Roles for Pathogen Interference in Influenza Vaccination, with Implications to Vaccine Effectiveness (VE) and Attribution of Influenza Deaths

Pathogen interference is the ability of one pathogen to alter the course and clinical outcomes of infection by another. With up to 3000 species of human pathogens the potential combinations are vast. These combinations operate within further immune complexity induced by infection with multiple persistent pathogens, and by the role which the human microbiome plays in maintaining health, immune function, and resistance to infection. All the above are further complicated by malnutrition in children and the elderly. Influenza vaccination offers a measure of protection for elderly individuals subsequently infected with influenza. However, all vaccines induce both specific and non-specific effects. The specific effects involve stimulation of humoral and cellular immunity, while the nonspecific effects are far more nuanced including changes in gene expression patterns and production of small RNAs which contribute to pathogen interference. Little is known about the outcomes of vaccinated elderly not subsequently infected with influenza but infected with multiple other non-influenza winter pathogens. In this review we propose that in certain years the specific antigen mix in the seasonal influenza vaccine inadvertently increases the risk of infection from other non-influenza pathogens. The possibility that vaccination could upset the pathogen balance, and that the timing of vaccination relative to the pathogen balance was critical to success, was proposed in 2010 but was seemingly ignored. Persons vaccinated early in the winter are more likely to experience higher pathogen interference. Implications to the estimation of vaccine effectiveness and influenza deaths are discussed.

Effectiveness of the quadrivalent inactivated influenza vaccine in Japan during the 2015-2016 season: A test-negative case-control study comparing the results by real time PCR, virus isolation

Background

We estimated influenza vaccine effectiveness (VE) in 2015–2016 season against medically attended, laboratory-confirmed influenza, when quadrivalent inactivated vaccine (IIV4) was first introduced in Japan, using test-negative case-control design. Influenza A(H1N1)pdm09 cocirculated with B/Yamagata and B/Victoria during the study period in Japan.

Method

We based our case definition on two laboratory tests, real-time reverse transcription polymerase chain reaction (RT PCR), and virus isolation and compared VEs based on these tests. In addition, VE was evaluated by rapid diagnostic test (RDT). Nasopharyngeal swabs were collected from outpatients who visited clinics with influenza-like illness (ILIs) in Hokkaido, Niigata, Gunma and Nagasaki prefectures.

Results

Among 713 children and adults enrolled in this study, 578 were influenza positive by RT PCR including, 392 influenza A and 186 influenza B, while 135 were tested negative controls. The adjusted VE by RT PCR for all ages against any influenza was low protection of 36.0% (95% confidence interval [CI], 3.1% to 58.6%), for influenza A was 30.0% (95% CI: −10.0% to 55.5%), and influenza B was moderate 50.2% (95% CI: 13.3% to 71.4%). Adjusted VE for virus isolation for A(H1N1)pdm09 was 37.1% (95% CI: 1.7% to 59.7%), Yamagata lineage 51.3% (95% CI: 6.4% to 74.7%) and Victoria lineage 21.3% (95% CI: −50.0% to 58.9%). VE was highest and protective in 0–5 years old group against any influenza and influenza A and B/Yamagata, but the protective effect was not observed for other age groups and B/Victoria. RDT demonstrated concordant results with RT PCR and virus isolation. Sequencing of hemagglutinin gene showed that all A(H1N1)pdm09 belong to clade 6B including 31 strains (88.6%), which belong to clade 6B.1 possessing S162N mutations that may alter antigenicity and affect VE for A(H1N1)pdm09.

Conclusions

IIV4 influenza vaccine during 2015–2016 was effective against A(H1N1)pdm09 and the two lineages of type B. Younger children was more protected than older children and adults by vaccination.

