Genome characterization of influenza A and B viruses in New South Wales, Australia, in 2019: A retrospective study using high-throughput whole genome sequencing

BACKGROUND

During the 2019 severe influenza season, New South Wales (NSW) experienced the highest number of cases in Australia. This study retrospectively investigated the genetic characteristics of influenza viruses circulating in NSW in 2019 and identified genetic markers related to antiviral resistance and potential virulence.

METHODS

The complete genomes of influenza A and B viruses were amplified using reverse transcription-polymerase chain reaction (PCR) and sequenced with an Illumina MiSeq platform.

RESULTS

When comparing the sequencing data with the vaccine strains and reference sequences, the phylogenetic analysis revealed that most NSW A/H3N2 viruses (n = 68; 94%) belonged to 3C.2a1b and a minority (n = 4; 6%) belonged to 3C.3a. These viruses all diverged from the vaccine strain A/Switzerland/8060/2017. All A/H1N1pdm09 viruses (n = 20) showed genetic dissimilarity from vaccine strain A/Michigan/45/2015, with subclades 6B.1A.5 and 6B.1A.2 identified. All B/Victoria-lineage viruses (n = 21) aligned with clade V1A.3, presenting triple amino acid deletions at positions 162-164 in the hemagglutinin protein, significantly diverging from the vaccine strain B/Colorado/06/2017. Multiple amino acid substitutions were also found in the internal proteins of influenza viruses, some of which have been previously reported in hospitalized influenza patients in Thailand. Notably, the oseltamivir-resistant marker H275Y was present in one immunocompromised patient infected with A/H1N1pdm09 and the resistance-related mutation I222V was detected in another A/H3N2-infected patient.

CONCLUSIONS

Considering antigenic drift and the constant evolution of circulating A and B strains, we believe continuous monitoring of influenza viruses in NSW via the high-throughput sequencing approach provides timely and pivotal information for both public health surveillance and clinical treatment.

Comparative Analysis of Symptomatology in Hospitalized Children with RSV, COVID-19, and Influenza Infections

BACKGROUND The clinical course of respiratory syncytial virus (RSV), SARS-CoV-2, and influenza infections comprises many non-specific symptoms, which makes diagnosis difficult. The aim of this study was to retrospectively analyze the symptomatology of these infections in children and to search for correlations between them. MATERIAL AND METHODS A total of 121 children with a positive RSV (n=61), influenza (n=31), or SARS-CoV-2 (n=29) antigen test were enrolled in this retrospective analysis. Children were aged up to 71 months (median, 8 months). The collected data were collated by performing statistical analysis using the chi-square test and comparing the results using OR (odds ratio) and 95%CI (confidence interval). RESULTS There was a higher risk of fever in children with influenza than in those with RSV. Patients infected with RSV had a higher risk of nasal blockage than those with SARS-CoV-2. Dyspnea was more common in RSV infection than in influenza. Severe, sleep-awakening cough was more frequent in children with RSV than in those with COVID-19. Influenza was more prevalent in children aged >24 months than in those aged 7-24 months. RSV-infected children had a higher risk of numerous auscultatory changes compared to those with SARS-CoV-2. In the case of RSV infection, symptoms requiring hospitalization occurred later than in SARS-CoV-2 infection. CONCLUSIONS Children aged >24 months were at higher risk of contracting influenza. Numerous auscultatory changes, nasal blockage, and dyspnea were more common in children with RSV. There was a higher risk of dyspnea in children with RSV. Fever was more frequent in children with influenza. However, none of the symptoms clearly indicated the etiology of the infection.

Clinical Presentation and Co-Detection of Respiratory Pathogens in Children Under 5 Years with Non-COVID-19 Bacterial and Viral Respiratory Tract Infections: A Prospective Study in Białystok, Poland (2021-2022)

BACKGROUND Respiratory tract infections (RTIs) in children often involve a complex interplay between viruses and bacteria. This study aimed to evaluate clinical presentation in children under 5 years old diagnosed with non-COVID-19 bacterial and viral respiratory tract co-infections between October 2021 and May 2022 in Białystok, Poland. MATERIAL AND METHODS We recruited 100 children under 5 years with RTIs who tested negative for SARS-CoV-2. Nasopharyngeal swabs were screened for 19 viruses and 7 bacterial strains using molecular assays. RESULTS Viral pathogens were detected in 71% of patients and bacterial pathogens were detected in 59%. The most common pathogens were Haemophilus influenzae (n=48), rhinoviruses (n=32), and Streptococcus pneumoniae (n=30). Single pathogens were detected in 36%, dual in 37%, triple in 15%, and quadruple in 2%. Bacterial pathogens were co-detected with viruses in 40 cases, mostly with rhinoviruses (n=15). Two different viruses were found in 14 children and the most common co-detection was adenovirus with rhinovirus (n=5); dyspnea (63% vs 11%) and wheezing (75% vs 22%) were more common in children with human bocavirus. Fever was a common symptom in children with human adenovirus (88% vs 58%). Detection of bacteria and multiple detections were more common in day-care attendees, but were not associated with clinical picture of RTI. CONCLUSIONS Consistent with previous studies, we found a high prevalence of rhinoviruses, despite ongoing implementation of non-pharmaceutical interventions to contain the COVID-19 pandemic. Co-detection of 2 different respiratory pathogens was frequent, but we found no evidence that this was associated with the severity of infections.

