Clinical Characteristics Are Similar across Type A and B Influenza Virus Infections

Background

Studies that aimed at comparing the clinical presentation of influenza patients across virus types and subtypes/lineages found divergent results, but this was never investigated using data collected over several years in a countrywide, primary care practitioners-based influenza surveillance system.

Methods

The IBVD (Influenza B in Vircases Database) study collected information on signs and symptoms at disease onset from laboratory-confirmed influenza patients of any age who consulted a sentinel practitioner in France. We compared the clinical presentation of influenza patients across age groups (0–4, 5–14, 15–64 and 65+ years), virus types (A, B) and subtypes/lineages (A(H3N2), pandemic A(H1N1), B Victoria, B Yamagata).

Results

Overall, 14,423 influenza cases (23.9% of which were influenza B) were included between 2003–2004 and 2012–2013. Influenza A and B accounted for over 50% of total influenza cases during eight and two seasons, respectively. There were minor differences in the distribution of signs and symptoms across influenza virus types and subtypes/lineages. Compared to patients aged 0–4 years, those aged 5–14 years were more likely to have been infected with type B viruses (OR 2.15, 95% CI 1.87–2.47) while those aged 15–64 years were less likely (OR 0.83, 95% CI 0.73–0.96). Males and influenza patients diagnosed during the epidemic period were less likely to be infected with type B viruses.

Conclusions

Despite differences in age distribution, the clinical illness produced by the different influenza virus types and subtypes is indistinguishable among patients that consult a general practitioner for acute respiratory infections.     

Seroprotective Antibodies to 2011 Variant Influenza A(H3N2v) and Seasonal Influenza A(H3N2) among Three Age Groups of US Department of Defense Service Members

Background

In 2011, a new variant of influenza A(H3N2) emerged that contained a recombination of genes from swine H3N2 viruses and the matrix (M) gene of influenza A(H1N1)pdm09 virus. New combinations and variants of pre-existing influenza viruses are worrisome if there is low or nonexistent immunity in a population, which increases chances for an outbreak or pandemic.

Methods

Sera collected in 2011 were obtained from US Department of Defense service members in three age groups: 19–21 years, 32–33 years, and 47–48 years. Pre- and post-vaccination samples were available for the youngest age group, and postvaccination samples for the two older groups. Specimens were tested using microneutralization assays for antibody titers against H3N2v (A/Indiana/10/2011) and seasonal H3N2 virus (A/Perth/16/2009).

Results

The youngest age group had significantly (p<0.05) higher geometric mean titers for H3N2v with 165 (95% confidence interval [CI]: 105–225) compared with the two older groups, aged 32–33 and 47–48 years, who had geometric mean titers of 68 (95% CI: 55–82) and 46 (95% CI: 24–65), respectively. Similarly, the youngest age group also had the highest geometric mean titers for seasonal H3N2. In the youngest age group, the proportion of patients who seroconverted after vaccination was 12% for H3N2v and 27% for seasonal H3N2.

Discussion

Our results were similar to previous studies that found highest seroprotection among young adults and decreasing titers among older adults. The proportion of 19- to 21-year-olds who seroconverted after seasonal vaccination was low and similar to previous findings. Improving our understanding of H3N2v immunity among different age groups in the United States can help inform vaccination plans if H3N2v becomes more transmissible in the future.     

Immunogenicity and Safety of Influenza Vaccination in Systemic Lupus Erythematosus Patients Compared with Healthy Controls: A Meta-Analysis

Objective

To assess the immunogenicity and safety of influenza vaccine in patients with systemic lupus erythematosus (SLE).

Methods

Relevant articles were retrieved from electronic databases. Seroprotection rate, seroconversion rate and factors that increase antibody geometric mean titer (GMT) were used as indices to measure the immunogenicity. The safety of vaccine was assessed through monitoring adverse events, which included side effects and SLE exacerbations. We performed a meta-analysis of influenza vaccine seroprotection, seroconversion and adverse effects. SLE exacerbation after vaccination was comprehensively described. We used the Committee for Proprietary Medicinal Products (CPMP) guidelines to determine whether influenza can induce adequate immunogenicity in patients with SLE.

Results

Eighteen studies with 1966 subjects met the inclusion criteria. At least 565 of the subjects were patients with low-to-moderate SLE Disease Activity Index (SLEDAI) score or stable SLE disease. Compared with the general population, seroprotection rate in SLE patients was significantly decreased in patients with H1N1 [odds ratio (OR) = 0.36, 95% confidence interval (CI): 0.27–0.50] and H3N2 vaccination (OR = 0.48, 95% CI: 0.24–0.93), but not influenza B vaccination (OR = 0.55, 95% CI: 0.24–1.25). Seroconversion rate also significantly decreased in patients with H1N1 (OR = 0.39, 95% CI: 0.27–0.57) and influenza B (OR = 0.47, 95% CI: 0.29–0.76) vaccination, but not H3N2 vaccination (OR = 0.62, 95% CI: 0.21–1.79). However, the immunogenicity of influenza vaccine in SLE patients almost reached that of the CPMP guidelines. The OR for side effects (patients versus healthy controls) was 3.24 (95% CI: 0.62–16.76). Among 1966 patients with SLE, 32 experienced mild exacerbation of SLE and five had serious side effects for other reasons.

