IMPORTANCE: Seasonal influenza is associated with substantial disease burden. The relationship between census tract-based social vulnerability and clinical outcomes among patients with influenza remains unknown. OBJECTIVE: To characterize associations between social vulnerability and outcomes among patients hospitalized with influenza and to evaluate seasonal influenza vaccine and influenza antiviral utilization patterns across levels of social vulnerability. DESIGN, SETTING, AND PARTICIPANTS: This retrospective repeated cross-sectional study was conducted among adults with laboratory-confirmed influenza-associated hospitalizations from the 2014 to 2015 through the 2018 to 2019 influenza seasons. Data were from a population-based surveillance network of counties within 13 states. Data analysis was conducted in December 2023. EXPOSURE: Census tract-based social vulnerability. MAIN OUTCOMES AND MEASURES: Associations between census tract-based social vulnerability and influenza outcomes (intensive care unit admission, invasive mechanical ventilation and/or extracorporeal membrane oxygenation support, and 30-day mortality) were estimated using modified Poisson regression as adjusted prevalence ratios. Seasonal influenza vaccine and influenza antiviral utilization were also characterized across levels of social vulnerability. RESULTS: Among 57 964 sampled cases, the median (IQR) age was 71 (58-82) years; 55.5% (95% CI, 51.5%-56.0%) were female; 5.2% (5.0%-5.4%) were Asian or Pacific Islander, 18.3% (95% CI, 18.0%-18.6%) were Black or African American, and 64.6% (95% CI, 64.2%-65.0%) were White; and 6.6% (95% CI, 6.4%-68%) were Hispanic or Latino and 74.7% (95% CI, 74.3%-75.0%) were non-Hispanic or Latino. High social vulnerability was associated with higher prevalence of invasive mechanical ventilation and/or extracorporeal membrane oxygenation support (931 of 13 563 unweighted cases; adjusted prevalence ratio [aPR], 1.25 [95% CI, 1.13-1.39]), primarily due to socioeconomic status (790 of 11 255; aPR, 1.31 [95% CI, 1.17-1.47]) and household composition and disability (773 of 11 256; aPR, 1.20 [95% CI, 1.09-1.32]). Vaccination status, presence of underlying medical conditions, and respiratory symptoms partially mediated all significant associations. As social vulnerability increased, the proportion of patients receiving seasonal influenza vaccination declined (-19.4% relative change across quartiles; P < .001) as did the proportion vaccinated by October 31 (-6.8%; P < .001). No differences based on social vulnerability were found in in-hospital antiviral receipt, but early in-hospital antiviral initiation (-1.0%; P = .01) and prehospital antiviral receipt (-17.3%; P < .001) declined as social vulnerability increased. CONCLUSIONS AND RELEVANCE: In this cross-sectional study, social vulnerability was associated with a modestly increased prevalence of invasive mechanical ventilation and/or extracorporeal membrane oxygenation support among patients hospitalized with influenza. Contributing factors may have included worsened baseline respiratory health and reduced receipt of influenza prevention and prehospital or early in-hospital treatment interventions among persons residing in low socioeconomic areas.

Annually, tens of thousands of U.S. children and adolescents are hospitalized with seasonal influenza virus infection. Both influenza vaccination and early initiation of antiviral treatment can reduce complications of influenza. Using data from two U.S. influenza surveillance networks for children and adolescents aged <18 years with medically attended, laboratory-confirmed influenza for whom antiviral treatment is recommended, the percentage who received treatment was calculated. Trends in antiviral treatment of children and adolescents hospitalized with influenza from the 2017-18 to the 2023-2024 influenza seasons were also examined. Since 2017-18, when 70%-86% of hospitalized children and adolescents with influenza received antiviral treatment, the proportion receiving treatment notably declined. Among children and adolescents with influenza during the 2023-24 season, 52%-59% of those hospitalized received antiviral treatment. During the 2023-24 season, 31% of those at higher risk for influenza complications seen in the outpatient setting in one network were prescribed antiviral treatment. These findings demonstrate that influenza antiviral treatment is underutilized among children and adolescents who could benefit from treatment. All hospitalized children and adolescents, and those at higher risk for influenza complications in the outpatient setting, should receive antiviral treatment as soon as possible for suspected or confirmed influenza.

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.

