The test-negative design for estimating influenza vaccine effectiveness

Objective

The test-negative design has emerged in recent years as the preferred method for estimating influenza vaccine effectiveness (VE) in observational studies. However, the methodologic basis of this design has not been formally developed.

Methods

In this paper we develop the rationale and underlying assumptions of the test-negative study. Under the test-negative design for influenza VE, study subjects are all persons who seek care for an acute respiratory illness (ARI). All subjects are tested for influenza infection. Influenza VE is estimated from the ratio of the odds of vaccination among subjects testing positive for influenza to the odds of vaccination among subjects testing negative.

Results

With the assumptions that (a) the distribution of non-influenza causes of ARI does not vary by influenza vaccination status, and (b) VE does not vary by health care-seeking behavior, the VE estimate from the sample can generalized to the full source population that gave rise to the study sample. Based on our derivation of this design, we show that test-negative studies of influenza VE can produce biased VE estimates if they include persons seeking care for ARI when influenza is not circulating or do not adjust for calendar time.

Conclusions

The test-negative design is less susceptible to bias due to misclassification of infection and to confounding by health care-seeking behavior, relative to traditional case-control or cohort studies. The cost of the test-negative design is the additional, difficult-to-test assumptions that incidence of non-influenza respiratory infections is similar between vaccinated and unvaccinated groups within any stratum of care-seeking behavior, and that influenza VE does not vary across care-seeking strata.     

Influenza vaccine effectiveness by test-negative design – Comparison of inpatient and outpatient settings

BackgroundObservational studies of influenza vaccine effectiveness (VE) are increasingly using the test-negative design. Studies are typically based in outpatient or inpatient settings, but these two approaches are rarely compared directly. The aim of our study was to assess whether influenza VE estimates differ between inpatient and outpatient settings.MethodsWe searched the literature from Medline, PubMed and Web of Science using a combination of keywords to identify published studies of influenza VE using the test-negative design. Studies assessing any type of influenza vaccine among any population in any setting were considered, while interim studies or re-analyses were excluded. Retrieved articles were reviewed, screened and categorized based on study setting, location and influenza season. We searched for parallel studies in inpatient and outpatient settings that were done in the same influenza season, in the same location, and in the same or similar age groups. For each of the pairs identified, we estimated the difference in VE estimates between settings, and we tested whether the average difference was significant using a paired t-test.ResultsIn total 25 pairs of estimates were identified that permitted comparisons between VE estimates in inpatient and outpatient study settings. Within pairs, the prevalence of influenza was generally higher among patients enrolled in the outpatient studies, while influenza vaccination coverage among the test-negative control groups was generally higher in the inpatient studies. There was no heterogeneity in the paired differences in VE, and the pooled difference in VE between inpatient and outpatient studies was −2% (95% confidence interval: −12%, 10%).ConclusionsWe found no differences in VE estimates between inpatient and outpatient settings by studies using the test-negative design. Further research involving direct comparisons of VE estimates from the two settings in the same populations and years would be valuable.     

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

Background

A modification to the case–control study design has become popular to assess vaccine effectiveness (VE) against viral infections. Subjects with symptomatic illness seeking medical care are tested by a highly specific polymerase chain reaction (PCR) assay for the detection of the infection of interest. Cases are subjects testing positive for the virus; those testing negative represent the comparison group. Influenza and rotavirus VE studies using this design are often termed “test-negative case-control” studies, but this design has not been formally described or evaluated. We explicitly state several assumptions of the design and examine the conditions under which VE estimates derived with it are valid and unbiased.

Methods

We derived mathematical expressions for VE estimators obtained using this design and examined their statistical properties. We used simulation methods to test the validity of the estimators and illustrate their performance using an influenza VE study as an example.

Results

Because the marginal ratio of cases to non-cases is unknown during enrollment, this design is not a traditional case-control study; we suggest the name “case test-negative” design. Under sets of increasingly general assumptions, we found that the case test-negative design can provide unbiased VE estimates. However, differences in health care-seeking behavior among cases and non-cases by vaccine status, strong viral interference, or modification of the probability of symptomatic illness by vaccine status can bias VE estimates.

