Influenza Outbreaks Research Articles

Evolutionary dynamics of the clade 2.3.4.4B H5N8 high-pathogenicity avian influenza outbreaks in coastal seabirds and other species in southern Africa from 2017 to 2019.

From late 2017 to early 2018, clade 2.3.4.4B H5N8 highly pathogenic avian influenza (HPAI) viruses caused mass die-offs of thousands of coastal seabirds along the southern coastline of South Africa. Terns (Laridae) especially were affected, but high mortalities in critically endangered and threatened species like African Penguins (Spheniscus demersus) caused international concern and, exactly a year later, the disease recurred at a key African Penguin breeding site on Halifax Island, Namibia. Twenty-five clade 2.3.4.4B H5N8 HPAI viruses from coastal seabirds and a Jackal Buzzard (Buteo rufofuscus) were isolated and/or sequenced in this study. Phylogenetic analyses of the full viral genomes and time to the most recent common ancestor (tMRCA) analyses of the HA, NA, PB1 and PA genes determined that the South African coastal seabird viruses formed a monophyletic group nested within the South African genotype 4 viruses. This sub-lineage likely originated from a single introduction by terrestrial birds around October 2017. Only the HA and NA sequences were available for the Namibian penguin viruses, but the phylogenetic data confirmed that the South African coastal seabird viruses from 2017 to 2018 were the source and the most closely related South African virus was found in a gull. tMRCA analyses furthermore determined that the progenitors of the five genotypes implicated in the earlier 2017 South African outbreaks in wild birds and poultry were dated at between 2 and 4months prior to the index cases. tMRCA and phylogenetic data also showed that the novel genotype 6 virus introduced to South Africa in 2018, and later also detected in Nigeria and Poland in 2019, most likely arose in late 2017 in West, Central or East Africa. We propose that it continued to circulate there, and that an unidentified reservoir was the source of both the South African outbreaks in early 2018 and in Nigeria in mid-2019.

Phylogenetic Inference of the 2022 Highly Pathogenic H7N3 Avian Influenza Outbreak in Northern Mexico.

The Mexican lineage H7N3 highly pathogenic avian influenza virus (HPAIV) has persisted in Mexican poultry since its first isolation in 2012. To date, the detection of this virus has gradually expanded from the initial one state to 18 states in Mexico. Despite the HPAIV H7N3 outbreak occurring yearly, the transmission pathways have never been studied, disallowing the establishment of effective control measures. We used a phylogenetic approach to unravel the transmission pathways of 2022 H7N3 HPAIVs in the new outbreak areas in Northern Mexico. We present genetic data of H7N3 viruses produced from 18 poultry farms infected in the spring of 2022. Our results indicate that the virus responsible for the current outbreak in Northern Mexico evolved from the Mexican lineage H7N3 HPAIV discovered in 2012. In the current outbreak, we identified five clusters of infection with four noticeably different genetic backgrounds. It is a cluster IV-like virus that was transmitted into one northern state causing an outbreak, then spreading to another neighboring northern state, possibly via a human-mediated mechanical transmission mechanism. The long-distance transmission event highlights the necessity for the more rigorous enforcement of biosafety measures in outbreaks. Additionally, we examined the evolutionary processes shaping the viral genetic and antigenic diversities. It is imperative to enhance active surveillance to include birds, the environment, and humans to detect HPAI in domestic poultry at an earlier point and eliminate it.

Effectiveness estimates for enhanced trivalent influenza vaccines in an aged care summer outbreak

An influenza outbreak occurred during summer (February 2019) in an aged-care facility in Sydney, Australia. Residents had not received the annual 2019 influenza vaccine while 76.7% had received 2018 influenza vaccines about 9 months prior. Overall, 2018 influenza vaccine effectiveness during this outbreak was high (93.6%). The effectiveness of the high-dose trivalent vaccine (HD-TIV) and adjuvanted trivalent (a-TIV) vaccine were 89.8% (95% confidence interval: 18.8%-98.7%) and 72.5% (95% confidence interval: −106.7%-96.3%) respectively. The differences in effectiveness between HD-TIV, a-TIV and SD-QIV, during the summer outbreak were not significant.