Basic principles of test-negative design in evaluating influenza vaccine effectiveness

Based on the unique characteristics of influenza, the concept of "monitoring" influenza vaccine effectiveness (VE) across the seasons using the same observational study design has been developed. In recent years, there has been a growing number of influenza VE reports using the test-negative design, which can minimize both misclassification of diseases and confounding by health care-seeking behavior. Although the test-negative designs offer considerable advantages, there are some concerns that widespread use of the test-negative design without knowledge of the basic principles of epidemiology could produce invalid findings. In this article, we briefly review the basic concepts of the test-negative design with respect to classic study design such as cohort studies or case-control studies. We also mention selection bias, which may be of concern in some countries where rapid diagnostic testing is frequently used in routine clinical practices, as in Japan.

The effectiveness of influenza vaccination in preventing hospitalisations of elderly individuals in two influenza seasons: a multicentre case-control study, Spain, 2013/14 and 2014/15

Influenza vaccination may limit the impact of influenza in the community. The aim of this study was to assess the effectiveness of influenza vaccination in preventing hospitalisation in individuals aged ≥ 65 years in Spain. A multicentre case–control study was conducted in 20 Spanish hospitals during 2013/14 and 2014/15. Patients aged ≥ 65 years who were hospitalised with laboratory-confirmed influenza were matched with controls according to sex, age and date of hospitalisation. Adjusted vaccine effectiveness (VE) was calculated by multivariate conditional logistic regression. A total of 728 cases and 1,826 matched controls were included in the study. Overall VE was 36% (95% confidence interval (CI): 22–47). VE was 51% (95% CI: 15–71) in patients without high-risk medical conditions and 30% (95% CI: 14–44) in patients with them. VE was 39% (95% CI: 20–53) in patients aged 65–79 years and 34% (95% CI: 11–51) in patients aged ≥ 80 years, and was greater against the influenza A(H1N1)pdm09 subtype than the A(H3N2) subtype. Influenza vaccination was effective in preventing hospitalisations of elderly individuals.

Vaccine epidemiology: Its role in promoting sound immunization programs in Japan

In Japan, the Vaccine Epidemiology Research Group created by the Ministry of Health, Labour and Welfare has played an important role in demonstrating the solid scientific basis for vaccine efficacy and safety since 2002. Members of the group, including epidemiologists, clinicians and microbiologists, have been conducting collaborative studies on vaccines for influenza, pertussis, rotavirus gastroenteritis, polio and pneumonia. So far, the group has achieved several works and contributed to the national vaccination program, including research on the immunogenicity of low doses of influenza vaccine among young children, the immunogenicity and effectiveness of the 2009 influenza pandemic vaccine among various risk groups, the interchangeability of live/inactivated polio vaccines, the health impact of influenza on pregnant women, and the monitoring of influenza vaccine effectiveness using case-control studies with a test-negative design. As part of the 18th Annual Meeting of the Japanese Society of Vaccinology, these accomplishments were featured in the Vaccine Epidemiology Symposium. This report summarizes the recent epidemiological studies on vaccine in Japan as a prologue to the next six papers collected from the symposium.

Concordance of interim and final estimates of influenza vaccine effectiveness: a systematic review

The World Health Organization's Global Influenza Surveillance and Response System meets twice a year to generate a recommendation for the composition of the seasonal influenza vaccine. Interim vaccine effectiveness (VE) estimates provide a preliminary indication of influenza vaccine performance during the season and may be useful for decision making. We reviewed 17 pairs of studies reporting 33 pairs of interim and final estimates using the test-negative design to evaluate whether interim estimates can reliably predict final estimates. We examined features of the study design that may be correlated with interim estimates being substantially different from their final estimates and identified differences related to change in study period and concomitant changes in sample size, proportion vaccinated and proportion of cases. An absolute difference of no more than 10% between interim and final estimates was found for 18 of 33 reported pairs of estimates, including six of 12 pairs reporting VE against any influenza, six of 10 for influenza A(H1N1)pdm09, four of seven for influenza A(H3N2) and two of four for influenza B. While we identified inconsistencies in the methods, the similarities between interim and final estimates support the utility of generating and disseminating preliminary estimates of VE while virus circulation is ongoing.

