The case test-negative design for studies of the effectiveness of influenza vaccine in inpatient settings

Seasonal Influenza Vaccine Effectiveness in Persons Aged 15-64 Years: A Systematic Review and Meta-Analysis

Influenza is a respiratory disease caused by the influenza virus, which is highly transmissible in humans. This paper presents a systematic review and meta-analysis of randomized controlled trials (RCTs) and test-negative designs (TNDs) to assess the vaccine effectiveness (VE) of seasonal influenza vaccines (SIVs) in humans aged 15 to 64 years. An electronic search to identify all relevant studies was performed. The outcome measure of interest was VE on laboratory-confirmed influenza (any strain). Quality assessment was performed using the Cochrane risk-of-bias tool for RCTs and the ROBINS-I tool for TNDs. The search identified a total of 2993 records, but only 123 studies from 73 papers were included in the meta-analysis. Of these studies, 9 were RCTs and 116 were TNDs. The pooled VE was 48% (95% CI: 42-54) for RCTs, 55.4% (95% CI: 43.2-64.9) when there was a match between the vaccine and most prevalent circulating strains and 39.3% (95% CI: 23.5-51.9) otherwise. The TNDs' adjusted VE was equal to 39.9% (95% CI: 31-48), 45.1 (95% CI: 38.7-50.8) when there was a match and 35.1 (95% CI: 29.0-40.7) otherwise. The match between strains included in the vaccine and strains in circulation is the most important factor in the VE. It increases by more than 25% when there is a match with the most prevalent circulating strains. The laboratorial method for confirmation of influenza is a possible source of bias when estimating VE.

Double Negative Control Inference in Test-Negative Design Studies of Vaccine Effectiveness

The test-negative design (TND) has become a standard approach to evaluate vaccine effectiveness against the risk of acquiring infectious diseases in real-world settings, such as Influenza, Rotavirus, Dengue fever, and more recently COVID-19. In a TND study, individuals who experience symptoms and seek care are recruited and tested for the infectious disease which defines cases and controls. Despite TND's potential to reduce unobserved differences in healthcare seeking behavior (HSB) between vaccinated and unvaccinated subjects, it remains subject to various potential biases. First, residual confounding bias may remain due to unobserved HSB, occupation as healthcare worker, or previous infection history. Second, because selection into the TND sample is a common consequence of infection and HSB, collider stratification bias may exist when conditioning the analysis on testing, which further induces confounding by latent HSB. In this paper, we present a novel approach to identify and estimate vaccine effectiveness in the target population by carefully leveraging a pair of negative control exposure and outcome variables to account for potential hidden bias in TND studies. We illustrate our proposed method with extensive simulation and an application to study COVID-19 vaccine effectiveness using data from the University of Michigan Health System.

Investigating confounding in network-based test-negative design influenza vaccine effectiveness studies-Experience from the DRIVE project

BACKGROUND

Establishing a large study network to conduct influenza vaccine effectiveness (IVE) studies while collecting appropriate variables to account for potential bias is important; the most relevant variables should be prioritized. We explored the impact of potential confounders on IVE in the DRIVE multi-country network of sites conducting test-negative design (TND) studies.

METHODS

We constructed a directed acyclic graph (DAG) to map the relationship between influenza vaccination, medically attended influenza infection, confounders, and other variables. Additionally, we used the Development of Robust and Innovative Vaccines Effectiveness (DRIVE) data from the 2018/2019 and 2019/2020 seasons to explore the effect of covariate adjustment on IVE estimates. The reference model was adjusted for age, sex, calendar time, and season. The covariates studied were presence of at least one, two, or three chronic diseases; presence of six specific chronic diseases; and prior healthcare use. Analyses were conducted by site and subsequently pooled.

RESULTS

The following variables were included in the DAG: age, sex, time within influenza season and year, health status and comorbidities, study site, health-care-seeking behavior, contact patterns and social precautionary behavior, socioeconomic status, and pre-existing immunity. Across all age groups and settings, only adjustment for lung disease in older adults in the primary care setting resulted in a relative change of the IVE point estimate >10%.

CONCLUSION

Our study supports a parsimonious approach to confounder adjustment in TND studies, limited to adjusting for age, sex, and calendar time. Practical implications are that necessitating fewer variables lowers the threshold for enrollment of sites in IVE studies and simplifies the pooling of data from different IVE studies or study networks.

