BACKGROUND: With the increased availability of licensed vaccines for respiratory viruses such as severe acute respiratory syndrome coronavirus 2, respiratory syncytial virus (RSV), and influenza virus, a better understanding of the viral aetiology of severe acute respiratory infections (SARI) among children could help in optimising the use of these vaccines. We conducted a study among children aged <5 years hospitalised with SARI at a tertiary care children's hospital in north India and tested for common respiratory pathogens. METHODS: We randomly enrolled eligible SARI cases aged <5 years from August 2013 to July 2015. SARI cases were defined as either <7-day history of fever with cough or in children aged eight days to three months, a physician diagnosis of acute lower respiratory infection requiring hospitalisation. We also enrolled an age-group matched control without any acute illness in a 2:1 ratio from the outpatient clinic within 24 hours of case enrolment. Nasopharyngeal and/or oropharyngeal swabs were collected and tested using TaqMan Array Cards, a real-time reverse transcription polymerase chain reaction-based multi-pathogen testing platform for selected respiratory viruses among the enrolled cases and controls. We compared the prevalence of each pathogen among cases and controls using the χ(2) (χ(2)) or Fisher exact test (P < 0.05). We used logistic regression to estimate adjusted odds ratios (aORs) which were then used to calculate aetiologic fractions (EFs). RESULTS: We enrolled 840 cases and 419 outpatient controls. Almost half of the individuals in the whole sample were aged <6 months (n = 521, 41.4%). Females made up 33.7% of cases and 37.2% of controls. Viral detections were more common among cases (69%, 95% confidence interval (CI) = 66, 73) compared to controls (33%; 95% CI = 29, 38) (P < 0.01). RSV (n = 257, 31%; 95% CI = 28, 34%) was the most common virus detected among cases. Influenza A was detected among 24 (3%; 95% CI = 2, 4%), and influenza B among 5 (1%; 95% CI = 0, 1%) cases. The association between the virus and SARI was strongest for RSV (aOR = 23; 95% CI = 12, 47; EF = 96%). Antivirals were administered to 1% of SARI cases while 78% received antibiotics. CONCLUSIONS: Using a multi-pathogen molecular detection method, we detected respiratory viruses among more than two-thirds of children aged <5 years admitted with SARI in the Delhi tertiary care children's hospital. The guidelines for preventing and managing SARI cases among children could be optimised further with the improved availability of antivirals and vaccines.

The COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) was established in March 2020 to monitor trends in hospitalizations associated with SARS-CoV-2 infection. COVID-NET is a geographically diverse population-based surveillance system for laboratory-confirmed COVID-19-associated hospitalizations with a combined catchment area covering approximately 10% of the US population. Data collected in COVID-NET includes monthly counts of hospitalizations for persons with confirmed SARS-CoV-2 infection who reside within the defined catchment area. A Bayesian modeling approach is proposed to estimate US national COVID-associated hospital admission rates based on information reported in the COVID-NET system. A key component of the approach is the ability to estimate uncertainty resulting from extrapolation of hospitalization rates observed within COVID-NET to the US population. In addition, the proposed model enables estimation of other contributors to uncertainty including temporal dependence among reported COVID-NET admission counts, the impact of unmeasured site-specific factors, and the frequency and accuracy of testing for SARS-CoV-2 infection. Based on the proposed model, an estimated 6.3 million (95% uncertainty interval (UI) 5.4-7.3 million) COVID-19-associated hospital admissions occurred in the United States from September 2020 through December 2023. Between April 2020 and December 2023, model-based monthly admission rate estimates ranged from a minimum of 1 per 10,000 population (95% UI 0.7-1.2) in June of 2023 to a highest monthly level of 16 per 10,000 (95% UI 13-19) in January 2022.

BACKGROUND: Global influenza-associated acute respiratory infections contribute to 3-5 million severe illnesses requiring hospitalization annually, with 90% of hospitalizations occurring among children < 5 years in developing countries. In Bangladesh, the inadequate availability of nationally representative, robust estimates of influenza-associated hospitalizations limits allocation of resources for prevention and control measures. METHODS: This study used data from the hospital-based influenza surveillance (HBIS) system in Bangladesh from 2010 to 2019 and healthcare utilization surveys to determine hospital utilization patterns in the catchment area. We estimated annual influenza-associated hospitalization numbers and rates for all age groups in Bangladesh using WHO methods, adjusted for a 6-day-a-week enrollment schedule, selective testing of specimens from children under five, and healthcare-seeking behavior, based on the proportion of symptomatic community participants seeking healthcare within the past week. We then estimated national hospitalization rates by multiplying age-specific hospitalization rates with the corresponding annual national census population. RESULTS: Annual influenza-associated hospitalization rates per 100,000 population for all ages ranged from 31 (95% CI: 27-36) in 2011 to 139 (95% CI: 130-149) in 2019. Children < 5 years old had the highest rates of influenza-associated hospitalization, ranging from 114 (95% CI: 90-138) in 2011 to 529 (95% CI: 481-578) in 2019, followed by adults aged ≥ 65 years with rates ranging from 46 (95% CI: 34-57) in 2012 to 252 (95% CI: 213-292) in 2019. The national hospitalization estimates for all ages during 2010-2019 ranged from 47,891 to 236,380 per year. CONCLUSIONS: The impact of influenza-associated hospitalizations in Bangladesh may be considerable, particularly for young children and older adults. Targeted interventions, such as influenza vaccination for these age groups, should be prioritized and evaluated.