BACKGROUND: While the estimated number of U.S. influenza-associated deaths is reported annually, detailed data on the epidemiology of influenza-associated deaths, including the burden of in-hospital versus post-hospital discharge deaths are limited. METHODS: Using data from the 2010-11 through 2018-19 seasons from the Influenza Hospitalization Surveillance Network, we linked cases to death certificates to identify patients who died from any cause during their influenza hospital stay or within 30 days post discharge. We described demographic and clinical characteristics of patients who died in hospital versus post discharge and characterized locations and causes of death (COD). RESULTS: Among 121,390 cases hospitalized with laboratory-confirmed influenza over 9 seasons, 5.5% died; 76% of deaths were in patients ≥65 years, 71% were non-Hispanic White, and 34% had ≥4 underlying medical conditions. Among all patients with an influenza-associated hospitalization who died, 48% of deaths occurred after hospital discharge; the median days from discharge to death was 9 days (IQR 3-19 days). Post-discharge deaths more often occurred in older patients and among those with underlying medical conditions. Only 37% of patients who died had "influenza" as a COD on their death certificate. Influenza was more frequently listed as a COD among persons who died in-hospital compared with cardiovascular disease among those who died after discharge. CONCLUSIONS: All-cause mortality burden is substantial among patients hospitalized with influenza, with almost 50% of deaths occurring within 30 days after hospital discharge. Surveillance systems should consider capture of post-discharge outcomes to better characterize the impact of influenza on all-cause mortality.

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

Background: The first licensed malaria vaccine, RTS,S/AS01<inf>E</inf>, confers moderate protection against symptomatic disease. Because many malaria infections are asymptomatic, we conducted a large-scale longitudinal parasite genotyping study of samples from a clinical trial exploring how vaccine dosing regimen affects vaccine efficacy. Method(s): Between Sept 28, 2017, and Sept 25, 2018, 1500 children aged 5-17 months were randomly assigned (1:1:1:1:1) to receive four different RTS,S/AS01<inf>E</inf> regimens or a rabies control vaccine in a phase 2b open-label clinical trial in Ghana and Kenya. Participants in the four RTS,S groups received two full doses at month 0 and month 1 and either full doses at month 2 and month 20 (group R012-20); full doses at month 2, month 14, month 26, and month 38 (group R012-14); fractional doses at month 2, month 14, month 26, and month 38 (group Fx012-14; early fourth dose); or fractional doses at month 7, month 20, and month 32 (group Fx017-20; delayed third dose). We evaluated the time to the first new genotypically detected infection and the total number of new infections during two follow-up periods (12 months and 20 months) in more than 36 000 dried blood spot specimens from 1500 participants. To study vaccine effects on time to the first new infection, we defined vaccine efficacy as one minus the hazard ratio (HR; RTS,S vs control) of the first new infection. We performed a post-hoc analysis of vaccine efficacy based on malaria infection status at first vaccination and force of infection by month 2. This trial (MAL-095) is registered with ClinicalTrials.gov, NCT03281291. Finding(s): We observed significant and similar vaccine efficacy (25-43%; 95% CI union 9-53) against first new infection for all four RTS,S/AS01<inf>E</inf> regimens across both follow-up periods (12 months and 20 months). Each RTS,S/AS01<inf>E</inf> regimen significantly reduced the mean number of new infections in the 20-month follow-up period by 1.1-1.6 infections (95% CI union 0.6-2.1). Vaccine efficacy against first new infection was significantly higher in participants who were infected with malaria (68%; 95% CI 50-80) than in those who were uninfected (37%; 23-48) at the first vaccination (p=0.0053). Interpretation(s): All tested dosing regimens blocked some infections to a similar degree. Improved vaccine efficacy in participants infected during vaccination could suggest new strategies for highly efficacious malaria vaccine development and implementation. Funding(s): GlaxoSmithKline Biologicals SA, PATH, Bill & Melinda Gates Foundation, and the German Federal Ministry of Education and Research. Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license

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

BACKGROUND: Drug resistance in Plasmodium falciparum is a major threat to malaria control efforts. Pathogen genomic surveillance could be invaluable for monitoring current and emerging parasite drug resistance. METHODS: Data from two decades (2000-2020) of continuous molecular surveillance of P. falciparum parasites from Senegal were retrospectively examined to assess historical changes in malaria drug resistance mutations. Several known drug resistance markers and their surrounding haplotypes were profiled using a combination of single nucleotide polymorphism (SNP) molecular surveillance and whole genome sequence based population genomics. RESULTS: This dataset was used to track temporal changes in drug resistance markers whose timing correspond to historically significant events such as the withdrawal of chloroquine (CQ) and the introduction of sulfadoxine-pyrimethamine (SP) in 2003. Changes in the mutation frequency at Pfcrt K76T and Pfdhps A437G coinciding with the 2014 introduction of seasonal malaria chemoprevention (SMC) in Senegal were observed. In 2014, the frequency of Pfcrt K76T increased while the frequency of Pfdhps A437G declined. Haplotype-based analyses of Pfcrt K76T showed that this rapid increase was due to a recent selective sweep that started after 2014. DISCUSSION (CONCLUSION): The rapid increase in Pfcrt K76T is troubling and could be a sign of emerging amodiaquine (AQ) resistance in Senegal. Emerging AQ resistance may threaten the future clinical efficacy of artesunate-amodiaquine (ASAQ) and AQ-dependent SMC chemoprevention. These results highlight the potential of molecular surveillance for detecting rapid changes in parasite populations and stress the need to monitor the effectiveness of AQ as a partner drug for artemisinin-based combination therapy (ACT) and for chemoprevention.