Comprehensive evaluation of an one pot quadruplex RT-qPCR assay for the simultaneously subtyping influenza A virus into H1, H3, N1 and N2

In the current study, an one pot quadruplex RT-qPCR assay was established and comprehensively evaluated. The assay's limit of detection could reach as low as 101 copies/reaction, with good repeatability profile and no cross-reaction with other respiratory pathogens. During clinical evaluation both by blinded samples and real clinical samples, the assay exhibited a 100% coincidence rate with individual commercial RT-qPCR assays. To the best of our knowledge, this is the first report on the simultaneous subtyping influenza A virus into H1, H3, N1, and N2 by one pot quadruplex RT-qPCR assay, which could improve the preparedness for future influenza outbreaks.

Efficient algorithms for real-time syndromic surveillance

ObjectiveOutbreaks of influenza-like diseases often cause spikes in the demand for hospital beds. Early detection of these outbreaks can enable improved management of hospital resources. The objective of this study was to test whether surveillance algorithms designed to be responsive to a wide range of anomalous decreases in the time between emergency department (ED) presentations with influenza-like illnesses provide efficient early detection of these outbreaks. MethodsOur study used data on ED presentations to major public hospitals in Queensland, Australia across 2017–2020. We developed surveillance algorithms for each hospital that flag potential outbreaks when the average time between successive ED presentations with influenza-like illnesses becomes anomalously small. We designed one set of algorithms to be responsive to a wide range of anomalous decreases in the time between presentations. These algorithms concurrently monitor three exponentially weighted moving averages (EWMAs) of the time between presentations and flag an outbreak when at least one EWMA falls below its control limit. We designed another set of algorithms to be highly responsive to narrower ranges of anomalous decreases in the time between presentations. These algorithms monitor one EWMA of the time between presentations and flag an outbreak when the EWMA falls below its control limit. Our algorithms use dynamic control limits to reflect that the average time between presentations depends on the time of year, time of day, and day of the week. ResultsWe compared the performance of the algorithms in detecting the start of two epidemic events at the hospital-level: the 2019 seasonal influenza outbreak and the early-2020 COVID-19 outbreak. The algorithm that concurrently monitors three EWMAs provided significantly earlier detection of these outbreaks than the algorithms that monitor one EWMA. ConclusionSurveillance algorithms designed to be responsive to a wide range of anomalous decreases in the time between ED presentations are highly efficient at detecting outbreaks of influenza-like diseases at the hospital level.

Serological and molecular investigation of canine influenza virus in Plateau State, Nigeria

Canine influenza is a highly contagious respiratory infection of dogs caused by the Influenza A Virus (IAV), characterized by cough, sneeze, nasal secretions, and inappetence. Infections can be mild, severe or fatal. Aquatic birds constitute a natural reservoir for IAV, which is transmitted to terrestrial birds, including poultry. IAV has also emerged in other mammalian species, including humans, swine, horses, and dogs. IAV epidemics in dogs are a recent development. Commonly detected Canine Influenza Virus (CIV) strains are A/H3N2 and A/H3N8 from avian and equine influenza, respectively. Nigeria’s agro-ecology witnessed widespread circulation of avian influenza since 2006, and recent outbreaks of equine influenza in 2018/2019 raise the possibility of inter-species transmission to dogs. To investigate canine Influenza in Plateau State, we collected 113 nasal swabs and 270 sera samples from dogs in clinics, live dog markets, and during dog vaccination campaigns. After extracting nucleic acid with the Qiagen kit, RT-PCR analysed swabs for the Influenza A matrix gene. Sera samples were screened by Enzyme-Linked Immunosorbent Assay before subtyping a cross-section for H3 antibody by Hemagglutination Inhibition. No matrix gene was amplified from extracted nucleic acid from the nasal swabs. Though few sera were reactive to influenza A nucleoprotein, none was positive for influenza A/H3. The H3N8 strain of equine influenza virus first caused an epidemic in dogs in 1999 in the United States. Subsequently, avian-origin H3N2 CIV emerged in dogs in China and South Korea in 2005. Past CIV epidemics arose from a single cross-species transmission of H3N8 subtype from a mammalian intermediate host and the H3N2 subtype from an avian reservoir. Even though this limited investigation did not detect CIV in Plateau State, the potential remains because of the persistent circulation of avian, swine, and equine Influenza in Nigeria, which requires more extensive virological and serological surveillance.

Reemerging Influenza Virus Infections during the Dominance of the Omicron SARS-CoV-2 Variant in Mexico.

