High expression of oleoyl-ACP hydrolase underpins life-threatening respiratory viral diseases.

Respiratory infections cause significant morbidity and mortality, yet it is unclear why some individuals succumb to severe disease. In patients hospitalized with avian A(H7N9) influenza, we investigated early drivers underpinning fatal disease. Transcriptomics strongly linked oleoyl-acyl-carrier-protein (ACP) hydrolase (OLAH), an enzyme mediating fatty acid production, with fatal A(H7N9) early after hospital admission, persisting until death. Recovered patients had low OLAH expression throughout hospitalization. High OLAH levels were also detected in patients hospitalized with life-threatening seasonal influenza, COVID-19, respiratory syncytial virus (RSV), and multisystem inflammatory syndrome in children (MIS-C) but not during mild disease. In olah-/- mice, lethal influenza infection led to survival and mild disease as well as reduced lung viral loads, tissue damage, infection-driven pulmonary cell infiltration, and inflammation. This was underpinned by differential lipid droplet dynamics as well as reduced viral replication and virus-induced inflammation in macrophages. Supplementation of oleic acid, the main product of OLAH, increased influenza replication in macrophages and their inflammatory potential. Our findings define how the expression of OLAH drives life-threatening viral disease.

PREDAC-CNN: predicting antigenic clusters of seasonal influenza A viruses with convolutional neural network.

Vaccination stands as the most effective and economical strategy for prevention and control of influenza. The primary target of neutralizing antibodies is the surface antigen hemagglutinin (HA). However, ongoing mutations in the HA sequence result in antigenic drift. The success of a vaccine is contingent on its antigenic congruence with circulating strains. Thus, predicting antigenic variants and deducing antigenic clusters of influenza viruses are pivotal for recommendation of vaccine strains. The antigenicity of influenza A viruses is determined by the interplay of amino acids in the HA1 sequence. In this study, we exploit the ability of convolutional neural networks (CNNs) to extract spatial feature representations in the convolutional layers, which can discern interactions between amino acid sites. We introduce PREDAC-CNN, a model designed to track antigenic evolution of seasonal influenza A viruses. Accessible at http://predac-cnn.cloudna.cn, PREDAC-CNN formulates a spatially oriented representation of the HA1 sequence, optimized for the convolutional framework. It effectively probes interactions among amino acid sites in the HA1 sequence. Also, PREDAC-CNN focuses exclusively on physicochemical attributes crucial for the antigenicity of influenza viruses, thereby eliminating unnecessary amino acid embeddings. Together, PREDAC-CNN is adept at capturing interactions of amino acid sites within the HA1 sequence and examining the collective impact of point mutations on antigenic variation. Through 5-fold cross-validation and retrospective testing, PREDAC-CNN has shown superior performance in predicting antigenic variants compared to its counterparts. Additionally, PREDAC-CNN has been instrumental in identifying predominant antigenic clusters for A/H3N2 (1968-2023) and A/H1N1 (1977-2023) viruses, significantly aiding in vaccine strain recommendation.

The Potential Benefits of Delaying Seasonal Influenza Vaccine Selections for the Northern Hemisphere: A Retrospective Modeling Study in the United States.

BACKGROUND: Antigenic similarity between vaccine viruses and circulating viruses is crucial for achieving high vaccine effectiveness against seasonal influenza. New non-egg-based vaccine production technologies could revise current vaccine formulation schedules. We aim to assess the potential benefit of delaying seasonal influenza vaccine virus selection decisions. METHODS: We identified seasons where season-dominant viruses presented increasing prevalence after vaccine formulation had been decided in February for the Northern Hemisphere, contributing to their antigenic discrepancy with vaccine viruses. Using a SEIR (susceptible-exposed-infectious-recovered) model of seasonal influenza in the United States, we evaluated the impact of updating vaccine decisions with more antigenically similar vaccine viruses on the influenza burden in the United States. RESULTS: In 2014-2015 and 2019-2020, the season-dominant A(H3N2) subclade and B/Victoria clade, respectively, presented increasing prevalence after vaccine decisions were already made for the Northern Hemisphere. Our model showed that the updated A(H3N2) vaccine could have averted 5000-65 000 influenza hospitalizations in the United States in 2014-2015, whereas updating the B/Victoria vaccine component did not substantially change influenza burden in the 2019-2020 season. CONCLUSIONS: With rapid vaccine production, revising current timelines for vaccine selection could result in substantial epidemiological benefits, particularly when additional data could help improve the antigenic match between vaccine and circulating viruses.