BACKGROUND: Novel influenza viruses pose a potential pandemic risk, and rapid detection of infections in humans is critical to characterizing the virus and facilitating the implementation of public health response measures. METHODS: We use a probabilistic framework to estimate the likelihood that novel influenza virus cases would be detected through testing in different community and healthcare settings (urgent care, emergency department, hospital, and intensive care unit [ICU]) while at low frequencies in the United States. Parameters were informed by data on seasonal influenza virus activity and existing testing practices. RESULTS: In a baseline scenario reflecting the presence of 100 novel virus infections with similar severity to seasonal influenza viruses, the median probability of detecting at least one infection per month was highest in urgent care settings (72%) and when community testing was conducted at random among the general population (77%). However, urgent care testing was over 15 times more efficient (estimated as the number of cases detected per 100,000 tests) due to the larger number of tests required for community testing. In scenarios that assumed increased clinical severity of novel virus infection, median detection probabilities increased across all healthcare settings, particularly in hospitals and ICUs (up to 100%) where testing also became more efficient. CONCLUSIONS: Our results suggest that novel influenza virus circulation is likely to be detected through existing healthcare surveillance, with the most efficient testing setting impacted by the disease severity profile. These analyses can help inform future testing strategies to maximize the likelihood of novel influenza detection.

BACKGROUND: Annual influenza vaccination is recommended for older adults but repeated vaccination with standard-dose influenza vaccine has been linked to reduced immunogenicity and effectiveness, especially against A(H3N2) viruses. METHODS: Community-dwelling Hong Kong adults aged 65-82 years were randomly allocated to receive 2017-2018 standard-dose quadrivalent, MF59-adjuvanted trivalent, high-dose trivalent, and recombinant-HA quadrivalent vaccination. Antibody response to unchanged A(H3N2) vaccine antigen was compared among participants with and without self-reported prior year (2016-2017) standard-dose vaccination. RESULTS: Mean fold rise (MFR) in antibody titers from day 0 to day 30 by hemagglutination inhibition and virus microneutralization assays were lower among 2017-2018 standard-dose and enhanced vaccine recipients with (range, 1.7-3.0) versus without (range, 4.3-14.3) prior 2016-2017 vaccination. MFR was significantly reduced by about one-half to four-fifths for previously vaccinated recipients of standard-dose and all 3 enhanced vaccines (β range, .21-.48). Among prior-year vaccinated older adults, enhanced vaccines induced higher 1.43 to 2.39-fold geometric mean titers and 1.28 to 1.74-fold MFR versus standard-dose vaccine by microneutralization assay. CONCLUSIONS: In the context of unchanged A(H3N2) vaccine strain, prior-year vaccination was associated with reduced antibody response among both standard-dose and enhanced influenza vaccine recipients. Enhanced vaccines improved antibody response among older adults with prior-year standard-dose vaccination.

We reviewed the tools that have been developed to characterize and communicate seasonal influenza activity in the United States. Here we focus on systematic surveillance and applied analytics, including seasonal burden and disease severity estimation, short-term forecasting, and longer-term modeling efforts. For each set of activities, we describe the challenges and opportunities that have arisen because of the COVID-19 pandemic. In conclusion, we highlight how collaboration and communication have been and will continue to be key components of reliable and actionable influenza monitoring, forecasting, and modeling activities.

Background: Enhancing outcomes post-hospitalisation requires an understanding of predictive factors for adverse events. This study aimed to estimate post-discharge mortality rates among patients with severe acute respiratory infection (SARI) in Bangladesh, identify associated factors, and document reported causes of death. Methods: From January 2012 to December 2019, we conducted follow-up calls to patients or their families 30 days after discharge to assess the status of patients with SARI. Proportions of deaths within 30 days of discharge were estimated, and a comparative analysis of demographics, clinical characteristics, and influenza illness between decedents and survivors was performed using multivariable Cox regression models. Findings: Among 23,360 patients with SARI (median age: 20 years, IQR: 1.5–48, 65% male), 351 (1.5%) died during hospitalisation. Of 23,009 patients alive at discharge, 20,044 (87%) were followed, with 633 (3.2%) deaths within 30 days of discharge. In children (<18 years), difficulty breathing (adjusted hazard ratio [aHR] 1.8; 95% CI 1.1–3.0), longer hospital stay (aHR 1.1; 95% CI 1.1–1.1), and heart diseases (aHR 8.5; 95% CI 3.2–23.1) were associated with higher post-discharge death risk. Among adults (≥18 years), difficulty breathing (aHR 2.3; 95% CI 1.7–3.0), chronic obstructive pulmonary disease (aHR 1.7; 95% CI 1.4–2.2), and intensive care unit admission (aHR 5.2; 95% CI 1.9–14.0) were linked to elevated post-discharge death risk. Influenza virus was detected in 13% (46/351) of in-hospital SARI deaths and 10% (65/633) of post-discharge SARI deaths. Interpretation: Nearly one in twenty patients with SARI died during hospitalisation or within 1 month of discharge, with two-thirds of deaths occurring post-discharge. Seasonal influenza vaccination is recommended to mitigate influenza-associated mortality. To enhance post-discharge outcomes, hospitals should consider developing safe-discharge algorithms, reinforcing post-discharge care plans, and establishing outpatient monitoring for recently discharged patients. Funding: Centers for Disease Control and (CDC), Atlanta, Georgia, USA [U01GH002259]. © 2024 The Author(s)