The burden of influenza in Mexico has been high. We aimed to characterize its epidemiological patterns before and during the coronavirus disease 2019 (COVID-19) pandemic. A retrospective cohort study was conducted and 5652 PCR-confirmed cases of influenza (October 2019–April 2022) were analyzed. The highest incidence (144 per million) was observed in December 2019 and rapidly decreased right before the start of the pandemic (February 2020). No cases were documented in the 2020–2021 season, and infections reemerged at a low level (8 per million) in December 2021. The case-fatality rates were around 5% in both seasons (p = 0.591). The dominant strains were AH1N1 and AH3N2 in the 2019–2020 and 2021–2022 seasons, respectively. In multiple analysis, males and older patients were at increased risk of a fatal outcome. Flu vaccination and infection by B lineages (vs. AH1N1) showed a protective effect. Our results suggest that the spread of the influenza virus reemerged in the 2021–2022 season when the SARS-CoV-2 Omicron variant (B.1.1.529) was dominant. Efforts focusing on the prevention of transmission of respiratory viral pathogens, together with flu vaccination, may be useful to reduce the risk of an influenza outbreak.

Technical guidelines for seasonal influenza vaccination in China (2022-2023)

Technical guidelines for seasonal influenza vaccination in China (2022-2023)

Disease progression, pathologic, and virologic findings of an equine influenza outbreak in rescue donkeys.

Equine influenza virus is a common cause of respiratory disease in equids. Few reports describe clinical presentation and disease progression in donkeys. Describe the clinical and diagnostic findings, outcome, and pathologic lesions associated with influenza pneumonia in donkeys. Thirteen unvaccinated donkeys ranging from 1week to 12 years of age and sharing clinical signs and exposure history. Retrospective case series. Medical records from June to July 2020 at the Colorado State Veterinary Teaching Hospital and collaborating referring veterinary practices were reviewed. The diagnosis was confirmed by molecular testing, virus isolation, and partial genetic and phylogenetic analysis of the virus. Survival in donkeys <1 year old was 16.6% (1/6) whereas survival in animals >1 year of age was 85.7% (6/7). Hemagglutinin gene sequencing and phylogenetic analysis confirmed a contemporary clade 1 Florida sublineage H3 virus as the causative agent. Clinical signs of equine influenza virus infection in donkeys are similar to those observed in horses. Prognosis for survival generally is good, but deaths have been observed especially in foals born to seronegative dams. This finding emphasizes the importance of prenatal vaccination protocols in all equids, including donkeys.

Technical guidelines for seasonal influenza vaccination in China (2022-2023)

Technical guidelines for seasonal influenza vaccination in China (2022-2023)

History of heart failure and chronic kidney disease and the risk for all-cause death after COVID-19 during the three first waves in comparison to influenza outbreaks in Sweden

Abstract Background Infection with SARS-CoV-2 (COVID-19) affects people globally causing hospitalisation and reduced life expectancy. To improve future preventive measures there is a need of extensive analysis on contributing risk factors for severe COVID-19 outcome. Purpose To explore how cardiorenal disease (CRD; heart failure and/or chronic kidney disease) impacted mortality in patients hospitalised for COVID-19 during the three first waves in Sweden in comparison to previous influenza outbreaks and with a sex perspective. Methods All patients in Sweden with a main hospital diagnosis of COVID-19 (January 2020-September 2021) or influenza (January 2015-December 2019) with previous CRD were identified in registries and compared with a reference group free from CRD but with COVID-19 or influenza. Associated risk of all-cause death during the first year was analysed using adjusted Cox proportional hazards models. Results In COVID-19 patients with and without prior history of CRD (n=44,866) mean age was 79.8 years (SD 11.8) and 43% were women. In influenza patients (n=8897) mean age was 80.6 (SD 11.5) years and 45% were women. COVID-19 vs. influenza was associated with higher mortality risk the first two waves (HR 1.53; 95% CI 1.45–1.62, p&amp;lt;0.001 and 1.52; 1.44–1.61, p&amp;lt;0.001) but not in the third wave (1.07; 0.99–1.14, p=0.072). The cumulative incidence of all-cause death was increased in COVID-19 patients and in influenza patients if CRD was present (Figure 1). Further, CRD was an independent risk factor for all-cause death after COVID-19 in men and women (men: 1.37; 1.31–1.44, p&amp;lt;0.001, women: 1.46; 1.38–1.54, p&amp;lt;0.001). At ages &amp;lt;70 years women with CRD had a similar mortality rate as men with CRD while at ages ≥70 years mortality rate was higher in men (Figure 2). Conclusions Outcome after COVID-19 is worse if CRD is present. In women at ages &amp;lt;70 years the presence of CRD attenuates the protective effect of female sex. Further COVID-19 was associated with higher mortality risk than influenza during the first two waves. Funding Acknowledgement Type of funding sources: Other. Main funding source(s): The Family Kamprad FoundationAstraZeneca (study sponsor)