Hemagglutinin stalk-specific Fc-mediated functions are associated with protection against influenza-illness after seasonal influenza vaccination in pregnant women.

BACKGROUND: Several influenza vaccine candidates aim to elicit antibodies against the conserved hemagglutinin stalk domain. Understanding the protective mechanism of these antibodies, which mediate broad neutralization and Fc-mediated functions, following seasonal vaccination is critical. METHODS: Plasma samples were obtained from a subset of pregnant women living with or without HIV-1 enrolled in a randomised trial (138 trivalent inactivated vaccine [TIV] and 145 placebo recipients). Twenty-three influenza-illness cases were confirmed within 6 months postpartum. We measured H1 stalk-specific antibody-dependent cellular phagocytosis (ADCP), complement deposition (ADCD) and cellular cytotoxicity (ADCC) at enrolment and 1-month post-vaccination. The association between these Fc-mediated functions and protection against influenza-illness following vaccination was examined using multiple logistic regression analysis and risk reduction thresholds were defined by the score associated with the lowest odds of influenza-illness. RESULTS: Amongst TIV and placebo recipients, lower H1 stalk-specific ADCP and ADCD activity was detected for participants with confirmed influenza compared with individuals without confirmed influenza-illness 1-month post-vaccination. Pre-existing ADCP scores ≥250 reduced the odds of A/H1N1 infection (odds ratio 0.11; p=0.01) with an 83% likelihood of risk reduction. Following TIV, ADCD scores of ≥25 and ≥15 significantly reduced the odds against A/H1N1 (0.10; p=0.01) and non-group 1 (0.06; p=0.0004) influenza virus infections, respectively. These ADCD scores were associated with >84% likelihood of risk reduction. H1 stalk-specific ADCC potential was not associated with protection against influenza-illness. CONCLUSION: H1 stalk-specific ADCD correlates with protection against influenza-illness following influenza vaccination during pregnancy. These findings provide insight into the protective mechanisms of HA stalk antibodies.

Safety and Immunogenicity of Respiratory Syncytial Virus Prefusion F Protein Vaccine when Co-administered with Adjuvanted Seasonal Quadrivalent Influenza Vaccine in Older Adults: A Phase 3 Randomized Trial.

BACKGROUND: We evaluated co-administration of adjuvanted seasonal quadrivalent influenza vaccine (FLU-aQIV) and respiratory syncytial virus (RSV) prefusion F protein-based vaccine (RSVPreF3 OA) in ≥65-year-olds. METHODS: This phase 3, open-label trial randomized ≥65-year-olds to receive FLU-aQIV and RSVPreF3 OA concomitantly (Co-Ad) or sequentially, 1 month apart (Control). Primary objectives were to demonstrate the non-inferiority of FLU-aQIV and RSVPreF3 OA co-administration versus sequential administration in terms of hemagglutination inhibition (HI) titers for each FLU-aQIV strain and RSV-A and RSV-B neutralization titers, 1 month post-vaccination. Reactogenicity and safety were also assessed. RESULTS: Overall, 1045 participants were vaccinated (Co-Ad: 523; Control: 522). Non-inferiority of FLU-aQIV and RSVPreF3 OA co-administration versus sequential administration was demonstrated in terms of HI titers for the A/Victoria(H1N1), B/Victoria, and B/Yamagata influenza strains and RSV-A neutralization titers (upper limits [ULs] of 95% confidence intervals [CIs] for adjusted geometric mean titer [GMT] ratios [Control/Co-Ad] ≤1.50) but not for A/Darwin(H3N2) HI titers (95% CI UL = 1.53). The immune response to A/Darwin(H3N2) was further assessed post-hoc using a microneutralization assay; the post-vaccination adjusted GMT ratio (Control/Co-Ad) was 1.23 (95% CI: 1.06-1.42, ie, UL ≤1.50), suggesting an adequate immune response to A/Darwin(H3N2) following co-administration. RSV-B neutralization titers were comparable between groups (95% CI UL for adjusted GMT ratio ≤1.50). Solicited adverse events were mostly mild or moderate and transient; unsolicited and serious adverse event rates were balanced between groups. CONCLUSIONS: Adjuvanted FLU-aQIV and RSVPreF3 OA had acceptable reactogenicity/safety profiles when co-administered in ≥65-year-olds, without clinically relevant interference with the immune responses to either vaccine. CLINICAL TRIALS REGISTRATION: NCT05568797.

