Interval Between Infections and Viral Hierarchy Are Determinants of Viral Interference Following Influenza Virus Infection in a Ferret Model

Viral Interference and Coinfections: A Perspective From Hospital Surveillance of Respiratory Viruses

Viral interference may influence pathogen transmission at the population level, potentially affecting seasonal epidemics of respiratory infections. A frequently employed association measure purported to reflect interference effects is the prevalence ratio, the proportion of individuals coinfected with two viruses divided by the product of the proportions of individuals infected by each virus separately. However, the prevalence ratio neglects three important factors relevant to coinfection detection in epidemiological surveillance programs: undetected mono-infections, duration of viral excretion or detectability and circulation patterns of both viruses. We propose a generalization of the prevalence ratio that accounts for these factors to better assess the presence or absence of viral interactions in epidemiological surveillance data. We applied this association measure to influenza-respiratory syncytial virus (RSV) coinfection data from a hospital-based surveillance program of respiratory infections in the province of Québec, Canada, from 2012-2013 to 2018-2019 (HospiVir program). Our analysis suggests that influenza-RSV interference may be important in children but less in adults. However, our results are sensitive to population-level seasonal attack rates; coinfection data could be compatible with interference in adults if assumed attack rates increased from 3% to 5% to over 10%.

Impact of COVID-19 on Respiratory Virus Infections in Children, Japan, 2018-2023

BACKGROUND

COVID-19, caused by SARS-CoV-2, was first documented in Japan in January 2020. We previously reported an increased risk of rhinovirus infections among children during the early phase of the COVID-19 pandemic. Here, we assessed the impact of COVID-19 on respiratory virus infections after SARS-CoV-2 spread nationwide.

METHODS

We analyzed clinical specimens from 4012 patients with respiratory infections in Yokohama, Japan from January 2018 to April 2023.

RESULTS

Among 15 representative respiratory viruses we detected (influenza virus, rhinovirus, coxsackievirus, echovirus, enterovirus, human coronavirus 229E, HKU1, NL63, and OC43, human metapneumovirus, human parainfluenza virus, human parechovirus, RSV, human adenovirus, human bocavirus, human parvovirus B19, herpes simplex virus type 1, and varicella-zoster virus), influenza was most affected by the COVID-19 pandemic, with no influenza viruses detected for nearly 3 years.

CONCLUSIONS

The decrease in influenza infections following the emergence of SARS-CoV-2 may have contributed to the previously reported increase in rhinovirus infections. The rhinovirus outbreak, rather than SARS-CoV-2, may have contributed to the decrease in enveloped virus infections (RSV, parainfluenza viruses, metapneumovirus, and coronavirus 229E, HKU1, NL63, and OC43), possibly due to negative virus-virus interactions.

How immunity shapes the long-term dynamics of influenza H3N2

Since its emergence in 1968, influenza A H3N2 has caused yearly epidemics in temperate regions. While infection confers immunity against antigenically similar strains, new antigenically distinct strains that evade existing immunity regularly emerge ('antigenic drift'). Immunity at the individual level is complex, depending on an individual's lifetime infection history. An individual's first infection with influenza typically elicits the greatest response with subsequent infections eliciting progressively reduced responses ('antigenic seniority'). The combined effect of individual-level immune responses and antigenic drift on the epidemiological dynamics of influenza are not well understood. Here we develop an integrated modelling framework of influenza transmission, immunity, and antigenic drift to show how individual-level exposure, and the build-up of population level immunity, shape the long-term epidemiological dynamics of H3N2. Including antigenic seniority in the model, we observe that following an initial decline after the pandemic year, the average annual attack rate increases over the next 80 years, before reaching an equilibrium, with greater increases in older age-groups. Our analyses suggest that the average attack rate of H3N2 is still in a growth phase. Further increases, particularly in the elderly, may be expected in coming decades, driving an increase in healthcare demand due to H3N2 infections.

Application of MIDD to accelerate the development of anti-infectives: Current status and future perspectives

This review examines the role of model-informed drug development (MIDD) in advancing antibacterial and antiviral drug development, with an emphasis on the inclusion of host system dynamics into modeling efforts. Amidst the growing challenges of multidrug resistance and diminishing market returns, innovative methodologies are crucial for continuous drug discovery and development. The MIDD approach, with its robust capacity to integrate diverse data types, offers a promising solution. In particular, the utilization of appropriate modeling and simulation techniques for better characterization and early assessment of drug resistance are discussed. The evolution of MIDD practices across different infectious disease fields is also summarized, and compared to advancements achieved in oncology. Moving forward, the application of MIDD should expand into host system dynamics as these considerations are critical for the development of "live drugs" (e.g. chimeric antigen receptor T cells or bacteriophages) to address issues like antibiotic resistance or latent viral infections.

Interferon as an immunoadjuvant to enhance antibodies following influenza B infection and vaccination in ferrets

Despite annual vaccination, influenza B viruses (IBV) continue to cause significant morbidity and mortality in humans. We have found that IBV infection resulted in a weaker innate and adaptive immune response than influenza A viruses (IAV) in ferrets. To understand and overcome the weak immune responses to IBV in ferrets, we administered type-I or type-III interferon (IFN) to ferrets following infection or vaccination and evaluated their effects on the immune response. IFN signaling following viral infection plays an important role in the initial innate immune response and affects subsequent adaptive immune responses. In the respiratory tract, IFN lambda (IFNL) has regulatory effects on adaptive immunity indirectly through thymic stromal lymphopoietin (TSLP), which then acts on immune cells to stimulate the adaptive response. Following IBV infection or vaccination, IFN treatment (IFN-Tx) upregulated gene expression of early inflammatory responses in the upper respiratory tract and robust IFN, TSLP, and inflammatory responses in peripheral blood cells. These responses were sustained following challenge or vaccination in IFN-Tx animals. Serum IFNL and TSLP levels were enhanced in IFN-Tx animals following challenge/rechallenge over mock-Tx; however, this difference was not observed following vaccination. Antibody responses in serum of IFN-Tx animals following IBV infection or vaccination increased more quickly and to higher titers and were sustained longer than mock-Tx animals over 3 months. Following rechallenge of infected animals 3 months post treatment, antibody levels remained higher than mock-Tx. However, IFN-Tx did not have an effect on antibody responses following challenge of vaccinated animals. A strong direct correlation was found between TSLP levels and antibody responses following challenge-rechallenge and vaccination-challenge indicating it as a useful tool for predicting adaptive immune responses following IBV infection or vaccination. The effects of IFN on strengthening both innate and adaptive responses to IBV may aid in development of more effective treatments following infection and improved influenza vaccines.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Unraveling the Role of Viral Interference in Disrupting Biennial RSV Epidemics in Northern Stockholm

Respiratory syncytial virus (RSV) primarily impacts infants and older adults, with seasonal winter outbreaks in temperate countries. Biennial cycles of RSV activity have also been identified in Northern Europe and some states in the United States. Delayed RSV activity was reported worldwide during the 2009 influenza pandemic, and a disrupted biennial pattern of RSV activity was observed in northern Stockholm following the pandemic. Biennial patterns shifted to early/large outbreaks in even-numbered years and late/small outbreaks in odd-numbered years. However, the mechanisms underpinning this change in pattern remain unknown. In this work, we constructed an age-stratified mechanistic model to explicitly test three factors that could lead to the change in RSV transmission dynamics: 1) birth rates, 2) temperatures, and 3) viral interference. By fitting the model to weekly RSV admission data over a 20-year period and comparing different models, we found that viral interference from influenza was the only mechanism that explained the shifted biennial pattern. Our work demonstrates the complex interplay between different respiratory viruses, providing evidence that supports the presence of interactions between the H1N1 pandemic influenza virus and RSV at the population level, with implications for future public health interventions.

