Household Transmission of Influenza A Viruses in 2021-2022

SARS-CoV-2 co-detection with other respiratory pathogens-descriptive epidemiological study

BACKGROUND

Co-detection of respiratory pathogens with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is poorly understood. This descriptive epidemiological study aimed to determine the effect of the interaction of different respiratory pathogens on clinical variables.

METHODS

We retrospectively reviewed the results of comprehensive multiplex polymerase chain reaction (PCR) testing from November 2020 to March 2023 to estimate respiratory pathogen co-detection rates in Shinjuku, Tokyo. We evaluated the interactions of respiratory pathogens, particularly SARS-CoV-2, between observed and expected co-detection. We estimated the trend of co-detection with SARS-CoV-2 in terms of age and sex and applied a multiple logistic regression model adjusted for age, testing period, and sex to identify influencing factors between co-detection and single detection for each pathogen.

RESULTS

Among 57,746 patients who underwent multiplex PCR testing, 10,516 (18.2%) had positive for at least one of the 22 pathogens. Additionally, 881 (1.5%) patients were confirmed to have a co-detection. SARS-CoV-2 exhibited negative interactions with adenovirus, coronavirus, human metapneumovirus, parainfluenza virus, respiratory syncytial virus, and rhino/enterovirus. SARS-CoV-2 co-detection with other pathogens occurred most frequently in patients of the youngest age group (0-4 years). A multiple logistic regression model indicated that younger age was the most influential factor for SARS-CoV-2 co-detection with other respiratory pathogens.

CONCLUSION

The study highlights the prevalence of SARS-CoV-2 co-detection with other respiratory pathogens in younger age groups, necessitating further exploration of the clinical implications and severity of SARS-CoV-2 co-detection.

Infection Rates and Symptomatic Proportion of SARS-CoV-2 and Influenza in Pediatric Population, China, 2023

We conducted a longitudinal cohort study of SARS-CoV-2 and influenza rates in childcare centers and schools in Wuxi, China, collecting 1,760 environmental samples and 9,214 throat swabs from 593 students (regardless of symptoms) in weekly collections during February-June 2023. We estimated a cumulative infection rate of 124.8 (74 episodes)/1,000 persons for SARS-CoV-2 and 128.2 (76 episodes)/1,000 persons for influenza. The highest SARS-CoV-2 infection rate was in persons 18 years of age, and for influenza, in children 4 years of age. The asymptomatic proportion of SARS-CoV-2 was 59.6% and 66.7% for influenza; SARS-CoV-2 symptomatic proportion was lower in 16-18-year-olds than in 4-6-year-olds. Only samples from frequently touched surface tested positive for SARS-CoV-2 (4/1,052) and influenza (1/1,052). We found asynchronous circulation patterns of SARS-CoV-2 and influenza, similar to trends in national sentinel surveillance. The results support vaccination among pediatric populations and other interventions, such as environmental disinfection in educational settings.

Influenza virus shedding and symptoms: Dynamics and implications from a multiseason household transmission study

Isolation of symptomatic infectious persons can reduce influenza transmission. However, virus shedding that occurs without symptoms will be unaffected by such measures. Identifying effective isolation strategies for influenza requires understanding the interplay between individual virus shedding and symptom presentation. From 2017 to 2020, we conducted a case-ascertained household transmission study using influenza real-time RT-qPCR testing of nasal swabs and daily symptom diary reporting for up to 7 days after enrolment (≤14 days after index onset). We assumed real-time RT-qPCR cycle threshold (Ct) values were indicators of quantitative virus shedding and used symptom diaries to create a score that tracked influenza-like illness (ILI) symptoms (fever, cough, or sore throat). We fit phenomenological nonlinear mixed-effects models stratified by age and vaccination status and estimated two quantities influencing isolation effectiveness: shedding before symptom onset and shedding that might occur once isolation ends. We considered different isolation end points (including 24 h after fever resolution or 5 days after symptom onset) and assumptions about the infectiousness of Ct shedding trajectories. Of the 116 household contacts with ≥2 positive tests for longitudinal analyses, 105 (91%) experienced ≥1 ILI symptom. On average, children <5 years experienced greater peak shedding, longer durations of shedding, and elevated ILI symptom scores compared with other age groups. Most individuals (63/105) shed <10% of their total shed virus before symptom onset, and shedding after isolation varied substantially across individuals, isolation end points, and infectiousness assumptions. Our results can inform strategies to reduce transmission from symptomatic individuals infected with influenza.