AIMS: In October 2023, the Tennessee Department of Health identified an outbreak of Shiga toxin-producing Escherichia coli (STEC) O157:H7 infections among elementary school students who attended school field trips to the same farm animal exhibit. Our aim was to determine STEC source and prevent additional illnesses by initiating epidemiologic, laboratory and environmental investigations. METHODS AND RESULTS: We identified cases using laboratory-based surveillance and by surveying caregivers of children who attended the exhibit. Probable cases were defined as illness with abdominal cramps or diarrhoea after attendance; confirmed cases were laboratory-confirmed STEC infection in an attendee or household contact. A site visit was conducted, and event organizers were interviewed. Human stool, animal faeces and environmental samples were tested for STEC O157:H7 by real-time polymerase chain reaction (PCR), culture and whole-genome sequencing (WGS). Approximately 2300 elementary school students attended the animal exhibit during 2 days. Field trip activities included contact with different farm animal species, drinking pasteurized milk outside animal enclosures and eating lunch in a separate building onsite. We received survey responses from 399 caregivers for 443 (19%) animal exhibit attendees. We identified 9 confirmed and 55 probable cases with illness onset dates during 26 September to 12 October. Seven children aged 1-7 years were hospitalized. Four children aged 1-6 years experienced haemolytic uraemic syndrome; none died. Laboratory testing identified STEC O157:H7 by culture from eight human stool samples with 0-1 allele difference by WGS. Three environmental samples had Shiga toxin (stx 2) genes detected by PCR, but no STEC isolates were recovered by culture. CONCLUSIONS: This is the largest reported STEC O157:H7 outbreak associated with an animal exhibit in Tennessee. We identified opportunities for educating school staff, event organizers and families about zoonotic disease risks associated with animal contact and published prevention measures.

BACKGROUND: The first licensed malaria vaccine, RTS,S/AS01(E), confers moderate protection against symptomatic disease. Because many malaria infections are asymptomatic, we conducted a large-scale longitudinal parasite genotyping study of samples from a clinical trial exploring how vaccine dosing regimen affects vaccine efficacy. METHODS: Between Sept 28, 2017, and Sept 25, 2018, 1500 children aged 5-17 months were randomly assigned (1:1:1:1:1) to receive four different RTS,S/AS01(E) regimens or a rabies control vaccine in a phase 2b open-label clinical trial in Ghana and Kenya. Participants in the four RTS,S groups received two full doses at month 0 and month 1 and either full doses at month 2 and month 20 (group R012-20); full doses at month 2, month 14, month 26, and month 38 (group R012-14); fractional doses at month 2, month 14, month 26, and month 38 (group Fx012-14; early fourth dose); or fractional doses at month 7, month 20, and month 32 (group Fx017-20; delayed third dose). We evaluated the time to the first new genotypically detected infection and the total number of new infections during two follow-up periods (12 months and 20 months) in more than 36 000 dried blood spot specimens from 1500 participants. To study vaccine effects on time to the first new infection, we defined vaccine efficacy as one minus the hazard ratio (HR; RTS,S vs control) of the first new infection. We performed a post-hoc analysis of vaccine efficacy based on malaria infection status at first vaccination and force of infection by month 2. This trial (MAL-095) is registered with ClinicalTrials.gov, NCT03281291. FINDINGS: We observed significant and similar vaccine efficacy (25-43%; 95% CI union 9-53) against first new infection for all four RTS,S/AS01(E) regimens across both follow-up periods (12 months and 20 months). Each RTS,S/AS01(E) regimen significantly reduced the mean number of new infections in the 20-month follow-up period by 1·1-1·6 infections (95% CI union 0·6-2·1). Vaccine efficacy against first new infection was significantly higher in participants who were infected with malaria (68%; 95% CI 50-80) than in those who were uninfected (37%; 23-48) at the first vaccination (p=0·0053). INTERPRETATION: All tested dosing regimens blocked some infections to a similar degree. Improved vaccine efficacy in participants infected during vaccination could suggest new strategies for highly efficacious malaria vaccine development and implementation. FUNDING: GlaxoSmithKline Biologicals SA, PATH, Bill & Melinda Gates Foundation, and the German Federal Ministry of Education and Research.