Effectiveness of an inactivated Covid-19 vaccine with homologous and heterologous boosters against Omicron in Brazil

The effectiveness of inactivated vaccines (VE) against symptomatic and severe COVID-19 caused by omicron is unknown. We conducted a nationwide, test-negative, case-control study to estimate VE for homologous and heterologous (BNT162b2) booster doses in adults who received two doses of CoronaVac in Brazil in the Omicron context. Analyzing 1,386,544 matched-pairs, VE against symptomatic disease was 8.6% (95% CI, 5.6-11.5) and 56.8% (95% CI, 56.3-57.3) in the period 8-59 days after receiving a homologous and heterologous booster, respectively. During the same interval, VE against severe Covid-19 was 73.6% (95% CI, 63.9-80.7) and 86.0% (95% CI, 84.5-87.4) after receiving a homologous and heterologous booster, respectively. Waning against severe Covid-19 after 120 days was only observed after a homologous booster. Heterologous booster might be preferable to individuals with completed primary series inactivated vaccine.

On Measuring Vaccine Effectiveness with Observational Study Designs

Herein, we present a bird's eye view of common observational study designs utilized for measurement of vaccine effectiveness. Assessing vaccines effectiveness is an integral part of vaccine research, particularly for the newly developed vaccines. A cohort study is prospective, directing from an exposure to one or more outcomes. The design is the best method to ascertain the attack rate of an infectious disease. A traditional case-control study is retrospective, directing from a given outcome to one or more exposures. The design cannot provide the relative risk, but it can provide the odds ratio, which is a good estimation of the relative risk when the attack rate is low. Critically depending on laboratory test results and performance, the test-negative case-control study design is another type of observational study commonly used nowadays for the evaluation of the vaccine effectiveness. Comparing to cohort and traditional case-control designs, conducting a test-negative case-control study is relatively cheaper and faster. Herein, we describe each of the above-mentioned study designs through examples generated by a Monte-Carlo simulation program assuming real-world conditions. CONCLUSION: The simulation shows that regardless of the study design employed, the diagnostic test specificity is of utmost importance in providing a valid estimate of the vaccine effectiveness.

Chronic obstructive pulmonary disease and influenza vaccination effect in preventing outpatient and inpatient influenza cases

Evidence of influenza vaccine effectiveness in preventing confirmed influenza among persons diagnosed with chronic obstructive pulmonary disease (COPD) is scarce. We assessed the average effect of influenza vaccination in the current and prior seasons in preventing laboratory-confirmed influenza in COPD patients. We carried out a pooled test-negative case–control design in COPD patients hospitalized or presented to primary healthcare centres with influenza-like illness who were tested for influenza in 2015/2016 to 2019/2020 seasons in Navarre, Spain. Influenza vaccination status in the current and 5 prior seasons was compared between confirmed-influenza cases and test-negative controls. Vaccination effect was compared between target patients for vaccination with and without COPD. Out of 1761 COPD patients tested, 542 (31%) were confirmed for influenza and 1219 were test-negative controls. Average effect for current-season vaccination in preventing influenza was 40% (95% CI 20–54%), and for vaccination in prior seasons only was 24% (95% CI –10 to 47%). Point estimates seemed higher in preventing outpatient cases (60% and 58%, respectively) than inpatient cases (37% and 19%, respectively), but differences were no statistically significant. Influenza vaccination effect was similar in target population with and without COPD (p = 0.339). Influenza vaccination coverage in control patients with COPD was 68.3%. A 13.7% of the influenza cases in patients with COPD could be prevented by extending the influenza vaccine coverage. Average effect of current-season influenza vaccination was moderate to prevent influenza in COPD persons. The increase of influenza vaccination coverage can still prevent COPD exacerbations.

Poor Vaccine Effectiveness against Influenza B-Related Severe Acute Respiratory Infection in a Temperate North Indian State (2019-2020): A Call for Further Data for Possible Vaccines with Closer Match

Background: Influenza vaccine uptake in India is poor, and scant data exist regarding the effectiveness of influenza vaccine against hospitalization. Methods: From October 2019 to March 2020, vaccination status of 1219 patients (males n = 571, aged 5–107 years; median, 50 years) hospitalized with severe acute respiratory illness (SARI) was assessed. The patients were tested for influenza viruses and their subtypes by RT PCR. Sequencing of the HA gene was performed. Vaccine effectiveness (VE) against influenza subtypes was estimated by the test negative design. Results: A total of 336 (27.5%) patients were influenza-positive, with influenza B/Victoria accounting for 49.7% (n = 167), followed by influenza A/H1N1 (47.6%; n = 155) and influenza A/H3N2 (4.4%; n = 15). About 6.8% and 8.6% of the influenza-positive and influenza-negative patients, respectively, had been vaccinated. Adjusted VE for any influenza strain was 13% (95% CI −42 to 47), which for influenza B was 0%. HA sequencing revealed that influenza B samples mainly belonged to subclade V1A.3/133R with deletion of residues 163–165, as against the 2-aa deletion in influenza B/Colorado/06/2017 strain, contained in the vaccine. VE for influenza A/H1N1 was 55%. Conclusions: Poor VE due to a genetic mismatch between the circulating strain and the vaccine strain calls for efforts to reduce the mismatch.