Comparison of Prevalence of Influenza and COVID-19: A Report From Hormozgan Province-Iran, 2019-2021

Background: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses produce a wide range of clinical disease severity, which varies from asymptomatic infection to death. The outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, Hubei, China, followed a seasonal influenza pandemic. The prevalence of influenza has changed since the outbreak of COVID-19. In this study, we have compared the prevalence of influenza and COVID-19 since the onset of the pandemic. Clinical symptoms were also assessed among patients. Materials and Methods: The present study was conducted in a single center on 229456 patients with the SARS in Hormozgan province, Iran, during 2019-2021 before and after the COVID-19 pandemic. Clinical features including age, sex, fever, cough, shortness of breath, nausea, dizziness, headache, body aches, and diarrhea were also analyzed. Results: The results indicated that out of a total of 229456 samples of patients, 71142 (31.00%) and 527 (.22%) cases were diagnosed with positive COVID-19 and positive influenza, respectively. Influenza activity decreased in March 2020 and remained low until September 2021, but it increased to near pre-pandemic seasonal levels since October 2021. The outbreak of influenza decreased by starting the restrictions and health protocols. Furthermore, the analysis of patients’ symptoms indicated that the most prevalent symptoms in influenza patients were fever, cough, and body pain, while the symptoms in COVID-19 patients were cough and headache. Conclusion: Social restrictions and adherence to health protocols could significantly reduce the incidence of seasonal influenza even after controlling the COVID-19 pandemic. Influenza and COVID-19 have similar symptoms in patients, so diagnostic tests are necessary for proper diagnosis and management.

Evaluating efficacy of cleaning and disinfection of vehicles and transport crates during Avian Influenza outbreaks

Evaluating efficacy of cleaning and disinfection of vehicles and transport crates during Avian Influenza outbreaks

Inference in Gaussian state-space models with mixed effects for multiple epidemic dynamics

The estimation from available data of parameters governing epidemics is a major challenge. In addition to usual issues (data often incomplete and noisy), epidemics of the same nature may be observed in several places or over different periods. The resulting possible inter-epidemic variability is rarely explicitly considered. Here, we propose to tackle multiple epidemics through a unique model incorporating a stochastic representation for each epidemic and to jointly estimate its parameters from noisy and partial observations. By building on a previous work for prevalence data, a Gaussian state-space model is extended to a model with mixed effects on the parameters describing simultaneously several epidemics and their observation process. An appropriate inference method is developed, by coupling the SAEM algorithm with Kalman-type filtering. Moreover, we consider here incidence data, which requires to develop a new version of the filtering algorithm. Its performances are investigated on SIR simulated epidemics for prevalence and incidence data. Our method outperforms an inference method separately processing each dataset. An application to SEIR influenza outbreaks in France over several years using incidence data is also carried out. Parameter estimations highlight a non-negligible variability between influenza seasons, both in transmission and case reporting. The main contribution of our study is to rigorously and explicitly account for the inter-epidemic variability between multiple outbreaks, both from the viewpoint of modeling and inference with a parsimonious statistical model.

Network Thermodynamics-Based Scalable Compartmental Model for Multi-Strain Epidemics