Comparing antibiotic prescriptions in primary care between SARS-CoV-2 and influenza: a retrospective observational study

BACKGROUND

Antibiotics are frequently prescribed during viral respiratory infection episodes in primary care. There is limited information about antibiotic prescription during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic in primary care and its association with risk factors for an adverse course.

AIM

To compare the proportion of antibiotic prescriptions between patients with COVID-19 and influenza or influenza-like symptoms, and to assess the association between antibiotic prescriptions and risk factors for an adverse course of COVID-19.

DESIGN & SETTING

An observational cohort study using pseudonymised and coded routine healthcare data extracted from 85 primary care practices in the Netherlands.

METHOD

Adult patients with influenza and influenza-like symptoms were included from the 2017 influenza season to the 2020 season. Adult patients with suspected or confirmed COVID-19 were included from the first (15 February 2020-1 August 2020) and second (1 August 2020-1 January 2021) SARS-CoV-2 waves. Proportions of antibiotic prescriptions were calculated for influenza and COVID-19 patients. Odds ratios (ORs) were used to compare the associations of antibiotic prescriptions in COVID-19 patients with risk factors, hospital admission, intensive care unit (ICU) admission, and mortality.

RESULTS

The proportion of antibiotic prescriptions during the first SARS-CoV-2 wave was lower than during the 2020 influenza season (9.6% versus 20.7%), difference 11.1% (95% confidence interval [CI] = 8.7 to 13.5). During the second SARS-CoV-2 wave, antibiotic prescriptions were associated with being aged ≥70 years (OR 2.05; 95% CI = 1.43 to 2.93), the number of comorbidities (OR 1.46; 95% CI = 1.18 to 1.82), and admission to hospital (OR 3.19; 95% CI = 2.02 to 5.03) or ICU (OR 4.64; 95% CI = 2.02 to 10.62).

CONCLUSION

Antibiotic prescription was less common during the SARS-CoV-2 pandemic than during influenza seasons, and was associated with an adverse course and its risk factors. The findings suggest a relatively targeted prescription policy of antibiotics in primary care during COVID-19.

Prevalence of chronic conditions and influenza vaccination coverage rates in Germany: Results of a health insurance claims data analysis

BACKGROUND

The significant annual burden caused by seasonal influenza has led to global calls for increased influenza vaccination coverage rates (VCRs). We aimed to estimate the proportion of the German population at high risk of serious illness from influenza due to chronic conditions and to estimate age-specific VCRs of people with/without chronic conditions.

METHODS

Using health insurance claims data covering nine influenza seasons (2010-2019), we assessed up to 7 million insured individuals per season across all German regions. Individuals were classified according to age and presence of chronic health conditions. VCRs were estimated using outpatient healthcare utilization documentation.

RESULTS

In the 2018-2019 influenza season, 47.3% of individuals had ≥1 chronic condition. Most common were circulatory disorders, accounting for more than a third of individuals with ≥1 condition. Prevalence of chronic diseases, and therefore the proportion of high-risk individuals, increased slightly over time across most age groups. A downward trend in influenza VCRs was observed in all age groups until the 2017-2018 season, followed by a noticeable increase in the 2018-2019 season. Highest VCRs occurred among individuals of ≥60 years, with a 38.5% VCR for this age group in the 2018-2019 season. Several factors, including age, chronic condition type, and geographical location, affected VCRs.

CONCLUSIONS

Influenza VCRs in individuals at high risk of severe complications from influenza infection are insufficient. Our results suggest that intensified public health efforts are necessary to reach the World Health Organization vaccination coverage target of 75%.

Role of Age in the Spread of Influenza, 2011-2019: Data From the US Influenza Vaccine Effectiveness Network

Intraseason timing of influenza infection among persons of different ages could reflect relative contributions to propagation of seasonal epidemics and has not been examined among ambulatory patients. Using data from the US Influenza Vaccine Effectiveness Network, we calculated risk ratios derived from comparing weekly numbers of influenza cases prepeak with those postpeak during the 2010-2011 through 2018-2019 influenza seasons. We sought to determine age-specific differences during the ascent versus descent of an influenza season by influenza virus type and subtype. We estimated 95% credible intervals around the risk ratios using Bayesian joint posterior sampling of weekly cases. Our population consisted of ambulatory patients with laboratory-confirmed influenza who enrolled in an influenza vaccine effectiveness study at 5 US sites during 9 influenza seasons after the 2009 influenza A virus subtype H1N1 (H1N1) pandemic. We observed that young children aged <5 years tended to more often be infected with H1N1 during the prepeak period, while adults aged ≥65 years tended to more often be infected with H1N1 during the postpeak period. However, for influenza A virus subtype H3N2, children aged <5 years were more often infected during the postpeak period. These results may reflect a contribution of different age groups to seasonal spread, which may differ by influenza virus type and subtype.

