Pandemic Risk Assessment Research Articles

Machine learning approaches for influenza A virus risk assessment identifies predictive correlates using ferret model in vivo data

In vivo assessments of influenza A virus (IAV) pathogenicity and transmissibility in ferrets represent a crucial component of many pandemic risk assessment rubrics, but few systematic efforts to identify which data from in vivo experimentation are most useful for predicting pathogenesis and transmission outcomes have been conducted. To this aim, we aggregated viral and molecular data from 125 contemporary IAV (H1, H2, H3, H5, H7, and H9 subtypes) evaluated in ferrets under a consistent protocol. Three overarching predictive classification outcomes (lethality, morbidity, transmissibility) were constructed using machine learning (ML) techniques, employing datasets emphasizing virological and clinical parameters from inoculated ferrets, limited to viral sequence-based information, or combining both data types. Among 11 different ML algorithms tested and assessed, gradient boosting machines and random forest algorithms yielded the highest performance, with models for lethality and transmission consistently better performing than models predicting morbidity. Comparisons of feature selection among models was performed, and highest performing models were validated with results from external risk assessment studies. Our findings show that ML algorithms can be used to summarize complex in vivo experimental work into succinct summaries that inform and enhance risk assessment criteria for pandemic preparedness that take in vivo data into account.

A(H2N2) and A(H3N2) influenza pandemics elicited durable cross-reactive and protective antibodies against avian N2 neuraminidases

Human cases of avian influenza virus (AIV) infections are associated with an age-specific disease burden. As the influenza virus N2 neuraminidase (NA) gene was introduced from avian sources during the 1957 pandemic, we investigate the reactivity of N2 antibodies against A(H9N2) AIVs. Serosurvey of healthy individuals reveal the highest rates of AIV N2 antibodies in individuals aged ≥65 years. Exposure to the 1968 pandemic N2, but not recent N2, protected against A(H9N2) AIV challenge in female mice. In some older adults, infection with contemporary A(H3N2) virus could recall cross-reactive AIV NA antibodies, showing discernable human- or avian-NA type reactivity. Individuals born before 1957 have higher anti-AIV N2 titers compared to those born between 1957 and 1968. The anti-AIV N2 antibodies titers correlate with antibody titers to the 1957 N2, suggesting that exposure to the A(H2N2) virus contribute to this reactivity. These findings underscore the critical role of neuraminidase immunity in zoonotic and pandemic influenza risk assessment.

An intelligent risk assessment on prediction of COVID-19 pandemic using DNN and TSA: An empirical case study in Thailand

The WHO has declared that the COVID-19 pandemic is a severe health crisis. Currently, variants of concern are delta and omicron, including sub-lineages of the omicron which are XBB and BQ.1 variants. Decision planning with situation awareness is important during the COVID-19 pandemic, especially demand planning for medical supplies following pandemic probability or severity via pandemic risk assessment. Therefore, this research proposes an intelligent risk assessment on the prediction of the COVID-19 pandemic using deep learning with deep neural network (DNN) and tunicate swarm algorithm (TSA). The results show the model can accurately predict the distance and elapsed time of the next COVID-19 case based upon the previous case and evaluate the associated risks. The contribution of this research, as prediction model is based upon a DNN, it has the ability to learn and by implementing the TSA, it can improve theoretically the performance of the DNN for more precise prediction and faster convergence to the optimal solution. The prediction results are practically expanded to analyze risk assessment using probability and the data envelopment analysis (DEA). The benefit of this research is that the proposed methodology demonstrates the prediction results using risks assessment based upon intelligent risk assessment charts. The Government or those involved can use the proposed methodology to achieve a better decision-making and management to control the COVID-19 pandemic in terms of supplying the medical supplies into pandemic areas.

COVID-19 Pandemic Risk Assessment: Systematic Review.