Resurgence of seasonal influenza driven by A/H3N2 and B/Victoria in succession during the 2023-2024 season in Beijing showing increased population susceptibility.

During the COVID-19 pandemic, non-pharmaceutical interventions were introduced to reduce exposure to respiratory viruses. However, these measures may have led to an "immunity debt" that could make the population more vulnerable. The goal of this study was to examine the transmission dynamics of seasonal influenza in the years 2023-2024. Respiratory samples from patients with influenza-like illness were collected and tested for influenza A and B viruses. The electronic medical records of index cases from October 2023 to March 2024 were analyzed to determine their clinical and epidemiological characteristics. A total of 48984 positive cases were detected, with a pooled prevalence of 46.9% (95% CI 46.3-47.5). This season saw bimodal peaks of influenza activity, with influenza A peaked in week 48, 2023, and influenza B peaked in week 1, 2024. The pooled positive rates were 28.6% (95% CI 55.4-59.6) and 18.3% (95% CI 18.0-18.7) for influenza A and B viruses, respectively. The median values of instantaneous reproduction number were 5.5 (IQR 3.0-6.7) and 4.6 (IQR 2.4-5.5), respectively. The hospitalization rate for influenza A virus (2.2%, 95% CI 2.0-2.5) was significantly higher than that of influenza B virus (1.1%, 95% CI 0.9-1.4). Among the 17 clinical symptoms studied, odds ratios of 15 symptoms were below 1 when comparing influenza A and B positive inpatients, with headache, weakness, and myalgia showing significant differences. This study provides an overview of influenza dynamics and clinical symptoms, highlighting the importance for individuals to receive an annual influenza vaccine.

The efficacy and safety of a quadrivalent live attenuated influenza nasal vaccine in Japanese children: A phase 3, randomized, placebo-controlled study.

BACKGROUND: Vaccination is the primary method of preventing influenza infection and complications in young children. We evaluated the efficacy and safety of a single dose of MEDI3250 (intranasal, quadrivalent, live attenuated influenza vaccine) in healthy Japanese children during the 2016/17 influenza season. METHODS: In this multicenter, randomized, double-blind, phase 3 study (jRCT2080223345), participants aged 2-18 years received MEDI3250 or placebo (2:1), stratified by age (2-6 years, 7-18 years). The primary and secondary endpoints were the incidence of confirmed symptomatic onset of influenza caused by a circulating wild-type strain or by a vaccine-matched strain, respectively. Safety outcomes included the incidence of adverse events (AEs) and vaccine-related AEs. RESULTS: Overall, 910 participants received MEDI3250 (n = 608) or placebo (n = 302). For the primary endpoint (regardless of the influenza subtype), the incidence of influenza onset was 25.5 % (MEDI3250) and 35.9 % (placebo); relative risk reduction, 28.8 % (95 % confidence interval, 12.5 %-42.0 %). For the secondary endpoint (vaccine-matched strain), the incidence was 10.9 % (MEDI3250) and 17.2 % (placebo); relative risk reduction, 36.6 % (95 % confidence interval, 6.5 %-56.8 %). Solicited AEs occurred in 67.6 % (MEDI3250) and 63.6 % (placebo). Most events were mild; nasal discharge was most common (59.2 % [MEDI3250] and 52.6 % [placebo]). Unsolicited AEs occurred in 36.0 % (MEDI3250) and 33.1 % (placebo). The most common unsolicited vaccine-related AE was diarrhea (2.3 %, both groups). CONCLUSIONS: MEDI3250 had a greater preventive effect against influenza onset in Japanese children than placebo; no new safety signals were observed relative to previous clinical and post-marketing studies of MEDI3250.