Simple models to include influenza vaccination history when evaluating the effect of influenza vaccination

Background

Most reports of influenza vaccine effectiveness consider current-season vaccination only.

Aim

We evaluated a method to estimate the effect of influenza vaccinations (EIV) considering vaccination history.

Methods

We used a test-negative design with well-documented vaccination history to evaluate the average EIV over eight influenza seasons (2011/12–2018/19; n = 10,356). Modifying effect was considered as difference in effects of vaccination in current and previous seasons and current-season vaccination only. We also explored differences between current-season estimates excluding from the reference category people vaccinated in any of the five previous seasons and estimates without this exclusion or only for one or three previous seasons.

Results

The EIV was 50%, 45% and 38% in people vaccinated in the current season who had previously received none, one to two and three to five doses, respectively, and it was 30% and 43% for one to two and three to five prior doses only. Vaccination in at least three previous seasons reduced the effect of current-season vaccination by 12 percentage points overall, 31 among outpatients, 22 in 9–65 year-olds, and 23 against influenza B. Including people vaccinated in previous seasons only in the unvaccinated category underestimated EIV by 9 percentage points on average (31% vs 40%). Estimates considering vaccination of three or five previous seasons were similar.

Conclusions

Vaccine effectiveness studies should consider influenza vaccination in previous seasons, as it can retain effect and is often an effect modifier. Vaccination status in three categories (current season, previous seasons only, unvaccinated) reflects the whole EIV.

Effect of influenza vaccination in patients with asthma

BACKGROUND:

Although annual influenza vaccination is recommended for persons with asthma, its effectiveness in this patient population is not well described. We evaluated the effect of influenza vaccination in the current and previous seasons in preventing influenza among people with asthma.

METHODS:

Using population health data from the Navarre region of Spain for the 2015/16 to 2019/20 influenza seasons, we conducted a test-negative case–control study to assess the effect of influenza vaccination in the current and 5 previous seasons. From patients presenting to hospitals and primary health care centres with influenza-like illness who underwent testing for influenza, we estimated the effects of influenza vaccination among patients with asthma overall and between those presenting as inpatients or outpatients, as well as between patients with and without asthma.

RESULTS:

Of 1032 patients who had asthma and were tested, we confirmed that 421 had influenza and the remaining 611 were test-negative controls. We found that the average effect of influenza vaccination was 43% (adjusted odds ratio [OR] 0.57, 95% confidence interval [CI] 0.40 to 0.80) for current-season vaccination regardless of previous doses, and 38% (adjusted OR 0.62, 95% CI 0.39 to 0.96) for vaccination in previous seasons only. Effects were similar for outpatients and inpatients. Among patients with asthma and confirmed influenza, current-season vaccination did not reduce the odds of hospital admission (adjusted OR 1.05, 95% CI 0.51 to 2.18). Influenza vaccination effects were similar for patients with and without asthma.

INTERPRETATION:

We estimated that, on average, current or previous influenza vaccination of people with asthma prevented almost half of influenza cases. These results support recommendations that people with asthma receive influenza vaccination.

Vaccine Effectiveness Against Influenza-Associated Hospitalizations Among Adults, 2018-2019, US Hospitalized Adult Influenza Vaccine Effectiveness Network

We estimated vaccine effectiveness (VE) for prevention of influenza-associated hospitalizations among adults during the 2018-2019 influenza season. Adults admitted with acute respiratory illness to 14 hospitals of the US Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN) and testing positive for influenza were cases; patients testing negative were controls. VE was estimated using logistic regression and inverse probability of treatment weighting. We analyzed data from 2863 patients with a mean age of 63 years. Adjusted VE against influenza A(H1N1)pdm09-associated hospitalization was 51% (95% confidence interval [CI], 25%-68%). Adjusted VE against influenza A(H3N2) virus-associated hospitalization was -2% (95% CI, -65% to 37%) and differed significantly by age, with VE of -130% (95% CI, -374% to -27%) among adults 18 to ≤56 years of age. Although vaccination halved the risk of influenza A(H1N1)pdm09-associated hospitalizations, it conferred no protection against influenza A(H3N2)-associated hospitalizations. We observed negative VE for young and middle-aged adults but cannot exclude residual confounding as a potential explanation.

Temporal Confounding in the Test-Negative Design

In the test-negative design, routine testing at health-care facilities is leveraged to estimate the effectiveness of an intervention such as a vaccine. The odds of vaccination for individuals who test positive for a target pathogen is compared with the odds of vaccination for individuals who test negative for that pathogen, adjusting for key confounders. The design is rapidly growing in popularity, but many open questions remain about its properties. In this paper, we examine temporal confounding by generalizing derivations to allow for time-varying vaccine status, including out-of-season controls, and open populations. We confirm that calendar time is an important confounder when vaccine status varies during the study. We demonstrate that, where time is not a confounder, including out-of-season controls can improve precision. We generalize these results to open populations. We use our theoretical findings to interpret 3 recent papers utilizing the test-negative design. Through careful examination of the theoretical properties of this study design, we provide key insights that can directly inform the implementation and analysis of future test-negative studies.