Effectiveness of seasonal influenza vaccination in community-dwelling elderly people: an individual participant data meta-analysis of test-negative design case-control studies

BACKGROUND

Several aggregate data meta-analyses have provided estimates of the effectiveness of influenza vaccination in community-dwelling elderly people. However, these studies ignored the effects of patient-level confounders such as sex, age, and chronic diseases that could bias effectiveness estimates. We aimed to assess the confounder-adjusted effectiveness of influenza vaccines on laboratory-confirmed influenza among elderly people by conducting a global individual participant data meta-analysis.

METHODS

In this individual participant data meta-analysis, we considered studies included in a previously conducted aggregate data meta-analysis that included test-negative design case-control studies published up to July 13, 2014. We contacted all authors of the included studies on Dec 1, 2014, to request individual participant data. Patients were excluded if their unique identifier was missing, their vaccination status was unknown, their outcome status was unknown, or they had had suspected influenza infection more than once in the same influenza season. Cases were patients with influenza-like illness symptoms who tested positive for at least one of A H1N1, A H1N1 pdm09, A H3N2, or B viruses; controls were patients with influenza-like illness symptoms who tested negative for these virus types or subtypes. Influenza vaccine effectiveness against overall and subtype-specific laboratory-confirmed influenza were the primary and secondary outcomes. We used a generalised linear mixed model to calculate adjusted vaccine effectiveness according to vaccine match to the circulating strains of influenza virus and intensity of the virus activity (epidemic or non-epidemic). Vaccine effectiveness was defined as the relative reduction in risk of laboratory-confirmed influenza in vaccinated patients compared with unvaccinated patients. We did subgroup analyses to estimate vaccine effectiveness according to hemisphere, age category, and health status.

FINDINGS

We received 23 of the 53 datasets included in the aggregate data meta-analysis. Furthermore, six additional datasets were provided by data collaborators, which resulted in individual participant data for a total of 5210 participants. A total of 4975 patients had the required data for analysis. Of these, 3146 (63%) were controls and 1829 (37%) were cases. Influenza vaccination was significantly effective during epidemic seasons irrespective of vaccine match status (matched adjusted vaccine effectiveness 44·38%, 95% CI 22·63-60·01; mismatched adjusted vaccine effectiveness 20·00%, 95% CI 3·46-33·68; analyses in the imputed dataset). Seasonal influenza vaccination did not show significant effectiveness during non-epidemic seasons. We found substantial variation in vaccine effectiveness across virus types and subtypes, with the highest estimate for A H1N1 pdm09 (53·19%, 10·25-75·58) and the lowest estimate for B virus types (-1·52%, -39·58 to 26·16). Although we observed no significant differences between subgroups in each category (hemisphere, age, and health status), influenza vaccination showed a protective effect among elderly people with cardiovascular disease, lung disease, or aged 75 years and younger.

INTERPRETATION

Influenza vaccination is moderately effective against laboratory-confirmed influenza in elderly people during epidemic seasons. More research is needed to investigate factors affecting vaccine protection (eg, brand-specific or type-specific vaccine effectiveness and repeated annual vaccination) in elderly people.

FUNDING

University Medical Center Groningen.

Influenza in the Asia-Pacific region: Findings and recommendations from the Global Influenza Initiative