Conclusions

Vaccine effectiveness estimates derived from case test-negative studies are valid and unbiased under a wide range of assumptions. However, if vaccinated cases are less severely ill and seek care less frequently than unvaccinated cases, then an appropriate adjustment for illness severity is required to avoid bias in effectiveness estimates. Viral interference will lead to a non-trivial bias in the vaccine effectiveness estimate from case test-negative studies only when incidence of influenza is extremely high and duration of transient non-specific immunity is long.     

Comparison of test-negative and syndrome-negative controls in SARS-CoV-2 vaccine effectiveness evaluations for preventing COVID-19 hospitalizations in the United States

BackgroundTest-negative design (TND) studies have produced validated estimates of vaccine effectiveness (VE) for influenza vaccine studies. However, syndrome-negative controls have been proposed for differentiating bias and true estimates in VE evaluations for COVID-19. To understand the use of alternative control groups, we compared characteristics and VE estimates of syndrome-negative and test-negative VE controls.MethodsAdults hospitalized at 21 medical centers in 18 states March 11–August 31, 2021 were eligible for analysis. Case patients had symptomatic acute respiratory infection (ARI) and tested positive for SARS-CoV-2. Control groups were test-negative patients with ARI but negative SARS-CoV-2 testing, and syndrome-negative controls were without ARI and negative SARS-CoV-2 testing. Chi square and Wilcoxon rank sum tests were used to detect differences in baseline characteristics. VE against COVID-19 hospitalization was calculated using logistic regression comparing adjusted odds of prior mRNA vaccination between cases hospitalized with COVID-19 and each control group.Results5811 adults (2726 cases, 1696 test-negative controls, and 1389 syndrome-negative controls) were included. Control groups differed across characteristics including age, race/ethnicity, employment, previous hospitalizations, medical conditions, and immunosuppression. However, control-group-specific VE estimates were very similar. Among immunocompetent patients aged 18–64 years, VE was 93 % (95 % CI: 90–94) using syndrome-negative controls and 91 % (95 % CI: 88–93) using test-negative controls.ConclusionsDespite demographic and clinical differences between control groups, the use of either control group produced similar VE estimates across age groups and immunosuppression status. These findings support the use of test-negative controls and increase confidence in COVID-19 VE estimates produced by test-negative design studies.     

Estimates of 2012/13 influenza vaccine effectiveness using the case test-negative control design with different influenza negative control groups

Background

In recent years several reports of influenza vaccine effectiveness (VE) have been made early for public health decision. The majority of these studies use the case test-negative control design (TND), which has been showed to provide, under certain conditions, unbiased estimates of influenza VE. Nevertheless, discussions have been taken on the best influenza negative control group to use. The present study aims to contribute to the knowledge on this field by comparing influenza VE estimates using three test-negative controls: all influenza negative, non-influenza respiratory virus and pan-negative.

Methods

Incident ILI patients were prospectively selected and swabbed by a sample of general practitioners. Cases were ILI patients tested positive for influenza and controls ILI patients tested negative for influenza. The influenza negative control group was divided into non-influenza virus control group and pan-negative control group. Data were collected on vaccination status and confounding factors. Influenza VE was estimated as one minus the odds ratio of been vaccinated in cases versus controls adjusted for confounding effect by logistic regression.

Results

Confounder adjusted influenza VE against medically attended laboratory-confirmed influenza was 68.4% (95% CI: 20.7–87.4%) using all influenza negatives controls, 82.1% (95% CI: 47.6–93.9%) using non-influenza controls and 49.4% (95% CI: −44.7% to 82.3%) using pan-negative controls.

Conclusions

Influenza VE estimates differed according to the influenza negative control group used. These results are in accordance with the expected under the hypothesis of differential viral interference between influenza vaccinated and unvaccinated individuals. Given the wide importance of TND study further studies should be conducted in order to clarify the observed differences.     