Influenza and Influenza-Like Respiratory Virus Infections in Children During the 2019/20 Influenza Seazon and the COVID-19 Pandemic in Poland: Data from the Department of Influenza Research, the National Influenza Center at the National Institute of Public Health, National Institute of Hygiene-National Research Institute and 16 Voivodeship Sanitary and Epidemiological Stations

BACKGROUND This population study aimed to investigate influenza and influenza-like respiratory virus infections in children during the 2019/20 influenza season and the coronavirus disease 2019 (COVID-19) pandemic in Poland. MATERIAL AND METHODS This study analyzed data from the National Influenza Centre, the Department of Influenza Research at the National Institute of Public Health, and 16 Voivodeship Sanitary and Epidemiological Stations in Poland. Nose and throat swabs were obtained from children during the 2019/20 influenza season and the COVID-19 pandemic. Viral RNA detection was performed using quantitative reverse transcription-polymerase chain reaction (qRT-PCR) to diagnose influenza virus infection and viral subtypes. RESULTS In the analyzed group, both cases of influenza A and B and infections with influenza-like viruses were confirmed. Among all cases caused by influenza viruses, influenza A was more frequent than B, with predominance of the A/H1N1/pdm09 subtype. The flu-like virus which infected most children was the human respiratory syncytial virus (RSV). The greatest number of cases with RSV was registered in the group of the youngest children (0-4 years). CONCLUSIONS This population study from Poland showed that during the COVID-19 pandemic, and during the winter influenza season of 2019/20, influenza and influenza-like viral infections in children showed some differences from previous influenza seasons. The findings highlight the importance of viral infection surveillance and influenza vaccination in the pediatric population.

Impact of coinfection status and comorbidity on disease severity in adult emergency department patients with influenza B

Background

Influenza B accounts for approximately one fourth of the seasonal influenza burden. However, research on the importance of influenza B has received less attention compared to influenza A. We sought to describe the association of both coinfections and comorbidities with disease severity among adults presenting to emergency departments (ED) with influenza B.

Methods

Nasopharyngeal samples from patients found to be influenza B positive in four US and three Taiwanese ED over four consecutive influenza seasons (2014–2018) were tested for coinfections with the ePlex RP RUO panel. Multivariable logistic regressions were fitted to model adjusted odds ratios (aOR) for two severity outcomes separately: hospitalization and pneumonia diagnosis. Adjusting for demographic factors, underlying health conditions, and the National Early Warning Score (NEWS), we estimated the association of upper respiratory coinfections and comorbidity with disease severity (including hospitalization or pneumonia).

Results

Amongst all influenza B positive individuals (n = 446), presence of another upper respiratory pathogen was associated with an increased likelihood of hospitalization (aOR = 2.99 [95% confidence interval (95% CI): 1.14–7.85, p = 0.026]) and pneumonia (aOR = 2.27 [95% CI: 1.25–4.09, p = 0.007]). Chronic lung diseases (CLD) were the strongest predictor for hospitalization (aOR = 3.43 [95% CI: 2.98–3.95, p < 0.001]), but not for pneumonia (aOR = 1.73 [95% CI: 0.80–3.78, p = 0.166]).

Conclusion

Amongst ED patients infected with influenza B, the presence of other upper respiratory pathogens was independently associated with both hospitalization and pneumonia; presence of CLD was also associated with hospitalization. These findings may be informative for ED clinician's in managing patients infected with influenza B.

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Background

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study.

Objective

This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset.

Methods

This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets.

Results

Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19).

Conclusions

To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

Distinguishing Causation From Correlation in the Use of Correlates of Protection to Evaluate and Develop Influenza Vaccines

There is increasing attention to the need to identify new immune markers for the evaluation of existing and new influenza vaccines. Immune markers that could predict individual protection against infection and disease, commonly called correlates of protection (CoPs), play an important role in vaccine development and licensing. Here, we discuss the epidemiologic considerations when evaluating immune markers as potential CoPs for influenza vaccines and emphasize the distinction between correlation and causation. While an immune marker that correlates well with protection from infection can be used as a predictor of vaccine efficacy, it should be distinguished from an immune marker that plays a mechanistic role in conferring protection against a clinical endpoint-the latter might be a more reliable predictor of vaccine efficacy and a more appropriate target for rational vaccine design. To clearly distinguish mechanistic and nonmechanistic CoPs, we suggest using the term "correlates of protection" for nonmechanistic CoPs, and ''mediators of protection'' for mechanistic CoPs. Furthermore, because the interactions among and relative importance of correlates or mediators of protection can vary according to age or prior vaccine experience, the effect sizes and thresholds for protective effects for CoPs could also vary in different segments of the population.

Influenza Vaccine in Heart Failure

BACKGROUND

Influenza infection is a serious event for patients with heart failure (HF). Little knowledge exists about the association between influenza vaccination and outcome in patients with HF. This study sought to determine whether influenza vaccination is associated with improved long-term survival in patients with newly diagnosed HF.

METHODS

We performed a nationwide cohort study including all patients who were >18 years of age and diagnosed with HF in Denmark in the period of January 1, 2003, to June 1, 2015 (n=134 048). We collected linked data using nationwide registries. Vaccination status, number, and frequency during follow-up were treated as time-varying covariates in time-dependent Cox regression.

