Modeling Optimal Age-Specific Vaccination Strategies Against Pandemic Influenza

In the context of pandemic influenza, the prompt and effective implementation of control measures is of great concern for public health officials around the world. In particular, the role of vaccination should be considered as part of any pandemic preparedness plan. The timely production and efficient distribution of pandemic influenza vaccines are important factors to consider in mitigating the morbidity and mortality impact of an influenza pandemic, particularly for those individuals at highest risk of developing severe disease. In this paper, we use a mathematical model that incorporates age-structured transmission dynamics of influenza to evaluate optimal vaccination strategies in the epidemiological context of the Spring 2009 A (H1N1) pandemic in Mexico. We extend previous work on age-specific vaccination strategies to time-dependent optimal vaccination policies by solving an optimal control problem with the aim of minimizing the number of infected individuals over the course of a single pandemic wave. Optimal vaccination policies are computed and analyzed under different vaccination coverages (21%–77%) and different transmissibility levels (R₀\mathcal{R}_{0} in the range of 1.8–3). The results suggest that the optimal vaccination can be achieved by allocating most vaccines to young adults (20–39 yr) followed by school age children (6–12 yr) when the vaccination coverage does not exceed 30%. For higher R₀\mathcal{R}_{0} levels ($\mathcal{R}_{0}>=2.4$\mathcal{R}_{0}>=2.4), or a time delay in the implementation of vaccination (>90 days), a quick and substantial decrease in the pool of susceptibles would require the implementation of an intensive vaccination protocol within a shorter period of time. Our results indicate that optimal age-specific vaccination rates are significantly associated with R₀\mathcal{R}_{0}, the amount of vaccines available and the timing of vaccination.     

Economic Analysis of Pandemic Influenza Vaccination Strategies in Singapore

Background

All influenza pandemic plans advocate pandemic vaccination. However, few studies have evaluated the cost-effectiveness of different vaccination strategies. This paper compares the economic outcomes of vaccination compared with treatment with antiviral agents alone, in Singapore.

Methodology

We analyzed the economic outcomes of pandemic vaccination (immediate vaccination and vaccine stockpiling) compared with treatment-only in Singapore using a decision-based model to perform cost-benefit and cost-effectiveness analyses. We also explored the annual insurance premium (willingness to pay) depending on the perceived risk of the next pandemic occurring.

Principal Findings

The treatment-only strategy resulted in 690 deaths, 13,950 hospitalization days, and economic cost of USD$497 million. For immediate vaccination, at vaccine effectiveness of >55%, vaccination was cost-beneficial over treatment-only. Vaccine stockpiling is not cost-effective in most scenarios even with 100% vaccine effectiveness. The annual insurance premium was highest with immediate vaccination, and was lower with increased duration to the next pandemic. The premium was also higher with higher vaccine effectiveness, attack rates, and case-fatality rates. Stockpiling with case-fatality rates of 0.4–0.6% would be cost-beneficial if vaccine effectiveness was >80%; while at case-fatality of >5% stockpiling would be cost-beneficial even if vaccine effectiveness was 20%. High-risk sub-groups warrant higher premiums than low-risk sub-groups.

Conclusions

The actual pandemic vaccine effectiveness and lead time is unknown. Vaccine strategy should be based on perception of severity. Immediate vaccination is most cost-effective, but requires vaccines to be available when required. Vaccine stockpiling as insurance against worst-case scenarios is also cost-effective. Research and development is therefore critical to develop and stockpile cheap, readily available effective vaccines.     

Seasonal Influenza Vaccination for Children in Thailand: A Cost-Effectiveness Analysis

Background

Seasonal influenza is a major cause of mortality worldwide. Routine immunization of children has the potential to reduce this mortality through both direct and indirect protection, but has not been adopted by any low- or middle-income countries. We developed a framework to evaluate the cost-effectiveness of influenza vaccination policies in developing countries and used it to consider annual vaccination of school- and preschool-aged children with either trivalent inactivated influenza vaccine (TIV) or trivalent live-attenuated influenza vaccine (LAIV) in Thailand. We also compared these approaches with a policy of expanding TIV coverage in the elderly.