BACKGROUND: A U.S. case-control study (2010-2014) demonstrated vaccine effectiveness (VE) for ≥ 1 dose of the thirteen-valent pneumococcal conjugate vaccine (PCV13) against vaccine-type (VT) invasive pneumococcal disease (IPD) at 86 %; however, it lacked statistical power to examine VE by number of doses and against individual serotypes. METHODS: We used the indirect cohort method to estimate PCV13 VE against VT-IPD among children aged < 5 years in the United States from May 1, 2010 through December 31, 2019 using cases from CDC's Active Bacterial Core surveillance, including cases enrolled in a matched case-control study (2010-2014). Cases and controls were defined as individuals with VT-IPD and non-PCV13-type-IPD (NVT-IPD), respectively. We estimated absolute VE using the adjusted odds ratio of prior PCV13 receipt (1-aOR x 100 %). RESULTS: Among 1,161 IPD cases, 223 (19.2 %) were VT cases and 938 (80.8 %) were NVT controls. Of those, 108 cases (48.4 %; 108/223) and 600 controls (64.0 %; 600/938) had received > 3 PCV13 doses; 23 cases (17.6 %) and 15 controls (2.4 %) had received no PCV doses. VE ≥ 3 PCV13 doses against VT-IPD was 90.2 % (95 % Confidence Interval75.4-96.1 %), respectively. Among the most commonly circulating VT-IPD serotypes, VE of ≥ 3 PCV13 doses was 86.8 % (73.7-93.3 %), 50.2 % (28.4-80.5 %), and 93.8 % (69.8-98.8 %) against serotypes 19A, 3, and 19F, respectively. CONCLUSIONS: At least three doses of PCV13 continue to be effective in preventing VT-IPD among children aged < 5 years in the US. PCV13 was protective against serotypes 19A and 19F IPD; protection against serotype 3 IPD did not reach statistical significance.

BACKGROUND: Respiratory syncytial virus (RSV) can cause hospitalization in young children and older adults. With vaccines and monoclonal antibody prophylaxis increasingly available, identifying social factors associated with severe illnesses can guide mitigation efforts. METHODS: Using data collected by the RSV Hospitalization Surveillance Network from 2016 to 2023, we identified RSV hospitalizations in Tennessee. We linked hospitalization information (eg, patient demographic characteristics and outcome) with population-level variables (eg, social vulnerability and health care insurance coverage) from publicly available data sets using census tract of residence. Hospitalization incidence was calculated and stratified by period (2016-2020 and 2020-2023). We modeled social vulnerability effect on hospitalization incidence using Poisson regression. RESULTS: Among 2687 RSV hospitalizations, there were 677 (25.2%) intensive care unit admissions and 38 (1.4%) deaths. The highest RSV hospitalization incidences occurred among children aged <5 years and adults aged ≥65 years: 272.8 per 100 000 person-years (95% CI, 258.6-287.0) and 60.6 (95% CI, 56.0-65.2), respectively. Having public health insurance was associated with higher hospitalization incidence as compared with not having public insurance: 60.5 per 100 000 person-years (95% CI, 57.6-63.4) vs 14.3 (95% CI, 13.4-15.2). Higher hospitalization incidence was associated with residing in a census tract in the most socially vulnerable quartile vs the least vulnerable quartile after adjusting for age, sex, and period (incidence rate ratio, 1.4; 95% CI, 1.3-1.6). CONCLUSIONS: RSV hospitalization was associated with living in more socially vulnerable census tracts. Population measures of social vulnerability might help guide mitigation strategies, including vaccine and monoclonal antibody promotion and provision to reduce RSV hospitalization.

Syndromic polymerase chain reaction (PCR) panels are used to test for pathogens that can cause rash illnesses, including measles. Rash illnesses have infectious and noninfectious causes, and approximately 5% of persons experience a rash 7-10 days after receipt of a measles, mumps, and rubella (MMR) vaccine. MMR vaccine includes live attenuated measles virus, which is detectable by PCR tests. No evidence exists of person-to-person transmission of measles vaccine virus, and illness does not typically result among immunocompetent persons. During September 2022-January 2023, the Tennessee Department of Health received two reports of measles detected by syndromic PCR panels. Both reports involved children (aged 1 and 6 years) without known risk factors for measles, who were evaluated for rash that occurred 11-13 days after routine MMR vaccination. After public health responses in Tennessee determined that both PCR panels had detected measles vaccine virus, six state health departments collaborated to assess the frequency and characteristics of persons receiving a positive measles PCR panel test result in the United States. Information was retrospectively collected from a commercial laboratory testing for measles in syndromic multiplex PCR panels. During May 2022-April 2023, among 1,548 syndromic PCR panels, 17 (1.1%) returned positive test results for measles virus. Among 14 persons who received a positive test result and for whom vaccination and case investigation information were available, all had received MMR vaccine a median of 12 days before specimen collection, and none had known risk factors for acquiring measles. All positive PCR results were attributed to detection of measles vaccine virus. Increased awareness among health care providers about potential measles detection by PCR after vaccination is needed. Any detection of measles virus by syndromic PCR testing should be immediately reported to public health agencies, which can use measles vaccination history and assessment of risk factors to determine the appropriate public health response. If a person recently received MMR vaccine and has no risk factors for acquiring measles, additional public health response is likely unnecessary.