How immune dynamics shape multi-season epidemics: a continuous-discrete model in one dimensional antigenic space.

We extend a previously published model for the dynamics of a single strain of an influenza-like infection. The model incorporates a waning acquired immunity to infection and punctuated antigenic drift of the virus, employing a set of coupled integral equations within a season and a discrete map between seasons. The long term behaviour of the model is demonstrated by examples where immunity to infection depends on the time since a host was last infected, and where immunity depends on the number of times that a host has been infected. The first scenario leads to complicated dynamics in some regions of parameter space, and to regions of parameter space with more than one attractor. The second scenario leads to a stable fixed point, corresponding to an identical epidemic each season. We also examine the model with both paradigms in combination, almost always but not exclusively observing a stable fixed point or periodic solution. Adding stochastic perturbations to the between season map fails to destroy the model's qualitative dynamics. Our results suggest that if the level of host immunity depends on the elapsed time since the last infection then the epidemiological dynamics may be unpredictable.

Acceptability, cost-effectiveness, and capacity of a facility-based seasonal influenza vaccination among high-risk groups: a study protocol in selected tertiary care hospitals of Bangladesh.

BACKGROUND: In Bangladesh, seasonal influenza imposes considerable disease and economic burden, especially for those at high-risk of severe disease. The most successful approach for influenza prevention is the administration of a vaccine. Many poor and middle-income nations, including Bangladesh, do not have a national strategy or program in place for seasonal influenza vaccines, despite the World Health Organization's (WHO) advice to prioritize high-risk populations. Additionally, there is a scarcity of substantial data on the cost-effectiveness of seasonal influenza vaccination in these countries. The aim of our study is to determine acceptability, health beliefs, barriers, and intention of receiving influenza vaccine among high-risk populations, assess the cost-effectiveness of implementing a facility-based seasonal influenza vaccination programme, and investigate the required capacity for a potential seasonal influenza vaccination programme. METHODS: We will undertake this study following STROBE guidelines. We will conduct the study in inpatient and outpatient departments of three selected tertiary-level hospitals leveraging the ongoing hospital-based influenza surveillance (HBIS) platform. The study population will include the WHO-defined four high-risk groups excluding healthcare workers: children six months to eight years, pregnant women, elderly ≥ 60 years, and adults with chronic diseases. We will collect quantitative data on participants' acceptability, health beliefs, barriers, and vaccination intentions using the health belief model (HBM) from patients meeting the criteria for high-risk populations attending two public tertiary-level hospitals. In one of the two public tertiary-level hospitals, we will arrange an influenza vaccination campaign before the influenza season, where the vaccine will be offered free of cost to high-risk patients, and in the second hospital, vaccination will not be offered. Both the vaccinated and unvaccinated participants will then be followed-up once a month for one year to record any influenza-like illness, hospitalization, and death. Additional data for objective two will be collected from patients with symptoms of influenza-like illness (ILI) and severe acute respiratory infection (SARI) at one public and one private hospital to determine both direct and indirect costs associated with influenza illness. We will estimate the required number of influenza vaccines, safe injections, and total storage volume utilizing secondary data. We will use a deterministic Markov decision-analytic model to estimate the cost-effectiveness of facility-based influenza vaccination in Bangladesh. DISCUSSION: The results of this study will enable the National Immunization Technical Advisory Group and the Ministry of Health & Family Welfare of Bangladesh to decide what steps to take to develop and implement an influenza vaccination strategy targeting high-risk populations. TRIAL REGISTRATION: The Clinicaltrials.gov registration number is NCT05996549. The registration for the protocol version 2.0 took place in August 2023, with the initial participant being enrolled in March 2022.

Changes in Attitudes and Barriers to Seasonal Influenza Vaccination from 2007 to 2023.