The impact of selection bias on vaccine effectiveness estimates from test-negative studies

IntroductionEstimates of vaccine effectiveness (VE) from test-negative studies may be subject to selection bias. In the context of influenza VE, we used simulations to identify situations in which meaningful selection bias can occur. We also analyzed observational study data for evidence of selection bias.MethodsFor the simulation study, we defined a hypothetical population whose members are at risk for acute respiratory illness (ARI) due to influenza and other pathogens. An unmeasured “healthcare seeking proclivity” affects both probability of vaccination and probability of seeking care for an ARI. We varied the direction and magnitude of these effects and identified situations where meaningful bias occurred. For the observational study, we reanalyzed data from the United States Influenza VE Network, an ongoing test-negative study. We compared “bias-naïve” VE estimates to bias-adjusted estimates, which used data from the source populations to correct for sampling bias.ResultsIn the simulation study, an unmeasured care-seeking proclivity could create selection bias if persons with influenza ARI were more (or less) likely to seek care than persons with non-influenza ARI. However, selection bias was only meaningful when rates of care seeking between influenza ARI and non-influenza ARI were very different. In the observational study, the bias-naïve VE estimate of 55% (95% CI, 47-–62%) was trivially different from the bias-adjusted VE estimate of 57% (95% CI, 49-–63%).ConclusionsIn combination, these studies suggest that while selection bias is possible in test-negative VE studies, this bias in unlikely to be meaningful under conditions likely to be encountered in practice. Researchers and public health officials can continue to rely on VE estimates from test-negative studies.     

A comparison of the test-negative and traditional case-control study designs with respect to the bias of estimates of rotavirus vaccine effectiveness

Estimation of the effectiveness of rotavirus vaccines via the test-negative control study design has gained popularity over the past few years. In this study design, children with severe diarrhea who test positive for rotavirus infection are considered as cases, while children who test negative serve as controls. We use a simple probability model to evaluate and compare the test-negative control and the traditional case-control designs with respect to the bias of resulting estimates of rotavirus vaccine effectiveness (VE). Comparisons are performed under two scenarios, corresponding to studies performed in high-income and low-income countries. We consider two potential sources of bias: (a) misclassification bias resulting from imperfect sensitivity and specificity of the test used to diagnose rotavirus infection, and (b) selection bias associated with possible effect of rotavirus vaccination on the probability of contracting severe non-rotavirus diarrhea.Our results suggest that both sources of bias may produce VE estimates with substantial bias. Particularly, lack of perfect specificity is associated with severe negative bias. For example, if the specificity of the diagnostic test is 90% then VE estimates from both types of case-control studies may under-estimate the true VE by more than 20%. If the vaccine protects children against non-rotavirus diarrhea then VE estimates from test-negative control studies may be close to zero even though the true VE is 50%. However, the sensitivity and specificity of the enzyme immunoassay test currently used to diagnose rotavirus infections are both over 99%, and there is no solid evidence that the existing rotavirus vaccines affect the rates of non-rotavirus diarrhea. We therefore conclude that the test-negative control study design is a convenient and reliable alternative for estimation of rotavirus VE.     

检测阴性设计在疫苗效果评价中的应用

疫苗在上市之前,通过安慰剂-随机对照试验,疫苗效力/效果可以得到规范的评价。但是,疫苗上市之后,如果采用安慰剂-随机对照试验来评价疫苗的效果,会产生伦理学上的问题。因此,疫苗上市后的效果评价一直是公共卫生领域面临的难题。近年来,检测阴性设计这一研究方法在国际上被广泛用于各类上市之后疫苗的效果评价中,例如流感疫苗、轮状病毒疫苗、霍乱疫苗、肺炎疫苗和EV71疫苗等。但是,目前国内关于检测阴性设计这一研究方法的文献报道很少。为此综述检测阴性设计的基本原理、应用步骤及优缺点,为我国开展检测阴性设计提供理论方法及依据。     

Methodologic issues regarding the use of three observational study designs to assess influenza vaccine effectiveness