BACKGROUND: Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programmes (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. METHODS: This study examined parasites from 3147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, a series of Poisson generalized linear mixed-effects models were constructed to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. RESULTS: Model-predicted incidence was compared with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (< 10/1000/annual [‰]). CONCLUSIONS: When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence > 10‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was < 10‰, many of the correlations between parasite genetics and incidence were reversed, which may reflect the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

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.

Persons with HIV (PWH) are at increased risk for bacterial infections, and previous publications document an increased risk for invasive meningococcal disease (IMD) in particular. This analysis provides evidence that PWH face a 6-fold increase in risk for IMD based on Active Bacterial Core surveillance data collected during 2009-2019.

Candida glabrata is one of the most common causes of systemic candidiasis, often resistant to antifungal medications. To describe the genomic context of emerging resistance, we conducted a retrospective analysis of 82 serially collected isolates from 33 patients from population-based candidemia surveillance in the United States. We used whole-genome sequencing to determine the genetic relationships between isolates obtained from the same patient. Phylogenetic analysis demonstrated that isolates from 29 patients were clustered by patient. The median SNPs between isolates from the same patient was 30 (range: 7-96 SNPs), while unrelated strains infected four patients. Twenty-one isolates were resistant to echinocandins, and 24 were resistant to fluconazole. All echinocandin-resistant isolates carried a mutation either in the FKS1 or FKS2 HS1 region. Of the 24 fluconazole-resistant isolates, 17 (71%) had non-synonymous polymorphisms in the PDR1 gene, which were absent in susceptible isolates. In 11 patients, a genetically related resistant isolate was collected after recovering susceptible isolates, indicating in vivo acquisition of resistance. These findings allowed us to estimate the intra-host diversity of C. glabrata and propose an upper boundary of 96 SNPs for defining genetically related isolates, which can be used to assess donor-to-host transmission, nosocomial transmission, or acquired resistance.IMPORTANCEIn our study, mutations associated to azole resistance and echinocandin resistance were detected in Candida glabrata isolates using a whole-genome sequence. C. glabrata is the second most common cause of candidemia in the United States, which rapidly acquires resistance to antifungals, in vitro and in vivo.

OBJECTIVES: Mpox surveillance was integral during the 2022 outbreak response. We evaluated implementation of mpox surveillance in Tennessee during an outbreak response and made recommendations for surveillance during emerging infectious disease outbreaks. METHODS: To understand surveillance implementation, system processes, and areas for improvement, we conducted 8 semistructured focus groups and 7 interviews with 36 health care, laboratory, and health department representatives during September 9-20, 2022. We categorized and analyzed session transcription and notes. We analyzed completeness and timeliness of surveillance data, including 349 orthopoxvirus-positive laboratory reports from commercial, public health, and health system laboratories during July 1-August 31, 2022. RESULTS: Participants described an evolving system and noted that existing informatics platforms inefficiently supported iterations of reporting requirements. Clear communication, standardization of terminology, and shared, adaptable, and user-friendly informatics platforms were prioritized for future emerging infectious disease surveillance systems. Laboratory-reported epidemiologic information was often incomplete; only 55% (191 of 349) of reports included patient address and telephone number. The median time from symptom onset to specimen collection was 5 days (IQR, 3-6 d), from specimen collection to laboratory reporting was 3 days (IQR, 1-4 d), from laboratory reporting to patient interview was 1 day (IQR, 1-3 d), and from symptom onset to patient interview was 9 days (IQR, 7-12 d). CONCLUSIONS: Future emerging infectious disease responses would benefit from standardized surveillance approaches that facilitate rapid implementation. Closer collaboration among informatics, laboratory, and clinical partners across jurisdictions and agencies in determining system priorities and designing workflow processes could improve flexibility of the surveillance platform and completeness and timeliness of laboratory reporting. Improved timeliness will facilitate public health response and intervention, thereby mitigating morbidity.