BACKGROUND: The aim of this study was to characterize the epidemiology of human seasonal coronaviruses (HCoVs) in southern Malawi. METHODS: We tested for HCoVs 229E, OC43, NL63, and HKU1 using real-time polymerase chain reaction (PCR) on upper respiratory specimens from asymptomatic controls and individuals of all ages recruited through severe acute respiratory illness (SARI) surveillance at Queen Elizabeth Central Hospital, Blantyre, and a prospective influenza-like illness (ILI) observational study between 2011 and 2017. We modeled the probability of having a positive PCR for each HCoV using negative binomial models, and calculated pathogen-attributable fractions (PAFs). RESULTS: Overall, 8.8% (539/6107) of specimens were positive for ≥1 HCoV. OC43 was the most frequently detected HCoV (3.1% [191/6107]). NL63 was more frequently detected in ILI patients (adjusted incidence rate ratio [aIRR], 9.60 [95% confidence interval {CI}, 3.25-28.30]), while 229E (aIRR, 8.99 [95% CI, 1.81-44.70]) was more frequent in SARI patients than asymptomatic controls. In adults, 229E and OC43 were associated with SARI (PAF, 86.5% and 89.4%, respectively), while NL63 was associated with ILI (PAF, 85.1%). The prevalence of HCoVs was similar between children with SARI and controls. All HCoVs had bimodal peaks but distinct seasonality. CONCLUSIONS: OC43 was the most prevalent HCoV in acute respiratory illness of all ages. Individual HCoVs had distinct seasonality that differed from temperate settings.

During the 2022-23 influenza season, early increases in influenza activity, co-circulation of influenza with other respiratory viruses, and high influenza-associated hospitalization rates, particularly among children and adolescents, were observed. This report describes the 2022-23 influenza season among children and adolescents aged <18 years, including the seasonal severity assessment; estimates of U.S. influenza-associated medical visits, hospitalizations, and deaths; and characteristics of influenza-associated hospitalizations. The 2022-23 influenza season had high severity among children and adolescents compared with thresholds based on previous seasons' influenza-associated outpatient visits, hospitalization rates, and deaths. Nationally, the incidences of influenza-associated outpatient visits and hospitalization for the 2022-23 season were similar for children aged <5 years and higher for children and adolescents aged 5-17 years compared with previous seasons. Peak influenza-associated outpatient and hospitalization activity occurred in late November and early December. Among children and adolescents hospitalized with influenza during the 2022-23 season in hospitals participating in the Influenza Hospitalization Surveillance Network, a lower proportion were vaccinated (18.3%) compared with previous seasons (35.8%-41.8%). Early influenza circulation, before many children and adolescents had been vaccinated, might have contributed to the high hospitalization rates during the 2022-23 season. Among symptomatic hospitalized patients, receipt of influenza antiviral treatment (64.9%) was lower than during pre-COVID-19 pandemic seasons (80.8%-87.1%). CDC recommends that all persons aged ≥6 months without contraindications should receive the annual influenza vaccine, ideally by the end of October.

BACKGROUND: Interpreting rRT-PCR results for human avian influenza A virus (AIV) detection in contaminated settings like live bird markets (LBMs) without serology or viral culture poses a challenge. METHODS: During February-March 2012 and November 2012-February 2013, we screened workers at nine LBMs in Dhaka, Bangladesh to confirm molecular detections of AIV RNA in respiratory specimens with serology. We tested nasopharyngeal (NP) and throat swabs from workers with influenza-like-illness (ILI) and NP, throat, and arm swabs from asymptomatic workers for influenza virus by rRT-PCR and sera for seroconversion and antibodies against HPAI A(H5N1) and A(H9N2) viruses. RESULTS: Among 1,273 ILI cases, 34 (2.6%) had A(H5), 56 (4%) had A(H9), and 6 (0.4%) had both A(H5) and A(H9) detected by rRT-PCR. Of 192 asymptomatic workers, A(H5) was detected in 8 (4%) NP and 38 (20%) arm swabs. Of 28 ILI cases with A(H5) or A(H9) detected, none had evidence of seroconversion, but 1 (3.5%) and 12 (43%), were seropositive for A(H5) and A(H9), respectively. CONCLUSION: Detection of AIV RNA in respiratory specimens from symptomatic and asymptomatic LBM workers without evidence of seroconversion or virus isolation suggests environmental contamination, emphasizing caution in interpreting rRT-PCR results in high viral load settings.

BACKGROUND: Pregnant women with their infants are considered at higher risk for influenza-associated complications, and the World Health Organization (WHO) recommends influenza vaccination during pregnancy to protect them, including their infants (0-6 months). There are limited data on the influenza burden among pregnant women and their infants (0-6 months), and there are no routine influenza vaccinations in Bangladesh. METHODS: Five annual cohorts (2013-2017) of pregnant women were enrolled from the eight sub-districts of Bangladesh before the influenza season (May-September); they were contacted weekly to identify new onset of influenza-like illness (ILI) (subjective or measured fever and cough) and acute respiratory illness (ARI) (at least two of these symptoms: cough, rhinorrhea, or difficulty in breathing) among their infants from birth to 6 months of age. We collected nasopharyngeal swabs from ILI and ARI cases, tested by real-time reverse transcription polymerase chain reaction (rRT-PCR) for influenza virus (including types and subtypes) and estimated influenza incidence (95% CI)/10000 pregnant women-months or infant-months, respectively. RESULTS: We enrolled 9020 pregnant women, followed for 26,709 pregnancy-months, and detected 1241 ILI episodes. We also followed 8963 infants for 51,518 infant-months and identified 5116 ARI episodes. Influenza positivity was 23% for ILI and 3% for ARI cases. The overall incidence (2013-2017) of influenza among pregnant women was 158.5/10000 pregnant women-months (95% CI: 141.4-177.6) and that among infants was 21.9/10000 infant-months (95% CI: 18.2-26.5). CONCLUSIONS: Although the data was collected more than 5 years ago, as the only baseline data, our findings illustrate evidence of influenza burden among pregnant women and infants (0-6 months), which may support preventive policy decisions in Bangladesh.

