Assessment of Virus Interference in a Test-negative Study of Influenza Vaccine Effectiveness

Specific and Nonspecific Effects of Influenza Vaccines

With the introduction of the influenza vaccine in the official immunization schedule of most countries, several data regarding the efficacy, tolerability, and safety of influenza immunization were collected worldwide. Interestingly, together with the confirmation that influenza vaccines are effective in reducing the incidence of influenza virus infection and the incidence and severity of influenza disease, epidemiological data have indicated that influenza immunization could be useful for controlling antimicrobial resistance (AMR) development. Knowledge of the reliability of these findings seems essential for precise quantification of the clinical relevance of influenza immunization. If definitively confirmed, these findings can have a relevant impact on influenza vaccine development and use. Moreover, they can be used to convince even the most recalcitrant health authorities of the need to extend influenza immunization to the entire population. In this narrative review, present knowledge regarding these particular aspects of influenza immunization is discussed. Literature analysis showed that the specific effects of influenza immunization are great enough per se to recommend systematic annual immunization of younger children, old people, and all individuals with severe chronic underlying diseases. Moreover, influenza immunization can significantly contribute to limiting the emergence of antimicrobial resistance. The problem of the possible nonspecific effects of influenza vaccines remains unsolved. The definition of their role as inducers of trained immunity seems essential not only to evaluate how much they play a role in the prevention of infectious diseases but also to evaluate whether they can be used to prevent and treat clinical conditions in which chronic inflammation and autoimmunity play a fundamental pathogenetic role.

An overview on viral interference during SARS-CoV-2 pandemic

Respiratory viruses represent the most frequent cause of mortality, morbidity and high healthcare costs for emergency visits and hospitalization in the pediatric age. Respiratory viruses can circulate simultaneously and can potentially infect the same host, determining different types of interactions, the so-called viral interference. The role of viral interference has assumed great importance since December 2019, when the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) came on the scene. The aim of this narrative review is to present our perspective regarding research in respiratory virus interference and discuss recent advances on the topic because, following SARS-CoV-2 restrictions mitigation, we are experimenting the co-circulation of respiratory viruses along with SARS-CoV-2. This scenario is raising many concerns about possible virus-virus interactions, both positive and negative, and the clinical, diagnostic and therapeutic management of these coinfections. Moreover, we cannot rule out that also climatic conditions and social behaviours are involved. Thus, this situation can lead to different population epidemic dynamics, including changes in the age of the targeted population, disease course and severity, highlighting the need for prospective epidemiologic studies and mathematical modelling able to predict the timing and magnitude of epidemics caused by SARS-CoV-2/seasonal respiratory virus interactions in order to adjust better public health interventions.

Effect of monovalent COVID-19 vaccines on viral interference between SARS-CoV-2 and several DNA viruses in patients with long-COVID syndrome

Epstein-Barr virus (EBV) reactivation may be involved in long-COVID symptoms, but reactivation of other viruses as a factor has received less attention. Here we evaluated the reactivation of parvovirus-B19 and several members of the Herpesviridae family (DNA viruses) in patients with long-COVID syndrome. We hypothesized that monovalent COVID-19 vaccines inhibit viral interference between SARS-CoV-2 and several DNA viruses in patients with long-COVID syndrome, thereby reducing clinical symptoms. Clinical and laboratory data for 252 consecutive patients with PCR-verified past SARS-CoV-2 infection and long-COVID syndrome (155 vaccinated and 97 non-vaccinated) were recorded during April 2021-May 2022 (median 243 days post-COVID-19 infection). DNA virus-related IgG and IgM titers were compared between vaccinated and non-vaccinated long-COVID patients and with age- and sex-matched non-infected, unvaccinated (pan-negative for spike-antibody) controls. Vaccination with monovalent COVID-19 vaccines was associated with significantly less frequent fatigue and multiorgan symptoms (p < 0.001), significantly less cumulative DNA virus-related IgM positivity, significantly lower levels of plasma IgG subfractions 2 and 4, and significantly lower quantitative cytomegalovirus IgG and IgM and EBV IgM titers. These results indicate that anti-SARS-CoV-2 vaccination may interrupt viral cross-talk in patients with long-COVID syndrome (ClinicalTrials.gov Identifier: NCT05398952).

