Hypertension in NF1: A closer look at the primacy of essential hypertension versus secondary causes.

BACKGROUND: We aimed to analyze hypertension in neurofibromatosis type 1 (NF1) in a Finnish population-based cohort in 1996-2014. METHODS: A cohort of 1365 individuals with confirmed NF1 was compared with a control cohort of 13,923 individuals matched for age, sex, and area of residence. Diagnoses of hypertension were retrieved from the Finnish Care Register for Health Care. These registered data were separately analyzed for secondary and essential hypertension. Purchases of antihypertensive drugs were queried from the Finnish Register of Reimbursed Drug Purchases. RESULTS: We identified 115 NF1 patients with hospital diagnosis of hypertension. Our findings revealed a hazard ratio (HR) of 1.64 (95% CI 1.34-2.00, p < 0.001) in NF1 versus controls. NF1 patients presented with a significantly increased hazard for both secondary hypertension (n = 9, HR 3.76, 95% CI 1.77-7.95, p < 0.001) and essential hypertension (n = 98, HR 1.73, 95% CI 1.39-2.14, p < 0.001). No difference in the HR of hypertension was observed between men and women, while NF1 patients with essential hypertension were, on average, younger than the controls. The proportions of individuals with antihypertensive medication did not differ between NF1 patients and controls (OR 0.85). CONCLUSION: NF1 is a risk factor for hypertension. Despite the recognized risk for secondary hypertension, essential hypertension is the predominant type in NF1.

Underreporting of SARS-CoV-2 infections during the first wave of the 2020 COVID-19 epidemic in Finland-Bayesian inference based on a series of serological surveys.

In Finland, the first wave of the COVID-19 epidemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) took place from March to June 2020, with the majority of COVID-19 cases diagnosed in the Helsinki-Uusimaa region. The magnitude and trend in the incidence of COVID-19 is one way to monitor the course of the epidemic. The diagnosed COVID-19 cases are a subset of the infections and therefore the COVID-19 incidence underestimates the SARS-CoV-2 incidence. The likelihood that an individual with SARS-CoV-2 infection is diagnosed with COVID-19 depends on the clinical manifestation as well as the infection testing policy and capacity. These factors may fluctuate over time and the underreporting of infections changes accordingly. Quantifying the extent of underreporting allows the assessment of the true incidence of infection. To obtain information on the incidence of SARS-CoV-2 infection in Finland, a series of serological surveys was initiated in April 2020. We develop a Bayesian inference approach and apply it to data from the serological surveys, registered COVID-19 cases, and external data on antibody development, to estimate the time-dependent underreporting of SARS-Cov-2 infections during the first wave of the COVID-19 epidemic in Finland. During the entire first wave, there were 1 to 5 (95% probability) SARS-CoV-2 infections for every COVID-19 case. The underreporting was highest before April when there were 4 to 17 (95% probability) infections for every COVID-19 case. It is likely that between 0.5%-1.0% (50% probability) and no more than 1.5% (95% probability) of the adult population in the Helsinki-Uusimaa region were infected with SARS-CoV-2 by the beginning of July 2020.

Presence of Streptococcus pyogenes in the throat in invasive Group A Streptococcal disease: a prospective two-year study in two health districts, Finland.

PURPOSE: Streptococcus pyogenes (Group A Streptococcus, GAS) is an important human pathogen that can cause severe invasive (iGAS) infections. Throat carriage has been assumed to possibly lead to hematogenous seeding. Retrospective studies may estimate the incidence of throat carriage in iGAS patients inaccurately. In this study we aimed to gather data on the presence of GAS in the throat among iGAS patients in a prospective setting. METHODS: We conducted a prospective clinical study covering iGAS infections in adult patients in two university hospitals in Finland from June 2018 to July 2020. Recruited patients' throats were swabbed for culture and isothermal amplification tests (IAT) to search for GAS. The study was registered at ClinicalTrials.gov as ID NCT03507101. RESULTS: We enrolled 45 patients. Throat swabs were obtained from 39/45 (87%) patients. Ten patients (22%) had a positive IAT for GAS. They were statistically significantly more likely to be male (9/10 [90%] vs 13/29 [45%], p = .024). Several different emm types caused the iGAS infections. CONCLUSIONS: GAS was frequently observed in throat swabs of patients with iGAS infection. This may suggest that hematogenous seeding from the nasopharynx is a possible portal of entry.