Introduction In the United States, COVID-19 is a nationally notifiable disease, cases and hospitalizations are reported to the CDC by states. 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 burden of COVID-19 from established sentinel surveillance systems is becoming more important. 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 COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. We created a model for six 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/or month, and performed covariate selection for each age group based on two methods, Least Absolute Shrinkage and Selection Operator (LASSO) and Spike and Slab selection methods. We validated our method by checking sensitivity of model estimates to covariate selection and model extrapolation as well as comparing our results to external data.Results We estimated 3,569,500 (90% Credible Interval:3,238,000 – 3,934,700) hospitalizations for a cumulative incidence of 1,089.8 (988.6 – 1,201.3) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 352 – 1,821per 100,000 between states. The age group with the highest cumulative incidence was aged ≥85 years (5,583.1; 5,061.0 – 6,157.5). The monthly hospitalization rate was highest in December (183.8; 154.5 – 218.0). 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 COVID-19 hospitalizations has potential to provide sustainable estimates for monitoring COVID-19 burden, as well as a flexible framework leveraging surveillance data.Competing Interest StatementThe authors have declared no competing interest.Funding StatementFunding for this work was supported by CDC (Atlanta, Georgia). The authors received no financial support for the research, authorship, or publication of these data.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesI confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.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.YesData will not be made available online.BRFSSBehavioral Risk Factor Surveillance SystemCDCCenters for Disease Control and PreventionCKDchronic kidney diseaseCOPDchronic obstructive pulmonary diseaseCOVID-19Coronavirus Disease 2019COVID-NETCoronavirus Disease 2019-Associated Hospitalization Surveillance NetworkCrICredible IntervalFluSurv-NETInfluenza Hospitalization Surveillance NetworkHHSDepartment of Health and Human ServicesICUintensive care unitLASSO east Absolute Shrinkage and Selection OperatorMCMCMarkov chain Monte CarloNCHSNational Center for Health StatisticsNNDSSNational Notifiable Disease Surveillance SystemNVSSNational Vital Statistics SystemSARS-CoV-2Severe Acute Respiratory Syndrome Coronavirus 2

We thank Dr. Alonso et al for their commentary1 on our articles, “Estimates of Seasonal Influenza‐Associated Mortality in Bangladesh, 2010‐2012”2 and “The National Burden of Influenza‐Associated Severe Acute Respiratory Illness Hospitalization in Rwanda, 2012‐2014.”3 In their commentary, they described three assumptions that we would like to address: (1) their use of “substantial” burden compared to “high” burden, (2) the comparability of influenza burden in tropical climate countries, and (3) the impact of the influenza A(H1N1)pdm09 virus on mortality. In addition, they describe three concerns about our estimates, which we would also like to clarify, specifically: (4) a mismatch in the timing of respiratory deaths and the influenza virus circulation period, (5) mortality attribution, and (6) the comparison with Institute of Health Metrics and Evaluation (IHME) estimates. We will address each of these comments or concerns in this brief response.

INTRODUCTION: The burden of influenza in Cambodia is not well known, but it would be useful for understanding the impact of seasonal epidemics and pandemics and to design appropriate policies for influenza prevention and control. The severe acute respiratory infection (SARI) surveillance system in Cambodia was used to estimate the national burden of SARI hospitalizations in Cambodia. METHODS: We estimated age-specific influenza-associated SARI hospitalization rates in three sentinel sites in Svay Rieng, Siem Reap and Kampong Cham provinces. We used influenza-associated SARI surveillance data for one year to estimate the numerator and hospital admission surveys to estimate the population denominator for each site. A national influenza-associated SARI hospitalization rate was calculated using the pooled influenza-associated SARI hospitalizations for all sites as a numerator and the pooled catchment population of all sites as denominator. National influenza-associated SARI case counts were estimated by applying hospitalization rates to the national population. RESULTS: The national annual rates of influenza-associated hospitalizations per 100 000 population was highest for the two youngest age groups at 323 for < 1 year and 196 for 1-4 years. We estimated 7547 influenza-associated hospitalizations for Cambodia with almost half of these represented by children younger than 5 years. DISCUSSION: We present national estimates of influenza-associated SARI hospitalization rates for Cambodia based on sentinel surveillance data from three sites. The results of this study indicate that the highest burden of severe influenza infection is borne by the younger age groups. These findings can be used to guide future strategies to reduce influenza morbidity.

BACKGROUND: Global estimates showed an estimate of up to 650,000 seasonal influenza-associated respiratory deaths annually. However, the mortality rate of seasonal influenza is unknown for most countries in the WHO Eastern Mediterranean Region, including Iran. We aimed to estimate the excess mortality attributable to seasonal influenza in Kerman province, southeast Iran for the influenza seasons 2006/2007-2011/2012. METHODS: We applied a Serfling model to the weekly total pneumonia and influenza (PI) mortality rate during winter to define the epidemic periods and to the weekly age-specific PI, respiratory, circulatory, and all-cause deaths during non-epidemic periods to estimate baseline mortality. The excess mortality was calculated as the difference between observed and predicted mortality. Country estimates were obtained by multiplying the estimated annual excess death rates by the populations of Iran. RESULTS: We estimated an annual average excess of 40 PI, 100 respiratory, 94 circulatory, and 306 all-cause deaths attributable to seasonal influenza in Kerman; corresponding to annual rates of 1.4 (95% confidence interval [CI] 1.1-1.8) PI, 3.6 (95% CI 2.6-4.8) respiratory, 3.4 (95% CI 2.1-5.2) circulatory, and 11.0 (95% CI 7.3-15.6) all-cause deaths per 100,000 population. Adults ≥75 years accounted for 56% and 53% of all excess respiratory and circulatory deaths, respectively. At country level, we would expect an annual of 1119 PI to 8792 all-cause deaths attributable to seasonal influenza. CONCLUSIONS: Our findings help to define the mortality burden of seasonal influenza, most of which affects adults aged ≥75 years. This study supports influenza prevention and vaccination programs in older adults.