Considerations for viral co-infection studies in human populations

When respiratory viruses co-circulate in a population, individuals may be infected with multiple pathogens and experience possible virus-virus interactions, where concurrent or recent prior infection with one virus affects the infection process of another virus. While experimental studies have provided convincing evidence for within-host mechanisms of virus-virus interactions, evaluating evidence for viral interference or potentiation using population-level data has proven more difficult. Recent studies have quantified the prevalence of co-detections using populations drawn from clinical settings. Here, we focus on selection bias issues associated with this study design. We provide a quantitative account of the conditions under which selection bias arises in these studies, review previous attempts to address this bias, and propose unbiased study designs with sample size estimates needed to ascertain viral interference. We show that selection bias is expected in cross-sectional co-detection prevalence studies conducted in clinical settings, except under a strict set of assumptions regarding the relative probabilities of being included in a study limited to individuals with clinical disease under different viral states. Population-wide studies that collect samples from participants irrespective of their clinical status would meanwhile require large sample sizes to be sufficiently powered to detect viral interference, suggesting that a study's timing, inclusion criteria, and the expected magnitude of interference are instrumental in determining feasibility.

Viral interference between severe acute respiratory syndrome coronavirus 2 and influenza A viruses

Some respiratory viruses can cause a viral interference through the activation of the interferon (IFN) pathway that reduces the replication of another virus. Epidemiological studies of coinfections between SARS-CoV-2 and other respiratory viruses have been hampered by non-pharmacological measures applied to mitigate the spread of SARS-CoV-2 during the COVID-19 pandemic. With the ease of these interventions, SARS-CoV-2 and influenza A viruses can now co-circulate. It is thus of prime importance to characterize their interactions. In this work, we investigated viral interference effects between an Omicron variant and a contemporary influenza A/H3N2 strain, in comparison with an ancestral SARS-CoV-2 strain and the 2009 pandemic influenza A/H1N1 virus. We infected nasal human airway epitheliums with SARS-CoV-2 and influenza, either simultaneously or 24 h apart. Viral load was measured by RT-qPCR and IFN-α/β/λ1/λ2 proteins were quantified by immunoassay. Expression of four interferon-stimulated genes (ISGs; OAS1/IFITM3/ISG15/MxA) was also measured by RT-droplet digital PCR. Additionally, susceptibility of each virus to IFN-α/β/λ2 recombinant proteins was determined. Our results showed that influenza A, and especially A/H3N2, interfered with both SARS-CoV-2 viruses, but that SARS-CoV-2 did not significantly interfere with A/H3N2 or A/H1N1. Consistently with these results, influenza, and particularly the A/H3N2 strain, caused a higher production of IFN proteins and expression of ISGs than SARS-CoV-2. SARS-CoV-2 induced a marginal IFN production and reduced the IFN response during coinfections with influenza. All viruses were susceptible to exogenous IFNs, with the ancestral SARS-CoV-2 and Omicron being less susceptible to type I and type III IFNs, respectively. Thus, influenza A causes a viral interference towards SARS-CoV-2 most likely through an IFN response. The opposite is not necessarily true, and a concurrent infection with both viruses leads to a lower IFN response. Taken together, these results help us to understand how SARS-CoV-2 interacts with another major respiratory pathogen.

Antigenic drift and subtype interference shape A(H3N2) epidemic dynamics in the United States

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997-2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection dynamics, presumably via heterosubtypic cross-immunity.

Ferrets as a Mammalian Model to Study Influenza Virus-Bacteria Interactions

Ferrets represent an invaluable model for the study of influenza virus pathogenicity and transmissibility. Ferrets are also employed for the study of bacterial pathogens that naturally infect humans at different anatomical sites. While viral and bacterial infection studies in isolation using animal models are important for furthering our understanding of pathogen biology and developing improved therapeutics, it is also critical to extend our knowledge to pathogen coinfections in vivo, to more closely examine interkingdom dynamics that may contribute to overall disease outcomes. We discuss how ferrets have been employed to study a diverse range of both influenza viruses and bacterial species and summarize key studies that have utilized the ferret model for primary influenza virus challenge followed by secondary bacterial infection. These copathogenesis studies have provided critical insight into the dynamic interplay between these pathogens, underscoring the utility of ferrets as a model system for investigating influenza virus-bacteria interactions.

Key Challenges for Respiratory Virus Surveillance while Transitioning out of Acute Phase of COVID-19 Pandemic

To support the ongoing management of viral respiratory diseases while transitioning out of the acute phase of the COVID-19 pandemic, many countries are moving toward an integrated model of surveillance for SARS-CoV-2, influenza virus, and other respiratory pathogens. Although many surveillance approaches catalyzed by the COVID-19 pandemic provide novel epidemiologic insight, continuing them as implemented during the pandemic is unlikely to be feasible for nonemergency surveillance, and many have already been scaled back. Furthermore, given anticipated cocirculation of SARS-CoV-2 and influenza virus, surveillance activities in place before the pandemic require review and adjustment to ensure their ongoing value for public health. In this report, we highlight key challenges for the development of integrated models of surveillance. We discuss the relative strengths and limitations of different surveillance practices and studies as well as their contribution to epidemiologic assessment, forecasting, and public health decision-making.

An overview on viral interference during SARS-CoV-2 pandemic

Respiratory viruses represent the most frequent cause of mortality, morbidity and high healthcare costs for emergency visits and hospitalization in the pediatric age. Respiratory viruses can circulate simultaneously and can potentially infect the same host, determining different types of interactions, the so-called viral interference. The role of viral interference has assumed great importance since December 2019, when the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) came on the scene. The aim of this narrative review is to present our perspective regarding research in respiratory virus interference and discuss recent advances on the topic because, following SARS-CoV-2 restrictions mitigation, we are experimenting the co-circulation of respiratory viruses along with SARS-CoV-2. This scenario is raising many concerns about possible virus-virus interactions, both positive and negative, and the clinical, diagnostic and therapeutic management of these coinfections. Moreover, we cannot rule out that also climatic conditions and social behaviours are involved. Thus, this situation can lead to different population epidemic dynamics, including changes in the age of the targeted population, disease course and severity, highlighting the need for prospective epidemiologic studies and mathematical modelling able to predict the timing and magnitude of epidemics caused by SARS-CoV-2/seasonal respiratory virus interactions in order to adjust better public health interventions.