Conclusion

Influenza vaccine has moderate effect on protecting patients with SLE. The side effects of influenza vaccine are not serious and are manageable. With consideration of a higher risk of SLE exacerbation and a more severe course of infection among SLE patients, influenza vaccination should be promoted among SLE patients with a low-to-moderate SLEDAI score or stable disease.     

Impact of the 2009 H1N1 Pandemic on Age-Specific Epidemic Curves of Other Respiratory Viruses: A Comparison of Pre-Pandemic,Pandemic and Post-Pandemic Periods in a Subtropical City

Background

The 2009 H1N1 influenza pandemic caused offseason peaks in temperate regions but coincided with the summer epidemic of seasonal influenza and other common respiratory viruses in subtropical Hong Kong. This study was aimed to investigate the impact of the pandemic on age-specific epidemic curves of other respiratory viruses.

Methods

Weekly laboratory-confirmed cases of influenza A (subtypes seasonal A(H1N1), A(H3N2), pandemic virus A(H1N1)pdm09), influenza B, respiratory syncytial virus (RSV), adenovirus and parainfluenza were obtained from 2004 to 2013. Age-specific epidemic curves of viruses other than A(H1N1)pdm09 were compared between the pre-pandemic (May 2004 – April 2009), pandemic (May 2009 – April 2010) and post-pandemic periods (May 2010 – April 2013).

Results

There were two peaks of A(H1N1)pdm09 in Hong Kong, the first in September 2009 and the second in February 2011. The infection rate was found highest in young children in both waves, but markedly fewer cases in school children were recorded in the second wave than in the first wave. Positive proportions of viruses other than A(H1N1)pdm09 markedly decreased in all age groups during the first pandemic wave. After the first wave of the pandemic, the positive proportion of A(H3N2) increased, but those of B and RSV remained slightly lower than their pre-pandemic proportions. Changes in seasonal pattern and epidemic peak time were also observed, but inconsistent across virus-age groups.

Conclusion

Our findings provide some evidence that age distribution, seasonal pattern and peak time of other respiratory viruses have changed since the pandemic. These changes could be the result of immune interference and changing health seeking behavior, but the mechanism behind still needs further investigations.     

Effectiveness of A(H1N1)pdm09 Influenza Vaccine in Adults Recommended for Annual Influenza Vaccination

Introduction

Because of variability in published A(H1N1)pdm09 influenza vaccine effectiveness estimates, we conducted a study in the adults belonging to the risk groups to assess the A(H1N1)pdm09 MF59-adjuvanted influenza vaccine effectiveness.

Methods

VE against influenza and/or pneumonia was assessed in the cohort study (n>25000), and vaccine effectiveness against laboratory-confirmed A(H1N1)pdm09 influenza was assessed in a matched case-control study (16 pairs). Odds ratios (OR) and their 95% confidence intervals (95% CI) were calculated by using multivariate logistic regression; vaccine effectiveness was estimated as (1-odds ratio)*100%.

Results

Vaccine effectiveness against laboratory-confirmed A(H1N1)pdm09 influenza and influenza and/or pneumonia was 98% (84–100%) and 33% (2–54%) respectively. The vaccine did not prevent influenza and/or pneumonia in 18–59 years old subjects, and was 49% (16–69%) effective in 60 years and older subjects.

Conclusions

Even though we cannot entirely rule out that selection bias, residual confounding and/or cross-protection has played a role, the present results indicate that the MF59-adjuvanted A(H1N1)pdm09 influenza vaccine has been effective in preventing laboratory-confirmed A(H1N1)pdm09 influenza and influenza and/or pneumonia, the latter notably in 60 years and older subjects.     

Evaluation of a Rapid Point of Care Test for Detecting Acute and Established HIV Infection,and Examining the Role of Study Quality on Diagnostic Accuracy: A Bayesian Meta-Analysis

Introduction

Fourth generation (Ag/Ab combination) point of care HIV tests like the FDA-approved Determine HIV1/2 Ag/Ab Combo test offer the promise of timely detection of acute HIV infection, relevant in the context of HIV control. However, a synthesis of their performance has not yet been done. In this meta-analysis we not only assessed device performance but also evaluated the role of study quality on diagnostic accuracy.

Methods

Two independent reviewers searched seven databases, including conferences and bibliographies, and independently extracted data from 17 studies. Study quality was assessed with QUADAS-2. Data on sensitivity and specificity (overall, antigen, and antibody) were pooled using a Bayesian hierarchical random effects meta-analysis model. Subgroups were analyzed by blood samples (serum/plasma vs. whole blood) and study designs (case-control vs. cross-sectional).