Methods and Findings

We developed an age-structured model to evaluate the cost-effectiveness of eight vaccination policies parameterized using country-level data from Thailand. For policies using LAIV, we considered five different age groups of children to vaccinate. We adopted a Bayesian evidence-synthesis framework, expressing uncertainty in parameters through probability distributions derived by fitting the model to prospectively collected laboratory-confirmed influenza data from 2005-2009, by meta-analysis of clinical trial data, and by using prior probability distributions derived from literature review and elicitation of expert opinion. We performed sensitivity analyses using alternative assumptions about prior immunity, contact patterns between age groups, the proportion of infections that are symptomatic, cost per unit vaccine, and vaccine effectiveness. Vaccination of children with LAIV was found to be highly cost-effective, with incremental cost-effectiveness ratios between about 2,000 and 5,000 international dollars per disability-adjusted life year averted, and was consistently preferred to TIV-based policies. These findings were robust to extensive sensitivity analyses. The optimal age group to vaccinate with LAIV, however, was sensitive both to the willingness to pay for health benefits and to assumptions about contact patterns between age groups.

Conclusions

Vaccinating school-aged children with LAIV is likely to be cost-effective in Thailand in the short term, though the long-term consequences of such a policy cannot be reliably predicted given current knowledge of influenza epidemiology and immunology. Our work provides a coherent framework that can be used for similar analyses in other low- and middle-income countries.     

The Impact of the Unstructured Contacts Component in Influenza Pandemic Modeling

Background

Individual based models have become a valuable tool for modeling the spatiotemporal dynamics of epidemics, e.g. influenza pandemic, and for evaluating the effectiveness of intervention strategies. While specific contacts among individuals into diverse environments (family, school/workplace) can be modeled in a standard way by employing available socio-demographic data, all the other (unstructured) contacts can be dealt with by adopting very different approaches. This can be achieved for instance by employing distance-based models or by choosing unstructured contacts in the local communities or by employing commuting data.

Methods/Results

Here we show how diverse choices can lead to different model outputs and thus to a different evaluation of the effectiveness of the containment/mitigation strategies. Sensitivity analysis has been conducted for different values of the first generation index G₀ , which is the average number of secondary infections generated by the first infectious individual in a completely susceptible population and by varying the seeding municipality. Among the different considered models, attack rate ranges from 19.1% to 25.7% for G₀ = 1.1, from 47.8% to 50.7% for G₀ = 1.4 and from 62.4% to 67.8% for G₀ = 1.7. Differences of about 15 to 20 days in the peak day have been observed. As regards spatial diffusion, a difference of about 100 days to cover 200 km for different values of G₀ has been observed.

Conclusion

To reduce uncertainty in the models it is thus important to employ data, which start being available, on contacts on neglected but important activities (leisure time, sport mall, restaurants, etc.) and time-use data for improving the characterization of the unstructured contacts. Moreover, all the possible effects of different assumptions should be considered for taking public health decisions: not only sensitivity analysis to various model parameters should be performed, but intervention options should be based on the analysis and comparison of different modeling choices.     

Modeling Seasonal Influenza Outbreak in a Closed College Campus: Impact of Pre-Season Vaccination,In-Season Vaccination and Holidays/Breaks

Background

College and university students experience substantial morbidity from influenza and influenza-like illness, and they can benefit substantially from vaccination. Public health authorities encourage vaccination not only before the influenza season but also into and even throughout the influenza season. We conducted the present study to assess the impact of various vaccination strategies including delayed (i.e., in-season) vaccination on influenza outbreaks on a college campus.

Methods/Findings

We used a Susceptible → Infected → Recovered (SIR) framework for our mathematical models to simulate influenza epidemics in a closed, college campus. We included both students and faculty/staff in the model and derived values for the model parameters from the published literature. The values for key model parameters were varied to assess the impact on the outbreak of various pre-season and delayed vaccination rates; one-way sensitivity analyses were conducted to test the sensitivity of the model outputs to changes in selected parameter values. In the base case, with a pre-season vaccination rate of 20%, no delayed vaccination, and 1 student index case, the total attack rate (total percent infected, TAR) was 45%. With higher pre-season vaccination rates TARs were lower. Even if vaccinations were given 30 days after outbreak onset, TARs were still lower than the TAR of 69% in the absence of vaccination. Varying the proportions of vaccinations given pre-season versus delayed until after the onset of the outbreak gave intermediate TAR values. Base case outputs were sensitive to changes in infectious contact rates and infectious periods and a holiday/break schedule.