Mathematical Modeling of the Lethal Synergism of Coinfecting Pathogens in Respiratory Viral Infections: A Review

Influenza A virus (IAV) infections represent a substantial global health challenge and are often accompanied by coinfections involving secondary viruses or bacteria, resulting in increased morbidity and mortality. The clinical impact of coinfections remains poorly understood, with conflicting findings regarding fatality. Isolating the impact of each pathogen and mechanisms of pathogen synergy during coinfections is challenging and further complicated by host and pathogen variability and experimental conditions. Factors such as cytokine dysregulation, immune cell function alterations, mucociliary dysfunction, and changes to the respiratory tract epithelium have been identified as contributors to increased lethality. The relative significance of these factors depends on variables such as pathogen types, infection timing, sequence, and inoculum size. Mathematical biological modeling can play a pivotal role in shedding light on the mechanisms of coinfections. Mathematical modeling enables the quantification of aspects of the intra-host immune response that are difficult to assess experimentally. In this narrative review, we highlight important mechanisms of IAV coinfection with bacterial and viral pathogens and survey mathematical models of coinfection and the insights gained from them. We discuss current challenges and limitations facing coinfection modeling, as well as current trends and future directions toward a complete understanding of coinfection using mathematical modeling and computer simulation.

Statistical Analysis of Common Respiratory Viruses Reveals the Binary of Virus-Virus Interaction

Respiratory viruses may interfere with each other and affect the epidemic trend of the virus. However, the understanding of the interactions between respiratory viruses at the population level is still very limited. We here conducted a prospective laboratory-based etiological study by enrolling 14,426 patients suffered from acute respiratory infection (ARI) in Beijing, China during 2005 to 2015. All 18 respiratory viruses were simultaneously tested for each nasal and throat swabs collected from enrolled patients using molecular tests. The virus correlations were quantitatively evaluated, and the respiratory viruses could be divided into two panels according to the positive and negative correlations. One included influenza viruses (IFVs) A, B, and respiratory syncytial virus (RSV), while the other included human parainfluenza viruses (HPIVs) 1/3, 2/4, adenovirus (Adv), human metapneumovirus (hMPV), and enterovirus (including rhinovirus, named picoRNA), α and β human coronaviruses (HCoVs). The viruses were positive-correlated in each panel, while negative-correlated between panels. After adjusting the confounding factors by vector autoregressive model, positive interaction between IFV-A and RSV and negative interaction between IFV-A and picoRNA are still be observed. The asynchronous interference of IFV-A significantly delayed the peak of β human coronaviruses epidemic. The binary property of the respiratory virus interactions provides new insights into the viral epidemic dynamics in human population, facilitating the development of infectious disease control and prevention strategies. IMPORTANCE Systematic quantitative assessment of the interactions between different respiratory viruses is pivotal for the prevention of infectious diseases and the development of vaccine strategies. Our data showed stable interactions among respiratory viruses at human population level, which are season irrelevant. Respiratory viruses could be divided into two panels according to their positive and negative correlations. One included influenza virus and respiratory syncytial virus, while the other included other common respiratory viruses. It showed negative correlations between the two panels. The asynchronous interference between influenza virus and β human coronaviruses significantly delayed the peak of β human coronaviruses epidemic. The binary property of the viruses indicated transient immunity induced by one kind of virus would play role on subsequent infection, which provides important data for the development of epidemic surveillance strategies.

Influenza A and Respiratory Syncytial Virus Trigger a Cellular Response That Blocks Severe Acute Respiratory Syndrome Virus 2 Infection in the Respiratory Tract

BACKGROUND

Multiple viruses cocirculate and contribute to the burden of respiratory disease. Virus-virus interactions can decrease susceptibility to infection and this interference can have an epidemiological impact. As humans are normally exposed to a community of cocirculating respiratory viruses, experimental coinfection studies are necessary to understand the disease mechanisms of multipathogen systems. We aimed to characterize interactions within the respiratory tract between severe acute respiratory syndrome virus 2 (SARS-CoV-2) and 2 major respiratory viruses: influenza A virus (IAV), and respiratory syncytial virus (RSV).

METHODS

We performed single infections and coinfections with SARS-CoV-2 combined with IAV or RSV in cultures of human bronchial epithelial cells. We combined microscopy with quantification of viral replication in the presence or absence of an innate immune inhibitor to determine changes in virus-induced pathology, virus spread, and virus replication.

RESULTS

SARS-CoV-2 replication is inhibited by both IAV and RSV. This inhibition is dependent on a functional antiviral response and the level of inhibition is proportional to the timing of secondary viral infection.

CONCLUSIONS

Infections with other respiratory viruses might provide transient resistance to SARS-CoV-2. It would therefore be expected that the incidence of coronavirus disease 2019 (COVID-19) may decrease during periods of high circulation of IAV and RSV.

Virus interference in CoViD-19

Virus interference is one of the oldest concepts in immunology. Recent findings indicate that it may depend on the host's anti-viral cellular immune surveillance processes, as well as on sequence-specific gene silencing mechanism guided by double-stranded RNA. Other biological events, unrelated to some degree at least from immune-dependent IFN or RNA-dependent viral interference may be at play as well. We discuss these biological mechanisms in the context of of the Systemic Acute Respiratory Syndrome Corona virus2 (SARS-CoV2) virus responsible for Corona Virus Disease 2019 (CoViD-19).

Evidence for influenza and RSV interaction from 10 years of enhanced surveillance in Nha Trang, Vietnam, a modelling study

Influenza and Respiratory Syncytial Virus (RSV) interact within their host posing the concern for impacts on heterologous viruses following vaccination. We aimed to estimate the population level impact of their interaction. We developed a dynamic age-stratified two-pathogen mathematical model that includes pathogen interaction through competition for infection and enhanced severity of dual infections. We used parallel tempering to fit its parameters to 11 years of enhanced hospital-based surveillance for acute respiratory illnesses (ARI) in children under 5 years old in Nha Trang, Vietnam. The data supported either a 41% (95%CrI: 36–54) reduction in susceptibility following infection and for 10.0 days (95%CrI 7.1–12.8) thereafter, or no change in susceptibility following infection. We estimate that co-infection increased the probability for an infection in <2y old children to be reported 7.2 fold (95%CrI 5.0–11.4); or 16.6 fold (95%CrI 14.5–18.4) in the moderate or low interaction scenarios. Absence of either pathogen was not to the detriment of the other. We find stronger evidence for severity enhancing than for acquisition limiting interaction. In this setting vaccination against either pathogen is unlikely to have a major detrimental effect on the burden of disease caused by the other.

Influenza and Respiratory Syncytial Virus (RSV) cause large burdens of disease. Instead of acting independently, there may be short term cross-protection between them. The evidence of this to date comes from ecological studies which are unable to test the mechanism, or biological studies that are unable to determine the population level impacts of such cross-protection. We create a mathematical model that simulates the circulation of these two viruses, and allows for cross-protection between them. We then fit this model to hospital reported cases of confirmed infection from Nha Trang, Vietnam in order to estimate whether any cross-protection exists in this setting. We show that there are two possibilities—either no interaction or moderate interaction that can result in the observed circulation patterns. However, we further show that co-infection results in an increased reporting rate, presumably due to increased severity.

Prospects on Repurposing a Live Attenuated Vaccine for the Control of Unrelated Infections

Live vaccines use attenuated microbes to acquire immunity against pathogens in a safe way. As live attenuated vaccines (LAVs) still maintain infectivity, the vaccination stimulates diverse immune responses by mimicking natural infection. Induction of pathogen-specific antibodies or cell-mediated cytotoxicity provides means of specific protection, but LAV can also elicit unintended off-target effects, termed non-specific effects. Such mechanisms as short-lived genetic interference and non-specific innate immune response or long-lasting trained immunity and heterologous immunity allow LAVs to develop resistance to subsequent microbial infections. Based on their safety and potential for interference, LAVs may be considered as an alternative for immediate mitigation and control of unexpected pandemic outbreaks before pathogen-specific therapeutic and prophylactic measures are deployed.