Efficacy and effectiveness of case isolation and quarantine during a growing phase of the COVID-19 epidemic in Finland.

Based on data collected as part of the contact tracing activity of the City of Helsinki Epidemiological Operations Unit, we evaluated the efficacy and effectiveness of isolating SARS-CoV-2 cases and quarantining their exposed contacts during a mildly growing phase of the COVID-19 epidemic in Finland in autumn 2020. Based on the observed symptom-to-symptom intervals in 1016 pairs of primary and secondary cases, we estimated that without case isolation or quarantine 40[Formula: see text] (90[Formula: see text] credible interval, CI 25-59) of transmission would have occurred on the day of or after symptom onset. One third of SARS-CoV-2 cases (N = 1521) had initially been quarantined, with a self-reported time until isolation (quarantine) of 0.8 days before symptom onset. This delay translates into an efficacy of 50[Formula: see text] (90[Formula: see text] CI 40-63) of averting secondary infections per quarantined case. Due to later isolation (mean 2.6 days after symptoms), the efficacy was smaller (24[Formula: see text]; 90[Formula: see text] CI 12-41) in those two third of the cases (N = 3101) whose isolation was prompted by their symptoms, i.e. without being previously quarantined. At the population level, we evaluated the effectiveness of case isolation and quarantine on the growth rate of the COVID-19 epidemic in the autumn of 2020. Under a wide range of underlying assumptions, the rate would have been at least 2 times higher without case isolation and quarantine. The numbers needed to isolate or quarantine to prevent one secondary case were 2 and 20, respectively.

Whole genome sequencing reveals new links between spa t172/CC59 methicillin-resistant Staphylococcus aureus cases in low-endemicity region of Southwest Finland, 2007‒2016.

Methicillin-resistant Staphylococcus aureus (MRSA) rates have remained relatively low in Finland. In Southwest Finland, however, annual MRSA incidence increased from 12 to 25/100,000 between 2007 and 2016 with spa t172 strain causing one fourth (237/983) of all cases. This provoked us to study the molecular epidemiology of t172-MRSA, aiming to better understand the transmission of this strain type. We combined epidemiological data and whole genome sequencing (WGS) of a set of 64 (27%, 64/237) t172-MRSA isolates covering 10 years. Isolates represented sporadic and index cases of all identified healthcare-associated outbreaks (HAOs) and family clusters (FCs). Among the included 62 isolates, core-genome MLST analysis revealed eight genomic clusters comprising 24 (38.7%) isolates and 38 (61.3%) non-clustered isolates. Cluster 1 comprised ten and the remaining seven clusters two isolates each, respectively. Two epidemiologically distinct HAOs were linked in cluster 1. FCs were involved in all clusters. All strains were associated with epidemic clonal complex CC59. We were able to confirm the spread of several successful t172-MRSA subclones in regional healthcare and the community. WGS complemented routine surveillance by revealing undetected links between t172-MRSA cases. Targeted, WGS-based typing could enhance MRSA surveillance without the need for routine WGS diagnostics.

Impact of Selected Meteorological Factors on COVID-19 Incidence in Southern Finland during 2020-2021.

We modelled the impact of selected meteorological factors on the daily number of new cases of the coronavirus disease 2019 (COVID-19) at the Hospital District of Helsinki and Uusimaa in southern Finland from August 2020 until May 2021. We applied a DLNM (distributed lag non-linear model) with and without various environmental and non-environmental confounding factors. The relationship between the daily mean temperature or absolute humidity and COVID-19 morbidity shows a non-linear dependency, with increased incidence of COVID-19 at low temperatures between 0 to -10 °C or at low absolute humidity (AH) values below 6 g/m3. However, the outcomes need to be interpreted with caution, because the associations found may be valid only for the study period in 2020-2021. Longer study periods are needed to investigate whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a seasonal pattern similar such as influenza and other viral respiratory infections. The influence of other non-environmental factors such as various mitigation measures are important to consider in future studies. Knowledge about associations between meteorological factors and COVID-19 can be useful information for policy makers and the education and health sector to predict and prepare for epidemic waves in the coming winters.