Influenza vaccine effectiveness against hospitalisation due to laboratory-confirmed influenza in children in England in the 2015-2016 influenza season - a test-negative case-control study

England has recently started a new paediatric influenza vaccine programme using a live-attenuated influenza vaccine (LAIV). There is uncertainty over how well the vaccine protects against more severe end-points. A test-negative case–control study was used to estimate vaccine effectiveness (VE) in vaccine-eligible children aged 2–16 years of age in preventing laboratory-confirmed influenza hospitalisation in England in the 2015–2016 season using a national sentinel laboratory surveillance system. Logistic regression was used to estimate the VE with adjustment for sex, risk-group, age group, region, ethnicity, deprivation and month of sample collection. A total of 977 individuals were included in the study (348 cases and 629 controls). The overall adjusted VE for all study ages and vaccine types was 33.4% (95% confidence interval (CI) 2.3–54.6) after adjusting for age group, sex, index of multiple deprivation, ethnicity, region, sample month and risk group. Risk group was shown to be an important confounder. The adjusted VE for all influenza types for the live-attenuated vaccine was 41.9% (95% CI 7.3–63.6) and 28.8% (95% CI −31.1 to 61.3) for the inactivated vaccine. The study provides evidence of the effectiveness of influenza vaccination in preventing hospitalisation due to laboratory-confirmed influenza in children in 2015–2016 and continues to support the rollout of the LAIV childhood programme.

Influenza vaccine effectiveness against hospitalization with laboratory-confirmed influenza in Greece: A pooled analysis across six seasons, 2013-2014 to 2018-2019

BACKGROUND

Monitoring seasonal influenza Vaccine Effectiveness (VE) is key to inform vaccination strategies and sustain uptake. Pooling data across multiple seasons increases precision and allows for subgroup analyses, providing more conclusive evidence. Our aim was to assess VE against hospitalization with laboratory-confirmed influenza in Greece over six seasons, from 2013 to 2014 to 2018-2019, using routinely collected surveillance data.

METHODS

Swab samples from hospitalized patients across the country were tested for influenza by RT-PCR. We used the test-negative design, with patients testing positive for influenza serving as cases and those testing negative serving as controls. VE was calculated as one minus the Odds Ratio (OR) for influenza vaccination, estimated by mixed-effects logistic regression and adjusted for age, sex, hospitalization type (being in intensive care or not), time from symptom onset to swabbing, and calendar time. Stratified estimates by age and hospitalization type were obtained, and also subgroup estimates by influenza type/subtype and season. Antigenic and genetic characterization of a subset of circulating influenza strains was performed.

RESULTS

A total of 3,882 test-positive cases and 5,895 test-negative controls were analyzed. Across all seasons, adjusted VE was 45.5% (95% CI: 31.6-56.6) against all influenza, 62.8% against A(H1N1)pdm09 (95% CI: 40.7-76.7), 28.2% against A(H3N2) (95% CI: 12.0-41.3) and 45.5% against influenza B (95% CI: 29.1-58.1). VE was slightly lower for patients aged 60 years and over, and similar between patients hospitalized inside or outside intensive care. Circulating A(H1N1)pdm09 and B strains were antigenically similar to the vaccine strains, whereas A(H3N2) were not.

CONCLUSION

Our results confirm the public health benefits from seasonal influenza vaccination, despite the suboptimal effectiveness against A(H3N2) strains. Continued monitoring of VE is essential, and routinely collected surveillance data can be valuable in this regard.

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.

Prevention of Influenza Hospitalization Among Adults in the United States, 2015-2016: Results From the US Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN)

BACKGROUND

Evidence establishing effectiveness of influenza vaccination for prevention of severe illness is limited. The US Hospitalized Adult Influenza Vaccine Effectiveness Network (HAIVEN) is a multiyear test-negative case-control study initiated in 2015-2016 to estimate effectiveness of vaccine in preventing influenza hospitalization among adults.

METHODS

Adults aged ≥18 years admitted to 8 US hospitals with acute respiratory illness and testing positive for influenza by polymerase chain reaction were cases; those testing negative were controls. Vaccine effectiveness was estimated with logistic regression adjusting for age, comorbidities, and other confounding factors and stratified by frailty, 2-year vaccination history, and clinical presentation.