Results

The overall specificity of the Determine Combo test was 99.1%, 95% credible interval (CrI) [97.3–99.8]. The overall pooled sensitivity for the device was at 88.5%, 95% [80.1–93.4]. When the components of the test were analyzed separately, the pooled specificities were 99.7%, 95% CrI [96.8–100] and 99.6%, 95% CrI [99.0–99.8], for the antigen and antibody components, respectively. Pooled sensitivity of the antibody component was 97.3%, 95% CrI [60.7–99.9], and pooled sensitivity for the antigen component was found to be 12.3%, 95% (CrI) [1.1–44.2]. No significant differences were found between subgroups by blood sample or study design. However, it was noted that many studies restricted their study sample to p24 antigen or RNA positive specimens, which may have led to underestimation of overall test performance. Detection bias, selection (spectrum) bias, incorporation bias, and verification bias impaired study quality.

Conclusions

Although the specificity of all test components was high, antigenic sensitivity will merit from an improvement. Besides the accuracy of the device itself, study quality, also impacts the performance of the test. These factors must be kept in mind in future evaluations of an improved device, relevant for global scale up and implementation.     

Transmission of the First Influenza A(H1N1)pdm09 Pandemic Wave in Australia Was Driven by Undetected Infections: Pandemic Response Implications

Background

During the first wave of influenza A(H1N1)pdm09 in Victoria, Australia the rapid increase in notified cases and the high proportion with relatively mild symptoms suggested that community transmission was established before cases were identified. This lead to the hypothesis that those with low-level infections were the main drivers of the pandemic.

Methods

A deterministic susceptible-infected-recovered model was constructed to describe the first pandemic wave in a population structured by disease severity levels of asymptomatic, low-level symptoms, moderate symptoms and severe symptoms requiring hospitalisation. The model incorporated mixing, infectivity and duration of infectiousness parameters to calculate subgroup-specific reproduction numbers for each severity level.

Results

With stratum-specific effective reproduction numbers of 1.82 and 1.32 respectively, those with low-level symptoms, and those with asymptomatic infections were responsible for most of the transmission. The effective reproduction numbers for infections resulting in moderate symptoms and hospitalisation were less than one. Sensitivity analyses confirmed the importance of parameters relating to asymptomatic individuals and those with low-level symptoms.

Conclusions

Transmission of influenza A(H1N1)pdm09 was largely driven by those invisible to the health system. This has implications for control measures–such as distribution of antivirals to cases and contacts and quarantine/isolation–that rely on detection of infected cases. Pandemic plans need to incorporate milder scenarios, with a graded approach to implementation of control measures.     

Estimated epidemiologic parameters and morbidity associated with pandemic H1N1 influenza

Background

In the face of an influenza pandemic, accurate estimates of epidemiologic parameters are required to help guide decision-making. We sought to estimate epidemiologic parameters for pandemic H1N1 influenza using data from initial reports of laboratory-confirmed cases.

Methods

We obtained data on laboratory-confirmed cases of pandemic H1N1 influenza reported in the province of Ontario, Canada, with dates of symptom onset between Apr. 13 and June 20, 2009. Incubation periods and duration of symptoms were estimated and fit to parametric distributions. We used competing-risk models to estimate risk of hospital admission and case-fatality rates. We used a Markov Chain Monte Carlo model to simulate disease transmission.

Results

The median incubation period was 4 days and the duration of symptoms was 7 days. Recovery was faster among patients less than 18 years old than among older patients (hazard ratio 1.23, 95% confidence interval 1.06–1.44). The risk of hospital admission was 4.5% (95% CI 3.8%–5.2%) and the case-fatality rate was 0.3% (95% CI 0.1%–0.5%). The risk of hospital admission was highest among patients less than 1 year old and those 65 years or older. Adults more than 50 years old comprised 7% of cases but accounted for 7 of 10 initial deaths (odds ratio 28.6, 95% confidence interval 7.3–111.2). From the simulation models, we estimated the following values (and 95% credible intervals): a mean basic reproductive number (R₀, the number of new cases created by a single primary case in a susceptible population) of 1.31 (1.25–1.38), a mean latent period of 2.62 (2.28–3.12) days and a mean duration of infectiousness of 3.38 (2.06–4.69) days. From these values we estimated a serial interval (the average time from onset of infectiousness in a case to the onset of infectiousness in a person infected by that case) of 4–5 days.