RESULTS

Follow-up was 99.8% with a median follow-up time of 3.7 years (interquartile range, 1.7-6.8 years). The vaccination coverage of the study cohort ranged from 16% to 54% during the study period. In unadjusted analysis, receiving ≥1 vaccinations during follow-up was associated with a higher risk of death. After adjustment for inclusion date, comorbidities, medications, household income, and education level, receiving ≥1 vaccinations was associated with an 18% reduced risk of death (all-cause: hazard ratio, 0.82; 95% CI, 0.81-0.84; P<0.001; cardiovascular causes: hazard ratio, 0.82; 95% CI, 0.81-0.84; P<0.001). Annual vaccination, vaccination early in the year (September to October), and greater cumulative number of vaccinations were associated with larger reductions in the risk of death compared with intermittent vaccination.

CONCLUSIONS

In patients with HF, influenza vaccination was associated with a reduced risk of both all-cause and cardiovascular death after extensive adjustment for confounders. Frequent vaccination and vaccination earlier in the year were associated with larger reductions in the risk of death compared with intermittent and late vaccination.

Enhanced Safety Surveillance of Influenza Vaccines in General Practice, Winter 2015-16: Feasibility Study

Background

The European Medicines Agency (EMA) requires vaccine manufacturers to conduct enhanced real-time surveillance of seasonal influenza vaccination. The EMA has specified a list of adverse events of interest to be monitored. The EMA sets out 3 different ways to conduct such surveillance: (1) active surveillance, (2) enhanced passive surveillance, or (3) electronic health record data mining (EHR-DM). English general practice (GP) is a suitable setting to implement enhanced passive surveillance and EHR-DM.

Objective

This study aimed to test the feasibility of conducting enhanced passive surveillance in GP using the yellow card scheme (adverse events of interest reporting cards) to determine if it has any advantages over EHR-DM alone.

Methods

A total of 9 GPs in England participated, of which 3 tested the feasibility of enhanced passive surveillance and the other 6 EHR-DM alone. The 3 that tested EPS provided patients with yellow (adverse events) cards for patients to report any adverse events. Data were extracted from all 9 GPs’ EHRs between weeks 35 and 49 (08/24/2015 to 12/06/2015), the main period of influenza vaccination. We conducted weekly analysis and end-of-study analyses.

Results

Our GPs were largely distributed across England with a registered population of 81,040. In the week 49 report, 15,863/81,040 people (19.57% of the registered practice population) were vaccinated. In the EPS practices, staff managed to hand out the cards to 61.25% (4150/6776) of the vaccinees, and of these cards, 1.98% (82/4150) were returned to the GP offices. Adverse events of interests were reported by 113 /7223 people (1.56%) in the enhanced passive surveillance practices, compared with 322/8640 people (3.73%) in the EHR-DM practices.

Conclusions

Overall, we demonstrated that GPs EHR-DM was an appropriate method of enhanced surveillance. However, the use of yellow cards, in enhanced passive surveillance practices, did not enhance the collection of adverse events of interests as demonstrated in this study. Their return rate was poor, data entry from them was not straightforward, and there were issues with data reconciliation. We concluded that customized cards prespecifying the EMA’s adverse events of interests, combined with EHR-DM, were needed to maximize data collection.

International Registered Report Identifier (IRRID)

RR2-10.1136/bmjopen-2016-015469

Feasibility of Point-of-Care Testing for Influenza Within a National Primary Care Sentinel Surveillance Network in England: Protocol for a Mixed Methods Study

Background

Point-of-care testing (POCT) for influenza promises to provide real-time information to influence clinical decision making and improve patient outcomes. Public Health England has published a toolkit to assist implementation of these tests in the UK National Health Service.

Objective

A feasibility study will be undertaken to assess the implementation of influenza POCT in primary care as part of a sentinel surveillance network.

Methods

We will conduct a mixed methods study to compare the sampling rates in practices using POCT and current virology swabbing practices not using POCT, and to understand the issues and barriers to implementation of influenza POCT in primary care workflows. The study will take place between March and May 2019. It will be nested in general practices that are part of the English national sentinel surveillance network run by the Royal College of General Practitioners Research and Surveillance Centre. The primary outcome is the number of valid influenza swabs taken and tested by the practices involved in the study using the new POCT.

Results

A total of 6 practices were recruited, and data collection commenced on March 11, 2019. Moreover, 312 swab samples had been collected at the time of submission of the protocol, which was 32.5% (312/960) of the expected sample size. In addition, 68 samples were positive for influenza, which was 20.1% (68/338) of the expected sample size.

Conclusions

To the best of our knowledge, this is the first time an evaluation study has been undertaken on POCT for influenza in general practice in the United Kingdom. This proposed study promises to shed light on the feasibility of implementation of POCT in primary care and on the views of practitioners about the use of influenza POCT in primary care, including its impact on primary care workflows.

International Registered Report Identifier (IRRID)

DERR1-10.2196/14186

Participatory Disease Surveillance Systems: Ethical Framework

Advances in information technology are changing public health at an unprecedented rate. Participatory surveillance systems are contributing to public health by actively engaging digital (eg, Web-based) communities of volunteer citizens to report symptoms and other pertinent information on public health threats and also by empowering individuals to promptly respond to them. However, this digital model raises ethical issues on top of those inherent in traditional forms of public health surveillance. Research ethics are undergoing significant changes in the digital era where not only participants' physical and psychological well-being but also the protection of their sensitive data have to be considered. In this paper, the digital platform of Influenzanet is used as a case study to illustrate those ethical challenges posed to participatory surveillance systems using digital platforms and mobile apps. These ethical challenges include the implementation of electronic consent, the protection of participants' privacy, the promotion of justice, and the need for interdisciplinary capacity building of research ethics committees. On the basis of our analysis, we propose a framework to regulate and strengthen ethical approaches in the field of digital public health surveillance.