Virus-virus interactions of febrile respiratory syndrome among patients in China based on surveillance data from February 2011 to December 2020

BACKGROUND

The burden of acute respiratory infections is still considerable, and virus-virus interactions may affect their epidemics, but previous evidence is inconclusive.

OBJECTIVE

To quantitatively investigate the interactions among respiratory viruses at both the population and individual levels.

METHODS

Cases tested for influenza virus (IV), respiratory syncytial virus (RSV), human parainfluenza virus (PIV), human Adenovirus (AdV), human coronavirus (CoV), human bocavirus (BoV) and rhinoviruses (RV) were collected from the pathogen surveillance for febrile respiratory syndrome (FRS) in China from February 2011 to December 2020. We used spearman's rank correlation coefficients and binary logistic regression models to analyze the interactions between any two of the viruses at the population and individual levels, respectively.

RESULTS

Among 120,237 cases, 4.5% were co-infected with two or more viruses. Correlation coefficients showed 7 virus pairs were positively correlated, namely: IV and RSV, PIV and AdV, PIV and CoV, PIV and BoV, PIV and RV, AdV and BoV, CoV and RV. Regression models showed except for the negative interaction between IV and RV (OR=0.70, 95%CI: 0.61-0.81), all other virus pairs had positive interactions.

CONCLUSION

Most of the respiratory viruses interact positively, while IV and RV interact negatively. This article is protected by copyright. All rights reserved.

Next generation live-attenuated influenza vaccine platforms

INTRODUCTION

Influenza virus is a major cause of seasonal epidemics and intermittent pandemics. Despite the current molecular biology and vaccine development, influenza virus infection is a significant burden. Vaccines are considered an essential countermeasure for effective control and prevention of influenza virus infection. Even though current influenza virus vaccines provide efficient protection against seasonal influenza outbreaks, the efficacy of these vaccines is not suitable due to antigenic changes of the viruses.

AREAS COVERED

This review focuses on different live-attenuated platforms for influenza virus vaccine development and proposes essential considerations for a rational universal influenza virus vaccine design.

EXPERT OPINION

Despite the recent efforts for universal influenza virus vaccines, there is a lack of broadly reactive antibodies' induction that can confer broad and long-lasting protection. Various strategies using live-attenuated influenza virus vaccines (LAIVs) are investigated to induce broadly reactive, durable, and cross-protective immune responses. LAIVs based on NS segment truncation prevent influenza virus infection and have shown to be effective vaccine candidates among other vaccine platforms. Although many approaches have been used for LAIVs generation, there is still a need to focus on the LAIVs development platforms to generate a universal influenza virus vaccine candidate.

The Epidemiological Pattern and Co-infection of Influenza A and B by Surveillance Network From 2009 to 2014 in Anhui Province, China

Influenza-like illness (ILI) is one of the most important public health problems globally, causing an enormous disease burden. Influenza infections are the most common cause of ILI. Bacterial and virus co-infection is common yet the data of co-infection with influenza A and B viruses are scarce. To identify the epidemiological patterns of and co-infection of influenza A and B in Anhui province, China, we analyzed the surveillance data of 5 years from 2009 to 2014 collected by the Chinese National influenzas network. The results showed that the weekly ratio of ILI was 3.96 ± 1.9% (95% CI 3.73–4.2%) in outpatients and the highest affected population was children under 5 years old. The epidemic of influenza viruses was highest during 2009–2010. For the other 4 surveillance years, school-aged people (5–14 years) were the most highly affected population. Influenza B and H3N2 viruses were more prevalent than H1N1pdm09 virus after 2010. In addition, a significant co-circulation of influenza A (H1N1pdm09 and H3N2) and influenza B virus was detected with 0.057% PCR positive rate during 2009–2014 in Eastern China, yet isolated only in pediatric patients. Our data reveals school-aged population would be the main vulnerable population and a distinct seasonality for influenza. In addition, the co-infection of influenza A and B were found in Anhui Province, China. Ongoing surveillance is critical to understand the seasonality variation and make evidence-based vaccination recommendations. Information on the epidemiological patterns and co-infections of influenza A and B can help us to implement different strategies for selecting vaccine formulations and monitoring new emerging influenza strains. In addition, the identification of the susceptible population can help us to develop more precise protection measures.

Treatment of Respiratory Viral Coinfections

With the advent of rapid multiplex PCR, physicians have been able to test for multiple viral pathogens when a patient presents with influenza-like illness. This has led to the discovery that many respiratory infections are caused by more than one virus. Antiviral treatment of viral coinfections can be complex because treatment of one virus will affect the time course of the other virus. Since effective antivirals are only available for some respiratory viruses, careful consideration needs to be given on the effect treating one virus will have on the dynamics of the other virus, which might not have available antiviral treatment. In this study, we use mathematical models of viral coinfections to assess the effect of antiviral treatment on coinfections. We examine the effect of the mechanism of action, relative growth rates of the viruses, and the assumptions underlying the interaction of the viruses. We find that high antiviral efficacy is needed to suppress both infections. If high doses of both antivirals are not achieved, then we run the risk of lengthening the duration of coinfection or even of allowing a suppressed virus to replicate to higher viral titers.

Influenza A(H1N1)pdm09 Virus but Not Respiratory Syncytial Virus Interferes with SARS-CoV-2 Replication during Sequential Infections in Human Nasal Epithelial Cells

The types of interactions between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and other respiratory viruses are not well-characterized due to the low number of co-infection cases described since the onset of the pandemic. We have evaluated the interactions between SARS-CoV-2 (D614G mutant) and influenza A(H1N1)pdm09 or respiratory syncytial virus (RSV) in the nasal human airway epithelium (HAE) infected simultaneously or sequentially (24 h apart) with virus combinations. The replication kinetics of each virus were determined by RT-qPCR at different post-infection times. Our results showed that during simultaneous infection, SARS-CoV-2 interferes with RSV-A2 but not with A(H1N1)pdm09 replication. The prior infection of nasal HAE with SARS-CoV-2 reduces the replication kinetics of both respiratory viruses. SARS-CoV-2 replication is decreased by a prior infection with A(H1N1)pdm09 but not with RSV-A2. The pretreatment of nasal HAE with BX795, a TANK-binding kinase 1 inhibitor, partially alleviates the reduced replication of SARS-CoV-2 or influenza A(H1N1)pdm09 during sequential infection with both virus combinations. Thus, a prior infection of nasal HAE with SARS-CoV-2 interferes with the replication kinetics of A(H1N1)pdm09 and RSV-A2, whereas only A(H1N1)pdm09 reduces the subsequent infection with SARS-CoV-2. The mechanism involved in the viral interference between SARS-CoV-2 and A(H1N1)pdm09 is mediated by the production of interferon.