Interpretation

The low estimates for R₀ indicate that effective mitigation strategies may reduce the final epidemic impact of pandemic H1N1 influenza.The emergence and global spread of pandemic H1N1 influenza led the World Health Organization to declare a pandemic on June 11, 2009. As the pandemic spreads, countries will need to make decisions about strategies to mitigate and control disease in the face of uncertainty.For novel infectious diseases, accurate estimates of epidemiologic parameters can help guide decision-making. A key parameter for any new disease is the basic reproductive number (R₀), defined as the average number of new cases created by a single primary case in a susceptible population. R₀ affects the growth rate of an epidemic and the final number of infected people. It also informs the optimal choice of control strategies. Other key parameters that affect use of resources, disease burden and societal costs during a pandemic are duration of illness, rate of hospital admission and case-fatality rate. Early in an epidemic, the case-fatality rate may be underestimated because of the temporal lag between onset of infection and death; the delay between initial identification of a new case and death may lead to an apparent increase in deaths several weeks into an epidemic that is an artifact of the natural history of the disease.We used data from initial reports of laboratory-confirmed pandemic H1N1 influenza to estimate epidemiologic parameters for pandemic H1N1 influenza. The parameters included R₀, incubation period and duration of illness. We also estimated risk of hospital admission and case-fatality rates, which can be used to estimate the burden of illness likely to be associated with this disease.     

A Large Proportion of the Mexican Population Remained Susceptible to A(H1N1)pdm09 Infection One Year after the Emergence of 2009 Influenza Pandemic

Background

The 2009 H1N1 influenza pandemic initially affected Mexico from April 2009 to July 2010. By August 2010, a fourth of the population had received the monovalent vaccine against the pandemic virus (A(H1N1)pdm09). To assess the proportion of the Mexican population who remained potentially susceptible to infection throughout the summer of 2010, we estimated the population seroprevalence to A(H1N1)pdm09 in a serosurvey of blood donors.

Methods

We evaluated baseline cross-reactivity to the pandemic strain and set the threshold for seropositivity using pre-pandemic (2005–2008) stored serum samples and sera from confirmed A(H1N1)pdm09 infected individuals. Between June and September 2010, a convenience sample serosurvey of adult blood donors, children, and adolescents was conducted in six states of Mexico. Sera were tested by the microneutralization (MN) and hemagglutination inhibition (HI) assays, and regarded seropositive if antibody titers were equal or exceeded 1:40 for MN and 1:20 for HI. Age-standardized seroprevalence were calculated using the 2010 National Census population.

Results

Sera from 1,484 individuals were analyzed; 1,363 (92%) were blood donors, and 121 (8%) children or adolescents aged ≤19 years. Mean age (standard deviation) was 31.4 (11.5) years, and 276 (19%) were women. A total of 516 (35%) participants declared history of influenza vaccination after April 2009. The age-standardized seroprevalence to A(H1N1)pdm09 was 48% by the MN and 41% by the HI assays, respectively. The youngest quintile, aged 1 to 22 years, had the highest the seroprevalence; 61% (95% confidence interval [CI]: 56, 66%) for MN, and 56% (95% CI: 51, 62%) for HI.

Conclusions

Despite high transmission of A(H1N1)pdm09 observed immediately after its emergence and extensive vaccination, over a half of the Mexican population remained potentially susceptible to A(H1N1)pdm09 infection. Subsequent influenza seasons with high transmission of A(H1N1)pdm09, as 2011–2012 and 2013–2014, are compatible with these findings.     

Low Rate of Pandemic A/H1N1 2009 Influenza Infection and Lack of Severe Complication of Vaccination in Pregnant Women: A Prospective Cohort Study

Background

In 2009, pregnant women were specifically targeted by a national vaccination campaign against pandemic A/H1N1 influenza virus. The objectives of the COFLUPREG study, initially set up to assess the incidence of serious forms of A/H1N1 influenza, were to assess the consequences of maternal vaccination on pregnancy outcomes and maternal seroprotection at delivery.

Methods

Pregnant women, between 12 and 35 weeks of gestation, non vaccinated against A/H1N1 2009 influenza were randomly selected to be included in a prospective cohort study conducted in three maternity centers in Paris (France) during pandemic period. Blood samples were planned to assess hemagglutination inhibition (HI) antibody against A/H1N1 2009 influenza at inclusion and at delivery.

Results

Among the 877 pregnant women included in the study, 678 (77.3%) had serum samples both at inclusion and delivery, and 320 (36.5%) received pandemic A/H1N1 2009 influenza vaccine with a median interval between vaccination and delivery of 92 days (95% CI 48–134). At delivery, the proportion of women with seroprotection (HI antibodies titers against A/H1N1 2009 influenza of 1∶40 or greater) was 69.9% in vaccinated women. Of the 422 non-vaccinated women with serological data, 11 (2.6%; 95%CI: 1.3–4.6) had laboratory documented A/H1N1 2009 influenza (1 with positive PCR and 10 with serological seroconversion). None of the 877 study’s women was hospitalized for flu. No difference on pregnancy outcomes was evidenced between vaccinated women, non-vaccinated women without seroconversion and non-vaccinated women with flu.

Conclusion

Despite low vaccine coverage, incidence of pandemic flu was low in this cohort of pregnant women.No effect on pregnancy and delivery outcomes was evidenced after vaccination.     

Cardiovascular and Renal Outcomes of Renin–Angiotensin System Blockade in Adult Patients with Diabetes Mellitus: A Systematic Review with Network Meta-Analyses

Background

Medications aimed at inhibiting the renin–angiotensin system (RAS) have been used extensively for preventing cardiovascular and renal complications in patients with diabetes, but data that compare their clinical effectiveness are limited. We aimed to compare the effects of classes of RAS blockers on cardiovascular and renal outcomes in adults with diabetes.