BACKGROUND: Older age and chronic conditions are associated with severe influenza outcomes; however, data are only comprehensively available for adults ≥65 years old. Using data from the Influenza Hospitalization Surveillance Network (FluSurv-NET), we identified characteristics associated with severe outcomes in adults 18-49 years old hospitalized with influenza. METHODS: We included FluSurv-NET data from nonpregnant adults 18-49 years old hospitalized with laboratory-confirmed influenza during the 2011-2012 through 2018-2019 seasons. We used bivariate and multivariable logistic regression to determine associations between select characteristics and severe outcomes including intensive care unit (ICU) admission, invasive mechanical ventilation (IMV), and in-hospital death. RESULTS: A total of 16 140 patients aged 18-49 years and hospitalized with influenza were included in the analysis; the median age was 39 years, and 26% received current-season influenza vaccine before hospitalization. Obesity, asthma, and diabetes mellitus were the most common chronic conditions. Conditions associated with a significantly increased risk of severe outcomes included age group 30-39 or 40-49 years (IMV, age group 30-39 years: adjusted odds ratio [aOR], 1.25; IMV, age group 40-49 years: aOR, 1.36; death, age group 30-39 years: aOR, 1.28; death, age group 40-49 years: aOR, 1.69), being unvaccinated (ICU: aOR, 1.18; IMV: aOR, 1.25; death: aOR, 1.48), and having chronic conditions including extreme obesity and chronic lung, cardiovascular, metabolic, neurologic, or liver diseases (ICU: range aOR, 1.22-1.56; IMV: range aOR, 1.17-1.54; death: range aOR, 1.43-2.36). CONCLUSIONS: To reduce the morbidity and mortality associated with influenza among adults aged 18-49 years, health care providers should strongly encourage receipt of annual influenza vaccine and lifestyle/behavioral modifications, particularly among those with chronic medical conditions.

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

This report summarizes new recommendation and updates previous recommendations of the Advisory Committee on Immunization Practices (ACIP) for postexposure prophylaxis (PEP) to prevent human rabies (CDC. Human rabies prevention---United States, 2008: recommendations of the Advisory Committee on Immunization Practices. MMWR 2008;57[No. RR-3]). Previously, ACIP recommended a 5-dose rabies vaccination regimen with human diploid cell vaccine (HDCV) or purified chick embryo cell vaccine (PCECV). These new recommendations reduce the number of vaccine doses to four. The reduction in doses recommended for PEP was based in part on evidence from rabies virus pathogenesis data, experimental animal work, clinical studies, and epidemiologic surveillance. These studies indicated that 4 vaccine doses in combination with rabies immune globulin (RIG) elicited adequate immune responses and that a fifth dose of vaccine did not contribute to more favorable outcomes. For persons previously unvaccinated with rabies vaccine, the reduced regimen of 4 1-mL doses of HDCV or PCECV should be administered intramuscularly. The first dose of the 4-dose course should be administered as soon as possible after exposure (day 0). Additional doses then should be administered on days 3, 7, and 14 after the first vaccination. ACIP recommendations for the use of RIG remain unchanged. For persons who previously received a complete vaccination series (pre- or postexposure prophylaxis) with a cell-culture vaccine or who previously had a documented adequate rabies virus-neutralizing antibody titer following vaccination with noncell-culture vaccine, the recommendation for a 2-dose PEP vaccination series has not changed. Similarly, the number of doses recommended for persons with altered immunocompetence has not changed; for such persons, PEP should continue to comprise a 5-dose vaccination regimen with 1 dose of RIG. Recommendations for pre-exposure prophylaxis also remain unchanged, with 3 doses of vaccine administered on days 0, 7, and 21 or 28. Prompt rabies PEP combining wound care, infiltration of RIG into and around the wound, and multiple doses of rabies cell-culture vaccine continue to be highly effective in preventing human rabies.

Genetic surveillance of the Plasmodium falciparum parasite shows great promise for helping National Malaria Control Programs (NMCPs) assess parasite transmission. Genetic metrics such as the frequency of polygenomic (multiple strain) infections, genetic clones, and the complexity of infection (COI, number of strains per infection) are correlated with transmission intensity. However, despite these correlations, it is unclear whether genetic metrics alone are sufficient to estimate clinical incidence. Here, we examined parasites from 3,147 clinical infections sampled between the years 2012-2020 through passive case detection (PCD) across 16 clinic sites spread throughout Senegal. Samples were genotyped with a 24 single nucleotide polymorphism (SNP) molecular barcode that detects parasite strains, distinguishes polygenomic (multiple strain) from monogenomic (single strain) infections, and identifies clonal infections. To determine whether genetic signals can predict incidence, we constructed a series of Poisson generalized linear mixed-effects models to predict the incidence level at each clinical site from a set of genetic metrics designed to measure parasite clonality, superinfection, and co-transmission rates. We compared the model-predicted incidence with the reported standard incidence data determined by the NMCP for each clinic and found that parasite genetic metrics generally correlated with reported incidence, with departures from expected values at very low annual incidence (<10/1000/annual [‰]). When transmission is greater than 10 cases per 1000 annual parasite incidence (annual incidence >10 ‰), parasite genetics can be used to accurately infer incidence and is consistent with superinfection-based hypotheses of malaria transmission. When transmission was <10 ‰, we found that many of the correlations between parasite genetics and incidence were reversed, which we hypothesize reflects the disproportionate impact of importation and focal transmission on parasite genetics when local transmission levels are low.