Estimating the generation time for influenza transmission using household data in the United States

The generation time, representing the interval between infections in primary and secondary cases, is essential for understanding and predicting the transmission dynamics of seasonal influenza, including the real-time effective reproduction number (Rt). However, comprehensive generation time estimates for seasonal influenza, especially post the 2009 influenza pandemic, are lacking. We estimated the generation time utilizing data from a 7-site case-ascertained household study in the United States over two influenza seasons, 2021/2022 and 2022/2023. More than 200 individuals who tested positive for influenza and their household contacts were enrolled within 7 days of the first illness in the household. All participants were prospectively followed for 10 days completing daily symptom diaries and collecting nasal swabs, which were tested for influenza via RT-PCR. We analyzed these data by modifying a previously published Bayesian data augmentation approach that imputes infection times of cases to obtain both intrinsic (assuming no susceptible depletion) and realized (observed within household) generation times. We assessed the robustness of the generation time estimate by varying the incubation period, and generated estimates of the proportion of transmission before symptomatic onset, infectious period, and latent period. We estimated a mean intrinsic generation time of 3.2 (95% credible interval, CrI: 2.9-3.6) days, with a realized household generation time of 2.8 (95% CrI: 2.7-3.0) days. The generation time exhibited limited sensitivity to incubation period variation. Estimates of the proportion of transmission that occurred before symptom onset, the infectious period, and the latent period were sensitive to variation in incubation periods. Our study contributes to the ongoing efforts to refine estimates of the generation time for influenza. Our estimates, derived from recent data following the COVID-19 pandemic, are consistent with previous pre-pandemic estimates, and will be incorporated into real-time Rt estimation efforts.

Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons

While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNV) were identified at a 0.5% frequency threshold. Within-host populations were subject to purifying selection with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4×10-6 vs. 9.42×10-7 and 3.45×10-6, p <0.001). Forty-five iSNV had evidence of parallel evolution, but were not overrepresented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNV across segments. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to purifying selection and genetic drift, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.

Asymptomatic and mildly symptomatic influenza virus infections by season -- Case-ascertained household transmission studies, United States, 2017-2023

Asymptomatic influenza virus infection occurs but may vary by factors such as age, influenza vaccination status, or influenza season. We examined the frequency of influenza virus infection and associated symptoms using data from two case-ascertained household transmission studies (conducted from 2017-2023) with prospective, systematic collection of respiratory specimens and symptoms. From the 426 influenza virus infected household contacts that met our inclusion criteria, 8% were asymptomatic, 6% had non-respiratory symptoms, 23% had acute respiratory symptoms, and 62% had influenza-like illness symptoms. Understanding the prevalence of asymptomatic and mildly symptomatic influenza cases is important for implementing effective influenza prevention strategies and enhancing the effectiveness of symptom-based surveillance systems.

Real-time investigation of an influenza A(H3N2) virus outbreak in a refugee community, November 2022

OBJECTIVES

To report epidemiological and virological results of an outbreak investigation of influenza-like illness (ILI) among refugees in Northern Italy.

STUDY DESIGN

Outbreak investigation of ILI cases observed among nearly 100 refugees in Northern Italy unvaccinated for influenza.

METHODS

An epidemiological investigation matched with a differential diagnosis was carried out for each sample collected from ILI cases to identify 10 viral pathogens (SARS-CoV-2, influenza virus type A and B, respiratory syncytial virus, metapneumovirus, parainfluenza viruses, rhinovirus, enterovirus, parechovirus, and adenovirus) by using specific real-time PCR assays according to the Centers for Disease Control and Prevention (CDC) protocols. In cases where the influenza virus type was identified, complete hemagglutinin (HA) gene sequencing and the related phylogenetic analysis were conducted.