Methods and Findings

Eligible trials were identified by electronic searches in PubMed/MEDLINE and the Cochrane Database of Systematic Reviews (1 January 2004 to 17 July 2014). Interventions of interest were angiotensin-converting enzyme (ACE) inhibitors, angiotensin receptor blockers (ARBs), and direct renin (DR) inhibitors. The primary endpoints were cardiovascular mortality, myocardial infarction, and stroke—singly and as a composite endpoint, major cardiovascular outcome—and end-stage renal disease [ESRD], doubling of serum creatinine, and all-cause mortality—singly and as a composite endpoint, progression of renal disease. Secondary endpoints were angina pectoris and hospitalization for heart failure. In all, 71 trials (103,120 participants), with a total of 14 different regimens, were pooled using network meta-analyses. When compared with ACE inhibitor, no other RAS blocker used in monotherapy and/or combination was associated with a significant reduction in major cardiovascular outcomes: ARB (odds ratio [OR] 1.02; 95% credible interval [CrI] 0.90–1.18), ACE inhibitor plus ARB (0.97; 95% CrI 0.79–1.19), DR inhibitor plus ACE inhibitor (1.32; 95% CrI 0.96–1.81), and DR inhibitor plus ARB (1.00; 95% CrI 0.73–1.38). For the risk of progression of renal disease, no significant differences were detected between ACE inhibitor and each of the remaining therapies: ARB (OR 1.10; 95% CrI 0.90–1.40), ACE inhibitor plus ARB (0.97; 95% CrI 0.72–1.29), DR inhibitor plus ACE inhibitor (0.99; 95% CrI 0.65–1.57), and DR inhibitor plus ARB (1.18; 95% CrI 0.78–1.84). No significant differences were showed between ACE inhibitors and ARBs with respect to all-cause mortality, cardiovascular mortality, myocardial infarction, stroke, angina pectoris, hospitalization for heart failure, ESRD, or doubling serum creatinine. Findings were limited by the clinical and methodological heterogeneity of the included studies. Potential inconsistency was identified in network meta-analyses of stroke and angina pectoris, limiting the conclusiveness of findings for these single endpoints.

Conclusions

In adults with diabetes, comparisons of different RAS blockers showed similar effects of ACE inhibitors and ARBs on major cardiovascular and renal outcomes. Compared with monotherapies, the combination of an ACE inhibitor and an ARB failed to provide significant benefits on major outcomes. Clinicians should discuss the balance between benefits, costs, and potential harms with individual diabetes patients before starting treatment.

Review registration

PROSPERO CRD42014014404     

Evaluation of the Intussusception Risk after Pentavalent Rotavirus Vaccination in Finnish Infants

Background

An association between rotavirus immunisation and intussusception (IS) has been suggested with present rotavirus vaccines in post-licensure studies. In Finland, rotavirus vaccination programme was implemented in September 2009 using a 2, 3, and 5 months schedule with the pentavalent rotavirus vaccine. By the end of 2013, it is estimated that 719 000 rotavirus vaccine doses have been given in the national programme of which 240 000 were first doses. Nationwide register allows us to evaluate the association between rotavirus vaccination and IS.

Methods and Materials

Cases of IS diagnosed during 1999–2013 were identified from National Hospital Discharge Register. All cases under 250 days of age diagnosed during 2009–2013 were confirmed by reviewing medical charts. Self-controlled case-series method was used to assess the risk of IS during 1–21 days compared to 22–42 days post vaccination.

Findings

In register data the relative incidence of IS at 2 months of age between the post and pre vaccination era was 9.1 (95%CI 2.0–84.3). We identified 22 verified cases with date of admission less than 43 days after any of the three rotavirus vaccine doses. The incidence of IS in the risk period after the 1st dose relative to the control period was 2.0 (95% CI 0.5–8.4; p = 0.34.) Number of excess IS cases per 100 000 first vaccine doses was therefore estimated to be 1.04 (95% CI 0.0–2.5), i.e. one additional IS case per 96 000 first doses of rotavirus vaccine (95% CI 54 600 to ∞). There was no risk detected after 2nd and 3rd doses.

Conclusion

The finding is in line with the recent published estimates. The benefits of rotavirus immunisation programme outweigh possible small risks of intussusception.     

Household Transmission of Influenza A(H1N1)pdm09 in the Pandemic and Post-Pandemic Seasons

Background

The transmission of influenza viruses occurs person to person and is facilitated by contacts within enclosed environments such as households. The aim of this study was to evaluate secondary attack rates and factors associated with household transmission of laboratory-confirmed influenza A(H1N1)pdm09 in the pandemic and post-pandemic seasons.