Conclusion

Delayed vaccination and holidays/breaks can be important adjunctive measures to complement traditional pre-season influenza vaccination for controlling and preventing influenza in a closed college campus.     

Elementary School-Based Influenza Vaccination: Evaluating Impact on Respiratory Illness Absenteeism and Laboratory-Confirmed Influenza

Background

Studies of influenza vaccine effectiveness in schools have assessed all-cause absenteeism rather than laboratory-confirmed influenza. We conducted an observational pilot study to identify absences due to respiratory illness and laboratory-confirmed influenza in schools with and without school-based vaccination.

Methods

A local public health agency initiated school-based influenza vaccination in two Wisconsin elementary schools during October 2010 (exposed schools); two nearby schools served as a comparison group (non-exposed schools). Absences due to fever or cough illness were monitored for 12 weeks. During the 4 weeks of peak influenza activity, parents of absent children with fever/cough illness were contacted and offered influenza testing.

Results

Parental consent for sharing absenteeism data was obtained for 937 (57%) of 1,640 students. Fifty-two percent and 28%, respectively, of all students in exposed and non-exposed schools were vaccinated. Absences due to fever or cough illness were significantly lower in the exposed schools during seven of 12 surveillance weeks. Twenty-seven percent of students at exposed schools and 39% at unexposed schools had one or more days of absence due to fever/cough illness (p<0.0001). There was no significant difference in the proportion of students absent for other reasons (p = 0.23). During the 4 week period of influenza testing, respiratory samples were obtained for 68 (42%) of 163 episodes of absence due to fever or cough illness. Influenza was detected in 6 students; 3 attended exposed schools.

Conclusions

Detection of laboratory-confirmed influenza in schools was challenging due to multiple consent requirements, difficulty obtaining samples from absent children, and a mild influenza season. School-based influenza vaccination was associated with reduced absenteeism due to fever or cough illness, but not absenteeism for other reasons. Although nonspecific, absence due to fever or cough illness may be a useful surrogate endpoint in school-based studies if identification of laboratory confirmed influenza is not feasible.     

Evaluation of Targeted Influenza Vaccination Strategies via Population Modeling

Background

Because they can generate comparable predictions, mathematical models are ideal tools for evaluating alternative drug or vaccine allocation strategies. To remain credible, however, results must be consistent. Authors of a recent assessment of possible influenza vaccination strategies conclude that older children, adolescents, and young adults are the optimal targets, no matter the objective, and argue for vaccinating them. Authors of two earlier studies concluded, respectively, that optimal targets depend on objectives and cautioned against changing policy. Which should we believe?

Methods and Findings

In matrices whose elements are contacts between persons by age, the main diagonal always predominates, reflecting contacts between contemporaries. Indirect effects (e.g., impacts of vaccinating one group on morbidity or mortality in others) result from off-diagonal elements. Mixing matrices based on periods in proximity with others have greater sub- and super-diagonals, reflecting contacts between parents and children, and other off-diagonal elements (reflecting, e.g., age-independent contacts among co-workers), than those based on face-to-face conversations. To assess the impact of targeted vaccination, we used a time-usage study''s mixing matrix and allowed vaccine efficacy to vary with age. And we derived mortality rates either by dividing observed deaths attributed to pneumonia and influenza by average annual cases from a demographically-realistic SEIRS model or by multiplying those rates by ratios of (versus adding to them differences between) pandemic and pre-pandemic mortalities.

Conclusions

In our simulations, vaccinating older children, adolescents, and young adults averts the most cases, but vaccinating either younger children and older adults or young adults averts the most deaths, depending on the age distribution of mortality. These results are consistent with those of the earlier studies.     

Adaptive Vaccination Strategies to Mitigate Pandemic Influenza: Mexico as a Case Study

Background

We explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic.

Methods and Findings

In the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters.

Conclusions

This modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics.     