Improved Real-Time Influenza Surveillance: Using Internet Search Data in Eight Latin American Countries

Background

Novel influenza surveillance systems that leverage Internet-based real-time data sources including Internet search frequencies, social-network information, and crowd-sourced flu surveillance tools have shown improved accuracy over the past few years in data-rich countries like the United States. These systems not only track flu activity accurately, but they also report flu estimates a week or more ahead of the publication of reports produced by healthcare-based systems, such as those implemented and managed by the Centers for Disease Control and Prevention. Previous work has shown that the predictive capabilities of novel flu surveillance systems, like Google Flu Trends (GFT), in developing countries in Latin America have not yet delivered acceptable flu estimates.

Objective

The aim of this study was to show that recent methodological improvements on the use of Internet search engine information to track diseases can lead to improved retrospective flu estimates in multiple countries in Latin America.

Methods

A machine learning-based methodology that uses flu-related Internet search activity and historical information to monitor flu activity, named ARGO (AutoRegression with Google search), was extended to generate flu predictions for 8 Latin American countries (Argentina, Bolivia, Brazil, Chile, Mexico, Paraguay, Peru, and Uruguay) for the time period: January 2012 to December of 2016. These retrospective (out-of-sample) Influenza activity predictions were compared with historically observed flu suspected cases in each country, as reported by Flunet, an influenza surveillance database maintained by the World Health Organization. For a baseline comparison, retrospective (out-of-sample) flu estimates were produced for the same time period using autoregressive models that only leverage historical flu activity information.

Results

Our results show that ARGO-like models’ predictive power outperform autoregressive models in 6 out of 8 countries in the 2012-2016 time period. Moreover, ARGO significantly improves on historical flu estimates produced by the now discontinued GFT for the time period of 2012-2015, where GFT information is publicly available.

Conclusions

We demonstrate here that a self-correcting machine learning method, leveraging Internet-based disease-related search activity and historical flu trends, has the potential to produce reliable and timely flu estimates in multiple Latin American countries. This methodology may prove helpful to local public health officials who design and implement interventions aimed at mitigating the effects of influenza outbreaks. Our methodology generally outperforms both the now-discontinued tool GFT, and autoregressive methodologies that exploit only historical flu activity to produce future disease estimates.

Enhanced passive surveillance of influenza vaccination in England, 2016-2017- an observational study using an adverse events reporting card

Influenza is a major public health burden, mainly prevented by vaccination. Recommendations on influenza vaccine composition are updated annually and constant benefit-risk monitoring is therefore needed. We conducted near-real-time enhanced passive surveillance (EPS) for the influenza vaccine, Fluarix Tetra, according to European Medicines Agency guidance, in 10 volunteer general practices in England using Fluarix Tetra as their principal influenza vaccine brand, from 1-Sep to 30-Nov-2016. The EPS method used a combination of routinely collected data from electronic health records (EHR) and a customized adverse events reporting card (AERC) distributed to participants vaccinated with Fluarix Tetra. For participants vaccinated with a different influenza vaccine, data were derived exclusively from the EHR. We reported weekly and cumulative incidence of pre-defined adverse events of interest (AEI) occurring within 7 days post-vaccination, adjusted for clustering effect. Of the 97,754 eligible participants, 19,334 (19.8%) received influenza vaccination, of whom 13,861 (71.7%) received Fluarix Tetra. A total of 1,049 participants receiving Fluarix Tetra reported AEIs; 703 (67%) used the AERC (adjusted cumulative incidence rate 4.96% [95% CI: 3.92−6.25]). Analysis by individual pre-specified AEI categories identified no safety signal for Fluarix Tetra. A total of 62 individuals reported an AEI with a known brand of non-GSK influenza vaccine and 54 with an unknown brand (adjusted cumulative incidence rate 2.59% [1.93−3.47] and 1.77% [1.42−2.20], respectively). In conclusion, the study identified no safety signal for Fluarix Tetra and showed that the AERC was a useful tool that complemented routine pharmacovigilance by allowing more comprehensive capture of AEIs.10.1080/21645515.2019.1565258-UF0001

Serological surveillance of influenza in an English sentinel network: pilot study protocol

BACKGROUND

Rapidly undertaken age-stratified serology studies can produce valuable data about a new emerging infection including background population immunity and seroincidence during an influenza pandemic. Traditionally seroepidemiology studies have used surplus laboratory sera with little or no clinical information or have been expensive detailed population based studies. We propose collecting population based sera from the Royal College of General Practitioners (RCGP) Research and Surveillance Centre (RSC), a sentinel network with extensive clinical data.

AIM

To pilot a mechanism to undertake population based surveys that collect serological specimens and associated patient data to measure seropositivity and seroincidence due to seasonal influenza, and create a population based serology bank. METHODS AND ANALYSIS: Setting and Participants: We will recruit 6 RCGP RSC practices already taking nasopharyngeal virology swabs. Patients who attend a scheduled blood test will be consented to donate additional blood samples. Approximately 100-150 blood samples will be collected from each of the following age bands - 18- 29, 30- 39, 40- 49, 50- 59, 60- 69 and 70+ years.