Effects of physical activity intervention on 24-h movement behaviors: a compositional data analysis.

We utilized compositional data analysis (CoDA) to study changes in the composition of the 24-h movement behaviors during an activity tracker based physical activity intervention. A total of 231 recently retired Finnish retirees were randomized into intervention and control groups. The intervention participants were requested to use a commercial activity tracker bracelet with daily activity goal and inactivity alerts for 12 months. The controls received no intervention. The 24-h movement behaviors, i.e., sleep, sedentary time (SED), light physical activity (LPA), and moderate-to-vigorous physical activity (MVPA) were estimated from wrist-worn ActiGraph data using the GGIR R-package. Three balance coordinates describing the composition of movement behaviors were applied: ratio of active vs. passive behaviors, LPA vs. MVPA, and sleep vs. SED. A linear mixed model was used to study changes between the baseline and 6-month time point. Overall, the changes in the 24-h movement behaviors were small and did not differ between the groups. Only the ratio of LPA to MVPA tended to change differently between the groups (group*time interaction p = 0.08) as the intervention group increased LPA similarly to controls but decreased their MVPA. In conclusion, the use of a commercial activity tracker may not be enough to induce changes in the 24-h movement behaviors among retirees.

Predictors of hospitalisation and death due to SARS-CoV-2 infection in Finland: A population-based register study with implications to vaccinations.

INTRODUCTION: The aim of this study was to investigate how age and underlying medical conditions affect the risk of severe outcomes following SARS-CoV-2 infection and how they should be weighed while prioritising vaccinations against COVID-19. METHODS: This population-based register study includes all SARS-CoV-2 PCR-test-positive cases until 24 Feb 2021, based on the Finnish National Infectious Diseases Register. The cases were linked to other registers to identify presence of predisposing factors and severe outcomes (hospitalisation, intensive care treatment, death). The odds of severe outcomes were compared in those with and without the pre-specified predisposing factors using logistic regression. Furthermore, population-based rates were compared between those with a given predisposing factor and those without any of the specified predisposing factors using negative binomial regression. RESULTS: Age and various comorbidities were found to be predictors of severe COVID-19. Compared to 60-69-year-olds, the odds ratio (OR) of death was 7.1 for 70-79-year-olds, 26.7 for 80-89-year-olds, and 55.8 for ≥ 90-year-olds. Among the 20-69-year-olds, chronic renal disease (OR 9.4), malignant neoplasms (5.8), hematologic malignancy (5.6), chronic pulmonary disease (5.4), and cerebral palsy or other paralytic syndromes (4.6) were strongly associated with COVID-19 mortality; severe disorders of the immune system (8.0), organ or stem cell transplant (7.2), chronic renal disease (6.7), and diseases of myoneural junction and muscle (5.5) were strongly associated with COVID-19 hospitalisation. Type 2 diabetes and asthma, two very common comorbidities, were associated with all three outcomes, with ORs from 2.1 to 4.3. The population-based rate of SARS-CoV-2 infection decreased with age. Taking the 60-69-year-olds as reference, the rate ratio was highest (3.0) for 20-29-year-olds and < 1 for 70-79-year-olds and 80-89-year-olds. CONCLUSION: Comorbidities predispose for severe COVID-19 among younger ages. In vaccine prioritisation both the risk of infection and the risk of severe outcomes, if infected, should be considered.

Approximate likelihood-based estimation method of multiple-type pathogen interactions: An application to longitudinal pneumococcal carriage data.