BACKGROUND: Influenza causes substantial morbidity and annual vaccination is the most important prevention strategy. Accurately measuring vaccine effectiveness (VE) is difficult. The clinical syndrome most closely associated with influenza virus infection, influenza-like illness (ILI), is not specific. In addition, laboratory confirmation is infrequently done, and available rapid diagnostic tests are imperfect. The objective of this study was to estimate the joint impact of rapid diagnostic test sensitivity and specificity on VE for three types of study designs: a cohort study, a traditional case-control study, and a case-control study that used as controls individuals with ILI who tested negative for influenza virus infection. METHODS: We developed a mathematical model with five input parameters: true VE, attack rates (ARs) of influenza-ILI and non-influenza-ILI and the sensitivity and specificity of the diagnostic test. RESULTS: With imperfect specificity, estimates from all three designs tended to underestimate true VE, but were similar except if fairly extreme inputs were used. Only if test specificity was 95% or more or if influenza attack rates doubled that of background illness did the case-control method slightly overestimate VE. The case-control method usually produced the highest and most accurate estimates, followed by the test-negative design. The bias toward underestimating true VE introduced by low test specificity increased as the AR of influenza- relative to non-influenza-ILI decreases and, to a lesser degree, with lower test sensitivity. CONCLUSIONS: Demonstration of a high influenza VE using tests with imperfect sensitivity and specificity should provide reassurance that the program has been effective in reducing influenza illnesses, assuming adequate control of confounding factors.     

Variable seasonal influenza vaccine effectiveness across geographical regions,age groups and levels of vaccine antigenic similarity with circulating virus strains: A systematic review and meta-analysis of the evidence from test-negative design studies after the 2009/10 influenza pandemic

BackgroundWe examined the influence of some factors on seasonal influenza vaccine effectiveness (VE) from test-negative design (TND) studies.MethodsWe systematically searched for full-text publications of VE against laboratory-confirmed influenza from TND studies in outpatient settings after the 2009/10 influenza pandemic. Two reviewers independently selected and extracted data from the included studies. We calculated pooled adjusted VE across geographical regions, age groups and levels of vaccine antigenic similarity with circulating virus strains, using an inverse variance, random-effects model.ResultsWe included 76 full-text articles from 11,931 citations. VE estimates against A(H1N1)pdm09, A(H3N2), influenza B, and all influenza were homogenous and point pooled VE higher in the Southern hemisphere compared with the Northern hemisphere. The difference in pooled VE between the Southern and Northern hemispheres was statistically significant for A(H3N2), influenza B, and all influenza. A consistent pattern was observed in pooled VE across both hemispheres and continents, with the highest point pooled VE being against A(H1N1)pdm09, followed by influenza B, and lowest against A(H3N2). A nearly consistent pattern was observed in pooled VE across age groups in the Northern hemisphere, with pooled VE mostly decreasing with age. Point pooled VE against A(H3N2), influenza B, and all influenza were statistically significantly higher when vaccine was antigenically similar to circulating virus strains compared with when antigenically dissimilar. Similar pattern was observed in the Northern hemisphere, but there was a lack of data from the Southern hemisphere.ConclusionConsistent patterns appear to exist in seasonal influenza VE across regions, age groups, and levels of vaccine antigenic similarity with circulating virus strains, with best vaccine performance against A(H1N1)pdm09 and worst against A(H3N2). The evidence highlights the need to consider geographical location, age, and vaccine antigenic similarity with circulating virus strains when designing and evaluating influenza VE studies.     

On the bias of estimates of influenza vaccine effectiveness from test–negative studies

Estimates of the effectiveness of influenza vaccines are commonly obtained from a test-negative design (TND) study, where cases and controls are patients seeking care for an acute respiratory illness who test positive and negative, respectively, for influenza infection. Vaccine effectiveness (VE) estimates from TND studies are usually interpreted as vaccine effectiveness against medically-attended influenza (MAI). However, it is also important to estimate VE against any influenza illness (symptomatic influenza (SI)) as individuals with SI are still a public health burden even if they do not seek medical care. We present a numerical method to evaluate the bias of TND-based estimates of influenza VE with respect to MAI and SI. We consider two sources of bias: (a) confounding bias due to a (possibly unobserved) covariate that is associated with both vaccination and the probability of the outcome of interest and (b) bias resulting from the effect of vaccination on the probability of seeking care. Our results indicate that (a) VE estimates may suffer from substantial confounding bias when a confounder has a different effect on the probabilities of influenza and non-influenza ARI, and (b) when vaccination reduces the probability of seeking care against influenza ARI, then estimates of VE against MAI may be unbiased while estimates of VE against SI may be have a substantial positive bias.     