The COVID-19 pandemic presents the possibility of future large-scale infectious disease outbreaks. In response, we conducted a systematic review of COVID-19 pandemic risk assessment to provide insights into countries' pandemic surveillance and preparedness for potential pandemic events in the post-COVID-19 era. We aim to systematically identify relevant articles and synthesize pandemic risk assessment findings to facilitate government officials and public health experts in crisis planning. This study followed the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines and included over 620,000 records from the World Health Organization COVID-19 Research Database. Articles related to pandemic risk assessment were identified based on a set of inclusion and exclusion criteria. Relevant articles were characterized based on study location, variable types, data-visualization techniques, research objectives, and methodologies. Findings were presented using tables and charts. Sixty-two articles satisfying both the inclusion and exclusion criteria were identified. Among the articles, 32.3% focused on local areas, while another 32.3% had a global coverage. Epidemic data were the most commonly used variables (74.2% of articles), with over half of them (51.6%) employing two or more variable types. The research objectives covered various aspects of the COVID-19 pandemic, with risk exposure assessment and identification of risk factors being the most common theme (35.5%). No dominant research methodology for risk assessment emerged from these articles. Our synthesized findings support proactive planning and development of prevention and control measures in anticipation of future public health threats.

Pandemic Risk Assessment for Swine Influenza A Virus in Comparative In Vitro and In Vivo Models.

Swine influenza A viruses pose a public health concern as novel and circulating strains occasionally spill over into human hosts, with the potential to cause disease. Crucial to preempting these events is the use of a threat assessment framework for human populations. However, established guidelines do not specify which animal models or in vitro substrates should be used. We completed an assessment of a contemporary swine influenza isolate, A/swine/GA/A27480/2019 (H1N2), using animal models and human cell substrates. Infection studies in vivo revealed high replicative ability and a pathogenic phenotype in the swine host, with replication corresponding to a complementary study performed in swine primary respiratory epithelial cells. However, replication was limited in human primary cell substrates. This contrasted with our findings in the Calu-3 cell line, which demonstrated a replication profile on par with the 2009 pandemic H1N1 virus. These data suggest that the selection of models is important for meaningful risk assessment.

Highly pathogenic avian influenza A(H5N1) virus of clade 2.3.4.4b isolated from a human case in Chile causes fatal disease and transmits between co-housed ferrets

ABSTRACT Clade 2.3.4.4b highly pathogenic avian influenza A(H5N1) viruses have caused large outbreaks within avian populations on five continents, with concurrent spillover into a variety of mammalian species. Mutations associated with mammalian adaptation have been sporadically identified in avian isolates, and more frequently among mammalian isolates following infection. Reports of human infection with A(H5N1) viruses following contact with infected wildlife have been reported on multiple continents, highlighting the need for pandemic risk assessment of these viruses. In this study, the pathogenicity and transmissibility of A/Chile/25945/2023 HPAI A(H5N1) virus, a novel reassortant with four gene segments (PB1, PB2, NP, MP) from North American lineage, isolated from a severe human case in Chile, was evaluated in vitro and using the ferret model. This virus possessed a high capacity to cause fatal disease, characterized by high morbidity and extrapulmonary spread in virus-inoculated ferrets. The virus was capable of transmission to naïve contacts in a direct contact setting, with contact animals similarly exhibiting severe disease, but did not exhibit productive transmission in respiratory droplet or fomite transmission models. Our results indicate that the virus would need to acquire an airborne transmissible phenotype in mammals to potentially cause a pandemic. Nonetheless, this work warrants continuous monitoring of mammalian adaptations in avian viruses, especially in strains isolated from humans, to aid pandemic preparedness efforts.

Pandemic Marine Risks Assessment for Marine Spatial Planning (MSP): A Case Study of Northport, Malaysia

The pandemic outbreak has emphasized the necessity of incorporating pandemic marine risk assessment as a critical component of marine spatial planning (MSP). The purpose of this study was to utilize the Risk Assessment Matrix (RAM) methodology to determine the most severely impacted zone at Northport, Port Klang. 31 senior management personnel at Northport, Port Klang were involved in a survey to assess the pandemic's severity in various zones. According to the findings, the Vehicle's Terminal zone had the highest score of 17.72, indicating it to be the most severely impacted zone, followed by the Passenger's Terminal zone (15.88), Distribution Centre zone (14.62), Bulk zone (14.52), Dangerous Good zone (14.13), Free Zone (14.10), Ancillary Service zone (13.65), and Container zone (13.39). These results can be integrated into Geographical Information System (GIS) and Multi Criteria Decision Analysis (MCDA) to convert themfrom numerical values to spatial data, and visualize them hierarchically. Additionally, this study's findings can contribute to enhancing MSP practices, not only at Northport, Port Klang, but also at other ports facing similar challenges. By including pandemic risk assessment as a crucial part of MSP, ports can develop effective pandemic response plans that prioritize the health and safety of port workers and visitors, as well as ensure the continuity of trade and economic activities.