This study investigated how factors and barriers to flu vaccination among college students has changed over the past 16 years. Data were collected from 440 students using a survey and compared to previous data from the same university. Respondents were also asked about their experiences with Covid-19 and its effect on their intent to vaccinate. We found that vaccination rates had increased from 12.4 to 30.5%. Among the unvaccinated, expense, fear of getting influenza from vaccination, fear of side effects, and lack of information have decreased by 28%, 20%, 17%, and 15% respectively. Time, convenience, and perceived risk are still significant barriers to vaccination. Students are getting more encouragement to vaccinate from their health care providers and parents, but it is becoming less effective. The Covid-19 pandemic has changed vaccine attitudes and vaccine fatigue has been a large contributor. Additionally, political affiliation has become a predictor of flu vaccine uptake with conservatives being less likely to vaccinate. There has also been a shift in motivation from concern for personal safety to concern for public safety.

Application of the Time Derivative (TD) Method for Early Alert of Influenza Epidemics.

BACKGROUND: In order to minimize the spread of seasonal influenza epidemic to communities worldwide, the Korea Disease Control and Prevention Agency has issued an influenza epidemic alert using the influenza epidemic threshold formula based on the results of the influenza-like illness (ILI) rate. However, unusual changes have occurred in the pattern of respiratory infectious diseases, including seasonal influenza, after the coronavirus disease 2019 (COVID-19) pandemic. As a result, the importance of detecting the onset of an epidemic earlier than the existing epidemic alert system is increasing. Accordingly, in this study, the Time Derivative (TD) method was suggested as a supplementary approach to the existing influenza alert system for the early detection of seasonal influenza epidemics. METHODS: The usefulness of the TD method as an early epidemic alert system was evaluated by applying the ILI rate for each week during past seasons when seasonal influenza epidemics occurred, ranging from the 2013-2014 season to the 2022-2023 season to compare it with the issued time of the actual influenza epidemic alert. RESULTS: As a result of applying the TD method, except for the two seasons (2020-2021 season and 2021-2022 season) that had no influenza epidemic, an influenza early epidemic alert was suggested during the remaining seasons, excluding the 2017-2018 and 2022-2023 seasons. CONCLUSION: The TD method is a time series analysis that enables early epidemic alert in real-time without relying on past epidemic information. It can be considered as an alternative approach when it is challenging to set an epidemic threshold based on past period information. This situation may arise when there has been a change in the typical seasonal epidemic pattern of various respiratory viruses, including influenza, following the COVID-19 pandemic.

Effect of environmental exposome and influenza infection on febrile seizure in children over 22 years: a time series analysis.

Febrile seizures are convulsions predominately occurring in young children. The effects of various exposomes, including influenza infection and external environmental factors, on febrile seizures have not been well-studied. In this study, we elucidated the relationships between ambient temperature, air pollutants, influenza infection, and febrile seizures using 22-year territory-wide hospitalization data in Hong Kong. The aggregated data were matched with the meteorological records and air pollutant concentrations. All-type and type-specific influenza-like illness positive (ILI+) rates were used as proxies for influenza activity. Distributed lag non-linear model in conjunction with the quasi-poisson generalized additive model was used to examine the associations of interest. According to the results, all-type influenza infections were significantly associated with an increased risk of hospital admissions for febrile seizures (cumulative adjusted relative risk [ARR] = 1.59 at 95th percentile vs. 0; 95% CI, 1.51-1.68). The effect of ILI + A/H3N2 on febrile seizure was more pronounced than other type-specific ILI + rates. A low mean ambient temperature was identified as a significant risk factor for febrile seizures (cumulative ARR = 1.50 at 5th percentile vs. median; 95% CI, 1.35-1.66), while the redox-weighted oxidant capacity and sulfur dioxide were not associated with febrile seizures. In conclusion, our study underscores that influenza infections and exposure to cold conditions were related to an increased risk of febrile seizures in children. Thus, we advocate for influenza vaccination before the onset of the cold season for children to mitigate the burden of febrile seizures.

The potential benefits of delaying seasonal influenza vaccine selections for the Northern Hemisphere: a retrospective modeling study in the United States.