RESULTS

We analyzed data from 236 cases and 1231 controls; mean age was 58 years. More than 90% of patients had ≥1 comorbidity elevating risk of influenza complications. Fifty percent of cases and 70% of controls were vaccinated. Vaccination was 51% (95% confidence interval [CI], 29%-65%) and 53% (95% CI, 11%-76%) effective in preventing hospitalization due to influenza A(H1N1)pdm09 and influenza B virus infection, respectively. Vaccine was protective for all age groups.

CONCLUSIONS

During the 2015-2016 US influenza A(H1N1)pdm09-predominant season, we found that vaccination halved the risk of influenza-association hospitalization among adults, most of whom were at increased risk of serious influenza complications due to comorbidity or age.

Influenza Vaccine Effectiveness Against Influenza A(H3N2) Hospitalizations in Children in Hong Kong in a Prolonged Season, 2016/2017

Background

Influenza A(H3N2) viruses circulated for 12 consecutive months in Hong Kong in 2016-2017, peaking in late June and July 2017. The objective of our study was to estimate the effectiveness of influenza vaccination in preventing hospitalizations in children in Hong Kong.

Methods

We conducted a test-negative study between 1 September 2016 and 31 August 2017, enrolling children 6 months to 17 years of age hospitalized for an acute respiratory infection. Influenza was diagnosed by PCR on nasopharyngeal aspirates.

Results

We enrolled 5514 children, including 3608 children 6 months to 2 years, 1600 children 3-5 years, and 1206 children 6-17 years of age. Influenza-associated hospitalizations occurred throughout the study year but time of vaccination of these children was also wide spread, from September 2016 to May 2017. Influenza vaccine effectiveness (VE) was 39.7% (95% confidence interval [CI], 14.7%-57.3%) against laboratory-confirmed influenza A(H3N2). In analyses stratified by time since vaccination, the VE against influenza A(H3N2) was 52.8% (95% CI, 17.1%-73.2%) within 3 months of vaccination, and 31.2% (95% CI, -6.6% to 55.6%) 4-6 months after vaccination.

Conclusions

Influenza vaccination was effective in preventing hospitalizations in children in Hong Kong.

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.

Vaccination history as a confounder of studies of influenza vaccine effectiveness

BACKGROUND

Vaccination history may confound estimates of influenza vaccine effectiveness (VE) when two conditions are present: (1) Influenza vaccination is associated with vaccination history and (2) vaccination modifies the risk of natural infection in the following seasons, either due to persisting vaccination immunity or due to lower previous risk of natural infection.

METHODS

Analytic arguments are used to define conditions for confounding of VE estimates by vaccination history. Simulation studies, both with accurate and inaccurate assessment of current and previous vaccination status, are used to explore the potential magnitude of these biases when using different statistical models to address confounding by vaccination history.

RESULTS

We found a potential for substantial bias of VE estimates by vaccination history if infection- and/or vaccination-derived immunity persisted from one season to the next and if vaccination uptake in individuals was seasonally correlated. Full adjustment by vaccination history, which is usually not feasible, resulted in unbiased VE estimates. Partial adjustment, i.e. only by prior season's vaccination status, significantly reduced confounding bias. Misclassification of vaccination status, which can also lead to substantial bias, interferes with the adjustment of VE estimates for vaccination history.

CONCLUSIONS

Confounding by vaccination history may bias VE estimates, but even partial adjustment by only the prior season's vaccination status substantially reduces confounding bias. Misclassification of vaccination status may compromise VE estimates and efforts to adjust for vaccination history.

Enterovirus A71 vaccine effectiveness in preventing enterovirus A71 infection among medically-attended hand, foot, and mouth disease cases, Beijing, China

Introduction: Enterovirus A71(EV-A71)-associated hand, foot, and mouth disease (HFMD) has been reported worldwide, and poses a particularly heavy burden on patients, families, and society in China. Three Chinese companies have licensed inactivated EV-A71 vaccines, all of which have demonstrated good efficacy for preventing EV-A71-associated disease in clinical trials. However, real-world performance of EV-A71 vaccine has not been evaluated.

Methods: We used a test-negative design case-control study to estimate vaccine effectiveness (VE) against medically attended EV-A71-associated HFMD. Subjects were children 5 years of age and under who had been in health facilities participating in the HFMD case and virologic surveillance platforms in Beijing. Enterovirus infections were laboratory confirmed, and EV-A71 vaccination status was extracted from electronic immunization records. Children testing positive for EV-A71 were cases; controls were children testing negative for EV-A71 infection. Logistic regression was used to estimate VE. We assessed sensitivity of VE estimates to control group inclusion criteria by repeating the regression analyses with two alternative control groups.

Results: A total of 2,184 HFMD patients aged 5 years and under were enrolled in the study; 24 were severe, and 2,160 were mild. For severe cases, two-dose VE estimate was 100% (95% CI: −68.1%, 100%). For mild cases, 1-dose and 2-dose adjusted VE estimates were 69.8% and 83.7%, respectively. Two-dose VE estimates varied by less than 4 percentage points regardless of control group definition.