Before the emergence of SARS-CoV-2, the virus that causes COVID-19, influenza activity in the United States typically began to increase in the fall and peaked in February. During the 2021-22 season, influenza activity began to increase in November and remained elevated until mid-June, featuring two distinct waves, with A(H3N2) viruses predominating for the entire season. This report summarizes influenza activity during October 3, 2021-June 11, 2022, in the United States and describes the composition of the Northern Hemisphere 2022-23 influenza vaccine. Although influenza activity is decreasing and circulation during summer is typically low, remaining vigilant for influenza infections, performing testing for seasonal influenza viruses, and monitoring for novel influenza A virus infections are important. An outbreak of highly pathogenic avian influenza A(H5N1) is ongoing; health care providers and persons with exposure to sick or infected birds should remain vigilant for onset of symptoms consistent with influenza. Receiving a seasonal influenza vaccine each year remains the best way to protect against seasonal influenza and its potentially severe consequences.

Background Severe acute respiratory infections (SARI) are a leading cause of hospitalizations in children, especially due to viral pathogens. We studied the prevalence of respiratory viruses among children aged <5 years hospitalized with severe acute respiratory infections (SARI) in Kashmir, India. Methods We conducted a prospective observational study in two tertiary care hospitals from October 2013 to September 2014, systematically enrolling two children aged <5 years with SARI per day. We defined SARI as history of fever or measured fever (≥38°C) and cough with onset in the last 7 days requiring hospitalization for children aged 3-59 months and as physician-diagnosed acute lower respiratory infection for children aged <3 months. Trained study staff screened children within 24 hours of hospitalization for SARI and collected clinical data and nasopharyngeal swabs from enrolled participants. We tested for respiratory syncytial virus (RSV) A and B, influenza viruses, rhinoviruses (HRV)/enteroviruses, adenovirus (AdV), bocavirus (BoV), human metapneumovirus (hMPV) A and B, coronaviruses (OC43, NL65, C229E), and parainfluenza viruses (PIV) 1, 2, 3 and 4 using standardized duplex real-time polymerase chain reaction. Results Among 4548 respiratory illness admissions screened from October 2013 to September 2014, 1026 met the SARI case definition, and 412 were enrolled (ages = 5 days to 58 months; median = 12 months). Among enrolees, 256 (62%) were positive for any virus; RSV was the most commonly detected (n = 118, 29%) followed by HRV/enteroviruses (n = 88, 21%), PIVs (n = 31, 8%), influenza viruses (n = 18, 4%), BoV (n = 15, 4%), coronaviruses (n = 16, 4%), AdV (n = 14, 3%), and hMPV (n = 9, 2%). Fifty-four children had evidence of virus co-detection. Influenza-associated SARI was more common among children aged 1-5 years (14/18, 78%) while most RSV detections occurred in children <12 months (83/118, 70%). Of the RSV viruses typed (n = 116), the majority were type B (94, 80%). Phylogenetic analysis of G gene of RSV showed circulation of the BA9 genotype with 60bp nucleotide duplication. Conclusions Respiratory viruses, especially RSV, contributed to a substantial proportion of SARI hospitalizations among children <5 years in north India. These data can help guide clinicians on appropriate treatment and prevention strategies. © 2022. The Author(s)

BACKGROUND: Although most adults infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) fully recover, a proportion have ongoing symptoms, or post-COVID conditions (PCC), after infection. The objective of this analysis was to estimate the number of United States (US) adults with activity-limiting PCC on 1 November 2021. METHODS: We modeled the prevalence of PCC using reported infections occurring from 1 February 2020 to 30 September 2021, and population-based, household survey data on new activity-limiting symptoms ≥1 month following SARS-CoV-2 infection. From these data sources, we estimated the number and proportion of US adults with activity-limiting PCC on 1 November 2021 as 95% uncertainty intervals, stratified by sex and age. Sensitivity analyses adjusted for underascertainment of infections and uncertainty about symptom duration. RESULTS: On 1 November 2021, at least 3.0-5.0 million US adults, or 1.2%-1.9% of the US adult population, were estimated to have activity-limiting PCC of ≥1 month's duration. Population prevalence was higher in females (1.4%-2.2%) than males. The estimated prevalence after adjusting for underascertainment of infections was 1.7%-3.8%. CONCLUSIONS: Millions of US adults were estimated to have activity-limiting PCC. These estimates can support future efforts to address the impact of PCC on the US population.

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 235 000 (95% UI, 175 000-305 000) 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.

BACKGROUND: In the United States, COVID-19 is a nationally notifiable disease, meaning cases and hospitalizations are reported to the CDC by states. 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 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 COVID-19-Associated Hospitalization Surveillance Network (COVID-NET) and a Bayesian hierarchical model for extrapolation. Hospitalization rates are calculated from patients hospitalized with a lab confirmed SARS-CoV-2 test during or within 14 days before admission. We created a model for six 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/or month, and performed covariate selection for each age group based on two methods, Least Absolute Shrinkage and Selection Operator (LASSO) and Spike and Slab selection methods. We validated our method by checking 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:3,250,500 - 3,945,400) hospitalizations for a cumulative incidence of 1,093.9 (992.4 - 1,204.6) hospitalizations per 100,000 population with COVID-19 in the United States from May 2020 through April 2021. Cumulative incidence varied from 359 - 1,856 per 100,000 between states. The age group with the highest cumulative incidence was aged ≥85 years (5,575.6; 5,066.4 - 6,133.7). The monthly hospitalization rate was highest in December (183.7; 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 with COVID-19 has potential to provide sustainable estimates for monitoring COVID-19 burden, as well as a flexible framework leveraging surveillance data.