BACKGROUNDS: Antigenic similarity between vaccine viruses and circulating viruses is crucial for achieving high vaccine effectiveness against seasonal influenza. New non-egg-based vaccine production technologies could revise current vaccine formulation schedules. We aim to assess the potential benefit of delaying seasonal influenza vaccine virus selection decisions. METHODS: We identified seasons where season-dominant viruses presented increasing prevalence after vaccine formulation had been decided in February for the Northern Hemisphere, contributing to their antigenic discrepancy with vaccine viruses. Using a SEIR model of seasonal influenza in the United States, we evaluated the impact of updating vaccine decisions with more antigenically-similar vaccine viruses on the influenza burden in the United States. RESULTS: In 2014/15 and 2019/20, the season-dominant A(H3N2) subclade and B/Victoria clade respectively presented increasing prevalence after vaccine decisions were already made for the Northern Hemisphere. Our model showed that the updated A(H3N2) vaccine could have averted 5,000-65,000 influenza hospitalizations in the United States in 2014/15, whereas updating the B/Victoria vaccine component did not substantially change influenza burden in 2019/20 season. CONCLUSIONS: With rapid vaccine production, revising current timelines for vaccine selection could result in substantial epidemiological benefits, particularly when additional data could help improve the antigenic match between vaccine and circulating viruses.

Geographically dependent individual-level models for infectious diseases transmission.

Infectious disease models can be of great use for understanding the underlying mechanisms that influence the spread of diseases and predicting future disease progression. Modeling has been increasingly used to evaluate the potential impact of different control measures and to guide public health policy decisions. In recent years, there has been rapid progress in developing spatio-temporal modeling of infectious diseases and an example of such recent developments is the discrete-time individual-level models (ILMs). These models are well developed and provide a common framework for modeling many disease systems; however, they assume the probability of disease transmission between two individuals depends only on their spatial separation and not on their spatial locations. In cases where spatial location itself is important for understanding the spread of emerging infectious diseases and identifying their causes, it would be beneficial to incorporate the effect of spatial location in the model. In this study, we thus generalize the ILMs to a new class of geographically dependent ILMs, to allow for the evaluation of the effect of spatially varying risk factors (e.g., education, social deprivation, environmental), as well as unobserved spatial structure, upon the transmission of infectious disease. Specifically, we consider a conditional autoregressive (CAR) model to capture the effects of unobserved spatially structured latent covariates or measurement error. This results in flexible infectious disease models that can be used for formulating etiological hypotheses and identifying geographical regions of unusually high risk to formulate preventive action. The reliability of these models is investigated on a combination of simulated epidemic data and Alberta seasonal influenza outbreak data ($2009$). This new class of models is fitted to data within a Bayesian statistical framework using Markov chain Monte Carlo methods.

Increased population susceptibility to seasonal influenza during the COVID-19 pandemic in China and the United States.

To the best of our knowledge, no previous study has quantitatively estimated the dynamics and cumulative susceptibility to influenza infections after the widespread lifting of COVID-19 public health measures. We constructed an imitated stochastic susceptible-infected-removed model using particle-filtered Markov Chain Monte Carlo sampling to estimate the time-dependent reproduction number of influenza based on influenza surveillance data in southern China, northern China, and the United States during the 2022-2023 season. We compared these estimates to those from 2011 to 2019 seasons without strong social distancing interventions to determine cumulative susceptibility during COVID-19 restrictions. Compared to the 2011-2019 seasons without a strong intervention with social measures, the 2022-2023 influenza season length was 45.0%, 47.1%, and 57.1% shorter in southern China, northern China, and the United States, respectively, corresponding to an 140.1%, 74.8%, and 50.9% increase in scale of influenza infections, and a 60.3%, 72.9%, and 45.1% increase in population susceptibility to influenza. Large and high-intensity influenza epidemics occurred in China and the United States in 2022-2023. Population susceptibility increased in 2019-2022, especially in China. We recommend promoting influenza vaccination, taking personal prevention actions on at-risk populations, and monitoring changes in the dynamic levels of influenza and other respiratory infections to prevent potential outbreaks in the coming influenza season.