Transmission of Pandemic H1N1 Influenza Virus and Impact of Prior Exposure to Seasonal Strains or Interferon Treatment

Novel swine-origin influenza viruses of the H1N1 subtype were first detected in humans in April 2009. As of 12 August 2009, 180,000 cases had been reported globally. Despite the fact that they are of the same antigenic subtype as seasonal influenza viruses circulating in humans since 1977, these viruses continue to spread and have caused the first influenza pandemic since 1968. Here we show that a pandemic H1N1 strain replicates in and transmits among guinea pigs with similar efficiency to that of a seasonal H3N2 influenza virus. This transmission was, however, partially disrupted when guinea pigs had preexisting immunity to recent human isolates of either the H1N1 or H3N2 subtype and was fully blocked through daily intranasal administration of interferon to either inoculated or exposed animals. Our results suggest that partial immunity resulting from prior exposure to conventional human strains may blunt the impact of pandemic H1N1 viruses in the human population. In addition, the use of interferon as an antiviral prophylaxis may be an effective way to limit spread in at-risk populations.A pandemic of novel swine-origin influenza virus (H1N1) is developing rapidly. As of 12 August 2009, nearly 180,000 cases had been reported to the WHO from around the globe (36). Sustained human-to-human transmission has furthermore been observed in multiple countries, prompting the WHO to declare a public health emergency of international concern and to raise the pandemic alert level to phase 6 (7).Swine are a natural host of influenza viruses, and although sporadic incidences of human infection with swine influenza viruses occur (8, 9, 14, 29, 35), human-to-human transmission is rare. H1N1 influenza viruses have likely circulated in swine since shortly after the 1918 human influenza pandemic (38). From the 1930s, when a swine influenza virus was first isolated, to the late 1990s, this classical swine lineage has remained relatively stable antigenically (34). In the late 1990s, however, genetic reassortment between a human H3N2 virus, a North American avian virus, and a classical swine influenza virus produced a triple reassortant virus, which subsequently spread among North American swine (34). Further reassortment events involving human influenza viruses led to the emergence in pigs of triple reassortants of the H1N1 and H1N2 subtypes (34). None of these swine viruses have demonstrated the potential for sustained human-to-human transmission.The swine-origin influenza viruses now emerging in the human population possess a previously uncharacterized constellation of eight genes (28). The NA and M segments derive from a Eurasian swine influenza virus lineage, having entered pigs from the avian reservoir around 1979, while the HA, NP, and NS segments are of the classical swine lineage and the PA, PB1, and PB2 segments derive from the North American triple reassortant swine lineage (13). This unique combination of genetic elements (segments from multiple swine influenza virus lineages, some of them derived from avian and human influenza viruses) may account for the improved fitness of pandemic H1N1 viruses, relative to that of previous swine isolates, in humans.Several uncertainties remain about how this outbreak will develop over time. Although the novel H1N1 virus has spread over a broad geographical area, the number of people known to be infected remains low in many countries, which could be due, at least in part, to the lack of optimal transmission of influenza viruses outside the winter season; thus, it is unclear at this point whether the new virus will become established in the long term. Two major factors will shape the epidemiology of pandemic H1N1 viruses in the coming months and years: the intrinsic transmissibility of the virus and the degree of protection offered by previous exposure to seasonal human strains. Initial estimates of the reproductive number (R₀) have been made based on the epidemiology of the virus to date and suggest that its rate of spread is intermediate between that of seasonal flu and that of previous pandemic strains (3, 11). However, more precise estimates of R₀ will depend on better surveillance data in the future. The transmission phenotype of pandemic H1N1 viruses in a ferret model was also recently reported and was found to be similar to (16, 27) or less efficient (25) than that of seasonal H1N1 strains. The reason for this discrepancy in the ferret model is unclear.Importantly, in considering the human population, the impact of immunity against seasonal strains on the transmission potential of pandemic H1N1 viruses is not clear. According to conventional wisdom, an influenza virus must be of a hemagglutinin (HA) subtype which is novel to the human population in order to cause a pandemic (18, 38). Analysis of human sera collected from individuals with diverse influenza virus exposure histories has indicated that in those born in the early part of the 20th century, neutralizing activity against A/California/04/09 (Cal/04/09) virus is often present (16). Conversely, serological analyses of ferret postinfection sera (13) and human pre- and postvaccination sera (4a) revealed that neutralizing antibodies against recently circulating human H1N1 viruses do not react with pandemic H1N1 isolates. These serological findings may explain the relatively small number of cases seen to date in individuals greater than 65 years of age (6). Even in the absence of neutralizing antibodies, however, a measure of immune protection sufficient to dampen transmission may be present in a host who has recently experienced seasonal influenza (10). If, on the other hand, transmission is high and immunity is low, then pandemic H1N1 strains will likely continue to spread rapidly through the population. In this situation, a range of pharmaceutical interventions will be needed to dampen the public health impact of the pandemic.Herein we used the guinea pig model (4, 21-24, 26, 30) to assess the transmissibility of the pandemic H1N1 strains Cal/04/09 and A/Netherlands/602/09 (NL/602/09) relative to that of previous human and swine influenza viruses. To better mimic the human situation, we then tested whether the efficiency of transmission is decreased by preexisting immunity to recent human H1N1 or H3N2 influenza viruses. Finally, we assessed the efficacy of intranasal treatment with type I interferon (IFN) in limiting the replication and transmission of pandemic H1N1 viruses.     