Outcomes of COVID-19 Infection in People Previously Vaccinated Against Influenza: Population-Based Cohort Study Using Primary Health Care Electronic Records

BACKGROUND

A possible link between influenza immunization and susceptibility to the complications of COVID-19 infection has been previously suggested owing to a boost in the immunity against SARS-CoV-2.

OBJECTIVE

This study aimed to investigate whether individuals with COVID-19 could have benefited from vaccination against influenza. We hypothesized that the immunity resulting from the previous influenza vaccination would boost part of the immunity against SARS-CoV-2.

METHODS

We performed a population-based cohort study including all patients with COVID-19 with registered entries in the primary health care (PHC) electronic records during the first wave of the COVID-19 pandemic (March 1 to June 30, 2020) in Catalonia, Spain. We compared individuals who took an influenza vaccine before being infected with COVID-19, with those who had not taken one. Data were obtained from Information System for Research in Primary Care, capturing PHC information of 5.8 million people from Catalonia. The main outcomes assessed during follow-up were a diagnosis of pneumonia, hospital admission, and mortality.

RESULTS

We included 309,039 individuals with COVID-19 and compared them on the basis of their influenza immunization status, with 114,181 (36.9%) having been vaccinated at least once and 194,858 (63.1%) having never been vaccinated. In total, 21,721 (19%) vaccinated individuals and 11,000 (5.7%) unvaccinated individuals had at least one of their outcomes assessed. Those vaccinated against influenza at any time (odds ratio [OR] 1.14, 95% CI 1.10-1.19), recently (OR 1.13, 95% CI 1.10-1.18), or recurrently (OR 1.10, 95% CI 1.05-1.15) before being infected with COVID-19 had a higher risk of presenting at least one of the outcomes than did unvaccinated individuals. When we excluded people living in long-term care facilities, the results were similar.

CONCLUSIONS

We could not establish a protective role of the immunity conferred by the influenza vaccine on the outcomes of COVID-19 infection, as the risk of COVID-19 complications was higher in vaccinated than in unvaccinated individuals. Our results correspond to the first wave of the COVID-19 pandemic, where more complications and mortalities due to COVID-19 had occurred. Despite that, our study adds more evidence for the analysis of a possible link between the quality of immunity and COVID-19 outcomes, particularly in the PHC setting.

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.

How influenza vaccination and virus interference may impact combined influenza-coronavirus disease burden

Demand for influenza vaccine rose as countries prepared for the second COVID-19 wave over the winter months of 2020-2021. High coverage of the influenza vaccine can significantly reduce morbidity and mortality of the burden of influenza. Natural influenza infection creates short-term non-specific immunity against respiratory viruses (virus interference). We model two viral diseases, both of the SEIR type, to investigate whether the influenza vaccine increases the combined disease burden of influenza and COVID-19 in a dual outbreak. We show that the combined disease burden’s behavior depends on virus interference factors and the proportion of the population vaccinated against influenza. Our results indicate that influenza vaccination only lowers the overall disease burden when net virus interference is relatively low.

Influenza Vaccine Effectiveness Estimates among US Department of Defense Adult Beneficiaries over Four Consecutive Influenza Seasons: A Test-Negative Design Study with Different Control Groups

A test-negative design study with different control groups (influenza test-negative controls, non-influenza virus positive controls, and pan-negative controls) was conducted to assess inactivated influenza vaccine effectiveness (VE) in adults aged ≥18 years, 2016-2017 through 2019-2020 influenza seasons. A database was developed from the US Department of Defense Global Respiratory Pathogen Surveillance Program. VE was estimated using a generalized linear mixed model with logit link and binomial distribution, adjusted for confounding effects. A total of 7114 adults including 2543 medically attended, laboratory-confirmed influenza-positive cases were identified. Using influenza test-negative controls, the adjusted VE in adults was 40% [95% confidence interval (CI): 33-46%] overall, including 46% (95% CI: 36-55%) for influenza A(H1N1)pdm09, 32% (95% CI: 19-42%) for influenza A(H3N2), and 54% (95% CI: 44-62%) for influenza B. The age-stratified analysis showed that VE estimates against influenza A(H1N1)pdm09 (34%; 95% CI: -29-66%) and influenza A(H3N2) (6%; 95% CI: -60-45%) were low and non-significant for elderly adults ≥65 years of age. Overall VE estimates against any influenza or by influenza (sub)types in adults were consistent when using influenza test-negative controls, non-influenza virus positive controls, and pan-negative controls. Inactivated influenza vaccination provided moderate protection against influenza virus infection, based on the analysis from a large number of adults aged ≥18 years over multiple influenza seasons.