Clinical, epidemiological, and genomic characteristics of a seasonal influenza A virus outbreak in Beijing: A descriptive study.

China experienced a severe influenza season that began at the end of February 2023. The aim of this post hoc analysis was to investigate the clinical, epidemiological, and genomic features of this outbreak in Beijing. The number of cases increased rapidly from the end of February and reached its peak in March, with 7262 confirmed cases included in this study. The median age was 33 years, and 50.3% of them were male. The average daily positive rate reached 69% during the peak period. The instantaneous reproduction number (Rt) showed a median of 2.1, exceeded 2.5 initially, and remaining above 1 for the following month. The most common symptoms were fever (75.0%), cough (51.0%), and expectoration (42.9%), with a median body temperature of 38.5°C (interquartile range 38-39). Eight clinical symptoms were more likely to be observed in cases with fever, with odds ratio greater than 1. Viral shedding time ranged from 3 to 25 days, with median of 7.5 days. The circulating viruses in Beijing mainly included H1N1pdm09 (clades 5a.2a and 5a.2a.1), following with H3N2 (clade 2a.2a.3a.1). The descriptive study suggests that influenza viruses in this influenza season had a higher transmissibility and longer shedding duration, with fever being the most common symptom.

Comparison of combination methods to create calibrated ensemble forecasts for seasonal influenza in the U.S.

The characteristics of influenza seasons vary substantially from year to year, posing challenges for public health preparation and response. Influenza forecasting is used to inform seasonal outbreak response, which can in turn potentially reduce the impact of an epidemic. The United States Centers for Disease Control and Prevention, in collaboration with external researchers, has run an annual prospective influenza forecasting exercise, known as the FluSight challenge. Uniting theoretical results from the forecasting literature with domain-specific forecasts from influenza outbreaks, we applied parametric forecast combination methods that simultaneously optimize model weights and calibrate the ensemble via a beta transformation and made adjustments to the methods to reduce their complexity. We used the beta-transformed linear pool, the finite beta mixture model, and their equal weight adaptations to produce ensemble forecasts retrospectively for the 2016/2017, 2017/2018, and 2018/2019 influenza seasons in the U.S. We compared their performance to methods that were used in the FluSight challenge to produce the FluSight Network ensemble, namely the equally weighted linear pool and the linear pool. Ensemble forecasts produced from methods with a beta transformation were shown to outperform those from the equally weighted linear pool and the linear pool for all week-ahead targets across in the test seasons based on average log scores. We observed improvements in overall accuracy despite the beta-transformed linear pool or beta mixture methods' modest under-prediction across all targets and seasons. Combination techniques that explicitly adjust for known calibration issues in linear pooling should be considered to improve probabilistic scores in outbreak settings.

Mortality in cancer patients with SARS-CoV-2 or seasonal influenza: an observational cohort study from a German-wide hospital network.

PURPOSE: At the beginning of the COVID-19 pandemic, SARS-CoV-2 was often compared to seasonal influenza. We aimed to compare the outcome of hospitalized patients with cancer infected by SARS-CoV-2 or seasonal influenza including intensive care unit admission, mechanical ventilation and in-hospital mortality. METHODS: We analyzed claims data of patients with a lab-confirmed SARS-CoV-2 or seasonal influenza infection admitted to one of 85 hospitals of a German-wide hospital network between January 2016 and August 2021. RESULTS: 29,284 patients with COVID-19 and 7442 patients with seasonal influenza were included. Of these, 360 patients with seasonal influenza and 1625 patients with COVID-19 had any kind of cancer. Cancer patients with COVID-19 were more likely to be admitted to the intensive care unit than cancer patients with seasonal influenza (29.4% vs 24.7%; OR 1.31, 95% CI 1.00-1.73 p < .05). No statistical significance was observed in the mechanical ventilation rate for cancer patients with COVID-19 compared to those with seasonal influenza (17.2% vs 13.6% OR 1.34, 95% CI 0.96-1.86 p = .09). 34.9% of cancer patients with COVID-19 and 17.9% with seasonal influenza died (OR 2.45, 95% CI 1.81-3.32 p < .01). Risk factors among cancer patients with COVID-19 or seasonal influenza for in-hospital mortality included the male gender, age, a higher Elixhauser comorbidity index and metastatic cancer. CONCLUSION: Among cancer patients, SARS-CoV-2 was associated with a higher risk for in-hospital mortality than seasonal influenza. These findings underline the need of protective measurements to prevent an infection with either COVID-19 or seasonal influenza, especially in this high-risk population.