Viral Interference between Respiratory Viruses

Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract and lead to virus‒virus interactions. Infection by a first virus could enhance or reduce infection and replication of a second virus, resulting in positive (additive or synergistic) or negative (antagonistic) interaction. The concept of viral interference has been demonstrated at the cellular, host, and population levels. The mechanisms involved in viral interference have been evaluated in differentiated airway epithelial cells and in animal models susceptible to the respiratory viruses of interest. A likely mechanism is the interferon response that could confer a temporary nonspecific immunity to the host. During the coronavirus disease pandemic, nonpharmacologic interventions have prevented the circulation of most respiratory viruses. Once the sanitary restrictions are lifted, circulation of seasonal respiratory viruses is expected to resume and will offer the opportunity to study their interactions, notably with severe acute respiratory syndrome coronavirus 2.

Time-Dependent Proinflammatory Responses Shape Virus Interference during Coinfections of Influenza A Virus and Influenza D Virus

Both influenza A virus (IAV) and influenza D virus (IDV) are enzootic in pigs. IAV causes approximately 100% morbidity with low mortality, whereas IDV leads to only mild respiratory diseases in pigs. In this study, we performed a series of coinfection experiments in vitro and in vivo to understand how IAV and IDV interact and cause pathogenesis during coinfection. The results showed that IAV inhibited IDV replication when infecting swine tracheal epithelial cells (STECs) with IAV 24 or 48 h prior to IDV inoculation and that IDV suppressed IAV replication when IDV preceded IAV inoculation by 48 h. Virus interference was not identified during simultaneous IAV/IDV infections or with 6 h between the two viral infections, regardless of their order. The interference pattern at 24 and 48 h correlated with proinflammatory responses induced by the first infection, which, for IDV, was slower than for IAV by about 24 h. The viruses did not interfere with each other if both infected the cells before proinflammatory responses were induced. Coinfection in pigs further demonstrated that IAV interfered with both viral shedding and virus replication of IDV, especially in the upper respiratory tract. Clinically, coinfection of IDV and IAV did not show significant enhancement of disease pathogenesis, compared with the pigs infected with IAV alone. In summary, this study suggests that interference during coinfection of IAV and IDV is primarily due to the proinflammatory response; therefore, it is dependent on the time between infections and the order of infection. This study facilitates our understanding of virus epidemiology and pathogenesis associated with IAV and IDV coinfection.

The pitfalls of inferring virus-virus interactions from co-detection prevalence data: application to influenza and SARS-CoV-2

There is growing experimental evidence that many respiratory viruses-including influenza and SARS-CoV-2-can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio-defined as the ratio of co-infection prevalence to the product of single-infection prevalences-should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two emerging or seasonal respiratory viruses. By focusing on the pair influenza-SARS-CoV-2, we first demonstrate that the prevalence ratio systematically underestimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection-such as a high reproduction number or a short infectious period-that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that ecological or epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.

Quo Vadis Influenza?

The number of influenza virus detections declined tremendously after the emergence and worldwide spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2); an effect most likely caused by non-pharmaceutical interventions to slow the spread of SARS-CoV-2. Recent data suggest that influenza virus detection has slightly increased in parts of the world, perhaps owing to the relaxation of social distancing measures.

SARS-CoV-2 coinfection with additional respiratory virus does not predict severe disease: a retrospective cohort study

Background

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) claimed over 4 million lives by July 2021 and continues to pose a serious public health threat.

Objectives

Our retrospective study utilized respiratory pathogen panel (RPP) results in patients with SARS-CoV-2 to determine if coinfection (i.e. SARS-CoV-2 positivity with an additional respiratory virus) was associated with more severe presentation and outcomes.

Methods

All patients with negative influenza/respiratory syncytial virus testing who underwent RPP testing within 7 days of a positive SARS-CoV-2 test at a large, academic medical centre in New York were examined. Patients positive for SARS-CoV-2 with a negative RPP were compared with patients positive for SARS-CoV-2 and positive for a virus by RPP in terms of biomarkers, oxygen requirements and severe COVID-19 outcome, as defined by mechanical ventilation or death within 30 days.

Results

Of the 306 SARS-CoV-2-positive patients with RPP testing, 14 (4.6%) were positive for a non-influenza virus (coinfected). Compared with the coinfected group, patients positive for SARS-CoV-2 with a negative RPP had higher inflammatory markers and were significantly more likely to be admitted (P = 0.01). Severe COVID-19 outcome occurred in 111 (36.3%) patients in the SARS-CoV-2-only group and 3 (21.4%) patients in the coinfected group (P = 0.24).

Conclusions

Patients infected with SARS-CoV-2 along with a non-influenza respiratory virus had less severe disease on presentation and were more likely to be admitted—but did not have more severe outcomes—than those infected with SARS-CoV-2 alone.

Which influenza viruses will emerge following the SARS-CoV-2 pandemic?

The world has experienced five pandemics in just over one hundred years, four due to influenza and one due to coronavirus (SARS-CoV-2). In each case of pandemic influenza, the pandemic influenza strain has replaced the previous seasonal influenza virus. Notably, throughout the SARS-CoV-2 pandemic, there has been a 99% reduction in influenza isolation globally. It is anticipated that influenza will re-emerge following the SARS-CoV-2 pandemic and circulate again. The potential for which influenza viruses will emerge is examined.

COVID-19 virtual patient cohort suggests immune mechanisms driving disease outcomes

To understand the diversity of immune responses to SARS-CoV-2 and distinguish features that predispose individuals to severe COVID-19, we developed a mechanistic, within-host mathematical model and virtual patient cohort. Our results suggest that virtual patients with low production rates of infected cell derived IFN subsequently experienced highly inflammatory disease phenotypes, compared to those with early and robust IFN responses. In these in silico patients, the maximum concentration of IL-6 was also a major predictor of CD8+ T cell depletion. Our analyses predicted that individuals with severe COVID-19 also have accelerated monocyte-to-macrophage differentiation mediated by increased IL-6 and reduced type I IFN signalling. Together, these findings suggest biomarkers driving the development of severe COVID-19 and support early interventions aimed at reducing inflammation.

Rhinovirus Reduces the Severity of Subsequent Respiratory Viral Infections by Interferon-Dependent and -Independent Mechanisms

Coinfection by heterologous viruses in the respiratory tract is common and can alter disease severity compared to infection by individual virus strains. We previously found that inoculation of mice with rhinovirus (RV) 2 days before inoculation with a lethal dose of influenza A virus [A/Puerto Rico/8/34 (H1N1) (PR8)] provides complete protection against mortality. Here, we extended that finding to a second lethal respiratory virus, pneumonia virus of mice (PVM), and analyzed potential mechanisms of RV-induced protection. RV completely prevented mortality and weight loss associated with PVM infection. Major changes in host gene expression upon PVM infection were delayed compared to PR8. RV induced earlier recruitment of inflammatory cells, which were reduced at later times in RV-inoculated mice. Findings common to both virus pairs included the upregulated expression of mucin-associated genes and dampening of inflammation-related genes in mice that were inoculated with RV before lethal virus infection. However, type I interferon (IFN) signaling was required for RV-mediated protection against PR8 but not PVM. IFN signaling had minor effects on PR8 replication and contributed to controlling neutrophilic inflammation and hemorrhagic lung pathology in RV/PR8-infected mice. These findings, combined with differences in virus replication levels and disease severity, suggest that the suppression of inflammation in RV/PVM-infected mice may be due to early, IFN-independent suppression of viral replication, while that in RV/PR8-infected mice may be due to IFN-dependent modulation of immune responses. Thus, a mild upper respiratory viral infection can reduce the severity of a subsequent severe viral infection in the lungs through virus-dependent mechanisms.