While the serotypes of Streptococcus pneumoniae are known to compete during colonization in human hosts, our knowledge of how competition occurs is still incomplete. New insights of pneumococcal between-type competition could be generated from carriage data obtained by molecular-based detection methods, which record more complete sets of serotypes involved in co-carriage than when detection is done by culture. Here, we develop a Bayesian estimation method for inferring between-type interactions from longitudinal data recording the presence/absence of the types at discrete observation times. It allows inference from data containing co-carriage of two or more serotypes, which is often the case when pneumococcal presence is determined by molecular-based methods. The computational burden posed by the increased number of types detected in co-carriage is addressed by approximating the likelihood under a multi-state model with the likelihood of only those trajectories with minimum number of acquisition and clearance events between observation times. The proposed method's performance was validated on simulated data. The estimates of the interaction parameters of acquisition and clearance were unbiased in settings with short sampling intervals between observation times. With less frequent sampling, the estimates of the interaction parameters became more biased, but their ratio, which summarizes the total interaction, remained unbiased. Confounding due to unobserved heterogeneity in exposure could be corrected by including individual-level random effects. In an application to empirical data about pneumococcal carriage in infants, we found new evidence for between-serotype competition in clearance, although the effect size was small.

Spotlight influenza: Estimation of influenza vaccine effectiveness in elderly people with assessment of residual confounding by negative control outcomes, Finland, 2012/13 to 2019/20.

BackgroundCohort studies on vaccine effectiveness are prone to confounding bias if the distribution of risk factors is unbalanced between vaccinated and unvaccinated study subjects.AimWe aimed to estimate influenza vaccine effectiveness in the elderly population in Finland by controlling for a sufficient set of confounders based on routinely available register data.MethodsFor each of the eight consecutive influenza seasons from 2012/13 through 2019/20, we conducted a cohort study comparing the hazards of laboratory-confirmed influenza in vaccinated and unvaccinated people aged 65-100 years using individual-level medical and demographic data. Vaccine effectiveness was estimated as 1 minus the hazard ratio adjusted for the confounders age, sex, vaccination history, nights hospitalised in the past and presence of underlying chronic conditions. To assess the adequacy of the selected set of confounders, we estimated hazard ratios of off-season hospitalisation for acute respiratory infection as a negative control outcome.ResultsEach analysed cohort comprised around 1 million subjects, of whom 37% to 49% were vaccinated. Vaccine effectiveness against laboratory-confirmed influenza ranged from 16% (95% confidence interval (CI): 12-19) to 48% (95% CI: 41-54). More than 80% of the laboratory-confirmed cases were hospitalised. The adjusted off-season hazard ratio estimates varied between 1.00 (95% CI: 0.94-1.05) and 1.08 (95% CI: 1.01-1.15), indicating that residual confounding was absent or negligible.ConclusionSeasonal influenza vaccination reduces the hazard of severe influenza disease in vaccinated elderly people. Data about age, sex, vaccination history and utilisation of hospital care proved sufficient to control confounding.

Increased risk for dementia in neurofibromatosis type 1.

PURPOSE: To determine the risk for dementia in neurofibromatosis type 1 (NF1) using a Finnish nationwide cohort of individuals with NF1, and data from national registries. METHODS: A Finnish cohort of 1,349 individuals with confirmed NF1 according to the US National Institutes of Health (NIH) diagnostic criteria was compared with a control cohort of 13,870 individuals matched for age, sex, and area of residence. Dementia-related hospital visits were retrieved from the Finnish Care Register for Health Care using International Classification of Diseases, 10th revision (ICD-10) diagnosis codes G30 and F00-F03. Purchases of antidementia drugs were queried with Anatomical Therapeutic Chemical (ATC) classification code N06D from the drug reimbursement register maintained by the Social Insurance Institution of Finland. The follow-up spanned 1998-2014. RESULTS: Totals of 16 and 165 individuals with at least two dementia-related diagnoses or drug purchases were identified in the NF1 and control cohorts, respectively. The hazard ratio for dementia in NF1 was 1.67 (95% confidence interval [CI] 1.00-2.80, P = 0.050). In an analysis stratified by the type of dementia, the risk for Alzheimer disease was increased in NF1 compared to controls with a hazard ratio of 2.88 (95% CI 1.47-5.66, P = 0.002). CONCLUSION: Dementia and especially Alzheimer disease are previously unrecognized neurological complications of NF1.