Three-season effectiveness of inactivated influenza vaccine in preventing influenza illness and hospitalization in children in Japan, 2013–2016

ObjectivesWe assessed the vaccine effectiveness (VE) of inactivated influenza vaccine (IIV) in children 6 months to 15 years of age in 2015/16 season. In addition, based on the data obtained during the three seasons from 2013 to 2016, we estimated the three-season VE in preventing influenza illness and hospitalization.MethodsOur study was conducted according to a test-negative case-control design (TNCC) and as a case-control study based on influenza rapid diagnostic test results.ResultsDuring 2015/16 season, the quadrivalent IIV was first used in Japan. The adjusted VE in preventing influenza illness was 49% (95% confidence interval [CI]: 42–55%) against any type of influenza, 57% (95% CI: 50–63%) against influenza A and 34% (95% CI: 23–44%) against influenza B. The 3-season adjusted VE was 45% (95% CI: 41–49%) against influenza virus infection overall (N = 12,888), 51% (95% CI: 47–55%) against influenza A (N = 10,410), and 32% (95% CI: 24–38%) against influenza B (N = 9232). An analysis by age groups showed low or no significant VE in infants or adolescents. By contrast, VE was highest in the young group (1–5 years old) and declined with age thereafter. The 3-season adjusted VE in preventing hospitalization as determined in a case-control study was 52% (95% CI: 42–60%) for influenza A and 28% (95% CI: 4–46%) for influenza B, and by TNCC design, it was 54% (95% CI: 41–65%) for influenza A and 34% (95% CI: 6–54%) for influenza B.ConclusionWe demonstrated not only VE in preventing illness, but also VE in preventing hospitalization based on much larger numbers of children than previous studies.     

Lineage-matched versus mismatched influenza B vaccine effectiveness following seasons of marginal influenza B circulation

BackgroundSeveral countries have recently transitioned from the trivalent inactivated influenza vaccine (TIV) to the quadrivalent inactivated influenza vaccine (QIV) in order to outweigh influenza B vaccine-mismatch. However, few studies thus far evaluated its benefits versus the TIV in a systematic manner. Our objective was to compare the QIV VE with lineage-mismatched TIV VE.MethodsWe estimated the 2015–2016, 2017–2018, 2019–2020 end-of season influenza B VE against laboratory-confirmed influenza-like illness (ILI) among community patients, using the test-negative design. VE was estimated for pre-determined age groups and for moving age intervals of 15 years.ResultsSince 2011–2012 season, alternate seasons in Israel were dominated by influenza B circulation. Compared with the lineage-mismatched TIV used during the 2015–2016 and 2017–2018 seasons, the 2019–2020 QIV showed the highest all-ages VE, with VE estimates of 56.9 (95% CI 30.1 to 73.4), 16.5 (95% CI –22.5 to 43.1) and ?25.8 (95% CI ?85.3 to 14.6) for the 2019–2020, 2017–2018 and 2015–2016 seasons, respectively. The 2019–2020 VE point estimated were the highest for the 0.5–4, 5–17 and 18–44 years age groups and for more 15-year age intervals as compared to the other seasons.ConclusionsOur results support the rapid transition from the TIV to the QIV.     