IMPORTANCE Respiratory viruses from diverse families cocirculate in human populations and are frequently detected within the same host. Although clinical studies suggest that infection by multiple different respiratory viruses may alter disease severity, animal models in which we can control the doses, timing, and strains of coinfecting viruses are critical to understanding how coinfection affects disease severity. Here, we compared gene expression and immune cell recruitment between two pairs of viruses (RV/PR8 and RV/PVM) inoculated sequentially in mice, both of which result in reduced severity compared to lethal infection by PR8 or PVM alone. Reduced disease severity was associated with suppression of inflammatory responses in the lungs. However, differences in disease kinetics and host and viral gene expression suggest that protection by coinfection with RV may be due to distinct molecular mechanisms. Indeed, we found that antiviral cytokine signaling was required for RV-mediated protection against lethal infection by PR8 but not PVM.

Anomalous influenza seasonality in the United States and the emergence of novel influenza B viruses

The 2019/2020 influenza season in the United States began earlier than any season since the 2009 H1N1 pandemic, with an increase in influenza-like illnesses observed as early as August. Also noteworthy was the numerical domination of influenza B cases early in this influenza season, in contrast to their typically later peak in the past. Here, we dissect the 2019/2020 influenza season not only with regard to its unusually early activity, but also with regard to the relative dynamics of type A and type B cases. We propose that the recent expansion of a novel influenza B/Victoria clade may be associated with this shift in the composition and kinetics of the influenza season in the United States. We use epidemiological transmission models to explore whether changes in the effective reproduction number or short-term cross-immunity between these viruses can explain the dynamics of influenza A and B seasonality. We find support for an increase in the effective reproduction number of influenza B, rather than support for cross-type immunity-driven dynamics. Our findings have clear implications for optimal vaccination strategies.

Assessing the impact of acute respiratory illnesses on the risk of subsequent respiratory illness

BACKGROUND

Whether acute respiratory illnesses (ARIs), often associated with virus detection, are associated with lower risk for subsequent ARI remains unclear. We assessed the association between symptomatic ARI and subsequent ARI in young children.

METHODS

In a prospective cohort of Peruvian children <3 years, we examined the impact of index ARI on subsequent ARI risk. Index ARI were matched with ≤3 asymptomatic observations and followed over 28 days. We compared risk of subsequent ARI between groups using conditional logistic regression adjusting for several covariates, accounting for repeat observations from individual children.

RESULTS

Among 983 index ARI, 339 (34%) had an ARI event during follow-up, compared with 876/2826 (31%) matched asymptomatic observations. We found no significant association of index ARI and subsequent ARI risk during follow-up overall (aOR 1.10, 95% CI 0.98, 1.23) or when limited to index ARI with respiratory viruses detected (aOR 1.03, 95% CI 0.86, 1.24). Similarly, when the outcome was limited to ARI in which viruses were detected, no significant association was seen (aOR 1.05, 95% CI 0.87, 1.27).

DISCUSSION

ARIs were not associated with short-term protection against subsequent ARI in these children. Additional longitudinal studies are needed to understand drivers of recurrent ARI in young children.

Mini Review: Virus Interference: History, Types and Occurrence in Crustaceans

Virus interference is a phenomenon in which two viruses interact within a host, affecting the outcome of infection of at least one of such viruses. The effect of this event was first observed in the XVIII century and it was first recorded even before virology was recognized as a distinct science from microbiology. Studies on virus interference were mostly done in the decades between 1930 and 1960 in viruses infecting bacteria and different vertebrates. The systems included in vivo experiments and later, more refined assays were done using tissue and cell cultures. Many viruses involved in interference are pathogenic to humans or to economically important animals. Thus the phenomenon may be relevant to medicine and to animal production due to the possibility to use it as alternative to chemical therapies against virus infections to reduce the severity of disease/mortality caused by a superinfecting virus. Virus interference is defined as the host resistance to a superinfection caused by a pathogenic virus causing obvious signs of disease and/or mortality due to the action of an interfering virus abrogating the replication of the former virus. Different degrees of inhibition of the superinfecting virus can occur. Due to the emergence of novel pathogenic viruses in recent years, virus interference has recently been revisited using different pathogens and hosts, including commercially important farmed aquatic species. Here, some highly pathogenic viruses affecting farmed crustaceans can be affected by interference with other viruses. This review presents data on the history of virus interference in hosts including bacteria and animals, with emphasis on the known cases of virus interference in crustacean hosts. Life Science Identifiers (LSIDs) Escherichia coli [(Migula 1895) Castellani & Chalmers 1919] Aedes albopictus (Skuse 1894) Liocarcinus depurator (Linnaeus 1758): urn:lsid:marinespecies.org:taxname:107387 Penaeus duorarum (Burkenroad 1939): urn:lsid:marinespecies.org:taxname:158334 Carcinus maenas (Linnaeus 1758): urn:lsid:marinespecies.org:taxname:107381 Macrobrachium rosenbergii (De Man 1879): urn:lsid:marinespecies.org:taxname:220137 Penaeus vannamei (Boone 1931): urn:lsid:zoobank.org:pub:C30A0A50-E309-4E24-851D-01CF94D97F23 Penaeus monodon (Fabricius 1798): urn:lsid:zoobank.org:act:3DD50D8B-01C2-48A7-B80D-9D9DD2E6F7AD Penaeus stylirostris (Stimpson 1874): urn:lsid:marinespecies.org:taxname:584982.

Therapeutic Exploitation of Viral Interference

Viral interference, originally, referred to a state of temporary immunity, is a state whereby infection with a virus limits replication or production of a second infecting virus. However, replication of a second virus could also be dominant over the first virus. In fact, dominance can alternate between the two viruses. Expression of type I interferon genes is many times upregulated in infected epithelial cells. Since the interferon system can control most, if not all, virus infections in the absence of adaptive immunity, it was proposed that viral induction of a nonspecific localized temporary state of immunity may provide a strategy to control viral infections. Clinical observations also support such a theory, which gave credence to the development of superinfection therapy (SIT). SIT is an innovative therapeutic approach where a non-pathogenic virus is used to infect patients harboring a pathogenic virus. For the functional cure of persistent viral infections and for the development of broad- spectrum antivirals against emerging viruses a paradigm shift was recently proposed. Instead of the virus, the therapy should be directed at the host. Such a host-directed-therapy (HDT) strategy could be the activation of endogenous innate immune response via toll-like receptors (TLRs). Superinfection therapy is such a host-directed-therapy, which has been validated in patients infected with two completely different viruses, the hepatitis B (DNA), and hepatitis C (RNA) viruses. SIT exerts post-infection interference via the constant presence of an attenuated non-pathogenic avian double- stranded (ds) RNA viral vector which boosts the endogenous innate (IFN) response. SIT could, therefore, be developed into a biological platform for a new "one drug, multiple bugs" broad-spectrum antiviral treatment approach.