Effect of influenza vaccine on COVID-19 mortality: a retrospective study

It has been proposed that vaccines may exert an unspecific protective effect against infectious agents, different than expected. Coronavirus disease 2019 (COVID-19) is a pandemic infection with high mortality in older patients due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The high number of vaccinations may be one of the reasons why children show a lower susceptibility to SARS-CoV-2 infection and milder severity when compared to adults. We have designed a study aimed at investigating whether the influenza vaccine may reduce the susceptibility and severity of SARS-CoV-2 infection. We retrospectively enrolled 635 patients who accessed our Emergency Department from March 1st to June 30th, 2020, and were diagnosed with COVID-19 infection confirmed by an RT-PCR on an oropharyngeal swab. Clinical data, outcomes, and influenza vaccination status were collected from the electronic medical records of our Hospital. We also used data from the Italian Health Ministry to compare the prevalence of flu vaccination among the general population of the Lazio Region and our enrolled patients. We then compared clinical outcomes between vaccinated and non-vaccinated patients, by univariate and multivariate analysis. COVID-19-positive patients older than 65 years reported a lower prevalence of flu vaccination when compared to the general population residing in the Lazio (p = 0.004). After correction for gender, age, and comorbidities, we found a lower risk of death at 60 days in patients with flu vaccination than in not vaccinated patients (p = 0.001). Our study shows that flu vaccination could reduce the mortality of COVID-19. Prospective studies are needed to confirm this result.

Assessing the impact of acute respiratory illnesses on the risk of subsequent respiratory illness

BACKGROUND

Whether acute respiratory illnesses (ARIs), often associated with virus detection, are associated with lower risk for subsequent ARI remains unclear. We assessed the association between symptomatic ARI and subsequent ARI in young children.

METHODS

In a prospective cohort of Peruvian children <3 years, we examined the impact of index ARI on subsequent ARI risk. Index ARI were matched with ≤3 asymptomatic observations and followed over 28 days. We compared risk of subsequent ARI between groups using conditional logistic regression adjusting for several covariates, accounting for repeat observations from individual children.

RESULTS

Among 983 index ARI, 339 (34%) had an ARI event during follow-up, compared with 876/2826 (31%) matched asymptomatic observations. We found no significant association of index ARI and subsequent ARI risk during follow-up overall (aOR 1.10, 95% CI 0.98, 1.23) or when limited to index ARI with respiratory viruses detected (aOR 1.03, 95% CI 0.86, 1.24). Similarly, when the outcome was limited to ARI in which viruses were detected, no significant association was seen (aOR 1.05, 95% CI 0.87, 1.27).

DISCUSSION

ARIs were not associated with short-term protection against subsequent ARI in these children. Additional longitudinal studies are needed to understand drivers of recurrent ARI in young children.

The Effect of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Mitigation Strategies on Seasonal Respiratory Viruses: A Tale of 2 Large Metropolitan Centers in the United States

To assess the impact of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on seasonal respiratory viruses, absolute case counts and viral reproductive rates from 2019-2020 were compared against previous seasons. Our findings suggest that the public health measures implemented to reduce SARS-CoV-2 transmission significantly reduced the transmission of other respiratory viruses.

Interim 2019/2020 Influenza Vaccine Effectiveness in Japan from October 2019 to January 2020

Herein, we report the interim vaccine effectiveness (VE) of a quadrivalent inactivated influenza vaccine, during the 2019/2020 influenza season, in Japan. We conducted a retrospective observational cohort study of 381 patients aged ≥15 years, who were enrolled with influenza like illnesses and examined via the rapid influenza diagnostic test, at the Ambulatory Care unit of the National Center for Global Health and Medicine in Tokyo, Japan, from the beginning of October 2019 to the end of January 2020. VE was estimated using a test-negative design. VE was calculated as (1 - odds ratio) × 100%, comparing influenza A test positivity between vaccinated and unvaccinated patients. Of the 381 patients initially screened for inclusion, 314 were enrolled in the study. Of these, 105 were vaccinated, 98 were diagnosed with influenza A, and 5 were diagnosed with influenza B. Overall VE against influenza A was 27.6% (95% confidence interval [CI], ‒21.1 to +57.4), and in patients aged ≥65 years, it was 47.3% (95% CI, ‒76.0 to +86.0). This indicates that the influenza vaccination offered continued protection during the 2019/2020 influenza season, but a detailed analysis of more cases with a careful consideration of methodology is necessary to estimate VE more precisely.