A model to analyze human and organizational factors contributing to pandemic risk assessment in manufacturing industries: FBN-HFACS modelling

This study presents a holistic model based on Fuzzy Bayesian Network-Human Factor Analysis and Classification System (FBN-HFACS) to analyze contributing factors in the pandemic, Covid 19, risk management under uncertainty. The model contains three main phases include employing a) HFACS to systematically identify influencing factors based on validation using content validity indicators, b) Fuzzy Set Theory to obtain the prior probability distribution of contributing factors in pandemic risk and address the epistemic uncertainty and subjectivity, and finally, c) Bayesian network to develop causality model of the risk, probabilistic inferences and handle parameter and model uncertainties. The Ratio of Variation (RoV), as BN-driven importance measures, is utilized to conduct sensitivity analysis and explore the most critical factors that yield effective safety countermeasures. The model is tested to investigate four large manufacturing industries in South Khorasan (Iran). It provided a deep understanding of influencing human and organizational factors and captured dependencies among those factors, while quantitative finding paves a way to efficiently make risk-based decisions to deal with the pandemic risks under uncertainty.

Hemagglutinin destabilization in H3N2 vaccine reference viruses skews antigenicity and prevents airborne transmission in ferrets.

During influenza virus entry, the hemagglutinin (HA) protein binds receptors and causes membrane fusion after endosomal acid activation. To improve vaccine efficiency and pandemic risk assessment for currently-dominant H3N2 influenza viruses, we investigated HA stability of 6 vaccine reference viruses and 42 circulating viruses. Recent vaccine reference viruses had destabilized HA proteins due to egg-adaptive mutation HA1-L194P. Virus growth in cell culture was independent of HA stability. In ferrets, the vaccine reference viruses and circulating viruses required a relatively stable HA (activation and inactivation pH<5.5) for airborne transmissibility. The recent vaccine reference viruses with destabilized HA proteins had reduced infectivity, had no airborne transmissibility unless reversion to HA1-P194L occurred, and had skewed antigenicity away from the studied viruses and circulating H3N2 viruses. Other vaccine reference viruses with stabilized HAs retained infectivity, transmissibility, and antigenicity. Therefore, HA stabilization should be prioritized over destabilization in vaccine reference virus selection to reduce mismatches between vaccine and circulating viruses.

Antigenic Characterization and Pandemic Risk Assessment of North American H1 Influenza A Viruses Circulating in Swine.

The first pandemic of the 21st century was caused by an H1N1 influenza A virus (IAV) introduced from pigs into humans, highlighting the importance of swine as reservoirs for pandemic viruses. Two major lineages of swine H1 circulate in North America: the 1A classical swine lineage (including that of the 2009 H1N1 pandemic) and the 1B human seasonal-like lineage. Here, we investigated the evolution of these H1 IAV lineages in North American swine and their potential pandemic risk. We assessed the antigenic distance between the HA of representative swine H1 and human seasonal vaccine strains (1978 to 2015) in hemagglutination inhibition (HI) assays using a panel of monovalent antisera raised in pigs. Antigenic cross-reactivity varied by strain but was associated with genetic distance. Generally, the swine 1A lineage viruses that seeded the 2009 H1 pandemic were antigenically most similar to the H1 pandemic vaccine strains, with the exception of viruses in the genetic clade 1A.1.1.3, which had a two-amino acid deletion mutation near the receptor-binding site, which dramatically reduced antibody recognition. The swine 1B lineage strains, which arose from previously circulating (pre-2009 pandemic) human seasonal viruses, were more antigenically similar to pre-2009 human seasonal H1 vaccine viruses than post-2009 strains. Human population immunity was measured by cross-reactivity in HI assays to representative swine H1 strains. There was a broad range of titers against each swine strain that was not associated with age, sex, or location. However, there was almost no cross-reactivity in human sera to the 1A.1.1.3 and 1B.2.1 genetic clades of swine viruses, and the 1A.1.1.3 and 1B.2.1 clades were also the most antigenically distant to the human vaccine strains. Our data demonstrate that the antigenic distances of representative swine strains from human vaccine strains represent an important part of the rational assessment of swine IAV for zoonotic risk research and pandemic preparedness prioritization. IMPORTANCE Human H1 influenza A viruses (IAV) spread to pigs in North America, resulting in a sustained circulation of two major groups of H1 viruses in swine. We quantified the genetic diversity of H1 in swine and measured antigenic phenotypes. We demonstrated that the swine H1 lineages were significantly different from the human vaccine strains and that this antigenic dissimilarity increased over time as the viruses evolved in swine. Pandemic preparedness vaccine strains for human vaccines also demonstrated a loss in similarity with contemporary swine strains. Human sera revealed a range of responses to swine IAV, including two groups of viruses with little to no immunity. The surveillance and risk assessment of IAV diversity in pig populations are essential to detect strains with reduced immunity in humans and provide critical information for pandemic preparedness.