Conclusions: Our findings suggested the vaccines performed well in the real world for children 5 years of age and under in Beijing, China.

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.

Immune History and Influenza Vaccine Effectiveness

The imperfect effectiveness of seasonal influenza vaccines is often blamed on antigenic mismatch, but even when the match appears good, effectiveness can be surprisingly low. Seasonal influenza vaccines also stand out for their variable effectiveness by age group from year to year and by recent vaccination status. These patterns suggest a role for immune history in influenza vaccine effectiveness, but inference is complicated by uncertainty about the contributions of bias to the estimates themselves. In this review, we describe unexpected patterns in the effectiveness of seasonal influenza vaccination and explain how these patterns might arise as consequences of study design, the dynamics of immune memory, or both. Resolving this uncertainty could lead to improvements in vaccination strategy, including the use of universal vaccines in experienced populations, and the evaluation of vaccine efficacy against influenza and other antigenically variable pathogens.

2015/16 seasonal vaccine effectiveness against hospitalisation with influenza A(H1N1)pdm09 and B among elderly people in Europe: results from the I-MOVE+ project

We conducted a multicentre test-negative case-control study in 27 hospitals of 11 European countries to measure 2015/16 influenza vaccine effectiveness (IVE) against hospitalised influenza A(H1N1)pdm09 and B among people aged ≥ 65 years. Patients swabbed within 7 days after onset of symptoms compatible with severe acute respiratory infection were included. Information on demographics, vaccination and underlying conditions was collected. Using logistic regression, we measured IVE adjusted for potential confounders. We included 355 influenza A(H1N1)pdm09 cases, 110 influenza B cases, and 1,274 controls. Adjusted IVE against influenza A(H1N1)pdm09 was 42% (95% confidence interval (CI): 22 to 57). It was 59% (95% CI: 23 to 78), 48% (95% CI: 5 to 71), 43% (95% CI: 8 to 65) and 39% (95% CI: 7 to 60) in patients with diabetes mellitus, cancer, lung and heart disease, respectively. Adjusted IVE against influenza B was 52% (95% CI: 24 to 70). It was 62% (95% CI: 5 to 85), 60% (95% CI: 18 to 80) and 36% (95% CI: -23 to 67) in patients with diabetes mellitus, lung and heart disease, respectively. 2015/16 IVE estimates against hospitalised influenza in elderly people was moderate against influenza A(H1N1)pdm09 and B, including among those with diabetes mellitus, cancer, lung or heart diseases.

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.

Low influenza vaccine effectiveness and the effect of previous vaccination in preventing admission with A(H1N1)pdm09 or B/Victoria-Lineage in patients 60 years old or older during the 2015/2016 influenza season

BACKGROUND

The 2015/2016 influenza season was characterized in Europe by the circulation of A(H1N1)pdm09 clade 6B.1 and B/Victoria-lineage influenza viruses. The components of the vaccines used in the current and past two seasons in the Valencia region were similar but not well matched to the 2015/2016 dominant influenza-circulating strains. We estimate influenza vaccine effectiveness (IVE) and interference of previous vaccination in preventing admission with A(H1N1)pdm09 or B/Victoria-lineage in this particular season.

METHODS

The Valencia Hospital Network for the Study of Influenza runs an active surveillance hospital-based study to collect clinical and virological data from consecutive admissions possibly related to influenza. Combined nasopharyngeal and pharyngeal swabs are analyzed by reverse transcription polymerase chain reaction, and the hemagglutinin is sequenced in a sample of positive influenza specimens. Vaccination is ascertained consulting a population vaccine information system. We estimate IVE using a test-negative approach.

RESULTS

During the 2015-2016 season, we recruited 1049 eligible admissions of patients 60 years or older, and 187 tested positive for influenza. The adjusted IVE in preventing admission with A(H1N1)pdm09 was 20.2%; 95% confidence interval (CI)  -21.3-47.5% and -33.2%; 95% CI, -140.1-26.1% in preventing admission with B/Victoria-lineage. The majority of A(H1N1)pdm09 sequenced viruses belonged to the emerging 6B.1 subclade, defined by S162N and I216T mutations in the hemagglutinin protein. When we restricted our analysis to those not vaccinated in the previous year, unadjusted IVE was 84.9% (95% CI 9.9-100.0) overall, 77.9% (-32.7-100.0%) in preventing A(H1N1)pdm09 and 48.8% (-219.5-100.0%) in preventing B/Yamagata-lineage admission.

CONCLUSIONS

Our findings indicate that IVE was low in preventing A(H1N1)pdm09 and strongly correlated with vaccination in the previous season. No effect in preventing admission with B/Victoria-lineage was observed. For the 2015/2016 season, IVE was low due to a mismatch and lack of concordance between the circulating and vaccine viruses.