Influenza Vaccination in Adults with Chronic Obstructive Pulmonary Disease: The Impact of a Diagnostic Breathing Test on Vaccination Rates

Introduction

Influenza vaccination rates are low in adults with chronic obstructive pulmonary disease (COPD). A diagnostic breathing test in adults with COPD may increase vaccination rates; however, research has not demonstrated this relationship. The purpose of this research was to determine if adults with COPD diagnosed by a breathing test were more likely to have had an influenza vaccination during the past 12 months when compared to those with COPD diagnosed without a breathing test.

Methods

This was a cross-sectional study using data from the 2011 Behavioral Risk Factor Surveillance System. Logistic regression examined the relationship between influenza vaccination among adults with COPD diagnosed with a breathing test (n = 13,201) compared to those diagnosed without a breathing test (n = 3,108), after controlling for all potential confounders.

Results

Overall, 49% of respondents with COPD received an influenza vaccination within the past 12 months and 78% reported their COPD was diagnosed by a breathing test. The prevalence of influenza vaccination in the past 12 months was greater in those with COPD diagnosed by a breathing test (53%) compared to those diagnosed without a breathing test (36%). In adjusted analysis, adults with COPD who had a breathing test were 31% (confidence interval 1.1, 1.6) more likely to have received an influenza vaccination in the past 12 months compared to those without a breathing test.

Discussion

A diagnostic breathing test for COPD was associated with increased likelihood of having had an influenza vaccination in the past 12 months. This may be an indicator of the relationship between knowledge of lung function and the need for preventative care, a sign of quality healthcare, or good health-seeking behaviors in patients with COPD. This research is the first to use a nationally representative sample to suggest that spirometry diagnosis of COPD may increase rates of influenza vaccination.     

The Shifting Demographic Landscape of Pandemic Influenza

Background

As Pandemic (H1N1) 2009 influenza spreads around the globe, it strikes school-age children more often than adults. Although there is some evidence of pre-existing immunity among older adults, this alone may not explain the significant gap in age-specific infection rates.

Methods and Findings

Based on a retrospective analysis of pandemic strains of influenza from the last century, we show that school-age children typically experience the highest attack rates in primarily naive populations, with the burden shifting to adults during the subsequent season. Using a parsimonious network-based mathematical model which incorporates the changing distribution of contacts in the susceptible population, we demonstrate that new pandemic strains of influenza are expected to shift the epidemiological landscape in exactly this way.

Conclusions

Our analysis provides a simple demographic explanation for the age bias observed for H1N1/09 attack rates, and suggests that this bias may shift in coming months. These results have significant implications for the allocation of public health resources for H1N1/09 and future influenza pandemics.     

Role of Substitutions in the Hemagglutinin in the Emergence of the 1968 Pandemic Influenza Virus

Hemagglutinin (HA) of H3N2/1968 pandemic influenza viruses differs from the putative avian precursor by seven amino acid substitutions. Substitutions Q226L and G228S are known to be essential for adaptation of avian HA to mammals. We found that introduction of avian-virus-like amino acids at five other HA positions (positions 62, 81, 92, 144, and 193) of A/Hong Kong/1/1968 virus decreased viral replication in human cells and transmission in pigs. Thus, substitutions at some of these positions facilitated emergence of the pandemic virus.     

