Impact of viral drift on vaccination dynamics and patterns of seasonal influenza

Rates of SARS-CoV-2 transmission and vaccination impact the fate of vaccine-resistant strains

Vaccines are thought to be the best available solution for controlling the ongoing SARS-CoV-2 pandemic. However, the emergence of vaccine-resistant strains may come too rapidly for current vaccine developments to alleviate the health, economic and social consequences of the pandemic. To quantify and characterize the risk of such a scenario, we created a SIR-derived model with initial stochastic dynamics of the vaccine-resistant strain to study the probability of its emergence and establishment. Using parameters realistically resembling SARS-CoV-2 transmission, we model a wave-like pattern of the pandemic and consider the impact of the rate of vaccination and the strength of non-pharmaceutical intervention measures on the probability of emergence of a resistant strain. As expected, we found that a fast rate of vaccination decreases the probability of emergence of a resistant strain. Counterintuitively, when a relaxation of non-pharmaceutical interventions happened at a time when most individuals of the population have already been vaccinated the probability of emergence of a resistant strain was greatly increased. Consequently, we show that a period of transmission reduction close to the end of the vaccination campaign can substantially reduce the probability of resistant strain establishment. Our results suggest that policymakers and individuals should consider maintaining non-pharmaceutical interventions and transmission-reducing behaviours throughout the entire vaccination period.

Projecting influenza vaccine effectiveness: A simulation study

The impact of influenza vaccination is largely measured by estimating vaccine effectiveness (VE), which vary in different seasons. Strain mutations and waning immunity present two key mechanisms affecting VE. We sought to quantify the relative effect of these mechanisms by projecting VE and the reduction of illness due to vaccination. We developed a stochastic age-structured agent-based simulation model of influenza transmission dynamics to encapsulate intraseason waning of immunity post-vaccination, and mutation-induced antigenic distance between circulating strains and vaccine strains. Parameterizing the model with published estimates, we projected the temporal and overall VE during an epidemic season, and estimated the reduction of infection for high (70%) and low (30%) vaccine efficacies to reflect the levels of vaccine-induced protection in randomized control trials. Both temporal and overall VE decreased as the attack rate increased, with lower median values for epidemics starting with strains that were antigenically more distant from vaccine strains. We observed a higher rate of temporal decline with considerably lower median values of the overall VE in the presence of intraseason waning of immunity compared with only the antigenic distance effect. The highest benefit of vaccination in preventing influenza infection was achieved at moderate attack rates in the range of 6%-15%. The results show that even when VE is relatively low in the population and almost negligible for older age groups (i.e., 50+ years), vaccination can still prevent significant illness in high-risk individuals; thereby reducing healthcare resource utilization and economic burden. Our study indicates that early vaccination remains an important strategy for alleviating the burden of seasonal influenza. Policy discussions on optimal timing of vaccination to reduce the effect of intraseason waning of immunity should be considered in the context of strain mutations within the epidemic course.

On the influenza vaccination policy through mathematical modeling

OBJECTIVES

Aimed at mitigating influenza transmission, this study assessed the timing of the vaccination program and took vaccine capacity, strain mismatch and priority group into consideration.

METHODS

An age-structured dynamic transmission model was fitted to the laboratory data of the national influenza surveillance system to reconstruct a baseline scenario with which the vaccination scenarios of interest could be compared. Outcome measures were defined as the impacts on the seasonal epidemic: decompression of the epidemic peak, reduction of the epidemic burden and change of the epidemic peak time.

RESULTS

It was found that vaccine capacity building, although indispensable, could not guarantee substantial impact on the seasonal influenza epidemic. Vaccine mismatch might greatly offset vaccine capacity building. Notably, advance vaccine distribution could compensate for some vaccine underperformance. In the case of a well-matched vaccine, advance vaccine distribution could even exploit its utility.

CONCLUSIONS

This study indicated that timely vaccine distribution should be put high on the agenda of seasonal influenza control policies. It provided a tangible platform for the policymakers to evaluate health policy impacts and to enhance risk communication with the public through mathematical modeling.