We here analyze data from the first year of an ongoing nationwide program of genetic surveillance of Plasmodium falciparum parasites in Senegal. The analysis is based on 1097 samples collected at health facilities during passive malaria case detection in 2019; it provides a baseline for analyzing parasite genetic metrics as they vary over time and geographic space. The study's goal was to identify genetic metrics that were informative about transmission intensity and other aspects of transmission dynamics, focusing on measures of genetic relatedness between parasites. We found the best genetic proxy for local malaria incidence to be the proportion of polygenomic infections (those with multiple genetically distinct parasites), although this relationship broke down at low incidence. The proportion of related parasites was less correlated with incidence while local genetic diversity was uninformative. The type of relatedness could discriminate local transmission patterns: two nearby areas had similarly high fractions of relatives, but one was dominated by clones and the other by outcrossed relatives. Throughout Senegal, 58% of related parasites belonged to a single network of relatives, within which parasites were enriched for shared haplotypes at known and suspected drug resistance loci and at one novel locus, reflective of ongoing selection pressure.

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.

INTRODUCTION: Influenza remains an important cause of hospitalizations in the United States. Estimating the number of influenza hospitalizations is vital for public health decision making. Combining existing surveillance systems through capture-recapture methods allows for more comprehensive burden estimations. METHODS: Data from independent surveillance systems were combined using capture-recapture methods to estimate influenza hospitalization rates for children and adults in Middle Tennessee during consecutive influenza seasons from 2016-17 through 2019-20. EIP identified cases through surveillance of laboratory results for hospitalized children and adults. HAIVEN and NVSN recruited hospitalized patients with respiratory symptoms or fever. Population-based influenza rates and the proportion of cases detected by each surveillance system were calculated. RESULTS: Estimated overall influenza hospitalization rates ranged from 23 influenza-related hospitalizations per 10,000 persons in 2016-17 to 40 per 10,000 persons in 2017-18. Adults age ≥65 years had the highest hospitalization rates across seasons and experienced a rate of 170 hospitalizations per 10,000 persons during the 2017-18 season. EIP consistently identified a higher proportion of influenza cases for adults and children compared with HAIVEN and NVSN, respectively. CONCLUSION: Current surveillance systems underestimate the influenza burden. Capture-recapture provides an alternative approach to use data from independent surveillance systems and complement population-based burden estimates.

Background The COVID-19 pandemic has caused substantial morbidity and mortality.Objectives To describe monthly demographic and clinical trends among adults hospitalized with COVID-19.Design Pooled cross-sectional.Setting 99 counties within 14 states participating in the Coronavirus Disease 2019-Associated Hospitalization Surveillance Network (COVID-NET).Patients U.S. adults (aged ≥18 years) hospitalized with laboratory-confirmed COVID-19 during March 1-December 31, 2020.Measurements Monthly trends in weighted percentages of interventions and outcomes including length of stay (LOS), intensive care unit admissions (ICU), invasive mechanical ventilation (IMV), vasopressor use and in-hospital death (death). Monthly hospitalization, ICU and death rates per 100,000 population.Results Among 116,743 hospitalized adults, median age was 62 years. Among 18,508 sampled adults, median LOS decreased from 6.4 (March) to 4.6 days (December). Remdesivir and systemic corticosteroid use increased from 1.7% and 18.9% (March) to 53.8% and 74.2% (December), respectively. Frequency of ICU decreased from 37.8% (March) to 20.5% (December). IMV (27.8% to 8.7%), vasopressors (22.7% to 8.8%) and deaths (13.9% to 8.7%) decreased from March to October; however, percentages of these interventions and outcomes remained stable or increased in November and December. Percentage of deaths significantly decreased over time for non-Hispanic White patients (p-value &lt;0.01) but not non-Hispanic Black or Hispanic patients. Rates of hospitalization (105.3 per 100,000), ICU (20.2) and death (11.7) were highest during December.Limitations COVID-NET covers approximately 10% of the U.S. population; findings may not be generalizable to the entire country.Conclusions After initial improvement during April-October 2020, trends in interventions and outcomes worsened during November-December, corresponding with the 3rd peak of the U.S. pandemic. These data provide a longitudinal assessment of trends in COVID-19-associated outcomes prior to widespread COVID-19 vaccine implementation.Competing Interest StatementDr. Evan Anderson reports grants from Pfizer, grants from Merck, grants from PaxVax, grants from Micron, grants from Sanofi-Pasteur, grants from Janssen, grants from MedImmune, grants from GSK, personal fees from Sanofi-Pasteur, personal fees from Pfizer, personal fees from Medscape, personal fees from Kentucky Bioprocessing, Inc, personal fees from Sanofi-Pasteur, outside the submitted work. Dr. William Schaffner reports personal fees from VBI Vaccines, 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 activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy. Sites participating in COVID-NET obtained approval from their respective state and local Institutional Review Boards, as applicable.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 registry, 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 check ist(s) and other pertinent material as supplementary files, if applicable.YesPublicly available data referred to in this analysis can be found at: https://gis.cdc.gov/grasp/covidnet/covid19_3.html https://gis.cdc.gov/grasp/covidnet/covid19_3.html