Prior Population Immunity Reduces the Expected Impact of CTL-Inducing Vaccines for Pandemic Influenza Control

Vaccines that trigger an influenza-specific cytotoxic T cell (CTL) response may aid pandemic control by limiting the transmission of novel influenza A viruses (IAV). We consider interventions with hypothetical CTL-inducing vaccines in a range of epidemiologically plausible pandemic scenarios. We estimate the achievable reduction in the attack rate, and, by adopting a model linking epidemic progression to the emergence of IAV variants, the opportunity for antigenic drift. We demonstrate that CTL-inducing vaccines have limited utility for modifying population-level outcomes if influenza-specific T cells found widely in adults already suppress transmission and prove difficult to enhance. Administration of CTL-inducing vaccines that are efficacious in "influenza-experienced" and "influenza-naive" hosts can likely slow transmission sufficiently to mitigate a moderate IAV pandemic. However if neutralising cross-reactive antibody to an emerging IAV are common in influenza-experienced hosts, as for the swine-variant H3N2v, boosting CTL immunity may be ineffective at reducing population spread, indicating that CTL-inducing vaccines are best used against novel subtypes such as H7N9. Unless vaccines cannot readily suppress transmission from infected hosts with naive T cell pools, targeting influenza-naive hosts is preferable. Such strategies are of enhanced benefit if naive hosts are typically intensively mixing children and when a subset of experienced hosts have pre-existing neutralising cross-reactive antibody. We show that CTL-inducing vaccination campaigns may have greater power to suppress antigenic drift than previously suggested, and targeting adults may be the optimal strategy to achieve this when the vaccination campaign does not have the power to curtail the attack rate. Our results highlight the need to design interventions based on pre-existing cellular immunity and knowledge of the host determinants of vaccine efficacy, and provide a framework for assessing the performance requirements of high-impact CTL-inducing vaccines.     

Cytotoxic T Lymphocytes Established by Seasonal Human Influenza Cross-React against 2009 Pandemic H1N1 Influenza Virus