RESULTS

The outbreak was caused by influenza A(H3N2): the attack rate was 83.3% in children aged 9-14 years, 84.6% in those aged 15-24 years, and 28.6% in adults ≥25 years. Phylogenetic analyses uncovered that A(H3N2) strains were closely related since they segregated in the same cluster, showing both a high mean nucleotide identity (100%), all belonging to the genetic sub-group 3C.2a1b.2a.2, as those mainly circulating into the general population in the same period.

CONCLUSIONS

The fact that influenza outbreak strains as well as the community strains were genetically related to the seasonal vaccine strain suggests that if an influenza prevention by vaccination strategy had been implemented, a lower attack rate of A(H3N2) and ILI cases might have been achieved.

Household Influenza Transmission and Healthcare Resource Utilization Among Patients Treated with Baloxavir vs Oseltamivir: A United States Outpatient Prospective Survey

INTRODUCTION

Influenza is a common, seasonal infectious disease with broad medical, economic, and social consequences. Real-world evidence on the effect of influenza treatment on household transmission and healthcare resource utilization is limited in outpatient settings in the USA. This study examined the real-world effectiveness of baloxavir vs oseltamivir in reducing influenza household transmission and healthcare resource utilization.

METHODS

This prospective electronic survey on patient-reported outcomes was conducted between October 2022 and May 2023 via CVS Pharmacy in the USA. Adult participants (≥ 18 years old) were eligible if they filled a prescription for baloxavir or oseltamivir at a CVS Pharmacy within 2 days of influenza symptom onset. Participant demographics, household transmission, and all-cause healthcare resource utilization were collected. Transmission and utilization outcomes were assessed using χ2 and Fisher exact tests.

RESULTS

Of 87,871 unique patients contacted, 1346 (1.5%) consented. Of 374 eligible patients, 286 (90 baloxavir- and 196 oseltamivir-treated patients) completed the survey and were included in the analysis. Mean age of participants was 45.4 years, 65.6% were female, and 86.7% were White. Lower household transmission was observed with baloxavir compared with oseltamivir therapy (17.8% vs 26.5%; relative risk = 0.67; 95% CI 0.41-1.11). Healthcare resource utilization, particularly emergency department visits (0.0% vs 4.6%), was also numerically lower in the baloxavir-treated group; no hospitalizations were reported in either cohort.

CONCLUSIONS

The findings from this real-world study suggest that antiviral treatment of influenza with baloxavir may decrease household transmission and reduce healthcare resource utilization compared with oseltamivir.

Exploring the spatiotemporal relationship between influenza and air pollution in Fuzhou using spatiotemporal weighted regression model

Air pollution has become a significant concern for human health, and its impact on influenza, has been increasingly recognized. This study aims to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza and to confirm a better method for infectious disease surveillance. Spearman correlation coefficient was used to evaluate the correlation between air pollution and the influenza case counts. VIF was used to test for collinearity among selected air pollutants. OLS regression, GWR, and STWR models were fitted to explore the potential spatiotemporal relationship between air pollution and influenza. The R2, the RSS and the AICc were used to evaluate and compare the models. In addition, the DTW and K-medoids algorithms were applied to cluster the county-level time-series coefficients. Compared with the OLS regression and GWR models, STWR model exhibits superior fit especially when the influenza outbreak changes rapidly and is able to more accurately capture the changes in different regions and time periods. We discovered that identical air pollutant factors may yield contrasting impacts on influenza within the same period in different areas of Fuzhou. NO2 and PM10 showed opposite impacts on influenza in the eastern and western areas of Fuzhou during all periods. Additionally, our investigation revealed that the relationship between air pollutant factors and influenza may exhibit temporal variations in certain regions. From 2013 to 2019, the influence coefficient of O3 on influenza epidemic intensity changed from negative to positive in the western region and from positive to negative in the eastern region. STWR model could be a useful method to explore the spatiotemporal heterogeneity of the impacts of air pollution on influenza in geospatial processes. The research findings emphasize the importance of considering spatiotemporal heterogeneity when studying the relationship between air pollution and influenza.