Modelling epidemics with fractional-dose vaccination in response to limited vaccine supply

The control strategies of emergency infectious diseases are constrained by limited medical resources. The fractional dose vaccination strategy as one of feasible strategies was proposed in response to global shortages of vaccine stockpiles. Although a variety of epidemic models have been developed under the circumstances of limited resources in treatment, few models particularly investigated vaccination strategies in resource-limited settings. In this paper, we develop a two-group SIR model with incorporation of proportionate mixing patterns and n-fold fractional dose vaccination related parameters to evaluate the efficiency of fractional dose vaccination on disease control at the population level. The existence and uniqueness of the final size of the two-group SIR epidemic model, the formulation of the basic reproduction number and the relationship between them are established. Moreover, numerical simulations are performed based on this two-group vector-free model to investigate the effectiveness of n-fold fractional dose vaccination by using the emergency outbreaks of yellow fever in Angola in 2016. By employing linear and nonlinear dose-response relationships, we compare the resulting fluctuations of four characteristics of the epidemics, which are the outbreak size, the peak time of the outbreak, the basic reproduction number and the infection attack rate (IAR). For both types of dose-response relationships, dose-fractionation takes positive effects in lowering the outbreak size, delay the peak time of the outbreak, reducing the basic reproduction number and the IAR of yellow fever only when the vaccine efficacy is high enough. Moreover, five-fold fractional dose vaccination strategy may not be the optimal vaccination strategy as proposed by the World Health Organization if the dose-response relationship is nonlinear.

Elicitation of Protective Antibodies against 20 Years of Future H3N2 Cocirculating Influenza Virus Variants in Ferrets Preimmune to Historical H3N2 Influenza Viruses

The vast majority of people already have preexisting immune responses to influenza viruses from one or more subtypes. However, almost all preclinical studies evaluate new influenza vaccine candidates in immunologically naive animals. Recently, our group demonstrated that priming naive ferrets with broadly reactive H1 COBRA HA-based vaccines boosted preexisting antibodies induced by wild-type H1N1 virus infections. These H1 COBRA hemagglutinin (HA) antigens induced antibodies with HAI activity against multiple antigenically different H1N1 viral variants. In this study, ferrets, preimmune to historical H3N2 viruses, were vaccinated with virus-like particle (VLP) vaccines expressing either an HA from a wild-type H3 influenza virus or a COBRA H3 HA antigen (T6, T7, T10, or T11). The elicited antisera had the ability to neutralize virus infection against either a panel of viruses representing vaccine strains selected by the World Health Organization or a set of viral variants that cocirculated during the same time period. Preimmune animals vaccinated with H3 COBRA T10 HA antigen elicited sera with higher hemagglutination inhibition (HAI) antibody titers than antisera elicited by VLP vaccines with wild-type HA VLPs in preimmune ferrets. However, while the T11 COBRA vaccine did not elicit HAI activity, the elicited antibodies did neutralize antigenically distinct H3N2 influenza viruses. Overall, H3 COBRA-based HA vaccines were able to neutralize both historical H3 and contemporary, as well as future, H3N2 viruses with higher titers than vaccines with wild-type H3 HA antigens. This is the first report demonstrating the effectiveness of a broadly reactive H3N3 vaccine in a preimmune ferret model.IMPORTANCE After exposure to influenza virus, the host generates neutralizing anti-hemagglutinin (anti-HA) antibodies against that specific infecting influenza strain. These antibodies can also neutralize some, but not all, cocirculating strains. The goal of next-generation influenza vaccines, such as HA head-based COBRA, is to stimulate broadly protective neutralizing antibodies against all strains circulating within a subtype, in particular those that persist over multiple influenza seasons, without requiring an update to the vaccine. To mimic the human condition, COBRA HA virus-like particle vaccines were tested in ferrets that were previously exposed to historical H3N2 influenza viruses. In this model, these vaccines elicited broadly protective antibodies that neutralized cocirculating H3N2 influenza viruses isolated over a 20-year period. This is the first study to show the effectiveness of H3N3 COBRA HA vaccines in a host with preexisting immunity to influenza.

Risk of influenza infection with low vaccine effectiveness: the role of avoidance behaviour

Low vaccine-effectiveness has been recognised as a key factor undermining efforts to improve strategies and uptake of seasonal influenza vaccination. Aiming to prevent disease transmission, vaccination may influence the perceived risk-of-infection and, therefore, alter the individual-level behavioural responses, such as the avoidance of contact with infectious cases. We asked how the avoidance behaviour of vaccinated individuals changes disease dynamics, and specifically the epidemic size, in the context of imperfect vaccination. For this purpose, we developed an agent-based simulation model, and parameterised it with published estimates and relevant databases for population demographics and agent characteristics. Encapsulating an age-stratified structure, we evaluated the per-contact risk-of-infection and estimated the epidemic size. Our results show that vaccination could lead to a larger epidemic size if the level of avoidance behaviour in vaccinated individuals reduces below that of susceptible individuals. Furthermore, the risk-of-infection in vaccinated individuals, which follows the pattern of age-dependent frailty index of the population, increases for older age groups, and may reach, or even exceed, the risk-of-infection in susceptible individuals. Our findings indicate that low engagement in avoidance behaviour can potentially offset the benefits of vaccination even for vaccines with high effectiveness. While highlighting the protective effects of vaccination, seasonal influenza immunisation programmes should enhance strategies to promote avoidance behaviour despite being vaccinated.