Social Distancing and SARS-CoV-2 Transmission Potential Early in the Epidemic in Finland.

BACKGROUND: Information about social mixing patterns under heavy social distancing is needed to model the impact of nonpharmaceutical interventions on SARS-CoV-2 transmission. METHODS: We conducted a survey on daily person-to-person contacts during the early phase of the SARS-CoV-2 epidemic in Finland, one month after strong social distancing measures had been introduced nationwide. We defined a contact as exchange of at least a few words in proximity of another person. We also considered physical ("skin-to-skin") contacts separately. Based on 3,171 reported contacts by 1,320 participants of 1-79 years of age, we estimated age-stratified contact matrices essential in modeling virus transmission. RESULTS: Compared with contacts during prepandemic conditions, as learned from the Finnish part of the Polymod study, there was a 72% (95% credible interval, CI = 71, 74) reduction in the daily number of all contacts and a 69% (95% CI = 66, 73) reduction in the daily number of physical contacts in April 2020. The largest reduction, of almost 90%, occurred in physical contacts by individuals more than 70 years of age. The estimated reduction in the transmission potential of the virus attributable solely to reduced contact frequencies varied between 59% (whole population; physical contacts; 95% CI = 52, 68) and 77% (over 20-year olds; physical contacts; 95% CI = 70, 89). CONCLUSIONS: We surmise that the large reduction in the daily numbers of social contacts in the early part of the SARS-CoV-2 epidemic in Finland was likely a major contributor to the steady decline of the epidemic in the country since early April.

Exposure misclassification bias in the estimation of vaccine effectiveness.

In epidemiology, a typical measure of interest is the risk of disease conditional upon exposure. A common source of bias in the estimation of risks and risk ratios is misclassification. Exposure misclassification affects the measurement of exposure, i.e. the variable one conditions on. This article explains how to assess biases under non-differential exposure misclassification when estimating vaccine effectiveness, i.e. the vaccine-induced relative reduction in the risk of disease. The problem can be described in terms of three binary variables: the unobserved true exposure status, the observed but potentially misclassified exposure status, and the observed true disease status. The bias due to exposure misclassification is quantified by the difference between the naïve estimand defined as one minus the risk ratio comparing individuals observed as vaccinated with individuals observed as unvaccinated, and the vaccine effectiveness defined as one minus the risk ratio comparing truly vaccinated with truly unvaccinated. The magnitude of the bias depends on five factors: the risks of disease in the truly vaccinated and the truly unvaccinated, the sensitivity and specificity of exposure measurement, and vaccination coverage. Non-differential exposure misclassification bias is always negative. In practice, if the sensitivity and specificity are known or estimable from external sources, the true risks and the vaccination coverage can be estimated from the observed data and, thus, the estimation of vaccine effectiveness based on the observed risks can be corrected for exposure misclassification. When analysing risks under misclassification, careful consideration of conditional probabilities is crucial.

Mitigation of biases in estimating hazard ratios under non-sensitive and non-specific observation of outcomes-applications to influenza vaccine effectiveness.

BACKGROUND: Non-sensitive and non-specific observation of outcomes in time-to-event data affects event counts as well as the risk sets, thus, biasing the estimation of hazard ratios. We investigate how imperfect observation of incident events affects the estimation of vaccine effectiveness based on hazard ratios. METHODS: Imperfect time-to-event data contain two classes of events: a portion of the true events of interest; and false-positive events mistakenly recorded as events of interest. We develop an estimation method utilising a weighted partial likelihood and probabilistic deletion of false-positive events and assuming the sensitivity and the false-positive rate are known. The performance of the method is evaluated using simulated and Finnish register data. RESULTS: The novel method enables unbiased semiparametric estimation of hazard ratios from imperfect time-to-event data. False-positive rates that are small can be approximated to be zero without inducing bias. The method is robust to misspecification of the sensitivity as long as the ratio of the sensitivity in the vaccinated and the unvaccinated is specified correctly and the cumulative risk of the true event is small. CONCLUSIONS: The weighted partial likelihood can be used to adjust for outcome measurement errors in the estimation of hazard ratios and effectiveness but requires specifying the sensitivity and the false-positive rate. In absence of exact information about these parameters, the method works as a tool for assessing the potential magnitude of bias given a range of likely parameter values.