Trends in respiratory diseases before and after the COVID-19 pandemic in China from 2010 to 2021.

BACKGROUND: The ongoing benefits of coronavirus disease 2019 (COVID-19) nonpharmaceutical interventions (NPIs) for respiratory infectious diseases in China are still unclear. We aimed to explore the changes in seven respiratory infectious diseases before, during, and after COVID-19 in China from 2010 to 2021. METHODS: The monthly case numbers of seven respiratory infectious diseases were extracted to construct autoregressive integrated moving average (ARIMA) models. Eight indicators of NPIs were chosen from the COVID-19 Government Response Tracker system. The monthly case numbers of the respiratory diseases and the eight indicators were used to establish the Multivariable generalized linear model (GLM) to calculate the incidence rate ratios (IRRs). RESULTS: Compared with the year 2019, the percentage changes in 2020 and 2021 were all below 100% ranging from 3.81 to 84.71%. Pertussis and Scarlet fever started to increase in 2021 compared with 2020, with a percentage change of 183.46 and 171.49%. The ARIMA model showed a good fit, and the predicted data fitted well with the actual data from 2010 to 2019, but the predicted data was bigger than the actual number in 2020 and 2021. All eight indicators could negatively affect the incidence of respiratory diseases. The seven respiratory diseases were significantly reduced during the COVID-19 pandemic in 2020 and 2021 compared with 2019, with significant estimated IRRs ranging from 0.06 to 0.85. In the GLM using data for the year 2020 and 2021, the IRRs were not significant after adjusting for the eight indicators in multivariate analysis. CONCLUSION: Our study demonstrated the incidence of the seven respiratory diseases decreased rapidly during the COVID-19 pandemic in 2020 and 2021. At the end of 2021, we did see a rising trend for the seven respiratory diseases compared to the year 2020 when the NPIs relaxed in China, but the rising trend was not significant after adjusting for the NPIs indicators. Our study showed that NPIs have an effect on respiratory diseases, but Relaxation of NPIs might lead to the resurgence of respiratory diseases.

Excess Invasive Meningococcal Disease Associated With Seasonal Influenza, South Africa, 2003-2018.

BACKGROUND: Invasive meningococcal disease (IMD) is a devastating illness with high mortality rates. Like influenza, endemic IMD is seasonal, peaking in winter. Studies suggest that circulation of influenza virus may influence the timing and magnitude of IMD winter peaks. METHODS: This ecological study used weekly data from 2 nationwide surveillance programs: Viral Watch (proportion of outpatient influenza-positive cases from throat or nasal swab samples) and GERMS-SA (laboratory-confirmed cases of IMD), occurring across South Africa from 2003 through 2018 in all age bands. A bivariate time series analysis using wavelet transform was conducted to determine cocirculation of the diseases and the time lag between the peak seasons. We modeled excess meningococcal disease cases attributable to influenza cocirculation, using univariate regression spline models. Stata and R statistical software packages were used for the analysis. RESULTS: A total of 5256 laboratory-confirmed IMD cases were reported, with an average annual incidence of 0.23 episodes per 100 000 population and a mean seasonal peak during week 32 (±3 weeks). Forty-two percent of swab samples (10 421 of 24 741) were positive for influenza during the study period. The mean peak for all influenza occurred at week 26 (±4 weeks). There was an average lag time of 5 weeks between annual influenza and IMD seasons. Overall, 5% (1%-9%) of IMD cases can be attributable to influenza cocirculation, with, on average, 17 excess IMD cases per year attributable to influenza. CONCLUSIONS: A quantifiable proportion of IMD in South Africa is associated with influenza cocirculation; therefore, seasonal influenza vaccination may have an effect on preventing a small portion of IMD in addition to preventing influenza.