Negative impact of prior influenza vaccination on current influenza vaccination among people infected and not infected in prior season: A test-negative case-control study in Japan

BackgroundAccumulating evidences indicate that repeated influenza vaccination has negative impact on the vaccine effectiveness (VE). However no published studies considered past influenza infection when assessing the VE of repeated vaccination.MethodsProspective surveillance was conducted from 2009 to 2012 at a community hospital on a small island in Japan. The study included all outpatients with an influenza-like illness (ILI) who attended the hospital, and a rapid diagnostic test (RDT) was used to diagnose influenza A/B infection. The VE of trivalent inactivated influenza vaccine (TIV) against medically attended influenza A (MA-fluA) was estimated using a test-negative case-control study design. The influence of TIV in the prior season on VE in the current season was investigated in the context of MA-fluA during the prior season.ResultsDuring the three influenza seasons, 5838 ILI episodes (4127 subjects) were analysed. Subjects who had an episode of MA-fluA in the prior season were at a significantly lower risk of MA-fluA in the current season (adjusted odds ratio: 0.38, 95% CI: 0.30–0.50). The overall adjusted VE was 28% (95% CI, 14–40). VE was substantially lower in subjects vaccinated in the prior season compared to those who had not been vaccinated in prior season (19%; 95% CI: 0–35 vs 46%; 95% CI: 26–60, test for interaction, P value <0.05). In subjects who did not have MA-fluA in the prior season showed the attenuation of VE due to repeated vaccination (13%; 95% CI: −7 to 30 vs 44%; 95% CI: 24–59, test for interaction, P < 0.05). However this effect was not detected in subjects who had contracted MA-fluA in the prior season.ConclusionsNegative effects of repeated vaccination were significant among those without history of MA-fluA in the prior season.     

The 2015–2016 influenza epidemic in Beijing,China: Unlike elsewhere,circulation of influenza A(H3N2) with moderate vaccine effectiveness

BackgroundWhile the 2015–2016 influenza season in the northern hemisphere was dominated by A(H1N1)pdm09 and B/Victoria viruses, in Beijing, China, there was also significant circulation of influenza A(H3N2) virus. In this report we estimate vaccine effectiveness (VE) against influenza A(H3N2) and other circulating viruses, and describe further characteristics of the 2015–2016 influenza season in Beijing.MethodsWe estimated VE of the 2015–2016 trivalent inactivated vaccine (TIV) against laboratory-confirmed influenza virus infection using the test-negative study design. The effect of prior vaccination on current VE was also examined.ResultsOf 11,000 eligible patients included in the study, 2969 (27.0%) were influenza positive. Vaccination coverage was 4.2% in both cases and controls. Adjusted VE against all influenza was 8% (95% CI: −16% to 27%): 18% (95% CI: −38% to 52%) for influenza A(H1N1)pdm09, 54% (95% CI: 16% to 74%) for influenza A(H3N2), and −8% (95% CI: −40% to 18%) for influenza B/Victoria. The overall VE for receipt of 2015–2016 vaccination only, 2014–2015 vaccination only, and vaccinations in both seasons was −15% (95% CI: −63% to 19%), −25% (95% CI: −78% to 13%), and 18% (95% CI: −11% to 40%), respectively.ConclusionsOverall the 2015–2016 TIV was protective against influenza infection in Beijing, with higher VE against the A(H3N2) viruses compared to A(H1N1)pdm09 and B viruses.     

Effectiveness of seasonal influenza vaccine in Australia, 2015: An epidemiological,antigenic and phylogenetic assessment

BackgroundA record number of laboratory-confirmed influenza cases were notified in Australia in 2015, during which type A(H3) and type B Victoria and Yamagata lineages co-circulated. We estimated effectiveness of the 2015 inactivated seasonal influenza vaccine against specific virus lineages and clades.MethodsThree sentinel general practitioner networks conduct surveillance for laboratory-confirmed influenza amongst patients presenting with influenza-like illness in Australia. Data from the networks were pooled to estimate vaccine effectiveness (VE) for seasonal trivalent influenza vaccine in Australia in 2015 using the case test-negative study design.ResultsThere were 2443 eligible patients included in the study, of which 857 (35%) were influenza-positive. Thirty-three and 19% of controls and cases respectively were reported as vaccinated. Adjusted VE against all influenza was 54% (95% CI: 42, 63). Antigenic characterisation data suggested good match between vaccine and circulating strains of A(H3); however VE for A(H3) was low at 44% (95% CI: 21, 60). Phylogenetic analysis indicated most circulating viruses were from clade 3C.2a, rather than the clade included in the vaccine (3C.3a). VE point estimates were higher against B/Yamagata lineage influenza (71%; 95% CI: 57, 80) than B/Victoria (42%, 95% CI: 13, 61), and in younger people.ConclusionsOverall seasonal vaccine was protective against influenza infection in Australia in 2015. Higher VE against the B/Yamagata lineage included in the trivalent vaccine suggests that more widespread use of quadrivalent vaccine could have improved overall effectiveness of influenza vaccine. Genetic characterisation suggested lower VE against A(H3) influenza was due to clade mismatch of vaccine and circulating viruses.     