The fourth roundtable meeting of the Global Influenza Initiative (GII) was held in Hong Kong, China, in July 2015. An objective of this meeting was to gain a broader understanding of the epidemiology, surveillance, vaccination policies and programs, and obstacles to vaccination of influenza in the Asia-Pacific region through presentations of data from Australia, Hong Kong, India, Indonesia, Malaysia, New Zealand, the Philippines, Taiwan, Thailand, and Vietnam. As well as a need for improved levels of surveillance in some areas, a range of factors were identified that act as barriers to vaccination in some countries, including differences in climate and geography, logistical challenges, funding, lack of vaccine awareness and education, safety concerns, perceived lack of vaccine effectiveness, and lack of inclusion in national guidelines. From the presentations at the meeting, the GII discussed a number of recommendations for easing the burden of influenza and overcoming the current challenges in the Asia-Pacific region. These recommendations encompass the need to improve surveillance and availability of epidemiological data; the development and publication of national guidelines, where not currently available and/or that are in line with those proposed by the World Health Organization; the requirement for optimal timing of vaccination programs according to local or country-specific epidemiology; and calls for advocacy and government support of vaccination programs in order to improve availability and uptake and coverage. In conclusion, in addition to the varied epidemiology of seasonal influenza across this diverse region, there are a number of logistical and resourcing issues that present a challenge to the development of optimally effective vaccination strategies and that need to be overcome to improve access to and uptake of seasonal influenza vaccines. The GII has developed a number of recommendations to address these challenges and improve the control of influenza.

Seasonal influenza vaccine effectiveness estimates: Development of a parsimonious case test negative model using a causal approach

BACKGROUND

Influenza vaccine effectiveness (VE) is increasingly estimated using the case-test negative study design. Cases have a symptom complex consistent with influenza and test positive for influenza, while non-cases have the same symptom complex but test negative. We aimed to determine a parsimonious logistic regression model for this study design when applied to patients in the community.

METHODS

To determine the minimum covariate set required, we used a previously published systematic review to find covariates and restriction criteria commonly included in case-test negative logistic regression models. Covariates were assessed for inclusion using a directed acyclic graph. We used data from the Victorian Influenza Sentinel Practice Network from 2007 to 2013, excluding the pandemic year of 2009, to test the model. VE was estimated as (1-adjusted OR) * 100%. Changes in model fit from addition of specified covariates were examined. Restriction criteria were examined using change in VE estimate. VE was estimated for each year, all years aggregated, and for influenza type and sub-type.

RESULTS

Using publicly available software, the directed acyclic graph indicated that covariates specifying age, time within the influenza season, immunocompromising comorbid conditions and year or study site, where applicable, were required for closure. The inclusion of sex was not required. Inclusions and exclusions were validated when testing the variables (when collected) with our data. Restriction by time between onset and swab was supported by the data. VE for all years aggregated was estimated as 53% (95%CI 38, 64). VE was estimated as 42% (95%CI 19, 59) for H3N2, 75% (95%CI 51, 88) for H1N1pdm09 and 63% (95%CI 38, 79) for influenza B.

CONCLUSION

Theoretical covariates specified by the directed acyclic graph were validated when tested against surveillance data. A parsimonious model using the case test negative design allows regular estimates of VE and aggregated estimates by year.

Effectiveness of seasonal influenza vaccine in preventing influenza primary care visits and hospitalisation in Auckland, New Zealand in 2015: interim estimates

Preliminary results for influenza vaccine effectiveness (VE) against acute respiratory illness with circulating laboratory-confirmed influenza viruses in New Zealand from 27 April to 26 September 2015, using a case test-negative design were 36% (95% confidence interval (CI): 11–54) for general practice encounters and 50% (95% CI: 20–68) for hospitalisations. VE against hospitalised influenza A(H3N2) illnesses was moderate at 53% (95% CI: 6–76) but improved compared with previous seasons.

Influenza vaccine effectiveness for hospital and community patients using control groups with and without non-influenza respiratory viruses detected, Auckland, New Zealand 2014

BACKGROUND

We aimed to estimate the protection afforded by inactivated influenza vaccine, in both community and hospital settings, in a well characterised urban population in Auckland during 2014.

