adults included in the analysis, 34% had DM. Compared to those without DM, adults with DM had higher rates of influenza-associated hospitalization (RR, 1.57 [95% CI, 1.43-1.72]), ICU admission (RR, 1.84 [95% CI, 1.67-2.04]), pneumonia (RR, 1.57 [95% CI, 1.42-1.73]), mechanical ventilation (RR, 1.95 [95% CI, 1.74-2.20]), and in-hospital death (RR, 1.48 [95% CI, 1.23-1.80]). CONCLUSIONS: Older adults with DM have higher rates of severe influenza-associated outcomes compared to those without DM. These findings reinforce the importance of preventing influenza virus infections through annual vaccination, and early treatment of influenza illness with antivirals in older adults with DM.

IMPORTANCE: Racial and ethnic minority groups, such as Black, Hispanic, American Indian or Alaska Native, and Asian or Pacific Islander persons, often experience higher rates of severe influenza disease. OBJECTIVE: To describe rates of influenza-associated hospitalization, intensive care unit (ICU) admission, and in-hospital death by race and ethnicity over 10 influenza seasons. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study used data from the Influenza-Associated Hospitalization Surveillance Network (FluSurv-NET), which conducts population-based surveillance for laboratory-confirmed influenza-associated hospitalizations in selected counties, representing approximately 9% of the US population. Influenza hospitalizations from the 2009 to 2010 season to the 2018 to 2019 season were analyzed. Data were analyzed from October 2020 to July 2021. MAIN OUTCOMES AND MEASURES: The main outcomes were age-adjusted and age-stratified rates of influenza-associated hospitalization, ICU admission, and in-hospital death by race and ethnicity overall and by influenza season. RESULTS: Among 113 352 persons with an influenza-associated hospitalization (34 436 persons [32.0%] aged ≥75 years; 61 009 [53.8%] women), 70 225 persons (62.3%) were non-Hispanic White (White), 24 850 persons (21.6%) were non-Hispanic Black (Black), 11 903 persons (10.3%) were Hispanic, 5517 persons (5.1%) were non-Hispanic Asian or Pacific Islander, and 857 persons (0.7%) were non-Hispanic American Indian or Alaska Native. Among persons aged younger than 75 years and compared with White persons of the same ages, Black persons were more likely to be hospitalized (eg, age 50-64 years: rate ratio [RR], 2.50 95% CI, 2.43-2.57) and to be admitted to an ICU (eg, age 50-64 years: RR, 2.09; 95% CI, 1.96-2.23). Among persons aged younger than 50 years and compared with White persons of the same ages, American Indian or Alaska Native persons were more likely to be hospitalized (eg, age 18-49 years: RR, 1.72; 95% CI, 1.51-1.96) and to be admitted to an ICU (eg, age 18-49 years: RR, 1.84; 95% CI, 1.40-2.42). Among children aged 4 years or younger and compared with White children, hospitalization rates were higher in Black children (RR, 2.21; 95% CI, 2.10-2.33), Hispanic children (RR, 1.87; 95% CI, 1.77-1.97), American Indian or Alaska Native children (RR, 3.00; 95% CI, 2.55-3.53), and Asian or Pacific Islander children (RR, 1.26; 95% CI, 1.16-1.38), as were rates of ICU admission (Black children: RR, 2.74; 95% CI, 2.43-3.09; Hispanic children: RR, 1.96; 95% CI, 1.73-2.23; American Indian and Alaska Native children: RR, 3.51; 95% CI, 2.45-5.05). In this age group and compared with White children, in-hospital death rates were higher among Hispanic children (RR, 2.98; 95% CI, 1.23-7.19), Black children (RR, 3.39; 95% CI, 1.40-8.18), and Asian or Pacific Islander children (RR, 4.35; 95% CI, 1.55-12.22). Few differences were observed in rates of severe influenza-associated outcomes by race and ethnicity among adults aged 75 years or older. For example, in this age group, compared with White adults, hospitalization rates were slightly higher only among Black adults (RR, 1.05; 95% CI 1.02-1.09). Overall, Black persons had the highest age-adjusted hospitalization rate (68.8 [95% CI, 68.0-69.7] hospitalizations per 100 000 population) and ICU admission rate (11.6 [95% CI, 11.2-11.9] admissions per 100 000 population). CONCLUSIONS AND RELEVANCE: This cross-sectional study found racial and ethnic disparities in rates of severe influenza-associated disease. These data identified subgroups for whom improvements in influenza prevention efforts could be targeted.