Influenza vaccine effectiveness in preventing hospitalization among Beijing residents in China, 2013–15

BackgroundEstimates of influenza vaccination effectiveness (VE) are valuable for populations where the vaccine has been promoted in order to support vaccination policy and to permit evaluation of vaccination strategies. Such studies would be important for China due to limited data available during seasons when the vaccine strains matched or mismatched the circulating viruses.MethodsWe conducted a test-negative study in hospitals in Beijing. Patients admitted to five hospitals in the city were enrolled during the winter influenza seasons of 2013–14 and 2014–15. Influenza virus infections were determined by PCR, and influenza vaccination records were extracted from a centralized electronic immunization registry. Influenza VE was estimated by logistic regression adjusting for age group, sex and chronic conditions, and matched by calendar week.ResultsA total of 2368 inpatients were recruited during the study period with a vaccination coverage in the control group of 12.8%. The overall estimate of influenza VE was 46.9% (95% CI: −20.4%, 76.6%) for the 2013–14 season and 5.0% (95% CI: −53.0%, 41.0%) for the 2014–15 season. Estimates of VE were relatively higher in children aged 6–17 years than older persons across two influenza seasons while estimates of VE for both adults and elderly were relatively low.ConclusionsOur findings were consistent with expected influenza vaccination effectiveness in seasons when the vaccine matched or mismatched circulating viruses. Strategies to increase influenza vaccine coverage could provide a public health benefit.     

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

BackgroundMonitoring 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.MethodsSwab 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.ResultsA 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.ConclusionOur 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 vaccine effectiveness against laboratory-confirmed influenza in a vaccine-mismatched influenza B-dominant season

BackgroundThe 2017–2018 influenza season in Israel was characterized by the predominance of influenza B Yamagata, with a lesser circulation of influenza A(H1N1)pdm09 and influenza A(H3N2). We estimated vaccine effectiveness (VE) of the inactivated influenza vaccine which was selected for use that season.MethodsEnd-of-season VE and 95% confidence intervals (CI) against laboratory-confirmed influenza-like illness (ILI) were estimated by means of the test-negative design. Age-specific VE analysis was carried out using a moving age interval.ResultsSpecimen were obtained from 1,453 community ILI patients; 610 (42.0%) were influenza-positive, among which 69.7% were B, 17.2% A(H1N1)pdm09 and 13.4% A(H3N2). A 98.6% of molecularly characterized influenza B belonged to the Yamagata lineage. Of the sampled individuals, 1320 were suitable for VE analysis. Of those vaccinated, 90.6% received the inactivated trivalent influenza vaccine (TIV) containing a Victoria lineage influenza B-like virus. VE against influenza A differed by age, with the highest VE of 72.9% (95%CI 31.9–89.2%) observed in children 0.5–14 years old, while all ages VE was 46.6% (95%CI 10.4–68.2%). All ages VE against influenza B was 23.2% (95%CI −10.1–46.4%) with age-specific analysis showing non-significant VE estimates. Utilizing a moving age interval of 15 years, afforded a detailed age-specific insight into influenza VE against the influenza viruses circulating during the 2017–2018 season.ConclusionsThe moderate-high 2017–2018 influenza A VE among children and adolescents, supports seasonal influenza vaccination at a young age. The low VE against influenza B in Israel, is most likely the result of influenza B/TIV-mismatch.