SARS-CoV-2 continues to upend human life by posing novel threats related to disease spread and mutations. Current models for the disease burden of SARS-CoV-2 consider the aggregate nature of the virus without differentiating between the potency of its multiple strains. Hence, there is a need to create a fundamental modeling framework for multi-strain viruses that considers the competing viral pathogenic pathways. Alongside the consideration that other viral pathogens may coexist, there is also a need for a generalizable modeling framework to account for multiple epidemics (i.e., multi-demics) scenarios, such as influenza and COVID-19 occurring simultaneously. We present a fundamental network thermodynamics approach for assessing, determining, and predicting viral outbreak severity, which extends well-known standard epidemiological models. In particular, we use historical data from New York City’s 2011–2019 influenza seasons and SARS-CoV-2 spread to identify the model parameters. In our model-based analysis, we employ a standard susceptible–infected–recovered (SIR) model with pertinent generalizations to account for multi-strain and multi-demics scenarios. We show that the reaction affinities underpinning the formation processes of our model can be used to categorize the severity of infectious or deceased populations. The spontaneity of occurrence captured by the change in Gibbs free energy of reaction (∆G) in the system suggests the stability of forward occurring population transfers. The magnitude of ∆G is used to examine past influenza outbreaks and infer epidemiological factors, such as mortality and case burden. This method can be extrapolated for wide-ranging utility in computational epidemiology. The risk of overlapping multi-demics seasons between influenza and SARS-CoV-2 will persist as a significant threat in forthcoming years. Further, the possibility of mutating strains requires novel ways of analyzing the network of competing infection pathways. The approach outlined in this study allows for the identification of new stable strains and the potential increase in disease burden from a complex systems perspective, thereby allowing for a potential response to the significant question: are the effects of a multi-demic greater than the sum of its individual viral epidemics?

Municipal and neighbourhood level wastewater surveillance and subtyping of an influenza virus outbreak

Recurrent influenza epidemics and pandemic potential are significant risks to global health. Public health authorities use clinical surveillance to locate and monitor influenza and influenza-like cases and outbreaks to mitigate hospitalizations and deaths. Currently, global integration of clinical surveillance is the only reliable method for reporting influenza types and subtypes to warn of emergent pandemic strains. The utility of wastewater surveillance (WWS) during the COVID-19 pandemic as a less resource intensive replacement or complement for clinical surveillance has been predicated on analyzing viral fragments in wastewater. We show here that influenza virus targets are stable in wastewater and partitions favorably to the solids fraction. By quantifying, typing, and subtyping the virus in municipal wastewater and primary sludge during a community outbreak, we forecasted a citywide flu outbreak with a 17-day lead time and provided population-level viral subtyping in near real-time to show the feasibility of influenza virus WWS at the municipal and neighbourhood levels in near real time using minimal resources and infrastructure.

Pandemic urbanization: How South Africa’s history of labor and disease control creates its current disparities

ABSTRACT The COVID-19 pandemic highlights the need for scholars to rethink how cities and urban spaces create and reproduce disproportionate social outcomes. The social, economic, and public health effects of the COVID-19 pandemic in South Africa have been shaped by the country’s legacy of “pandemic urbanization.” Pandemic urbanization refers to the use of urban space as a mechanism to create social, economic, and racialized divides in the name of pandemic control. Illness and infectious disease are used as instruments for segregation, and as justification for segregation through spatial policies. Through a systematic review and synthesis of peer-reviewed literature, this paper argues that the early urbanization of pre-apartheid South Africa, which is intimately tied to the control of bubonic plague, tuberculosis, and Spanish influenza outbreaks in the early 20th century, is central to the country’s current inequalities, including those brought into stark relief by COVID-19. It shows that methods of labor and infectious disease control worked in tandem to structure South African spatial division. In doing so, this paper synthesizes important literature to tie the production of South African urban space to the active creation of categories of “race.” South Africa’s historical geography informs global discussions on racial capitalism, as the country’s past illustrates a process well beyond its borders. Given the centrality of urbanization and space within this history, a theorization highlighting spatial justice should be at the heart of pandemic and post-pandemic responses.

IRF7-deficient MDCK cell based on CRISPR/Cas9 technology for enhancing influenza virus replication and improving vaccine production.

The influenza virus is a cause of seasonal epidemic disease and enormous economic injury. The best way to control influenza outbreaks is through vaccination. The Madin-Darby canine kidney cell line (MDCK) is currently approved to manufacture influenza vaccines. However, the viral load from cell-based production is limited by host interferons (IFN). Interferon regulating factor 7 (IRF7) is a transcription factor for type-I IFN that plays an important role in regulating the anti-viral mechanism and eliminating viruses. We developed IRF7 knock-out MDCK cells (IRF7−/ − MDCK) using CRISPR/Cas9 technology. The RNA expression levels of IRF7 in the IRF7−/ − MDCK cells were reduced by 94.76% and 95.22% under the uninfected and infected conditions, respectively. Furthermore, the IRF7 protein level was also significantly lower in IRF7−/ − MDCK cells for both uninfected (54.85% reduction) and viral infected conditions (32.27% reduction) compared to WT MDCK. The differential expression analysis of IFN-related genes demonstrated that the IRF7−/ − MDCK cell had a lower interferon response than wildtype MDCK under the influenza-infected condition. Gene ontology revealed down-regulation of the defense response against virus and IFN-gamma production in IRF7−/ − MDCK. The evaluation of influenza viral titers by RT-qPCR and hemagglutination assay (HA) revealed IRF7−/ − MDCK cells had higher viral titers in cell supernatant, including A/pH1N1 (4 to 5-fold) and B/Yamagata (2-fold). Therefore, the IRF7−/ − MDCK cells could be applied to cell-based influenza vaccine production with higher capacity and efficiency.