Association between democratic governance and excess mortality during the COVID-19 pandemic: an observational study

BackgroundExcess mortality has been used to assess the overall health impact of COVID-19 across countries. Democracies aim to build trust in government and enable checks and balances on decision making,...

Selection for infectivity profiles in slow and fast epidemics, and the rise of SARS-CoV-2 variants.

Evaluating the characteristics of emerging SARS-CoV-2 variants of concern is essential to inform pandemic risk assessment. A variant may grow faster if it produces a larger number of secondary infections ("R advantage") or if the timing of secondary infections (generation time) is better. So far, assessments have largely focused on deriving the R advantage assuming the generation time was unchanged. Yet, knowledge of both is needed to anticipate the impact. Here, we develop an analytical framework to investigate the contribution of both the R advantage and generation time to the growth advantage of a variant. It is known that selection on a variant with larger R increases with levels of transmission in the community. We additionally show that variants conferring earlier transmission are more strongly favored when the historical strains have fast epidemic growth, while variants conferring later transmission are more strongly favored when historical strains have slow or negative growth. We develop these conceptual insights into a new statistical framework to infer both the R advantage and generation time of a variant. On simulated data, our framework correctly estimates both parameters when it covers time periods characterized by different epidemiological contexts. Applied to data for the Alpha and Delta variants in England and in Europe, we find that Alpha confers a+54% [95% CI, 45-63%] R advantage compared to previous strains, and Delta +140% [98-182%] compared to Alpha, and mean generation times are similar to historical strains for both variants. This work helps interpret variant frequency dynamics and will strengthen risk assessment for future variants of concern.

Pandemic Risk Assessment and Management in a Bayesian Framework

Pandemic Risk Assessment and Management in a Bayesian Framework

Development of a Pandemic Residual Risk Assessment Tool for Building Organizational Resilience within Polish Enterprises

Development of a Pandemic Residual Risk Assessment Tool for Building Organizational Resilience within Polish Enterprises

Development of a Pandemic Residual Risk Assessment Tool for Building Organizational Resilience within Polish Enterprises.

The purpose of the research paper was to develop a universal residual risk assessment tool based on the use of risk control measures related to Covid-19 in order to determine the state of organizational resilience of individual industries or organizations. The article proposes and analyzes a pandemic residual risk assessment tool, which is a simple and universal source for residual risk estimation based on a five-step consequence/probability matrix, a five-step hierarchy of risk controls, and a general formula for calculating residual risk. The methodology of the survey is based on a questionnaire with 16 questions used for the initial validation of the residual risk scale, of which six related to the potential of organizational resilience. The pilot survey was conducted in 66 enterprises in Poland. On the basis of the survey, four measures related to the use of control measures against threats after the outbreak of the Covid-19 pandemic have been proposed. These are personal protective equipment (PPE) controls, administrative controls, engineering controls, and substitution controls. Using the survey results, we estimated averages of the response results, and, on their basis, we estimated the residual risks for individual types of enterprises according to the type of business and its size. Based on the calculations, a strong correlation was found between the potential of organizational resilience and the individual use of control measures. Therefore, the main finding of the survey proves that effective risk management builds organizational resilience in enterprises. The practical implications of the study allow the management staff to find out what aspects related to the use of control measures need to be paid attention to in order to minimize residual risk.

Influenza A Virus Field Surveillance at a Swine-Human Interface.