Methods

During the 2009–2010 and 2010–2011 influenza seasons, 76 sentinel physicians in Navarra, Spain, took nasopharyngeal and pharyngeal swabs from patients diagnosed with influenza-like illness. A trained nurse telephoned households of those patients who were laboratory-confirmed for influenza A(H1N1)pdm09 to ask about the symptoms, risk factors and vaccination status of each household member.

Results

In the 405 households with a patient laboratory-confirmed for influenza A(H1N1)pdm09, 977 susceptible contacts were identified; 16% of them (95% CI 14–19%) presented influenza-like illness and were considered as secondary cases. The secondary attack rate was 14% in 2009–2010 and 19% in the 2010–2011 season (p = 0.049), an increase that mainly affected persons with major chronic conditions. In the multivariate logistic regression analysis, the risk of being a secondary case was higher in the 2010–2011 season than in the 2009–2010 season (adjusted odds ratio: 1.72; 95% CI 1.17–2.54), and in children under 5 years, with a decreasing risk in older contacts. Influenza vaccination was associated with lesser incidence of influenza-like illness near to statistical significance (adjusted odds ratio: 0.29; 95% CI 0.08–1.03).

Conclusion

The secondary attack rate in households was higher in the second season than in the first pandemic season. Children had a greater risk of infection. Preventive measures should be maintained in the second pandemic season, especially in high-risk persons.     

Guillain-Barré Syndrome and Adjuvanted Pandemic Influenza A (H1N1) 2009 Vaccines: A Multinational Self-Controlled Case Series in Europe

Background

The risk of Guillain-Barré syndrome (GBS) following the United States'' 1976 swine flu vaccination campaign in the USA led to enhanced active surveillance during the pandemic influenza (A(H1N1)pdm09) immunization campaign. This study aimed to estimate the risk of GBS following influenza A(H1N1)pdm09 vaccination.

Methods

A self-controlled case series (SCCS) analysis was performed in Denmark, Finland, France, Netherlands, Norway, Sweden, and the United Kingdom. Information was collected according to a common protocol and standardised procedures. Cases classified at levels 1–4a of the Brighton Collaboration case definition were included. The risk window was 42 days starting the day after vaccination. Conditional Poisson regression and pooled random effects models estimated adjusted relative incidences (RI). Pseudo likelihood and vaccinated-only methods addressed the potential contraindication for vaccination following GBS.

Results

Three hundred and three (303) GBS and Miller Fisher syndrome cases were included. Ninety-nine (99) were exposed to A(H1N1)pdm09 vaccination, which was most frequently adjuvanted (Pandemrix and Focetria). The unadjusted pooled RI for A(H1N1)pdm09 vaccination and GBS was 3.5 (95% Confidence Interval (CI): 2.2–5.5), based on all countries. This lowered to 2.0 (95% CI: 1.2–3.1) after adjustment for calendartime and to 1.9 (95% CI: 1.1–3.2) when we accounted for contra-indications. In a subset (Netherlands, Norway, and United Kingdom) we further adjusted for other confounders and there the RI decreased from 1.7 (adjusted for calendar month) to 1.4 (95% CI: 0.7–2.8), which is the main finding.

Conclusion

This study illustrates the potential of conducting European collaborative vaccine safety studies. The main, fully adjusted analysis, showed that the RI of GBS was not significantly elevated after influenza A(H1N1)pdm09 vaccination (RI = 1.4 (95% CI: 0.7–2.8). Based on the upper limits of the pooled estimate we can rule out with 95% certainty that the number of excess GBS cases after influenza A(H1N1)pdm09 vaccination would be more than 3 per million vaccinated.     

Surveillance for Seasonal Influenza Virus Prevalence in Hospitalized Children with Lower Respiratory Tract Infection in Guangzhou,China during the Post-Pandemic Era

Background

Influenza A(H1N1)pdm09, A(H3N2) and B viruses have co-circulated in the human population since the swine-origin human H1N1 pandemic in 2009. While infections of these subtypes generally cause mild illnesses, lower respiratory tract infection (LRTI) occurs in a portion of children and required hospitalization. The aim of our study was to estimate the prevalence of these three subtypes and compare the clinical manifestations in hospitalized children with LRTI in Guangzhou, China during the post-pandemic period.

Methods

Children hospitalized with LRTI from January 2010 to December 2012 were tested for influenza A/B virus infection from their throat swab specimens using real-time PCR and the clinical features of the positive cases were analyzed.

Results

Of 3637 hospitalized children, 216 (5.9%) were identified as influenza A or B positive. Infection of influenza virus peaked around March in Guangzhou each year from 2010 to 2012, and there were distinct epidemics of each subtype. Influenza A(H3N2) infection was more frequently detected than A(H1N1)pdm09 and B, overall. The mean age of children with influenza A virus (H1N1/H3N2) infection was younger than those with influenza B (34.4 months/32.5 months versus 45 months old; p<0.005). Co-infections of influenza A/ B with mycoplasma pneumoniae were found in 44/216 (20.3%) children.