COVID-19 testing provides information regarding exposure and transmission risks, guides preventative measures (e.g., if and when to start and end isolation and quarantine), identifies opportunities for appropriate treatments, and helps assess disease prevalence (1). At-home rapid COVID-19 antigen tests (at-home tests) are a convenient and accessible alternative to laboratory-based diagnostic nucleic acid amplification tests (NAATs) for SARS-CoV-2, the virus that causes COVID-19 (2-4). With the emergence of the SARS-CoV-2 B.1.617.2 (Delta) and B.1.1.529 (Omicron) variants in 2021, demand for at-home tests increased(†) (5). At-home tests are commonly used for school- or employer-mandated testing and for confirmation of SARS-CoV-2 infection in a COVID-19-like illness or following exposure (6). Mandated COVID-19 reporting requirements omit at-home tests, and there are no standard processes for test takers or manufacturers to share results with appropriate health officials (2). Therefore, with increased COVID-19 at-home test use, laboratory-based reporting systems might increasingly underreport the actual incidence of infection. Data from a cross-sectional, nonprobability-based online survey (August 23, 2021-March 12, 2022) of U.S. adults aged ≥18 years were used to estimate self-reported at-home test use over time, and by demographic characteristics, geography, symptoms/syndromes, and reasons for testing. From the Delta-predominant period (August 23-December 11, 2021) to the Omicron-predominant period (December 19, 2021-March 12, 2022)(§) (7), at-home test use among respondents with self-reported COVID-19-like illness(¶) more than tripled from 5.7% to 20.1%. The two most commonly reported reasons for testing among persons who used an at-home test were COVID-19 exposure (39.4%) and COVID-19-like symptoms (28.9%). At-home test use differed by race (e.g., self-identified as White [5.9%] versus self-identified as Black [2.8%]), age (adults aged 30-39 years [6.4%] versus adults aged ≥75 years [3.6%]), household income (>$150,000 [9.5%] versus $50,000-$74,999 [4.7%]), education (postgraduate degree [8.4%] versus high school or less [3.5%]), and geography (New England division [9.6%] versus West South Central division [3.7%]). COVID-19 testing, including at-home tests, along with prevention measures, such as quarantine and isolation when warranted, wearing a well-fitted mask when recommended after a positive test or known exposure, and staying up to date with vaccination,** can help reduce the spread of COVID-19. Further, providing reliable and low-cost or free at-home test kits to underserved populations with otherwise limited access to COVID-19 testing could assist with continued prevention efforts.

BACKGROUND: Seasonal influenza-associated excess mortality estimates can be timely and provide useful information on the severity of an epidemic. This methodology can be leveraged during an emergency response or pandemic. METHOD: For Denmark, Spain, and the United States, we estimated age-stratified excess mortality for (i) all-cause, (ii) respiratory and circulatory, (iii) circulatory, (iv) respiratory, and (v) pneumonia, and influenza causes of death for the 2015/2016 and 2016/2017 influenza seasons. We quantified differences between the countries and seasonal excess mortality estimates and the death categories. We used a time-series linear regression model accounting for time and seasonal trends using mortality data from 2010 through 2017. RESULTS: The respective periods of weekly excess mortality for all-cause and cause-specific deaths were similar in their chronological patterns. Seasonal all-cause excess mortality rates for the 2015/2016 and 2016/2017 influenza seasons were 4.7 (3.3-6.1) and 14.3 (13.0-15.6) per 100,000 population, for the United States; 20.3 (15.8-25.0) and 24.0 (19.3-28.7) per 100,000 population for Denmark; and 22.9 (18.9-26.9) and 52.9 (49.1-56.8) per 100,000 population for Spain. Seasonal respiratory and circulatory excess mortality estimates were two to three times lower than the all-cause estimates. DISCUSSION: We observed fewer influenza-associated deaths when we examined cause-specific death categories compared with all-cause deaths and observed the same trends in peaks in deaths with all death causes. Because all-cause deaths are more available, these models can be used to monitor virus activity in near real time. This approach may contribute to the development of timely mortality monitoring systems during public health emergencies.

BACKGROUND: The European Centres for Disease Prevention and Control (ECDC) estimates that seasonal influenzacauses 4-50 million symptomatic infections in the EU/EEA each year and 15,000-70,000 European citizens die of causes associated with influenza. We used modelling methods to estimate influenza-associated mortality for the European Union by age group and country. METHODS: We compiled influenza-associated respiratory mortality estimates for 31 countries around the world (11 countries in the EU) during 2002-2011 (excluding the 2009 pandemic). From these we extrapolated the influenza mortality burden for all 193 countries of the world, including the 28 countries of the EU, using a multiple imputation approach. To study the effect of vaccination programs, we obtained data from the EU-funded VENICE project regarding the percentage of persons over 65 who were vaccinated in each country; the data ranged from 2% to 82% between the 21 countries which provided estimates for the 2006/07 reference season. RESULTS: We estimated that an average of 27,600 (range 16,200-39,000) respiratory deaths were associated with seasonal influenza in the 28 EU countries per winter; 88% were among people 65 years and older, and the rates of mortality in this age group were roughly 35 times higher compared with those < 65 years. Estimates varied considerably across the EU; for example, rates in the elderly ranged from 21.6 (12.5-35.1) per 100,000 in Portugal to 36.5 (16.4-62.5) in Luxembourg, a difference of nearly 70%. We were unable to find a negative correlation between vaccination coverage rates and influenza-associated mortality estimates in the elderly. CONCLUSION: Our EU estimate of influenza-associated respiratory mortality is broadly consistent with the ECDC estimate. More research is needed to explain the observed variation in mortality across the EU, and on possible bias that could explain the unexpected lack of mortality benefits associated with European elderly influenza vaccination programs.