Background As of August 21, 2021, &gt;60% of the U.S. population aged ≥18 years were fully vaccinated with vaccines highly effective in preventing hospitalization due to Coronavirus Disease-2019 (COVID-19). Infection despite full vaccination (vaccine breakthrough) has been reported, but characteristics of those with vaccine breakthrough resulting in hospitalization and relative rates of hospitalization in unvaccinated and vaccinated persons are not well described, including during late June and July 2021 when the highly transmissible Delta variant predominated.Methods From January 1–June 30, 2021, cases defined as adults aged ≥18 years with laboratory-confirmed Severe Acute Respiratory Coronavirus-2 (SARS-CoV-2) infection were identified from &gt;250 acute care hospitals in the population-based COVID-19-Associated Hospitalization Surveillance Network (COVID-NET). Through chart review for sampled cases, we examine characteristics associated with vaccination breakthrough. From January 24–July 24, 2021, state immunization information system data linked to both &gt;37,000 cases representative cases and the defined surveillance catchment area population were used to compare weekly hospitalization rates in vaccinated and unvaccinated individuals. Unweighted case counts and weighted percentages are presented.Results From January 1 – June 30, 2021, fully vaccinated cases increased from 1 (0.01%) to 321 (16.1%) per month. Among 4,732 sampled cases, fully vaccinated persons admitted with COVID-19 were older compared with unvaccinated persons (median age 73 years [Interquartile Range (IQR) 65-80] v. 59 years [IQR 48-70]; p&lt;0.001), more likely to have 3 or more underlying medical conditions (201 (70.8%) v. 2,305 (56.1%), respectively; p&lt;0.001) and be residents of long-term care facilities [37 (14.5%) v. 146 (5.5%), respectively; p&lt;0.001]. From January 24 – July 24, 2021, cumulative hospitalization rates were 17 times higher in unvaccinated persons compared with vaccinated persons (423 cases per 100,000 population v. 26 per 100,000 population, respectively); rate ratios were 23, 22 and 13 for those aged 18-49, 50-64, and ≥65 years respectively. For June 27 – July 24, hospitalization rates were ≥10 times higher in unvaccinated persons compared with vaccinated persons for all age groups across all weeks.Conclusion Population-based hospitalization rates show that unvaccinated adults aged ≥18 years are 17 times more likely to be hospitalized compared with vaccinated adults. Rates are far higher in unvaccinated persons in all adult age groups, including during a period when the Delta variant was the predominant strain of the SARS-CoV-2 virus. Vaccines continue to play a critical role in preventing serious COVID-19 illness and remain highly effective in preventing COVID-19 hospitalizations.Competing Interest StatementAll authors have completed and submitted the International Committee of Medical Journal Editors form for disclosure of potential conflicts of interest. Evan J. Anderson reports grants from Pfizer, grants from Merck, grants from PaxVax, grants from Micron, grants from Sanofi-Pasteur, grants from Janssen, grants from MedImmune, grants from GSK, personal fees from Sanofi-Pasteur, personal fees from Pfizer, personal fees from Medscape, personal fees from Kentucky Bioprocessing, Inc, personal fees from Sanofi-Pasteur, personal fees from Janssen, outside the submitted work; and his institution has also received funding from NIH to conduct clinical trials of Moderna and Janssen COVID-19 vaccines. Ruth Lynfield reports Associate Editor for American Academy of Pediatrics Red Book (Committee on Infectious Diseases), donated fee to Minnesota Department of Health. Laurie M. Billing reports grants from Council of State and Territorial Epidemiologists (CSTE), during the conduct of the study; grants from Centers for Disease Control and Prevention (CDC) outside the submitted work. William Schaffner reports personal fees from VBI Vaccines, outside the submitted work. No other potential conflicts of interest were disclosed.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 activity was reviewed by CDC and was conducted consistent with applicable federal law and CDC policy (see e.g., 45 C.F.R. part 46.102(l)(2), 21 C.F.R. part 56; 42 U.S.C. 241(d); 5 U.S.C.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 registry, 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.YesPublicly available data referred to in this analysis can be found at: https://gis.cdc.gov/grasp/covidnet/covid19_3.html https://gis.cdc.gov/grasp/COVIDNet/COVID19_5.html https://gis.cdc.gov/grasp/covidnet/covid19_3.html https://gis.cdc.gov/grasp/COVIDNet/COVID19_5.html

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.