Competition between RSV and influenza: Limits of modelling inference from surveillance data

Respiratory Syncytial Virus (RSV) and Influenza cause a large burden of disease. Evidence of their interaction via temporary cross-protection implies that prevention of one could inadvertently lead to an increase in the burden of the other. However, evidence for the public health impact of such interaction is sparse and largely derives from ecological analyses of peak shifts in surveillance data. To test the robustness of estimates of interaction parameters between RSV and Influenza from surveillance data we conducted a simulation and back-inference study. We developed a two-pathogen interaction model, parameterised to simulate RSV and Influenza epidemiology in the UK. Using the infection model in combination with a surveillance-like stochastic observation process we generated a range of possible RSV and Influenza trajectories and then used Markov Chain Monte Carlo (MCMC) methods to back-infer parameters including those describing competition. We find that in most scenarios both the strength and duration of RSV and Influenza interaction could be estimated from the simulated surveillance data reasonably well. However, the robustness of inference declined towards the extremes of the plausible parameter ranges, with misleading results. It was for instance not possible to tell the difference between low/moderate interaction and no interaction. In conclusion, our results illustrate that in a plausible parameter range, the strength of RSV and Influenza interaction can be estimated from a single season of high-quality surveillance data but also highlights the importance to test parameter identifiability a priori in such situations.

Would the interference phenomenon be applied as an alternative option for prophylaxis against COVID-19?

The coronavirus disease 2019 (COVID-19) is an emerged infectious disease characterized by a severe pneumonia leading to death in some cases. Currently, no licensed vaccines, drugs, or biologics have been confirmed to be absolutely effective in prophylaxis or treatment of this novel infection. Therefore, the treatment of this highly contagious disease remains a global concern and emergency. The viral interference is a competition phenomenon by which a primary virus infecting a cell prohibits the infection of the same cell by another (secondary) virus. The phenomenon has recently been indicated to be exploited for antiviral strategies. This strategy, particularly when there is no efficient drug against a viral infection, is of high importance. Some researchers have studied the application of the phenomenon among different viruses. In this paper, I discussed the possibility of the application of interference phenomenon in prophylaxis of the disease.

Host-shift as the cause of emerging infectious diseases: Experimental approaches using Drosophila-virus interactions

Host shifts, when a cross-species transmission of a pathogen can lead to successful infections, are the main cause of emerging infectious diseases, such as COVID-19. A complex challenge faced by the scientific community is to address the factors that determine whether the cross-species transmissions will result in spillover or sustained onwards infections. Here we review recent literature and present a perspective on current approaches we are using to understand the mechanisms underlying host shifts. We highlight the usefulness of the interactions between Drosophila species and viruses as an ideal study model. Additionally, we discuss how cross-infection experiments - when pathogens from a natural reservoir are intentionally injected in novel host species- can test the effect cross-species transmissions may have on the fitness of virus and host, and how the host phylogeny may influence this response. We also discuss experiments evaluating how cooccurrence with other viruses or the presence of the endosymbiont bacteria Wolbachia may affect the performance of new viruses in a novel host. Finally, we discuss the need of surveys of virus diversity in natural populations using next-generation sequencing technologies. In the long term, these approaches can contribute to a better understanding of the basic biology of host shifts.

Earliest infections predict the age distribution of seasonal influenza A cases

Seasonal variation in the age distribution of influenza A cases suggests that factors other than age shape susceptibility to medically attended infection. We ask whether these differences can be partly explained by protection conferred by childhood influenza infection, which has lasting impacts on immune responses to influenza and protection against new influenza A subtypes (phenomena known as original antigenic sin and immune imprinting). Fitting a statistical model to data from studies of influenza vaccine effectiveness (VE), we find that primary infection appears to reduce the risk of medically attended infection with that subtype throughout life. This effect is stronger for H1N1 compared to H3N2. Additionally, we find evidence that VE varies with both age and birth year, suggesting that VE is sensitive to early exposures. Our findings may improve estimates of age-specific risk and VE in similarly vaccinated populations and thus improve forecasting and vaccination strategies to combat seasonal influenza.

Comparative Seasonal Respiratory Virus Epidemic Timing in Utah

Previous studies have found evidence of viral interference between seasonal respiratory viruses. Using laboratory-confirmed data from a Utah-based healthcare provider, Intermountain Health Care, we analyzed the time-specific patterns of respiratory syncytial virus (RSV), influenza A, influenza B, human metapneumovirus, rhinovirus, and enterovirus circulation from 2004 to 2018, using descriptive methods and wavelet analysis (n = 89,462) on a local level. The results showed that RSV virus dynamics in Utah were the most consistent of any of the viruses studied, and that the other seasonal viruses were generally in synchrony with RSV, except for enterovirus (which mostly occurs late summer to early fall) and influenza A and B during pandemic years.

Evidence for Cross-Protection Against Subsequent Febrile Respiratory Illness Episodes From Prior Infections by Different Viruses Among Singapore Military Recruits 2009-2014

Background

Few studies have evaluated the relative cross-protection conferred by infection with different groups of viruses through studies of sequential infections in humans. We investigated the presence of short-lived relative cross-protection conferred by specific prior viral infections against subsequent febrile respiratory illness (FRI).

Methods

Men enlisted in basic military training between December 2009 and December 2014 were recruited, with the first FRI as the study entry point. ResPlex II assays and real-time polymerase chain reaction assays were used to detect viral pathogens in nasal wash samples, and survival analyses were performed to determine whether infection with particular viruses conferred short-lived relative cross-protection against FRI.

Results

Prior infection with adenovirus (hazard ratio [HR], 0.24; 95% confidence interval [CI], .14–.44) or influenza virus (HR, 0.52; 95% CI, .38–.73) conferred relative protection against subsequent FRI episode. Results were statistically significant even after adjustment for the interval between enlistment and FRI (P < .001). Adenovirus-positive participants with FRI episodes tended to be protected against subsequent infection with adenovirus, coronavirus, enterovirus/rhinovirus, and influenza virus (P = .062–.093), while men with influenza virus–positive FRI episodes tended be protected against subsequent infection with adenovirus (P = .044) and influenza virus (P = .081).

Conclusion

Prior adenovirus or influenza virus infection conferred cross-protection against subsequent FRI episodes relative to prior infection due to other circulating viruses.

Genetic variations on 31 and 450 residues of influenza A nucleoprotein affect viral replication and translation

Background

Influenza A viruses cause epidemics/severe pandemics that pose a great global health threat. Among eight viral RNA segments, the multiple functions of nucleoprotein (NP) play important roles in viral replication and transcription.

Methods

To understand how NP contributes to the virus evolution, we analyzed the NP gene of H3N2 viruses in Taiwan and 14,220 NP sequences collected from Influenza Research Database. The identified genetic variations were further analyzed by mini-genome assay, virus growth assay, viral RNA and protein expression as well as ferret model to analyze their impacts on viral replication properties.

Results

The NP genetic analysis by Taiwan and global sequences showed similar evolution pattern that the NP backbones changed through time accompanied with specific residue substitutions from 1999 to 2018. Other than the conserved residues, fifteen sporadic substitutions were observed in which the 31R, 377G and 450S showed higher frequency. We found 31R and 450S decreased polymerase activity while the dominant residues (31 K and 450G) had higher activity. The 31 K and 450G showed better viral translation and replication in vitro and in vivo.