While working overnight at a swine exhibition, we identified an influenza A virus (IAV) outbreak in swine, Nanopore sequenced 13 IAV genomes from samples we collected, and predicted in real time that these viruses posed a novel risk to humans due to genetic mismatches between the viruses and current prepandemic candidate vaccine viruses (CVVs). We developed and used a portable IAV sequencing and analysis platform called Mia (Mobile Influenza Analysis) to complete and characterize full-length consensus genomes approximately 18 h after unpacking the mobile lab. Exhibition swine are a known source for zoonotic transmission of IAV to humans and pose a potential pandemic risk. Genomic analyses of IAV in swine are critical to understanding this risk, the types of viruses circulating in swine, and whether current vaccines developed for use in humans would be predicted to provide immune protection. Nanopore sequencing technology has enabled genome sequencing in the field at the source of viral outbreaks or at the bedside or pen-side of infected humans and animals. The acquired data, however, have not yet demonstrated real-time, actionable public health responses. The Mia system rapidly identified three genetically distinct swine IAV lineages from three subtypes, A(H1N1), A(H3N2), and A(H1N2). Analysis of the hemagglutinin (HA) sequences of the A(H1N2) viruses identified >30 amino acid differences between the HA1 of these viruses and the most closely related CVV. As an exercise in pandemic preparedness, all sequences were emailed to CDC collaborators who initiated the development of a synthetically derived CVV.IMPORTANCE Swine are influenza virus reservoirs that have caused outbreaks and pandemics. Genomic characterization of these viruses enables pandemic risk assessment and vaccine comparisons, though this typically occurs after a novel swine virus jumps into humans. The greatest risk occurs where large groups of swine and humans comingle. At a large swine exhibition, we used Nanopore sequencing and on-site analytics to interpret 13 swine influenza virus genomes and identified an influenza virus cluster that was genetically highly varied to currently available vaccines. As part of the National Strategy for Pandemic Preparedness exercises, the sequences were emailed to colleagues at the CDC who initiated the development of a synthetically derived vaccine designed to match the viruses at the exhibition. Subsequently, this virus caused 14 infections in humans and was the dominant U.S. variant virus in 2018.

Infection of NOD.SCID.IL2rg−/− Mice with Non‐Mouse‐Adapted Swine‐Origin and Human‐Origin H1 and H3 Influenza A Viruses

ObjectiveInfluenza A viruses (IAV) emerging from animal reservoirs pose pandemic influenza threat. Investigation of human population immunity against swine‐origin IAVs identified at the animal‐human interface is critical to understanding the risk associated with these viruses. The ability to use humanized mouse models incorporating natural anti‐IAV immunity could advance current pandemic risk assessment strategies. However, it is widely accepted that IAV infection in mice requires serial passage, though the natural susceptibility of immunodeficient mice is unclear. Further, use of mouse‐adapted IAVs may not accurately reflect antigenic and pathologic features of non‐mouse‐adapted viruses. Our objective was to investigate the susceptibility of the immunodeficient NOD.SCID.IL2rg−/− (NSG) mouse strain to infection with non‐mouse‐adapted human‐ and swine‐origin IAVs. We hypothesized that NSG mice would be naturally susceptible to infection with non‐mouse‐adapted human‐ and swine‐origin hemagglutinin subtype 1 (H1) and H3 IAVs.MethodsPairs of adult NSG mice were intranasally inoculated with one of seven IAVs [swine‐origin (H1 delta1, H1 gamma, H3 human‐like, H3 cluster IV), human seasonal (H1N1, H3N2)] (105–106 TCID50 in 50uL PBS) or sterile PBS. Animals were observed for 96 hours post‐challenge prior to euthanasia and postmortem tissue collection. Lungs were split: viral quantification was performed via endpoint dilution assay, and virus‐associated pathology was assessed via microscopic examination of formalin‐fixed paraffin‐embedded (FFPE) tissues.ResultsInfectious virus was recovered from the lungs of all virus‐challenged NSG mice (n=14). H1 subtype IAVs caused rapid weight loss in challenged mice at 96 hours post‐infection (mean decrease 14.1% body weight) as compared to H3 subtype IAV‐challenge and control mice, which showed no significant weight loss. Microscopic lung lesions included acute airway epithelial degeneration and necrosis, acute peribronchial/bronchiolar inflammation, consolidation, and hemorrhage. Pulmonary lesions and immunohistochemical (IHC) labeling in all H1 IAV‐challenged mice (n=8) were consistent with IAV infection, and lesions were most severe in this group. In contrast, the pulmonary pathology in H3 IAV‐challenged mice ranged from mild to absent.ConclusionsThese findings support the general potential of non‐mouse‐adapted IAV isolates to cause clinical and microscopic disease in NSG mice. While this contradicts the general consensus that IAV is not naturally infectious in mice, there are key differences between H1 and H3 subtype IAVs suggesting HA subtype influences infection. Future challenge studies with additional non‐mouse‐adapted IAVs will help clarify this phenomenon and establish the limitations of their use in humanized mouse models of anti‐IAV immunity.Support or Funding InformationFederal funds from Centers of Excellence for Influenza Research and Surveillance, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract number HHSN272201400006C were used for this work. Additional support provided by The Ohio State University Graduate School.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Structural and Molecular Characterization of the Hemagglutinin from the Fifth-Epidemic-Wave A(H7N9) Influenza Viruses.