Health care personnel (HCP) can be exposed to SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), both within and outside the workplace, increasing their risk for infection. Among 6,760 adults hospitalized during March 1-May 31, 2020, for whom HCP status was determined by the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), 5.9% were HCP. Nursing-related occupations (36.3%) represented the largest proportion of HCP hospitalized with COVID-19. Median age of hospitalized HCP was 49 years, and 89.8% had at least one underlying medical condition, of which obesity was most commonly reported (72.5%). A substantial proportion of HCP with COVID-19 had indicators of severe disease: 27.5% were admitted to an intensive care unit (ICU), 15.8% required invasive mechanical ventilation, and 4.2% died during hospitalization. HCP can have severe COVID-19-associated illness, highlighting the need for continued infection prevention and control in health care settings as well as community mitigation efforts to reduce transmission.

BACKGROUND: Data on risk factors for COVID-19-associated hospitalization are needed to guide prevention efforts and clinical care. We sought to identify factors independently associated with COVID-19-associated hospitalizations. METHODS: U.S. community-dwelling adults (≥18 years) hospitalized with laboratory-confirmed COVID-19 during March 1-June 23, 2020 were identified from the COVID-19-Associated Hospitalization Surveillance Network (COVID-NET), a multi-state surveillance system. To calculate hospitalization rates by age, sex, and race/ethnicity strata, COVID-NET data served as the numerator and Behavioral Risk Factor Surveillance System estimates served as the population denominator for characteristics of interest. Underlying medical conditions examined included hypertension, coronary artery disease, history of stroke, diabetes, obesity [BMI ≥30 kg/m 2], severe obesity [BMI≥40 kg/m 2], chronic kidney disease, asthma, and chronic obstructive pulmonary disease. Generalized Poisson regression models were used to calculate adjusted rate ratios (aRR) for hospitalization. RESULTS: Among 5,416 adults, hospitalization rates were higher among those with ≥3 underlying conditions (versus without)(aRR: 5.0; 95%CI: 3.9, 6.3), severe obesity (aRR:4.4; 95%CI: 3.4, 5.7), chronic kidney disease (aRR:4.0; 95%CI: 3.0, 5.2), diabetes (aRR:3.2; 95%CI: 2.5, 4.1), obesity (aRR:2.9; 95%CI: 2.3, 3.5), hypertension (aRR:2.8; 95%CI: 2.3, 3.4), and asthma (aRR:1.4; 95%CI: 1.1, 1.7), after adjusting for age, sex, and race/ethnicity. Adjusting for the presence of an individual underlying medical condition, higher hospitalization rates were observed for adults aged ≥65, 45-64 (versus 18-44 years), males (versus females), and non-Hispanic black and other race/ethnicities (versus non-Hispanic whites). CONCLUSION: Our findings elucidate groups with higher hospitalization risk that may benefit from targeted preventive and therapeutic interventions.

Annual estimates of the influenza disease burden provide information to evaluate programs and allocate resources. We used a multiplier method with routine population-based surveillance data on influenza hospitalization in the United States to correct for under-reporting and estimate the burden of influenza for seasons after the 2009 pandemic. Five sites of the Influenza Hospitalization Surveillance Network (FluSurv-NET) collected data on the frequency and sensitivity of influenza testing during two seasons to estimate under-detection. Population-based rates of influenza-associated hospitalization and Intensive Care Unit admission from 2010-2013 were extrapolated to the U.S. population from FluSurv-NET and corrected for under-detection. Influenza deaths were calculated using a ratio of deaths to hospitalizations. We estimated that influenza-related hospitalizations were under-detected during 2010-11 by a factor of 2.1 (95%CI 1.7-2.9) for age < 18 years, 3.1 (2.4-4.5) for ages 18-64 years, and 5.2 (95%CI 3.8-8.3) for age 65+. Results were similar in 2011-12. Extrapolated estimates for 3 seasons from 2010-2013 included: 114,192-624,435 hospitalizations, 18,491-95,390 ICU admissions, and 4,915-27,174 deaths per year; 54-70% of hospitalizations and 71-85% of deaths occurred among adults aged 65+. Influenza causes a substantial disease burden in the U.S. that varies by age and season. Periodic estimation of multipliers across multiple sites and age groups improves our understanding of influenza detection in sentinel surveillance systems. Adjusting surveillance data using a multiplier method is a relatively simple means to estimate the impact of influenza and the subsequent value of interventions to prevent influenza.