The B.1.1.529 (Omicron) variant of SARS-CoV-2, the virus that causes COVID-19, was first clinically identified in the United States on December 1, 2021, and spread rapidly. By late December, it became the predominant strain, and by January 15, 2022, it represented 99.5% of sequenced specimens in the United States* (1). The Omicron variant has been shown to be more transmissible and less virulent than previously circulating variants (2,3). To better understand the severity of disease and health care utilization associated with the emergence of the Omicron variant in the United States, CDC examined data from three surveillance systems and a large health care database to assess multiple indicators across three high-COVID-19 transmission periods: December 1, 2020-February 28, 2021 (winter 2020-21); July 15-October 31, 2021 (SARS-CoV-2 B.1.617.2 [Delta] predominance); and December 19, 2021-January 15, 2022 (Omicron predominance). The highest daily 7-day moving average to date of cases (798,976 daily cases during January 9-15, 2022), emergency department (ED) visits (48,238), and admissions (21,586) were reported during the Omicron period, however, the highest daily 7-day moving average of deaths (1,854) was lower than during previous periods. During the Omicron period, a maximum of 20.6% of staffed inpatient beds were in use for COVID-19 patients, 3.4 and 7.2 percentage points higher than during the winter 2020-21 and Delta periods, respectively. However, intensive care unit (ICU) bed use did not increase to the same degree: 30.4% of staffed ICU beds were in use for COVID-19 patients during the Omicron period, 0.5 percentage points lower than during the winter 2020-21 period and 1.2 percentage points higher than during the Delta period. The ratio of peak ED visits to cases (event-to-case ratios) (87 per 1,000 cases), hospital admissions (27 per 1,000 cases), and deaths (nine per 1,000 cases [lagged by 3 weeks]) during the Omicron period were lower than those observed during the winter 2020-21 (92, 68, and 16 respectively) and Delta (167, 78, and 13, respectively) periods. Further, among hospitalized COVID-19 patients from 199 U.S. hospitals, the mean length of stay and percentages who were admitted to an ICU, received invasive mechanical ventilation (IMV), and died while in the hospital were lower during the Omicron period than during previous periods. COVID-19 disease severity appears to be lower during the Omicron period than during previous periods of high transmission, likely related to higher vaccination coverage,(†) which reduces disease severity (4), lower virulence of the Omicron variant (3,5,6), and infection-acquired immunity (3,7). Although disease severity appears lower with the Omicron variant, the high volume of ED visits and hospitalizations can strain local health care systems in the United States, and the average daily number of deaths remains substantial.(§) This underscores the importance of national emergency preparedness, specifically, hospital surge capacity and the ability to adequately staff local health care systems. In addition, being up to date on vaccination and following other recommended prevention strategies are critical to preventing infections, severe illness, or death from COVID-19.

In the United States, COVID-19 has become a leading cause of death since 2020. However, the number of COVID-19 deaths reported from death certificates is likely to represent an underestimate of the total deaths related to SARS-CoV-2 infections. Estimating those deaths not captured through death certificates is important to understanding the full burden of COVID-19 on mortality. In this work, we explored enhancements to an existing approach by employing Bayesian hierarchical models to estimate unrecognized deaths attributed to COVID-19 using weekly state-level COVID-19 viral surveillance and mortality data in the United States from March 2020 to April 2021. We demonstrated our model using those aged 85 years who died. First, we used a spatial-temporal binomial regression model to estimate the percent of positive SARS-CoV-2 test results. A spatial-temporal negative-binomial model was then used to estimate unrecognized COVID-19 deaths by exploiting the spatial-temporal association between SARS-CoV-2 percent positive and all-cause mortality counts using an excess mortality approach. Computationally efficient Bayesian inference was accomplished via the Polya-Gamma representation of the binomial and negative-binomial models. Among those aged 85 years, we estimated 58,200 (95% CI: 51,300, 64,900) unrecognized COVID-19 deaths, which accounts for 26% (95% CI: 24%, 29%) of total COVID-19 deaths in this age group. Our modeling results suggest that COVID-19 mortality and the proportion of unrecognized deaths among deaths attributed to COVID-19 vary by time and across states.

Influenza burden estimates are essential to informing prevention and control policies. To complement recent influenza vaccine production capacity in Vietnam, we used acute respiratory infection (ARI) hospitalization data, severe acute respiratory infection (SARI) surveillance data, and provincial population data from 4 provinces representing Vietnam's major regions during 2014-2016 to calculate provincial and national influenza-associated ARI and SARI hospitalization rates. We determined the proportion of ARI admissions meeting the World Health Organization SARI case definition through medical record review. The mean influenza-associated hospitalization rates per 100,000 population were 218 (95% uncertainty interval [UI] 197-238) for ARI and 134 (95% UI 119-149) for SARI. Influenza-associated SARI hospitalization rates per 100,000 population were highest among children <5 years of age (1,123; 95% UI 946-1,301) and adults >65 years of age (207; 95% UI 186-227), underscoring the need for prevention and control measures, such as vaccination, in these at-risk populations.