The avian influenza A(H7N9) virus continues to cause human infections in China and is a major ongoing public health concern. Five epidemic waves of A(H7N9) infection have occurred since 2013, and the recent fifth epidemic wave saw the emergence of two distinct lineages with elevated numbers of human infection cases and broader geographic distribution of viral diseases compared to the first four epidemic waves. Moreover, highly pathogenic avian influenza (HPAI) A(H7N9) viruses were also isolated during the fifth epidemic wave. Here, we present a detailed structural and biochemical analysis of the surface hemagglutinin (HA) antigen from viruses isolated during this recent epidemic wave. Results highlight that, compared to the 2013 virus HAs, the fifth-wave virus HAs remained a weak binder to human glycan receptor analogs. We also studied three mutations, V177K-K184T-G219S, that were recently reported to switch a 2013 A(H7N9) HA to human-type receptor specificity. Our results indicate that these mutations could also switch the H7 HA receptor preference to a predominantly human binding specificity for both fifth-wave H7 HAs analyzed in this study.IMPORTANCE The A(H7N9) viruses circulating in China are of great public health concern. Here, we report a molecular and structural study of the major surface proteins from several recent A(H7N9) influenza viruses. Our results improve the understanding of these evolving viruses and provide important information on their receptor preference that is central to ongoing pandemic risk assessment.

Ferrets as Models for Influenza Virus Transmission Studies and Pandemic Risk Assessments.

The ferret transmission model is extensively used to assess the pandemic potential of emerging influenza viruses, yet experimental conditions and reported results vary among laboratories. Such variation can be a critical consideration when contextualizing results from independent risk-assessment studies of novel and emerging influenza viruses. To streamline interpretation of data generated in different laboratories, we provide a consensus on experimental parameters that define risk-assessment experiments of influenza virus transmissibility, including disclosure of variables known or suspected to contribute to experimental variability in this model, and advocate adoption of more standardized practices. We also discuss current limitations of the ferret transmission model and highlight continued refinements and advances to this model ongoing in laboratories. Understanding, disclosing, and standardizing the critical parameters of ferret transmission studies will improve the comparability and reproducibility of pandemic influenza risk assessment and increase the statistical power and, perhaps, accuracy of this model.

Population Serologic Immunity to Human and Avian H2N2 Viruses in the United States and Hong Kong for Pandemic Risk Assessment.

BackgroundInfluenza A pandemics cause significant mortality and morbidity. H2N2 viruses have caused a prior pandemic, and are circulating in avian reservoirs. The age-related frequency of current population immunity to H2 viruses was evaluated.MethodsHemagglutinin inhibition (HAI) assays against historical human and recent avian influenza A(H2N2) viruses were performed across age groups in Rochester, New York, and Hong Kong, China. The impact of existing cross-reactive HAI immunity on the effective reproduction number was modeled.ResultsOne hundred fifty individual sera from Rochester and 295 from Hong Kong were included. Eighty-five percent of patients born in Rochester and Hong Kong before 1968 had HAI titers ≥1:40 against A/Singapore/1/57, and >50% had titers ≥1:40 against A/Berkeley/1/68. The frequency of titers ≥1:40 to avian H2N2 A/mallard/England/727/06 and A/mallard/Netherlands/14/07 in subjects born before 1957 was 62% and 24%, respectively. There were no H2 HAI titers >1:40 in individuals born after 1968. These levels of seroprevalence reduce the initial reproduction number of A/Singapore/1/1957 or A/Berkeley/1/68 by 15%–20%. A basic reproduction number (R0) of the emerging transmissible virus <1.2 predicts a preventable pandemic.ConclusionsPopulation immunity to H2 viruses is insufficient to block epidemic spread of H2 virus. An H2N2 pandemic would have lower impact in those born before 1968.