While few children and young adults have cross-protective antibodies to the pandemic H1N1 2009 (pdmH1N1) virus, the illness remains mild. The biological reasons for these epidemiological observations are unclear. In this study, we demonstrate that the bulk memory cytotoxic T lymphocytes (CTLs) established by seasonal influenza viruses from healthy individuals who have not been exposed to pdmH1N1 can directly lyse pdmH1N1-infected target cells and produce gamma interferon (IFN-γ) and tumor necrosis factor alpha (TNF-α). Using influenza A virus matrix protein 1 (M1_58-66) epitope-specific CTLs isolated from healthy HLA-A2⁺ individuals, we further found that M1_58-66 epitope-specific CTLs efficiently killed both M1_58-66 peptide-pulsed and pdmH1N1-infected target cells ex vivo. These M1_58-66-specific CTLs showed an effector memory phenotype and expressed CXCR3 and CCR5 chemokine receptors. Of 94 influenza A virus CD8 T-cell epitopes obtained from the Immune Epitope Database (IEDB), 17 epitopes are conserved in pdmH1N1, and more than half of these conserved epitopes are derived from M1 protein. In addition, 65% (11/17) of these epitopes were 100% conserved in seasonal influenza vaccine H1N1 strains during the last 20 years. Importantly, seasonal influenza vaccination could expand the functional M1_58-66 epitope-specific CTLs in 20% (4/20) of HLA-A2⁺ individuals. Our results indicated that memory CTLs established by seasonal influenza A viruses or vaccines had cross-reactivity against pdmH1N1. These might explain, at least in part, the unexpected mild pdmH1N1 illness in the community and also might provide some valuable insights for the future design of broadly protective vaccines to prevent influenza, especially pandemic influenza.Since its first identification in North America in April 2009, the novel pandemic H1N1 2009 (pdmH1N1) virus has been spreading in humans worldwide, giving rise to the first pandemic in the 21st century (13, 18). The pdmH1N1 virus contains a unique gene constellation, with its NA and M gene segments being derived from the Eurasian swine lineage while the other gene segments originated from the swine triple-reassortant H1N1 lineage. The triple-reassortant swine viruses have in turn derived the HA, NP, and NS gene segments from the classical swine lineage (20). The 1918 pandemic virus gave rise to both the seasonal influenza H1N1 and the classical swine H1N1 virus lineages (41). Evolution in different hosts during the subsequent 90 years has led to increasing antigenic differences between recent seasonal H1N1 viruses and swine H1 viruses (42). Thus, younger individuals have no antibodies that cross neutralize pdmH1N1, while those over 65 years of age are increasingly likely to have cross-neutralizing antibodies to pdmH1N1 (10, 25).Currently available seasonal influenza vaccines do not induce cross-reactive antibodies against this novel virus in any age group (10, 25). In animal models, it has been shown that pdmH1N1 replicated more efficiently and caused more severe pathological lesions than the current seasonal influenza virus (28). However, most patients with pdmH1N1 virus infection show a mild illness comparable to seasonal influenza (9, 42). The incidence of severe cases caused by pdmH1N1 was not significantly higher than that caused by human seasonal influenza viruses (43). These findings imply that seasonal influenza A virus-specific memory T cells preexisting in previously infected individuals may have cross-protection to this novel pdmH1N1.Cross-reactivity of influenza A virus-specific T-cell immunity against heterosubtypic strains which are serologically distinct has been demonstrated (5, 29, 33, 47). Humans who have not been exposed to avian influenza A (H5N1) virus do have cross-reactive memory CD4 and CD8 T cells to a wide range of H5N1 peptides (33, 47). More recently, one study also showed that some seasonal influenza A virus-specific memory T cells in individuals without exposure to prior pdmH1N1 infection can recognize pdmH1N1 (24). However, the results in most of these studies were determined by the gamma interferon (IFN-γ) responses to influenza virus peptides. Although the recalled IFN-γ response is commonly used to detect memory CD4 and CD8 T cells, the activated T cells that bind major histocompatibility complex (MHC)-presented peptide are not necessarily capable of lysing the target cells (6). In addition, the peptides, but not the whole virus, may not be able to fully represent the human cross-response against the virus as a whole. Therefore, in addition to cytokine production, the demonstration of direct antigen-specific cytotoxicity of cytotoxic T lymphocytes (CTLs) against both peptide-pulsed and virus-infected target cells is needed for better understanding of human CTL responses against pdmH1N1 virus.In this study, using bulk memory CTLs and epitope-specific CTLs established by seasonal influenza A viruses and epitope-specific peptide from healthy individuals, respectively, we evaluated their cross-cytotoxicity and cytokine responses to pdmH1N1. We also examined the expression of chemokine receptors CXCR3 and CCR5, which could help CTLs to migrate to the site of infection. In addition, to understand whether the seasonal influenza vaccines have benefit for people who have not been exposed to pdmH1N1, we further examined the ability of seasonal influenza vaccines to induce the conserved M1_58-66 epitope-specific CTLs in HLA-A2-seropositive healthy individuals.     

Pandemic Influenza H1N1 2009, Innate Immunity,and the Impact of Immunosenescence on Influenza Vaccine

Seasonal and pandemic strains of influenza have widespread implications for the global economy and global health. This has been highlighted recently as the epidemiologic characteristics for hospitalization and mortality for pandemic influenza H1N1 2009 are now emerging. While treatment with neuraminidase inhibitors are effective for seasonal and pandemic influenza, prevention of morbidity and mortality through effective vaccines requires a rigorous process of research and development. Vulnerable populations such as older adults (i.e., > age 65 years) suffer the greatest impact from seasonal influenza yet do not have a consistent seroprotective response to seasonal influenza vaccines due to a combination of factors. This short narrative review will highlight the emerging epidemiologic characteristics of pandemic H1N1 2009 and focus on immunosenescence, innate immune system responses to influenza virus infection and vaccination, and influenza vaccine responsiveness as it relates to seasonal and H1N1 pandemic influenza vaccines.     

Progress and Challenge in Computational Identification of Influenza Virus Reassortment

Virologica Sinica - Genomic reassortment is an important evolutionary mechanism for influenza viruses. In this process, the novel viruses acquire new characteristics by the exchange of the intact...