Influenza in Children and Adolescents: Epidemiology, Management, and Prevention

EDUCATION GAP

Influenza is among the most common infectious causes of pediatric emergency department visits and hospitalizations. Clinicians should use evidence-based guidelines to learn how to identify, manage, prevent, and treat influenza cases. Disease caused by influenza virus can be mitigated with appropriate treatment and prevention efforts.

OBJECTIVES After completing this article, readers should be able to:

1. Describe the virology and epidemiology of influenza.

2. List the clinical features and complications of influenza infections.

3. List the benefits and limitations of testing modalities for the diagnosis of influenza.

4. Appropriately apply American Academy of Pediatrics, Infectious Diseases Society of America, and Centers for Disease Control and Prevention (CDC) treatment guidelines for influenza or suspected influenza.

5. Describe the importance of influenza vaccination.

Impact of Nonpharmacological Interventions on Severe Acute Respiratory Infections in Children: From the National Surveillance Database

BACKGROUND

Nonpharmacological interventions (NPIs) reduce the incidence of respiratory infections. After NPIs imposed during the coronavirus disease 2019 pandemic ceased, respiratory infections gradually increased worldwide. However, few studies have been conducted on severe respiratory infections requiring hospitalization in pediatric patients. This study compares epidemiological changes in severe respiratory infections during pre-NPI, NPI, and post-NPI periods in order to evaluate the effect of that NPI on severe respiratory infections in children.

METHODS

We retrospectively studied data collected at 13 Korean sentinel sites from January 2018 to October 2022 that were lodged in the national Severe Acute Respiratory Infections (SARIs) surveillance database.

RESULTS

A total of 9,631 pediatric patients were admitted with SARIs during the pre-NPI period, 579 during the NPI period, and 1,580 during the post-NPI period. During the NPI period, the number of pediatric patients hospitalized with severe respiratory infections decreased dramatically, thus from 72.1 per 1,000 to 6.6 per 1,000. However, after NPIs ceased, the number increased to 22.8 per 1,000. During the post-NPI period, the positive test rate increased to the level noted before the pandemic.

CONCLUSION

Strict NPIs including school and daycare center closures effectively reduced severe respiratory infections requiring hospitalization of children. However, childcare was severely compromised. To prepare for future respiratory infections, there is a need to develop a social consensus on NPIs that are appropriate for children.

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.

Reciprocal enhancement of SARS-CoV-2 and influenza virus replication in human pluripotent stem cell-derived lung organoids

Patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza A virus (FLUAV) coinfections were associated with severe respiratory failure and more deaths. Because of the lack of a relevant lung model system, the pathobiology of co-infections between SARS-CoV-2 and FLUAV remains less understood. Here, we developed a model for studying SARS-CoV-2 and FLUAV coinfection using human pluripotent stem cell-induced alveolar type II organoids (hiAT2). hiAT2 organoids were susceptible to infection by both viruses and had features of severe lung damage. We found that infection with a single virus markedly enhanced the susceptibility to other virus infections and was linked with the upregulation of respective cell entry receptors. SARS-CoV-2 delta variants upregulated α-2-3-linked sialic acid, while FLUAV upregulated angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2). Upregulation of ACE2 and TMPRSS2 was mediated by the FLUAV infection rather than individual viral proteins. RNA sequencing revealed that coinfection by SARS-CoV-2 and FLUAV caused hyperactivation of proinflammatory and immune-related signaling pathways and cellular damage compared to a respective single virus in hiAT2 organoids. Together, these studies established a relevant lung model system of hiAT2 organoids for understanding the biology of SARS-CoV-2 and FLUAV coinfection. This study also provides insight into molecular mechanisms underlying enhanced infectivity and severity in patients with co-infection of SARS-CoV-2 and FLUAV, which may aid in the development of newer therapeutics for the prevention and management of such co-infection cases.