Influenza Vaccine Effectiveness in the Inpatient Setting: Evaluation of Potential Bias in the Test-Negative Design by Use of Alternate Control Groups

The test-negative design is validated in outpatient, but not inpatient, studies of influenza vaccine effectiveness. The prevalence of chronic pulmonary disease among inpatients can lead to nonrepresentative controls. Test-negative design estimates are biased if vaccine administration is associated with incidence of noninfluenza viruses. We evaluated whether control group selection and effects of vaccination on noninfluenza viruses biased vaccine effectiveness in our study. Subjects were enrolled at the University of Michigan and Henry Ford hospitals during the 2014-2015 and 2015-2016 influenza seasons. Patients presenting with acute respiratory infection were enrolled and tested for respiratory viruses. Vaccine effectiveness was estimated using 3 control groups: negative for influenza, positive for other respiratory virus, and pan-negative individuals; it was also estimated for other common respiratory viruses. In 2014-2015, vaccine effectiveness was 41.1% (95% CI: 1.7, 64.7) using influenza-negative controls, 24.5% (95% CI: -42.6, 60.1) using controls positive for other virus, and 45.8% (95% CI: 5.7, 68.9) using pan-negative controls. In 2015-2016, vaccine effectiveness was 68.7% (95% CI: 44.6, 82.5) using influenza-negative controls, 63.1% (95% CI: 25.0, 82.2) using controls positive for other virus, and 71.1% (95% CI: 46.2, 84.8) using pan-negative controls. Vaccination did not alter odds of other respiratory viruses. Results support use of the test-negative design among inpatients.

The Use of Test-negative Controls to Monitor Vaccine Effectiveness: A Systematic Review of Methodology

BACKGROUND

The test-negative design is an increasingly popular approach for estimating vaccine effectiveness (VE) due to its efficiency. This review aims to examine published test-negative design studies of VE and to explore similarities and differences in methodological choices for different diseases and vaccines.

METHODS

We conducted a systematic search on PubMed, Web of Science, and Medline, for studies reporting the effectiveness of any vaccines using a test-negative design. We screened titles and abstracts and reviewed full texts to identify relevant articles. We created a standardized form for each included article to extract information on the pathogen of interest, vaccine(s) being evaluated, study setting, clinical case definition, choices of cases and controls, and statistical approaches used to estimate VE.

RESULTS

We identified a total of 348 articles, including studies on VE against influenza virus (n = 253), rotavirus (n = 48), pneumococcus (n = 24), and nine other pathogens. Clinical case definitions used to enroll patients were similar by pathogens of interest but the sets of symptoms that defined them varied substantially. Controls could be those testing negative for the pathogen of interest, those testing positive for nonvaccine type of the pathogen of interest, or a subset of those testing positive for alternative pathogens. Most studies controlled for age, calendar time, and comorbidities.

CONCLUSIONS

Our review highlights similarities and differences in the application of the test-negative design that deserve further examination. If vaccination reduces disease severity in breakthrough infections, particular care must be taken in interpreting vaccine effectiveness estimates from test-negative design studies.

Influenza vaccination and respiratory virus interference among Department of Defense personnel during the 2017-2018 influenza season

PURPOSE

Receiving influenza vaccination may increase the risk of other respiratory viruses, a phenomenon known as virus interference. Test-negative study designs are often utilized to calculate influenza vaccine effectiveness. The virus interference phenomenon goes against the basic assumption of the test-negative vaccine effectiveness study that vaccination does not change the risk of infection with other respiratory illness, thus potentially biasing vaccine effectiveness results in the positive direction. This study aimed to investigate virus interference by comparing respiratory virus status among Department of Defense personnel based on their influenza vaccination status. Furthermore, individual respiratory viruses and their association with influenza vaccination were examined.

RESULTS

We compared vaccination status of 2880 people with non-influenza respiratory viruses to 3240 people with pan-negative results. Comparing vaccinated to non-vaccinated patients, the adjusted odds ratio for non-flu viruses was 0.97 (95% confidence interval (CI): 0.86, 1.09; p = 0.60). Additionally, the vaccination status of 3349 cases of influenza were compared to three different control groups: all controls (N = 6120), non-influenza positive controls (N = 2880), and pan-negative controls (N = 3240). The adjusted ORs for the comparisons among the three control groups did not vary much (range: 0.46-0.51).