METHODS

We will send the samples to the Public Health England (PHE) Seroepidemiology Unit for processing and storage. These samples will be tested for influenza antibodies, using haemagglutination inhibition assays. Serology results will be pseudonymised, sent to the RCGP RSC and combined using existing processes at the RCGP RSC secure hub. The influenza seroprevalence results from the RCGP cohort will be compared against those from the annual PHE influenza residual serosurvey.

ETHICS AND DISSEMINATION

Ethical approval was granted by the Proportionate Review Sub- Committee of the London - Camden & Kings Cross on 6 February 2018. This study received approval from Health Research Authority on 7 February 2018. On completion the results will be made available via peer-reviewed journals.

[Mortality attributable to influenza in pre-vaccination and post-vaccination periods in Argentina: an ecological study (2002-2016)Mortalidade atribuível à gripe no período pré-vacinal e pós-vacinal na Argentina: estudo ecológico (2002-2016)]

Objetivos

Comparar las tasas de mortalidad por infección respiratoria aguda grave atribuible a gripe (IRAG) entre los períodos antes de la vacunación (AV) y después de la vacunación (DV), conocer la evolución histórica y estacionalidad de serie histórica entre 2002-2016 y estimar el riesgo de morir de niños entre 6 y 23 meses mediante el empleo de un modelo estadístico.

Métodos

Estudio de serie histórica con datos oficiales de mortalidad del informe estadístico de defunción. Se consideraron como IRAG los códigos de CIE-10 entre J09-18.9 y J22X. Se calcularon tasas brutas (TB) y ajustadas por edad (TAE) y se compararon los períodos AV (2002-2009) y DV (2010-2016) con prueba de χ2. El mejor modelo estadístico fue el que comparó las defunciones por IRAG en niños durante el 2002 con otros años. Se analizaron los datos con programa R, nivel de significancia P <0,05.

Resultados

El 4,6% (301 747) de las defunciones fueron por IRAG, con una edad mediana de 82 años, el porcentaje de fallecidos menores de dos años disminuyó en el período DV (2,34% a 0,99%, P < 0,05). Se presentó una marcada estacionalidad en invierno. Las TAE en gerontes pasaron de 259,8 AV a 328,6 por 100 000 personas DV (P < 0,05). En los niños, la TB disminuyó de manera significativa, estimando que el riesgo de morir por IRAG, comparado con el año 2 002, fue significativamente menor durante 3 años DV.

Conclusiones

La disminución de la mortalidad por gripe en Argentina fue más evidente en niños, con un descenso estimado de 3,5 niños fallecidos por IRAG por mes.

Burden of medically attended influenza in Norway 2008-2017

Background

The burden of influenza in Norway remains uncertain, and data on seasonal variations and differences by age groups are needed.

Objective

To describe number of patients diagnosed with influenza in Norway each season and the number treated in primary or specialist health care by age. Further, to compare the burden of seasonal influenza with the 2009‐2010 pandemic outbreak.

Methods

We used Norwegian national health registries and identified all patients diagnosed with influenza from 2008 to 2017. We calculated seasonal rates, compared hospitalized patients with patients in primary care and compared seasonal influenza with the 2009‐2010 pandemic outbreak.

Results

Each season, on average 1.7% of the population were diagnosed with influenza in primary care, the average rate of hospitalization was 48 per 100 000 population while the average number of hospitalized patients each season was nearly 2500. The number of hospitalized influenza patients ranged from 579 in 2008‐2009 to 4973 in 2016‐2017. Rates in primary care were highest among young adults while hospitalization rates were highest in patients 80 years and older and in children below 5 years. The majority of in‐hospital deaths were in patients 70 years and older. Fewer patients were hospitalized during the 2009‐2010 pandemic than in seasonal outbreaks, but during the pandemic, more people in the younger age groups were hospitalized and fatal cases were younger.

Conclusion

Influenza causes a substantial burden in primary care and hospitals. In non‐pandemic seasons, people above 80 years have the highest risk of influenza hospitalization and death.

Understanding barriers to effective management of influenza outbreaks by residential aged care facilities

OBJECTIVE

To identify the perceived barriers to the implementation of the Australian national guidelines on influenza outbreak management with Sydney Local Health District (SLHD) residential aged care facility (RACF) staff.

METHODS

All SLHD RACFs were invited to participate in a telephone interview. The questionnaire collected information about demographic characteristics and participants' level of agreement with statements regarding perceived barriers to implementing the national guidelines for influenza outbreak management.

RESULTS

Twenty-eight of 61 RACFs (46%) participated in the study. The three most common barriers identified were as follows: scepticism towards staff influenza vaccination (n = 13, 46%); the effort required to read the national guidelines (n = 11, 39%); and lack of infrastructure to physically separate residents during an outbreak (n = 10, 36%).

CONCLUSIONS

We recommend implementing and evaluating programmes which address misconceptions about influenza vaccination amongst RACF staff. Further, all RACF staff, including care staff, should receive targeted education on the role of infection control in influenza outbreak management.

Clinical features of Mycoplasma pneumoniae coinfection and need for its testing in influenza pneumonia patients

Background

To investigate the clinical features of coinfection due to Mycoplasma pneumoniae (M. pneumoniae), a common copathogen in influenza, in influenza pneumonia patients.