Conclusions

This study contributes the understanding to the prevalence of seasonal influenza viruses in hospitalized children with LRTI in Guangzhou, China during the post pandemic period. High rate of mycoplasma pneumoniae co-infection with influenza viruses might contribute to severe disease in the hospitalized children.     

Meta-Analysis of a Complex Network of Non-Pharmacological Interventions: The Example of Femoral Neck Fracture

Background

Surgical interventions raise specific methodological issues in network meta-analysis (NMA). They are usually multi-component interventions resulting in complex networks of randomized controlled trials (RCTs), with multiple groups and sparse connections.

Purpose

To illustrate the applicability of the NMA in a complex network of surgical interventions and to prioritize the available interventions according to a clinically relevant outcome.

Methods

We considered RCTs of treatments for femoral neck fracture in adults. We searched CENTRAL, MEDLINE, EMBASE and ClinicalTrials.gov up to November 2015. Two reviewers independently selected trials, extracted data and used the Cochrane Collaboration’s tool for assessing the risk of bias. A group of orthopedic surgeons grouped similar but not identical interventions under the same node. We synthesized the network using a Bayesian network meta-analysis model. We derived posterior odds ratios (ORs) and 95% credible intervals (95% CrIs) for all possible pairwise comparisons. The primary outcome was all-cause revision surgery.

Results

Data from 27 trials were combined, for 4,186 participants (72% women, mean age 80 years, 95% displaced fractures). The median follow-up was 2 years. With hemiarthroplasty (HA) and total hip arthroplasty (THA) as a comparison, risk of surgical revision was significantly higher with the treatments unthreaded cervical osteosynthesis (OR 8.0 [95% CrI 3.6–15.5] and 5.9 [2.4–12.0], respectively), screw (9.4 [6.0–16.5] and 6.7 [3.9–13.6]) and plate (12.5 [5.8–23.8] and 7.8 [3.8–19.4]).

Conclusions

In older women with displaced femoral neck fractures, arthroplasty (HA and THA) is the most effective treatment in terms of risk of revision surgery.

Systematic Review Registration

PROSPERO no. CRD42013004218.

Level of Evidence

Network Meta-Analysis, Level 1.     

Impact of Influenza on Health-Related Quality of Life among Confirmed (H1N1)2009 Patients

Background

We aimed to assess the changes in health-related quality of life (HRQL) in patients with confirmed diagnosis of influenza (H1N1)2009, and to estimate the individual and societal loss of quality-adjusted life years (QALYs) caused by the pandemic.

Methods and Results

Longitudinal study of patients recruited at major hospitals and primary care centers in Spain. Patients reported their HRQL (EQ-5D) during their influenza episode and seven days prior to it. A subsample was monitored to evaluate HRQL after recovery. HRQL loss was estimated as the difference between EQ-5D prior to the influenza episode and during it. Individual QALY loss (disutility multiplied by the duration of the influenza episode in days) for confirmed cases was calculated and used to estimate the societal loss in Spain (with the official estimations). A total of 432 inpatients and 563 outpatients were included, of whom 145 and 184, respectively, were followed up. Baseline mean HRQL loss was 0.58 (95% CI, 0.53–0.63) for inpatients and 0.43 (95% CI, 0.40–0.46) for outpatients. The majority of the 145 inpatients and 184 outpatients who were followed up regained initial HRQL levels, presenting a mean difference of 0.01 between the EQ-5D score prior to and after the influenza episode. Individual QALY losses for inpatients (0.031, 95% CI, 0.025–0.037) were higher than for outpatients (0.009, 95% CI, 0.007–0.011), while societal QALY losses were reversed: 94 years for inpatients and 6,778 years for outpatients. For fatal cases (an official number of 318), we estimated a QALY loss of 11,981.

Conclusions

The influenza (H1N1)2009 pandemic had a significant but temporary impact on the HRQL of the majority of confirmed in- and outpatients. The societal impact of the influenza pandemic in Spain was estimated to be higher than other acute conditions. These results provide useful data for future cost-utility analyses.     

Effective Detection of the 2009 H1N1 Influenza Pandemic in U.S. Veterans Affairs Medical Centers Using a National Electronic Biosurveillance System

Background

The 2008–09 influenza season was the time in which the Department of Veterans Affairs (VA) utilized an electronic biosurveillance system for tracking and monitoring of influenza trends. The system, known as ESSENCE or Electronic Surveillance System for the Early Notification of Community-based Epidemics, was monitored for the influenza season as well as for a rise in influenza cases at the start of the H1N1 2009 influenza pandemic. We also describe trends noted in influenza-like illness (ILI) outpatient encounter data in VA medical centers during the 2008–09 influenza season, before and after the recognition of pandemic H1N1 2009 influenza virus.