Conclusions

These findings indicated variations identified in evolution have roles in modulating viral replication in vitro and in vivo. This study demonstrates that the interaction between variations of NP during virus evolution deserves future attention.

Association Between Preceding Viral Respiratory Infection and Subsequent Respiratory Illnesses Among Children: A Prospective Cohort Study in the Philippines

Background

Acute respiratory infection (ARI) is of great concern in public health. It remains unclear whether viral infections can affect the host’s susceptibility to subsequent ARIs.

Methods

A prospective cohort study on ARIs of children below 5 years old was conducted in the Philippines from 2014 to 2016. The respiratory symptoms were recorded daily, and nasopharyngeal swabs were collected at both household and health facilities. The specimens were tested for respiratory viruses. We then determined whether viral etiology was associated with the severity of the present ARI and whether previous viral infections was associated with subsequent ARIs.

Results

A total of 3851 children and 16337 ARI episodes were enrolled and recorded, respectively. Samples were collected from 24% of all ARI episodes; collection rate at the healthcare facilities was 95%. Enterovirus D68, rhinovirus species C, and respiratory syncytial virus were significantly associated with severe ARIs. The risk for subsequent ARIs was significantly enhanced after infections with adenovirus, influenza A virus, parainfluenza virus type 4, and rhinovirus species C.

Conclusions

This study revealed that viral etiology plays a significant role in the severity of the present ARI and that viral infection affects the host’s susceptibility to subsequent ARIs.

The epidemiological signature of influenza B virus and its B/Victoria and B/Yamagata lineages in the 21st century

We describe the epidemiological characteristics, pattern of circulation, and geographical distribution of influenza B viruses and its lineages using data from the Global Influenza B Study. We included over 1.8 million influenza cases occurred in thirty-one countries during 2000–2018. We calculated the proportion of cases caused by influenza B and its lineages; determined the timing of influenza A and B epidemics; compared the age distribution of B/Victoria and B/Yamagata cases; and evaluated the frequency of lineage-level mismatch for the trivalent vaccine. The median proportion of influenza cases caused by influenza B virus was 23.4%, with a tendency (borderline statistical significance, p = 0.060) to be higher in tropical vs. temperate countries. Influenza B was the dominant virus type in about one every seven seasons. In temperate countries, influenza B epidemics occurred on average three weeks later than influenza A epidemics; no consistent pattern emerged in the tropics. The two B lineages caused a comparable proportion of influenza B cases globally, however the B/Yamagata was more frequent in temperate countries, and the B/Victoria in the tropics (p = 0.048). B/Yamagata patients were significantly older than B/Victoria patients in almost all countries. A lineage-level vaccine mismatch was observed in over 40% of seasons in temperate countries and in 30% of seasons in the tropics. The type B virus caused a substantial proportion of influenza infections globally in the 21^st century, and its two virus lineages differed in terms of age and geographical distribution of patients. These findings will help inform health policy decisions aiming to reduce disease burden associated with seasonal influenza.

Investigating Viral Interference Between Influenza A Virus and Human Respiratory Syncytial Virus in a Ferret Model of Infection

Epidemiological studies have observed that the seasonal peak incidence of influenza virus infection is sometimes separate from the peak incidence of human respiratory syncytial virus (hRSV) infection, with the peak incidence of hRSV infection delayed. This is proposed to be due to viral interference, whereby infection with one virus prevents or delays infection with a different virus. We investigated viral interference between hRSV and 2009 pandemic influenza A(H1N1) virus (A[H1N1]pdm09) in the ferret model. Infection with A(H1N1)pdm09 prevented subsequent infection with hRSV. Infection with hRSV reduced morbidity attributed to infection with A(H1N1)pdm09 but not infection, even when an increased inoculum dose of hRSV was used. Notably, infection with A(H1N1)pdm09 induced higher levels of proinflammatory cytokines, chemokines, and immune mediators in the ferret than hRSV. Minimal cross-reactive serological responses or interferon γ–expressing cells were induced by either virus ≥14 days after infection. These data indicate that antigen-independent mechanisms may drive viral interference between unrelated respiratory viruses that can limit subsequent infection or disease.

Novel Approaches for The Development of Live Attenuated Influenza Vaccines

Influenza virus still represents a considerable threat to global public health, despite the advances in the development and wide use of influenza vaccines. Vaccination with traditional inactivate influenza vaccines (IIV) or live-attenuated influenza vaccines (LAIV) remains the main strategy in the control of annual seasonal epidemics, but it does not offer protection against new influenza viruses with pandemic potential, those that have shifted. Moreover, the continual antigenic drift of seasonal circulating influenza viruses, causing an antigenic mismatch that requires yearly reformulation of seasonal influenza vaccines, seriously compromises vaccine efficacy. Therefore, the quick optimization of vaccine production for seasonal influenza and the development of new vaccine approaches for pandemic viruses is still a challenge for the prevention of influenza infections. Moreover, recent reports have questioned the effectiveness of the current LAIV because of limited protection, mainly against the influenza A virus (IAV) component of the vaccine. Although the reasons for the poor protection efficacy of the LAIV have not yet been elucidated, researchers are encouraged to develop new vaccination approaches that overcome the limitations that are associated with the current LAIV. The discovery and implementation of plasmid-based reverse genetics has been a key advance in the rapid generation of recombinant attenuated influenza viruses that can be used for the development of new and most effective LAIV. In this review, we provide an update regarding the progress that has been made during the last five years in the development of new LAIV and the innovative ways that are being explored as alternatives to the currently licensed LAIV. The safety, immunogenicity, and protection efficacy profile of these new LAIVs reveal their possible implementation in combating influenza infections. However, efforts by vaccine companies and government agencies will be needed for controlled testing and approving, respectively, these new vaccine methodologies for the control of influenza infections.

Effect of strain-specific maternally-derived antibodies on influenza A virus infection dynamics in nursery pigs

Reducing the number of influenza A virus (IAV) infected pigs at weaning is critical to minimize IAV spread to other farms. Sow vaccination is a common measure to reduce influenza levels at weaning. However, the impact of maternally-derived antibodies on IAV infection dynamics in growing pigs is poorly understood. We evaluated the effect of maternally-derived antibodies at weaning on IAV prevalence at weaning, time of influenza infection, number of weeks that pigs tested IAV positive, and estimated quantity of IAV in nursery pigs. We evaluated 301 pigs within 10 cohorts for their influenza serological (seroprevalence estimated by hemagglutination inhibition (HI) test) and virological (prevalence) status. Nasal swabs were collected weekly and pigs were bled 3 times throughout the nursery period. There was significant variability in influenza seroprevalence, HI titers and influenza prevalence after weaning. Increase in influenza seroprevalence at weaning was associated with low influenza prevalence at weaning and delayed time to IAV infection throughout the nursery. Piglets with IAV HI titers of 40 or higher at weaning were also less likely to test IAV positive at weaning, took longer to become infected, tested IAV RT-PCR positive for fewer weeks, and had higher IAV RT-PCR cycle threshold values compared to piglets with HI titers less than 40. Our findings suggest that sow vaccination or infection status that results in high levels of IAV strain-specific maternally-derived antibodies may help to reduce IAV circulation in both suckling and nursery pigs.