OBJECTIVE: Estimates of the burden of influenza are needed to inform prevention and control activities for seasonal influenza, including to support the development of appropriate vaccination policies. We used sentinel surveillance data on severe acute respiratory infection (SARI) to estimate the burden of influenza-associated hospitalizations in the Lao People's Democratic Republic. METHODS: Using methods developed by the World Health Organization, we combined data from hospital logbook reviews with epidemiological and virological data from influenza surveillance from 1 January to 31 December 2016 in defined catchment areas for two sentinel sites (Champasack and Luang Prabang provincial hospitals) to derive population-based estimates of influenza-associated SARI hospitalization rates. Hospitalization rates by age group were then applied to national age-specific population estimates using 2015 census data. RESULTS: We estimated the overall influenza-associated SARI hospitalization rate to be 48/100 000 population (95% confidence interval [CI]: 44-51) or 3097 admissions (95% CI: 2881-3313). SARI hospitalization rates were estimated to be as low as 40/100 000 population (95% CI: 37-43) and as high as 92/100 000 population (95% CI: 87-98) after accounting for SARI patient underascertainment in hospital logbooks. Influenza-associated SARI hospitalization rates were highest in children aged < 5 years (219; 95% CI: 198-241) and persons aged (3) 65 years (106; 95% CI: 91-121). DISCUSSION: Our findings have identified age groups at higher risk for influenza-associated SARI hospitalization, which will support policy decisions for influenza prevention and control strategies, including for vaccination. Further work is needed to estimate the burdens of outpatient influenza and influenza in specific high-risk subpopulations.

BACKGROUND: In the United States, Coronavirus Disease 2019 (COVID-19) deaths are captured through the National Notifiable Disease Surveillance System and death certificates reported to the National Vital Statistics System (NVSS). However, not all COVID-19 deaths are recognized and reported because of limitations in testing, exacerbation of chronic health conditions that are listed as the cause of death, or delays in reporting. Estimating deaths may provide a more comprehensive understanding of total COVID-19-attributable deaths. METHODS: We estimated COVID-19 unrecognized attributable deaths, from March 2020-April 2021, using all-cause deaths reported to NVSS by week and six age groups (0-17, 18-49, 50-64, 65-74, 75-84, and ≥85 years) for 50 states, New York City, and the District of Columbia using a linear time series regression model. Reported COVID-19 deaths were subtracted from all-cause deaths before applying the model. Weekly expected deaths, assuming no SARS-CoV-2 circulation and predicted all-cause deaths using SARS-CoV-2 weekly percent positive as a covariate were modelled by age group and including state as a random intercept. COVID-19-attributable unrecognized deaths were calculated for each state and age group by subtracting the expected all-cause deaths from the predicted deaths. FINDINGS: We estimated that 766,611 deaths attributable to COVID-19 occurred in the United States from March 8, 2020-May 29, 2021. Of these, 184,477 (24%) deaths were not documented on death certificates. Eighty-two percent of unrecognized deaths were among persons aged ≥65 years; the proportion of unrecognized deaths were 0•24-0•31 times lower among those 0-17 years relative to all other age groups. More COVID-19-attributable deaths were not captured during the early months of the pandemic (March-May 2020) and during increases in SARS-CoV-2 activity (July 2020, November 2020-February 2021). DISCUSSION: Estimating COVID-19-attributable unrecognized deaths provides a better understanding of the COVID-19 mortality burden and may better quantify the severity of the COVID-19 pandemic. FUNDING: None.

BACKGROUND: Data on influenza incidence during pregnancy in China are limited. METHODS: From October 2015 to September 2018, we conducted active surveillance for acute respiratory illness (ARI) among women during pregnancy. Nurses conducted twice weekly phone and text message follow-up upon enrollment until delivery to identify new episodes of ARI. Nasal and throat swabs were collected ≤10 days from illness onset to detect influenza. RESULTS: In total, we enrolled 18 724 pregnant women median aged 28 years old, 37% in first trimester, 48% in second trimester, and 15% in third trimester, with seven self-reported influenza vaccination during pregnancy. In the 18-week epidemic period during October 2015 to September 2016, influenza incidence was 0.7/100 person-months (95% CI: 0.5-0.9). In the cumulative 29-week-long epidemic during October 2016 to September 2017, influenza incidence was 1.0/100 person-months (95% CI: 0.8-1.2). In the 11-week epidemic period during October 2017 to September 2018, influenza incidence was 2.1/100 person-months (95% CI: 1.9-2.4). Influenza incidence was similar by trimester. More than half of the total influenza illnesses had no elevated temperature and cough. Most influenza-associated ARIs were mild, and <5.1% required hospitalization. CONCLUSIONS: Influenza illness in all trimesters of pregnancy was common. These data may help inform decisions regarding the use of influenza vaccine to prevent influenza during pregnancy.

The vaccine efficacy of standard-dose seasonal inactivated influenza vaccines (S-IIV) can be improved by the use of vaccines with higher antigen content or adjuvants. We conducted a randomized controlled trial in older adults to compare cellular and antibody responses of S-IIV versus enhanced vaccines (eIIV): MF59-adjuvanted (A-eIIV), high-dose (H-eIIV), and recombinant-hemagglutinin (HA) (R-eIIV). All vaccines induced comparable H3-HA-specific IgG and elevated antibody-dependent cellular cytotoxicity (ADCC) activity at day 30 post vaccination. H3-HA-specific ADCC responses were greatest following H-eIIV. Only A-eIIV increased H3-HA-IgG avidity, HA-stalk IgG and ADCC activity. eIIVs also increased polyfunctional CD4+ and CD8+ T cell responses, while cellular immune responses were skewed toward single-cytokine-producing T cells among S-IIV subjects. Our study provides further immunological evidence for the preferential use of eIIVs in older adults as each vaccine platform had an advantage over the standard-dose vaccine in terms of NK cell activation, HA-stalk antibodies, and T cell responses.