METHODS

We used two different comparison groups, all patients who tested negative for influenza and only those patients who tested negative for influenza and had a non-influenza respiratory virus detected, to calculate the vaccine effectiveness in a test negative study design. Estimates were made separately for general practice outpatient consultations and hospitalised patients, stratified by age group and by influenza type and subtype. Vaccine status was confirmed by electronic record for general practice patients and all respiratory viruses were detected by real time polymerase chain reaction.

RESULTS

1039 hospitalised and 1154 general practice outpatient consultations met all the study inclusion criteria and had a respiratory sample tested for influenza and other respiratory viruses. Compared to general practice patients, hospitalised patients were more likely to be very young or very old, to be Māori or Pacific Islander, to have a low income and to suffer from chronic disease. Vaccine effectiveness (VE) adjusted for age and other participant characteristics using all influenza negative controls was 42% (95% CI: 16 to 60%) for hospitalised and 56% (95% CI: 35 to 70%) for general practice patients. The vaccine appeared to be most effective against the influenza A(H1N1)pdm09 strain with an adjusted VE of 62% (95% CI:38 to 77%) for hospitalised and 59% (95% CI:36 to 74%) for general practice patients, using influenza virus negative controls. Similar results found when patients testing positive for a non-influenza respiratory virus were used as the control group.

CONCLUSION

This study contributes to validation of the test negative design and confirms that inactivated influenza vaccines continue to provide modest but significant protection against laboratory-confirmed influenza.

Integrated Sentinel Surveillance Linking Genetic, Antigenic, and Epidemiologic Monitoring of Influenza Vaccine-Virus Relatedness and Effectiveness During the 2013-2014 Influenza Season

BACKGROUND

Canada's Sentinel Physician Surveillance Network links genetic, antigenic, and vaccine effectiveness (VE) measures in an integrated platform of influenza monitoring, described here for the 2013-2014 influenza season of resurgent A(H1N1)pdm09 and late-season type B activity.

METHODS

VE was estimated as [1 - odds ratio] × 100% and compared vaccination status between individuals who tested positive (cases) and those who tested negative (controls) for influenza virus. Vaccine-virus relatedness was assessed by genomic sequence analysis and hemagglutination inhibition assays.

RESULTS

Analyses included 1037 controls (of whom 33% were vaccinated) and 663 cases (of whom 14% were vaccinated). A total of 415 cases tested positive for A(H1N1)pdm09 virus, 15 tested positive for A(H3N2) virus, 191 tested positive for B/Yamagata-lineage virus, 6 tested positive for B/Victoria-lineage virus, and 36 tested positive for viruses of unknown subtype or lineage. A(H1N1)pdm09 viruses belonged to clade 6B, distinguished by a K163Q substitution, but remained antigenically similar to the A/California/07/2009-like vaccine strain, with an adjusted VE of 71% (95% confidence interval [CI], 58%-80%). Most B/Yamagata-lineage viruses (83%) clustered phylogenetically with the prior (ie, 2012-2013) season's B/Wisconsin/01/2010-like clade 3 vaccine strain, while only 17% clustered with the current (ie, 2013-2014) season's B/Massachusetts/02/2012-like clade 2 vaccine strain. The adjusted VE for B/Yamagata-lineage virus was 73% (95% CI, 57%-84%), with a lower VE obtained after partial calendar-time adjustment for clade-mismatched B/Wisconsin/01/2010-like virus (VE, 63%; 95% CI, 41%-77%), compared with that for clade-matched B/Massachusetts/02/2012-like virus (VE, 88%; 95% CI, 48%-97%). No A(H3N2) viruses clustered with the A/Texas/50/2012-like clade 3C.1 vaccine strain, and more than half were antigenically mismatched, but sparse data did not support VE estimation.

CONCLUSIONS

VE corresponded with antigenically conserved A(H1N1)pdm09 and lineage-matched B/Yamagata viruses with clade-level variation. Surveillance linking genotypic, phenotypic, and epidemiologic measures of vaccine-virus relatedness and effectiveness could better inform predictions of vaccine performance and reformulation.