Methodology/Principal Findings

We determined prevalence of ILI coded visits using VA''s ESSENCE for 2008–09 seasonal influenza (Sept. 28, 2008–April 25, 2009 corresponding to CDC 2008–2009 flu season weeks 40–16) and the early period of pandemic H1N1 2009 (April 26, 2009–July 31, 2009 corresponding to CDC 2008–2009 flu season weeks 17–30). Differences in diagnostic ICD-9-CM code frequencies were analyzed using Chi-square and odds ratios. There were 649,574 ILI encounters captured representing 633,893 patients. The prevalence of VA ILI visits mirrored the CDC''s Outpatient ILI Surveillance Network (ILINet) data with peaks in late December, early February, and late April/early May, mirroring the ILINet data; however, the peaks seen in the VA were smaller. Of 31 ILI codes, 6 decreased and 11 increased significantly during the early period of pandemic H1N1 2009. The ILI codes that significantly increased were more likely to be symptom codes. Although influenza with respiratory manifestation (487.1) was the most common code used among 150 confirmed pandemic H1N1 2009 cases, overall it significantly decreased since the start of the pandemic.

Conclusions/Significance

VA ESSENCE effectively detected and tracked changing ILI trends during pandemic H1N1 2009 and represents an important temporal alerting system for monitoring health events in VA facilities.     

Estimated cumulative incidence of pandemic (H1N1) influenza among pregnant women during the first wave of the 2009 pandemic

Background

Hospitalization and lab confirmed cases of H1N1 have been reported during the first wave of the 2009 pandemic but these are not accurate measures of influenza incidence in the population. We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic.

Methods

Two panels of stored frozen serum specimens collected for routine prenatal screening were randomly selected for testing before (March 2009, n = 252) and after (August 2009, n = 296) the first wave of the pandemic. A standard hemagglutination inhibition assay was used to detect the presence of IgG antibodies against the pandemic (H1N1) 2009 virus. The cumulative incidence of pandemic (H1N1) influenza was calculated as the difference between the point prevalence rates in the first and second panels.

Results

Of the specimens collected in March, 7.1% were positive for the IgG antibodies (serum antibody titre ≥ 1:40). The corresponding prevalence was 15.7% among the specimens collected in August. The difference indicated a cumulative incidence of 8.6% (95% confidence interval [CI] 3.2%–13.7%). The rate differed geographically, the highest being in the northern regions (20.8%, 95% CI 7.9%–31.8%), as compared with 4.0% (95% CI 0.0%–11.9%) in Winnipeg and 8.9% (95% CI 0.0%–18.8%) in the rest of the province.

Interpretation

We estimated that the cumulative incidence of pandemic (H1N1) influenza among pregnant women in Manitoba during the first wave of the 2009 pandemic was 8.6%. It was 20.8% in the northern regions of the province.During the first wave of the pandemic (H1N1) 2009, the province of Manitoba was more severely affected than almost any other Canadian province.¹ Pregnant women in particular had higher rates of laboratory-confirmed infection and of severe illness.² However, the number of laboratory-confirmed cases is not an accurate measure of the incidence of influenza in the population. The number and geographic distribution of confirmed cases are influenced by differences in access to medical care, physicians’ practices and other factors.³We estimated the cumulative incidence of pandemic (H1N1) influenza among pregnant women in the province of Manitoba during the first wave of the 2009 pandemic. We did this by measuring the point seroprevalence in random samples of pregnant women presenting for routine prenatal screening before and after the first wave.     

The Association of Meningococcal Disease with Influenza in the United States, 1989–2009

Importance and Objective

Prior influenza infection is a risk factor for invasive meningococcal disease. Quantifying the fraction of meningococcal disease attributable to influenza could improve understanding of viral-bacterial interaction and indicate additional health benefits to influenza immunization.

Design, Setting and Participants

A time series analysis of the association of influenza and meningococcal disease using hospitalizations in 9 states from 1989–2009 included in the State Inpatient Databases from the Agency for Healthcare Research and Quality and the proportion of positive influenza tests by subtype reported to the Centers for Disease Control. The model accounts for the autocorrelation of meningococcal disease and influenza between weeks, temporal trends, co-circulating respiratory syncytial virus, and seasonality. The influenza-subtype-attributable fraction was estimated using the model coefficients. We analyzed the synchrony of seasonal peaks in hospitalizations for influenza, respiratory syncytial virus, and meningococcal disease.

Results and Conclusions

In 19 of 20 seasons, influenza peaked≤2 weeks before meningococcal disease, and peaks were highly correlated in time (ρ = 0.95; P <.001). H3N2 and H1N1 peaks were highly synchronized with meningococcal disease while pandemic H1N1, B, and respiratory syncytial virus were not. Over 20 years, 12.8% (95% CI, 9.1–15.0) of meningococcal disease can be attributable to influenza in the preceding weeks with H3N2 accounting for 5.2% (95% CI, 3.0–6.5), H1N1 4.3% (95% CI, 2.6–5.6), B 3.0% (95% CI, 0.8–4.9) and pH1N1 0.2% (95% CI, 0–0.4). During the height of influenza season, weekly attributable fractions reach 59%. While vaccination against meningococcal disease is the most important prevention strategy, influenza vaccination could provide further protection, particularly in young children where the meningococcal disease vaccine is not recommended or protective against the most common serogroup.