CONCLUSIONS

Receipt of influenza vaccination was not associated with virus interference among our population. Examining virus interference by specific respiratory viruses showed mixed results. Vaccine derived virus interference was significantly associated with coronavirus and human metapneumovirus; however, significant protection with vaccination was associated not only with most influenza viruses, but also parainfluenza, RSV, and non-influenza virus coinfections.

Challenges in estimating influenza vaccine effectiveness

Introduction: Influenza vaccination is regarded as the most effective way to prevent influenza infection. Due to the rapid genetic changes that influenza viruses undergo, seasonal influenza vaccines must be reformulated and re-administered annually necessitating the evaluation of influenza vaccine effectiveness (VE) each year. The estimation of influenza VE presents numerous challenges. Areas Covered: This review aims to identify, discuss, and, where possible, offer suggestions for dealing with the following challenges in estimating influenza VE: different outcomes of interest against which VE is estimated, study designs used to assess VE, sources of bias and confounding, repeat vaccination, waning immunity, population level effects of vaccination, and VE in at-risk populations. Expert Opinion: The estimation of influenza VE has improved with surveillance networks, better understanding of sources of bias and confounding, and the implementation of advanced statistical methods. Future research should focus on better estimates of the indirect effects of vaccination, the biological effects of vaccination, and how vaccines interact with the immune system. Specifically, little is known about how influenza vaccination impacts an individual's infectiousness, how vaccines wane over time, and the impact of repeated vaccination.

A Dynamic Model for Evaluation of the Bias of Influenza Vaccine Effectiveness Estimates From Observational Studies

Given that influenza vaccination is now widely recommended in the United States, observational studies based on patients with acute respiratory illness (ARI) remain as the only option to estimate influenza vaccine effectiveness (VE). We developed a dynamic probability model to evaluate bias of VE estimates from passive surveillance cohort, test-negative, and traditional case-control studies. The model includes 2 covariates (health status and health awareness) that might affect the probabilities of vaccination, developing ARI, and seeking medical care. Our results suggest that test-negative studies produce unbiased estimates of VE against medically attended influenza when: 1) Vaccination does not affect the probability of noninfluenza ARI; and 2) health status has the same effect on the probability of influenza and noninfluenza ARIs. The same estimate might be severely biased (i.e., estimated VE - true VE ≥ 0.20) for estimating VE against symptomatic influenza if the vaccine affects the probability of seeking care against influenza ARI. VE estimates from test-negative studies might also be severely biased for both outcomes of interest when vaccination affects the probability of noninfluenza ARI, but estimates from passive surveillance cohort studies are unbiased in this case. Finally, VE estimates from traditional case-control studies suffer from bias regardless of the source of bias.

Estimating Influenza Vaccine Effectiveness With the Test-Negative Design Using Alternative Control Groups: A Systematic Review and Meta-Analysis

One important assumption in case-control studies is that control selection should be independent of exposure. Nevertheless, it has been hypothesized that virus interference might lead to a correlation between receipt of influenza vaccination and increased risk of infection with other respiratory viruses. We investigated whether such a phenomenon might affect a study design commonly used to estimate influenza vaccine effectiveness (VE). We searched publications in MEDLINE, PubMed, and Web of Science. We identified 12 studies using the test-negative design (2011–2017) that reported VE estimates separately derived by 3 alternative control groups: 1) all patients testing negative for influenza (FLU), VE_FLU−; 2) patients who tested positive for other/another respiratory virus (ORV), VE_ORV+; and 3) patients who tested negative for all viruses in the panel (PAN), VE_PAN−. These included VE estimates from 7 countries for all age groups from 2003/2004 to 2013/2014. We observed no difference in vaccination coverage between the ORV-positive and PAN-negative control groups. A total of 63 VE_FLU− estimates, 62 VE_ORV+ estimates, and 33 VE_PAN− estimates were extracted. Pooled estimates of the difference in VE (ΔVE) were very similar between groups. In meta-regression, no association was found between the selection of control group and VE estimates. In conclusion, we did not find any differences in VE estimates based on the choice of control group.