Effectiveness of influenza vaccines in preventing severe influenza illness among adults: A systematic review and meta-analysis of test-negative design case-control studies

OBJECTIVES

Summary evidence of influenza vaccine effectiveness (IVE) against hospitalized influenza is lacking. We conducted a meta-analysis of studies reporting IVE against laboratory-confirmed hospitalized influenza among adults.

METHODS

We searched Pubmed (January 2009 to November 2016) for studies that used test-negative design (TND) to enrol patients hospitalized with influenza-associated conditions. Two independent authors selected relevant articles. We calculated pooled IVE against any and (sub)type specific influenza among all adults, and stratified by age group (18-64 and 65 years and above) using random-effects models.

RESULTS

We identified 3411 publications and 30 met our inclusion criteria. Between 2010-11 and 2014-15, the pooled seasonal IVE was 41% (95%CI:34;48) for any influenza (51% (95%CI:44;58) among people aged 18-64y and 37% (95%CI:30;44) among ≥65 years). IVE was 48% (95%CI:37;59),37% (95%CI:24;50) and 38% (95%CI:23;53) against influenza A(H1N1)pdm09, A(H3N2) and B, respectively. Among persons aged ≥65 year, IVE against A(H3N2) was 43% (95%CI:33;53) in seasons when circulating and vaccine strains were antigenically similar and 14% (95%CI:-3;30) when A(H3N2) variant viruses predominated.

CONCLUSIONS

Influenza vaccines provided moderate protection against influenza-associated hospitalizations among adults. They seemed to provide low protection among elderly in seasons where vaccine and circulating A(H3N2) strains were antigenically variant.

Waning protection of influenza vaccination during four influenza seasons, 2011/2012 to 2014/2015

BACKGROUND

Concerns have been raised about intraseasonal waning of the protection conferred by influenza vaccination.

METHODS

During four influenza seasons, we consecutively recruited individuals aged 18years or older who had received seasonal influenza vaccine and were subsequently admitted to the hospital for influenza infection, asassessed by reverse transcription polymerase chain reaction. We estimated the adjusted odds ratio (aOR) of influenza infection by date of vaccination, defined by tertiles, as early, intermediate or late vaccination. We used a test-negative approach with early vaccination as reference to estimate the aOR of hospital admission with influenza among late vaccinees. We conducted sensitivity analyses by means of conditional logistic regression, Cox proportional hazards regression, and using days between vaccination and hospital admission rather than vaccination date.

RESULTS

Among 3615 admitted vaccinees, 822 (23%) were positive for influenza. We observed a lower risk of influenza among late vaccinees during the 2011/2012 and 2014/2015A(H3N2)-dominant seasons: aOR=0.68 (95% CI: 0.47-1.00) and 0.69 (95% CI: 0.50-0.95). We found no differences in the risk of admission with influenza among late versus early vaccinees in the 2012/2013A(H1N1)pdm09-dominant or 2013/2014B/Yamagata lineage-dominant seasons: aOR=1.18 (95% CI: 0.58-2.41) and 0.98 (95% CI: 0.56-1.72). When we restricted our analysis to individuals aged 65years or older, we found a statistically significant lower risk of admission with influenza among late vaccinees during the 2011/2012 and 2014/2015A(H3N2)-dominant seasons: aOR=0.61 (95% CI: 0.41-0.91) and 0.69 (95% CI: 0.49-0.96). We observed 39% (95% CI: 9-59%) and 31% (95% CI: 5-50%) waning of vaccine effectiveness among participants aged 65years or older during the two A(H3N2)-dominant seasons. Similar results were obtained in the sensitivity analyses.

CONCLUSION

Waning of vaccine protection was observed among individuals aged 65years old or over in two A(H3N2)-dominant influenza seasons.

Live-Attenuated Influenza Vaccine Effectiveness in Children From 2009 to 2015-2016: A Systematic Review and Meta-Analysis

BACKGROUND

This systematic review and meta-analysis describes and consolidates findings from all studies that assessed the effectiveness of live-attenuated influenza vaccine (LAIV) against laboratory-confirmed influenza since the 2009 pandemic in children and young adults.

METHODS

A MEDLINE search was conducted for articles published from January 1, 2010 to November 30, 2016. All original publications reporting an effectiveness estimate of LAIV against cases of influenza confirmed by reverse-transcription polymerase chain reaction or culture were retained for analysis. Effectiveness estimates were categorized by LAIV formulation (monovalent, trivalent, and quadrivalent) and strain (any influenza strain, A(H1N1)pdm09, A(H3N2), and B strains). Consolidated estimates were obtained with a random-effects model.