Short-Term Coarse Particulate Exposure and Daily Cardio-Respiratory Hospital Admissions in the Helsinki Capital Region

BACKGROUND AND AIM Short-term exposure to coarse inhalable particles (2.5 µg/m3&amp;#x3e;PMcoarse&amp;#x3c;10 µg/m3) has been suggested to increase the risk of respiratory disease independently of fine particles, but studies present mixed findings which are even less clear for other outcomes. This study aims to assess the relationship between short-term exposure to PMcoarse and total admissions for cardio-pulmonary diseases. METHODS We conducted a seventeen-year (01/2001-12/2017) time-series study of the daily admissions for cardio-respiratory disease in relation to the mean levels of coarse particles. We obtained air pollution data from the Helsinki Region Environmental Services Authority, meteorological data from the Finnish Meteorological Institute, and hospital exit records from the Finnish Institute for Health and Welfare. We modelled the association between particles and cardiorespiratory admissions using log-linked quasi-Poisson regression. Penalised splines were used to adjust for the time-trend and the meteorological variables. These models were also adjusted for the weekday, pollen concentration, and influenza outbreaks. Different lag structures were explored in both single-pollutant and multipollutant models. The multipollutant models were simultaneously adjusted for PM2.5, NO2, and O3. RESULTS The mean(standard deviation) concentration of PMcoarse was 6.6(5.9) (µg/m3), while the mean (standard deviation) daily numbers of cardiovascular and respiratory admissions were 25.9(7.3) and 21.3(7.4), respectively. A 10 µg/m3 increase in the same day PMcoarse was associated with a 1.7% (95% CI, 0.4%—3.1%) and a 1.9% (95% CI, 0.5%—3.4%) excess daily risk of respiratory admissions in the single-pollutant and multipollutant models, respectively; same-day excess cardiovascular admissions risks were 0.6% (95% CI, -0.5%—1.7%) and 0.3% (95% CI, -0.9%—1.4%) in similar models. CONCLUSIONS Short-term exposure to PMcoarse can increase respiratory admission risks independently of co-pollutants but has a less determinate effect on cardiovascular admissions. A guideline framework should be considered for PMcoarse. KEYWORDS Coarse Particles, Cardiovascular Admissions, Respiratory Admissions, Time-Series, Fine Particles

Chemically Modified Bovine β-Lactoglobulin as a Broad-Spectrum Influenza Virus Entry Inhibitor with the Potential to Combat Influenza Outbreaks.

Frequent outbreaks of the highly pathogenic influenza A virus (AIV) infection, together with the lack of broad-spectrum influenza vaccines, call for the development of broad-spectrum prophylactic agents. Previously, 3-hydroxyphthalic anhydride-modified bovine β-lactoglobulin (3HP-β-LG) was proven to be effective against human immunodeficiency virus (HIV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and it has also been used in the clinical control of cervical human papillomavirus (HPV) infections. Here, we show its efficacy in potently inhibiting infection by divergent influenza A and B viruses. Mechanistic studies suggest that 3HP-β-LG binds, possibly through its negatively charged residues, to the receptor-binding domain in the hemagglutinin 1 (HA1) subunit in the HA of the influenza virus, thus inhibiting the attachment of the HA to sialic acid on host cells. The intranasal administration of 3HP-β-LG led to the protection of mice against challenges by influenza A(H1N1)/PR8, A(H3N2), and A(H7N9) viruses. Furthermore, 3HP-β-LG is highly stable when stored at 50 °C for 30 days and it shows excellent safety in vitro and in vivo. Collectively, our findings suggest that 3HP-β-LG could be successfully repurposed as an intranasal prophylactic agent to prevent influenza virus infections during influenza outbreaks.