Computationally Optimized Broadly Reactive Hemagglutinin Elicits Hemagglutination Inhibition Antibodies against a Panel of H3N2 Influenza Virus Cocirculating Variants

Each influenza season, a set of wild-type viruses, representing one H1N1, one H3N2, and one to two influenza B isolates, are selected for inclusion in the annual seasonal influenza vaccine. In order to develop broadly reactive subtype-specific influenza vaccines, a methodology called computationally optimized broadly reactive antigens (COBRA) was used to design novel hemagglutinin (HA) vaccine immunogens. COBRA technology was effectively used to design HA immunogens that elicited antibodies that neutralized H5N1 and H1N1 isolates. In this report, the development and characterization of 17 prototype H3N2 COBRA HA proteins were screened in mice and ferrets for the elicitation of antibodies with HA inhibition (HAI) activity against human seasonal H3N2 viruses that were isolated over the last 48 years. The most effective COBRA HA vaccine regimens elicited antibodies with broader HAI activity against a panel of H3N2 viruses than wild-type H3 HA vaccines. The top leading COBRA HA candidates were tested against cocirculating variants. These variants were not efficiently detected by antibodies elicited by the wild-type HA from viruses selected as the vaccine candidates. The T-11 COBRA HA vaccine elicited antibodies with HAI and neutralization activity against all cocirculating variants from 2004 to 2007. This is the first report demonstrating broader breadth of vaccine-induced antibodies against cocirculating H3N2 strains compared to the wild-type HA antigens that were represented in commercial influenza vaccines.IMPORTANCE There is a need for an improved influenza vaccine that elicits immune responses that recognize a broader number of influenza virus strains to prevent infection and transmission. Using the COBRA approach, a set of vaccines against influenza viruses in the H3N2 subtype was tested for the ability to elicit antibodies that neutralize virus infection against not only historical vaccine strains of H3N2 but also a set of cocirculating variants that circulated between 2004 and 2007. Three of the H3N2 COBRA vaccines recognized all of the cocirculating strains during this era, but the chosen wild-type vaccine strains were not able to elicit antibodies with HAI activity against these cocirculating strains. Therefore, the COBRA vaccines have the ability to elicit protective antibodies against not only the dominant vaccine strains but also minor circulating strains that can evolve into the dominant vaccine strains in the future.

Variation in loss of immunity shapes influenza epidemics and the impact of vaccination

BACKGROUND

Protective antibody immunity against the influenza A virus wanes in 2-7 years due to antigenic drift of the virus' surface proteins. The duration of immune protection is highly variable because antigenic evolution of the virus is irregular. Currently, the variable nature of the duration of immunity has had little attention in analyses of the impact of vaccination, including cost-effectiveness studies.

METHODS

We developed a range of mathematical transmission models to investigate the effect of variable duration of immunity on the size of seasonal epidemics. The models range from simple conceptual to more realistic, by distinguishing between infection- versus vaccination-induced immunity, by inclusion of primary vaccine failure, by assuming a leaky vaccine, and by the inclusion of age-dependent contact patterns.

RESULTS

We show that annual variation in the duration of immunity causes large variation in the size of epidemics, and affects the effectiveness of vaccination. Accumulation of susceptible individuals in one or more mild seasons results in a disproportionately large outbreak in a subsequent season. Importantly, variation in the duration of immunity increases the average infection attack rate when the vaccination coverage is around the outbreak threshold. Specifically, in a tailored age-stratified model with a realistic reproduction number (R ₀ = 1.4) and vaccination coverage of 25%, we find that the attack rate in unvaccinated children (<10 years old) is negligible if the duration of immunity is constant, while on average 2.8% (2.5-97.5% percentiles: 1.8-4.1%) of the children are infected if the duration of immunity is variable. These findings stem from the buildup of susceptibility over multiple seasons by waning of immunity, and the nonlinear relation between susceptibility and infection attack rates.

CONCLUSIONS

The models illustrate that variation in the duration of immunity impacts the long-term effectiveness of vaccination, and that vaccine effectiveness cannot be judged for each year in isolation. Our findings have implications for vaccination strategies that aim to maximize the vaccination coverage while extending the age range of persons eligible for vaccination.