RESULTS

A total of 24 publications presenting 29 observational studies were retained for meta-analysis. Live-attenuated influenza vaccine was not shown to be effective against A(H1N1)pdm09 strains as a monovalent formulation in 2009-2010 or as a trivalent formulation from 2010-2011 to 2013-2014, but consolidated sample sizes were small. It was effective as a quadrivalent formulation but less effective than inactivated influenza vaccine (IIV). Live-attenuated influenza vaccine was consistently effective against B strains and matched A(H3N2) strains but was not shown to provide significant protection against mismatched A(H3N2) strains in 2014-2015.

CONCLUSIONS

These findings confirm that effectiveness of LAIV against A(H1N1)pdm09 strains has been lower than IIV. A systematic investigation has been initiated to determine the root cause of the difference in effectiveness between pre- and postpandemic A(H1N1) vaccine strains and to identify a more consistently effective A(H1N1)pdm09 vaccine strain.

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

BACKGROUND

The observational test-negative study design is used to estimate vaccine effectiveness against influenza virus infection. An important assumption of the test-negative design is that vaccination does not affect the risk of infection with another virus. If such virus interference occurred, detection of other respiratory viruses would be more common among influenza vaccine recipients and vaccine effectiveness estimates could differ. We evaluated the potential for virus interference using data from the Influenza Incidence Surveillance Project.

METHODS

From 2010 to 2013, outpatients presenting to clinics in 13 US jurisdictions with acute respiratory infections were tested for influenza and other respiratory viruses. We investigated whether virus interference might affect vaccine effectiveness estimates by first evaluating the sensitivity of estimates using alternative control groups that include or exclude patients with other respiratory virus detections by age group and early/middle/late stage of influenza seasons. Second, we evaluated the association between influenza vaccination receipt and other respiratory virus detection among influenza test-negative patients.

RESULTS

Influenza was detected in 3,743/10,650 patients (35%), and overall vaccine effectiveness was 47% (95% CI: 42%, 52%). Estimates using each control group were consistent overall or when stratified by age groups, and there were no differences among early, middle, or late phase during influenza season. We found no associations between detection of other respiratory viruses and receipt of influenza vaccination.

CONCLUSIONS

In this 3-year test-negative design study in an outpatient setting in the United States, we found no evidence of virus interference or impact on influenza vaccine effectiveness estimation.

Interim estimates of the effectiveness of influenza vaccination against influenza-associated hospitalization in children in Hong Kong, 2015-16

From 1 September 2015 through 31 January 2016, we enrolled 2068 children 6 months to 17 years of age admitted to hospital with a febrile acute respiratory infection in our test‐negative study. Information on receipt of 2015–16 northern hemisphere inactivated influenza vaccination was elicited from parents or legal guardians. Using conditional logistic regression adjusting for age and matching on calendar time, we estimated influenza vaccine effectiveness against hospitalization with influenza A or B to be 79.2% (95% confidence interval: 42.0%–92.4%). Annual influenza vaccination should be more widely used in children in Hong Kong.

Influenza Vaccine Effectiveness Against Antigenically Drifted Influenza Higher Than Expected in Hospitalized Adults: 2014-2015

BACKGROUND

The 2014-2015 influenza season was severe, with circulating influenza A (H3N2) viruses that were antigenically drifted from the vaccine virus. Reported vaccine effectiveness (VE) estimates from ambulatory care settings were markedly decreased.

METHODS

Adults, hospitalized at 2 hospitals in southeast Michigan for acute respiratory illnesses, defined by admission diagnoses, of ≤10 days duration were prospectively enrolled. Throat and nasal swab specimens were collected, combined, and tested for influenza by real-time reverse transcription polymerase chain reaction. VE was estimated by comparing the vaccination status of those testing positive for influenza with those testing negative in logistic regression models adjusted for age, sex, hospital, calendar time, time from illness onset to specimen collection, frailty score, and Charlson comorbidity index (CCI).

RESULTS

Among 624 patients included in the analysis, 421 (68%) were vaccinated, 337 (54%) were female, 220 (35%) were age ≥65 years, and 92% had CCI > 0, indicating ≥1 comorbid conditions. Ninety-eight (16%) patients tested positive for influenza A (H3N2); among 60 (61%) A (H3N2) viruses tested by pyrosequencing, 53 (88%) belonged to the drifted 3C.2a genetic group. Adjusted VE was 43% (95% confidence interval [CI], 4-67) against influenza A (H3N2); 40% (95% CI, -13 to 68) for those <65 years, and 48% (95% CI, -33 to 80) for those ≥65 years. Sensitivity analyses largely supported these estimates.

CONCLUSIONS

VE estimates appeared higher than reports from similar studies in ambulatory care settings, suggesting that the 2014-2015 vaccine may have been more effective in preventing severe illness requiring hospitalization.