Impact and effectiveness of a conjugate vaccine against invasive pneumococcal disease in Finland - a modelling approach.

The evaluation of the public health impact of a vaccination program is essential in monitoring its policy relevance. Vaccine impact (VI) is usually assessed in a before-after design, in which data on disease burden without vaccination program is required from a historical reference period. It takes into account the indirect effects and therefore aims to describe the public health performance of the vaccination program in the population. Vaccine effectiveness (VE), measured in parallel settings, quantifies the benefit for an individual of being vaccinated but does not address the indirect effects of a vaccination program. The motivation of this paper is to gain insight into patterns of how VI and VE have manifested under large-scale use of a ten-valent pneumococcal conjugate vaccine in Finnish children. We construct a simple pseudo-dynamic model that mimics typical post-vaccination trends in the incidences of pneumococcal carriage and invasive disease in children when the proportion of vaccine-type carriage decreases. In the context of the model, we define the parameters of interest for VI and VE and explore how their expected values evolve over time. For comparison, we demonstrate the application of VI and VE estimation by using register data.

Haploinsufficiency of the NF1 gene is associated with protection against diabetes.

BACKGROUND: The hereditary predisposition to diabetes is only partially explained by genes identified so far. Neurofibromatosis type 1 (NF1) is a rare monogenic dominant syndrome caused by aberrations of the NF1 gene. Here, we used a cohort of 1410 patients with NF1 to study the association of the NF1 gene with type 1 (T1D) and type 2 diabetes (T2D). METHODS: A total of 1410 patients were confirmed to fulfil the National Institutes of Health diagnostic criteria for NF1 by individually reviewing their medical records. The patients with NF1 were compared with 14 017 controls matched for age, sex and area of residence as well as 1881 non-NF1 siblings of the patients with NF1. Register-based information on purchases of antidiabetic medication and hospital encounters related to diabetes were retrieved. The Cox proportional hazards model was used to calculate the relative risk for diabetes in NF1. RESULTS: Patients with NF1 showed a lower rate of T2D when compared with a 10-fold control cohort (HR 0.27, 95% CI 0.17 to 0.43) or with their siblings without NF1 (HR 0.28, 95% CI 0.16 to 0.47). The estimates remained practically unchanged after adjusting the analyses for history of obesity and dyslipidaemias. The rate of T1D in NF1 was decreased although statistically non-significantly (HR 0.58, 95% CI 0.27 to 1.25). CONCLUSION: Haploinsufficiency of the NF1 gene may protect against T2D and probably T1D. Since NF1 negatively regulates the Ras signalling pathway, the results suggest that the Ras pathway may be involved in the pathogenesis of diabetes.

Changing epidemiology of methicillin-resistant Staphylococcus aureus in a low endemicity area-new challenges for MRSA control.

The incidence of methicillin-resistant Staphylococcus aureus (MRSA) has increased sharply in Hospital District of Southwest Finland (HD). To understand reasons behind this, a retrospective, population-based study covering 10 years was conducted. All new 983 MRSA cases in HD from January 2007 to December 2016 were analysed. Several data sources were used to gather background information on the cases. MRSA cases were classified as healthcare-associated (HA-MRSA), community-associated (CA-MRSA), and livestock contact was determined (livestock-associated MRSA, LA-MRSA). Spa typing was performed to all available strains. The incidence of MRSA doubled from 12.4 to 24.9 cases/100000 persons/year. The proportion of clinical infections increased from 25 to 32% in the 5-year periods, respectively, (p < 0.05). The median age decreased from 61 years in 2007 to 30 years in 2016. HA-MRSA accounted for 68% of all cases, of which 32% associated with 26 healthcare outbreaks. The proportion of CA-MRSA cases increased from 13% in 2007 to 43% in 2016. Of CA-MRSA cases, 43% were among family clusters, 32% in immigrants and 4% were LA-MRSA. The Gini-Simpson diversity index for spa types increased from 0.86 to 0.95 from the first to the second 5-year period. The proportion of a predominant strain t172 decreased from 43% in 2009 to 7% in 2016. The rise in the proportion of CA-MRSA, the switch to younger age groups, the complexity of possible transmission routes and the growing spa-type diversity characterize our current MRSA landscape. This creates challenges for targeted infection control measures, demanding further studies.