Methods

We reviewed 4,465 patients with influenza who visited a tertiary care hospital emergency department in Seoul (Korea) from 2010 through 2016, and underwent immunoglobulin M (IgM) serology or polymerase chain reaction (PCR) for M. pneumoniae. Influenza pneumonia was defined as laboratory-confirmed influenza plus radiographic pneumonia. Patients with healthcare-associated pneumonia or non-mycoplasma bacterial coinfection were excluded. Clinical, laboratory, and radiographic findings and outcomes of the influenza pneumonia patients with and without M. pneumoniae coinfection were compared. Multivariable logistic regression analysis was performed to identify factors associated with the coinfection.

Results

Of 244 influenza pneumonia patients, 41 (16.8%) had M. pneumoniae coinfection. These patients were younger with a higher frequency of age of 5-10 years, and had higher white blood cell (WBC) and lymphocyte counts; lower concentration of C-reactive protein (CRP). The coinfection had no association with specific radiographic findings and poor outcome. Multivariable analysis showed the age of 5-10 years (adjusted odds ratio, 18.83; 95% confidence interval, 5.899-60.08; P<0.001) as the factor associated with the coinfection.

Conclusions

M. pneumoniae coinfection in influenza pneumonia may be associated with the age of 5-10 years, and otherwise clinically indistinct from influenza pneumonia without the coinfection. This finding suggests the need for M. pneumoniae testing in patients aged 5-10 years with influenza pneumonia.

Research Ethics in the European Influenzanet Consortium: Scoping Review

Background

Influenzanet was launched in several European countries to monitor influenza-like illness during flu seasons with the help of volunteering participants and Web-based technologies. As in the case of developing fields, ethical approaches are not well developed in the collection, processing, and analysis of participants’ information. Existing controversies and varying national ethical regulations can, thus, hamper efficient cross-border research collaboration to the detriment of quality disease surveillance.

Objective

This scoping review characterizes current practices on how ethical, legal, and social issues (ELSIs) pertinent to research ethics are handled by different Influenzanet country groups to analyze similarities and identify the need for further harmonization of ethical approaches.

Methods

A literature search was carried out on PubMed, Web of Science, Global Digital Library on Ethics, and Bioethics Literature Database to identify ELSIs for Influenzanet country platforms. Only English-language papers were included with publication dates from 2003 to 2017. Publications were screened for the application of bioethics principles in the implementation of country platforms. Additional publications gathered from the Influenzanet Consortium website, reference screening, and conference proceeding were screened for ELSIs.

Results

We gathered 96 papers from our search methodology. In total, 28 papers that mentioned ELSIs were identified and included in this study. The Research Ethics Committee (REC) approvals were sought for recruiting participants and collecting their data in 8 of 11 country platforms and informed e-consent was sought from participants in 9 of 11 country platforms. Furthermore, personal data protection was ensured throughout the Consortium using data anonymization before processing and analysis and using aggregated data.

Conclusions

Epidemics forecasting activities, such as Influenzanet, are beneficial; however, its benefits could be further increased through the harmonization of data gathering and ethical requirements. This objective is achievable by the Consortium. More transparency should be promoted concerning REC-approved research for Influenzanet-like systems. The validity of informed e-consent could also be increased through the provision of a user friendly and standard information sheet across the Consortium where participants agree to its terms, conditions, and privacy policies before being able to fill in the questionnaire. This will help to build trust in the general public while preventing any decline in participation.

Accurate Influenza Monitoring and Forecasting Using Novel Internet Data Streams: A Case Study in the Boston Metropolis

Background

Influenza outbreaks pose major challenges to public health around the world, leading to thousands of deaths a year in the United States alone. Accurate systems that track influenza activity at the city level are necessary to provide actionable information that can be used for clinical, hospital, and community outbreak preparation.

Objective

Although Internet-based real-time data sources such as Google searches and tweets have been successfully used to produce influenza activity estimates ahead of traditional health care–based systems at national and state levels, influenza tracking and forecasting at finer spatial resolutions, such as the city level, remain an open question. Our study aimed to present a precise, near real-time methodology capable of producing influenza estimates ahead of those collected and published by the Boston Public Health Commission (BPHC) for the Boston metropolitan area. This approach has great potential to be extended to other cities with access to similar data sources.

Methods

We first tested the ability of Google searches, Twitter posts, electronic health records, and a crowd-sourced influenza reporting system to detect influenza activity in the Boston metropolis separately. We then adapted a multivariate dynamic regression method named ARGO (autoregression with general online information), designed for tracking influenza at the national level, and showed that it effectively uses the above data sources to monitor and forecast influenza at the city level 1 week ahead of the current date. Finally, we presented an ensemble-based approach capable of combining information from models based on multiple data sources to more robustly nowcast as well as forecast influenza activity in the Boston metropolitan area. The performances of our models were evaluated in an out-of-sample fashion over 4 influenza seasons within 2012-2016, as well as a holdout validation period from 2016 to 2017.

Results

Our ensemble-based methods incorporating information from diverse models based on multiple data sources, including ARGO, produced the most robust and accurate results. The observed Pearson correlations between our out-of-sample flu activity estimates and those historically reported by the BPHC were 0.98 in nowcasting influenza and 0.94 in forecasting influenza 1 week ahead of the current date.