Explanations for Not Receiving the Seasonal Influenza Vaccine: An Ontario Canada Based Survey

Despite evidence of the importance of the seasonal influenza vaccine for both individual and population health, only a third of the Ontario population received the vaccine in 2013/2014. The objective of this study was to identify why Ontarians are not getting the seasonal influenza vaccine. Written responses to the question "Why didn't you get the seasonal flu vaccine in the last flu season?" were deductively analyzed using the Conceptual Model of Vaccine Hesitancy. Inductive coding was also conducted to identify explanations that fall outside of the present model and may be unique to the seasonal influenza vaccine. Data were collected between August and early September, 2014 through a survey in the Region of Waterloo, Ontario. Overall, 91.4% of responses could be explained using the conceptual model and specifically relate to perceived importance of vaccination (46.8%), moral convictions (19.4%), and past experiences with vaccinations services (14.5%). Notably, explanations related to healthcare professional attitudes, risk perceptions and trust, and subjective norms were identified to a much lesser extent than those discussed above. The remaining 8.6% of responses cannot be explained by the model because they do not relate to hesitancy. Our data contribute to the minimal body of Canadian research investigating low uptake of the seasonal flu vaccine, adding to an evidence-base upon which to inform promotional campaigns. Our data also highlight the utility of the Conceptual Model of Vaccine Hesitancy for the design and analysis of research investigating seasonal flu vaccine refusal or delay.

Use of computational and recombinant technologies for developing novel influenza vaccines

Influenza vaccine design has changed considerably with advancements in bioinformatics and computational biology. Improved surveillance efforts provide up-to-date information about influenza sequence diversity and assist with monitoring the spread of epidemics and vaccine efficacy rates. The advent of next-generation sequencing, epitope scanning and high-throughput analysis all help decipher influenza-associated protein interactions as well as predict immune responsiveness based on host genetic diversity. Computational approaches are utilized in nearly all aspects of vaccine design, from modeling, compatibility predictions, and optimization of antigens in various platforms. This overview discusses how computational techniques strengthen vaccine efforts against highly diverse influenza species.

The coexistence or replacement of two subtypes of influenza

A pandemic subtype of influenza A sometimes replaces but sometimes coexists with the previous seasonal subtype. For example, the 1957 pandemic subtype H2N2 replaced the seasonal subtype H1N1; whereas after 1977 subtypes H1N1 (from the pandemic) and H3N2 continue to coexist. In an attempt to understand these alternatives, a hybrid model for the dynamics of influenza A is formulated. During an epidemic season the model takes into account cross-immunity of strains depending on the most recent seasonal infection. This cross-immunity reduces susceptibility to related strains of the seasonal subtype, and wanes with time due to virus drift. The population is assumed to reach an equilibrium distribution in susceptibility after several seasons, and then a pandemic subtype appears. Individuals who have been infected by the seasonal subtype all have the same cross-immunity to the pandemic subtype. A combination of theoretical and numerical analyses shows that for very strong cross-immunity between the subtypes the pandemic cannot invade, whereas for strong and weak cross-immunity there is coexistence for the season following the pandemic, and for intermediate levels of cross-immunity the pandemic may replace the seasonal subtype. This replacement depends on the basic reproduction numbers of seasonal and pandemic influenza. Vaccination against the seasonal subtype is found to slightly increase this range for pandemic replacement, with the range increasing with increasing vaccine protection and with the length of time that vaccine-induced immunity lasts.

The Possible Impact of Vaccination for Seasonal Influenza on Emergence of Pandemic Influenza via Reassortment

BACKGROUND

One pathway through which pandemic influenza strains might emerge is reassortment from coinfection of different influenza A viruses. Seasonal influenza vaccines are designed to target the circulating strains, which intuitively decreases the prevalence of coinfection and the chance of pandemic emergence due to reassortment. However, individual-based analyses on 2009 pandemic influenza show that the previous seasonal vaccination may increase the risk of pandemic A(H1N1) pdm09 infection. In view of pandemic influenza preparedness, it is essential to understand the overall effect of seasonal vaccination on pandemic emergence via reassortment.

METHODS AND FINDINGS

In a previous study we applied a population dynamics approach to investigate the effect of infection-induced cross-immunity on reducing such a pandemic risk. Here the model was extended by incorporating vaccination for seasonal influenza to assess its potential role on the pandemic emergence via reassortment and its effect in protecting humans if a pandemic does emerge. The vaccination is assumed to protect against the target strains but only partially against other strains. We find that a universal seasonal vaccine that provides full-spectrum cross-immunity substantially reduces the opportunity of pandemic emergence. However, our results show that such effectiveness depends on the strength of infection-induced cross-immunity against any novel reassortant strain. If it is weak, the vaccine that induces cross-immunity strongly against non-target resident strains but weakly against novel reassortant strains, can further depress the pandemic emergence; if it is very strong, the same kind of vaccine increases the probability of pandemic emergence.

CONCLUSIONS

Two types of vaccines are available: inactivated and live attenuated, only live attenuated vaccines can induce heterosubtypic immunity. Current vaccines are effective in controlling circulating strains; they cannot always help restrain pandemic emergence because of the uncertainty of the oncoming reassortant strains, however. This urges the development of universal vaccines for prevention of pandemic influenza.