Effectiveness of 2 Influenza Vaccines in Nationwide Cohorts of Finnish 2-Year-Old Children in the Seasons 2015-2016 Through 2017-2018.

BACKGROUND: From 2015-2016 through 2017-2018, injectable, trivalent inactivated influenza vaccines (IIV3) and a nasal spray, tetravalent live-attenuated influenza vaccine (LAIV4) were used in parallel in Finland. To understand how well vaccination with each vaccine type protected children against influenza under real-life conditions, vaccine effectiveness in 2-year-olds was estimated for all 3 seasons. METHODS: Each season, a nationwide register-based cohort study was conducted. The study population comprised 60 088, 60 860, and 60 345 children in 2015-2016, 2016-2017, and 2017-2018, respectively. Laboratory-confirmed influenza was the study outcome. Seasonal influenza vaccination with either LAIV4 or IIV3 was the time-dependent exposure of interest. Vaccine effectiveness was defined as 1 minus the hazard ratio comparing vaccinated with unvaccinated children. RESULTS: From 2015-2016 through 2017-2018, the effectiveness of LAIV4 against influenza of any virus type was estimated at 54.2% (95% confidence interval, 32.2-69.0%), 20.3% (-12.7%, 43.6%), and 30.5% (10.9-45.9%); the corresponding effectiveness of IIV3 was 77.2% (48.9-89.8%), 24.5% (-29.8%, 56.1%), and -20.1% (-61.5%, 10.7%). Neither influenza vaccine clearly excelled in protecting children. The LAIV4 effectiveness against type B was greater than against type A and greater than the IIV3 effectiveness against type B. CONCLUSIONS: To understand how influenza vaccines could be improved, vaccine effectiveness must be analyzed by vaccine and virus type. Effectiveness estimates also expressing overall protection levels are needed to guide individual and programmatic decision-making processes. Supported by this analysis, the vaccination program in Finland now recommends LAIV4 and injectable, tetravalent inactivated influenza vaccines replacing IIV3.

Cohort study design for estimating the effectiveness of seasonal influenza vaccines in real time based on register data: The Finnish example.

This paper presents the principles of implementing register-based cohort studies as currently applied for real-time estimation of influenza vaccine effectiveness in Finland. All required information is retrieved from computerised national registers and deterministically linked via the unique personal identity code assigned to each Finnish resident. The study cohorts comprise large subpopulations eligible for a free seasonal influenza vaccination as part of the National Vaccination Programme. The primary outcome is laboratory-confirmed influenza. Each study subject is taken to be at risk of experiencing the outcome from the onset of the influenza season until the first of the following three events occurs: outcome, loss to follow up or end of season. Seasonal influenza vaccination is viewed as time-dependent exposure. Accordingly, each subject may contribute unvaccinated and vaccinated person-time during their time at risk. The vaccine effectiveness is estimated as one minus the influenza incidence rate ratio comparing the vaccinated with the unvaccinated within the study cohorts. Data collection in register-based research is an almost fully automated process. The effort, resources and the time spent in the field are relatively small compared to other observational study designs. This advantage is pivotal when vaccine effectiveness estimates are needed in real time. The paper outlines possible limitations of register-based cohort studies. It also addresses the need to explore how national and subnational registers available in the Nordic countries and elsewhere can be utilised in vaccine effectiveness research to guide decision making and to improve individual health as well as public health.