Conclusions

We show that information from Internet-based data sources, when combined using an informed, robust methodology, can be effectively used as early indicators of influenza activity at fine geographic resolutions.

Determinants of Participants' Follow-Up and Characterization of Representativeness in Flu Near You, A Participatory Disease Surveillance System

Background

Flu Near You (FNY) is an Internet-based participatory surveillance system in the United States and Canada that allows volunteers to report influenza-like symptoms using a brief weekly symptom report.

Objective

Our objective was to evaluate the representativeness of the FNY population compared with the general population of the United States, explore the demographic and behavioral characteristics associated with FNY’s high-participation users, and summarize results from a user survey of a cohort of FNY participants.

Methods

We compared (1) the representativeness of sex and age groups of FNY participants during the 2014-2015 flu season versus the general US population and (2) the distribution of Human Development Index (HDI) scores of FNY participants versus that of the general US population. We analyzed associations between demographic and behavioral factors and the level of participant follow-up (ie, high vs low). Finally, descriptive statistics of responses from FNY’s 2015 and 2016 end-of-season user surveys were calculated.

Results

During the 2014-2015 influenza season, 47,234 unique participants had at least one FNY symptom report that was either self-reported (users) or submitted on their behalf (household members). The proportion of female FNY participants was significantly higher than that of the general US population (n=28,906, 61.2% vs 51.1%, P<.001). Although each age group was represented in the FNY population, the age distribution was significantly different from that of the US population (P<.001). Compared with the US population, FNY had a greater proportion of individuals with HDI >5.0, signaling that the FNY user distribution was more affluent and educated than the US population baseline. We found that high-participation use (ie, higher participation in follow-up symptom reports) was associated with sex (females were 25% less likely than men to be high-participation users), higher HDI, not reporting an influenza-like illness at the first symptom report, older age, and reporting for household members (all differences between high- and low-participation users P<.001). Approximately 10% of FNY users completed an additional survey at the end of the flu season that assessed detailed user characteristics (3217/33,324 in 2015; 4850/44,313 in 2016). Of these users, most identified as being either retired or employed in the health, education, and social services sectors and indicated that they achieved a bachelor’s degree or higher.

Conclusions

The representativeness of the FNY population and characteristics of its high-participation users are consistent with what has been observed in other Internet-based influenza surveillance systems. With targeted recruitment of underrepresented populations, FNY may improve as a complementary system to timely tracking of flu activity, especially in populations that do not seek medical attention and in areas with poor official surveillance data.

Evaluating Google, Twitter, and Wikipedia as Tools for Influenza Surveillance Using Bayesian Change Point Analysis: A Comparative Analysis

Background

Traditional influenza surveillance relies on influenza-like illness (ILI) syndrome that is reported by health care providers. It primarily captures individuals who seek medical care and misses those who do not. Recently, Web-based data sources have been studied for application to public health surveillance, as there is a growing number of people who search, post, and tweet about their illnesses before seeking medical care. Existing research has shown some promise of using data from Google, Twitter, and Wikipedia to complement traditional surveillance for ILI. However, past studies have evaluated these Web-based sources individually or dually without comparing all 3 of them, and it would be beneficial to know which of the Web-based sources performs best in order to be considered to complement traditional methods.

Objective

The objective of this study is to comparatively analyze Google, Twitter, and Wikipedia by examining which best corresponds with Centers for Disease Control and Prevention (CDC) ILI data. It was hypothesized that Wikipedia will best correspond with CDC ILI data as previous research found it to be least influenced by high media coverage in comparison with Google and Twitter.

Methods

Publicly available, deidentified data were collected from the CDC, Google Flu Trends, HealthTweets, and Wikipedia for the 2012-2015 influenza seasons. Bayesian change point analysis was used to detect seasonal changes, or change points, in each of the data sources. Change points in Google, Twitter, and Wikipedia that occurred during the exact week, 1 preceding week, or 1 week after the CDC’s change points were compared with the CDC data as the gold standard. All analyses were conducted using the R package “bcp” version 4.0.0 in RStudio version 0.99.484 (RStudio Inc). In addition, sensitivity and positive predictive values (PPV) were calculated for Google, Twitter, and Wikipedia.

Results

During the 2012-2015 influenza seasons, a high sensitivity of 92% was found for Google, whereas the PPV for Google was 85%. A low sensitivity of 50% was calculated for Twitter; a low PPV of 43% was found for Twitter also. Wikipedia had the lowest sensitivity of 33% and lowest PPV of 40%.

Conclusions

Of the 3 Web-based sources, Google had the best combination of sensitivity and PPV in detecting Bayesian change points in influenza-related data streams. Findings demonstrated that change points in Google, Twitter, and Wikipedia data occasionally aligned well with change points captured in CDC ILI data, yet these sources did not detect all changes in CDC data and should be further studied and developed.

The Development of Surveillance Systems

Surveillance systems in public health practice have increased in number and sophistication with advances in data collection, analysis, and communication. When the Communicable Disease Center (now the Centers for Disease Control and Prevention) was founded some 70 years ago, surveillance referred to the close observation of individuals with suspected smallpox, plague, or cholera. Alexander Langmuir, head of the Epidemiology Branch, redefined surveillance as the epidemiology-based critical factor in infectious disease control. I joined Langmuir as assistant chief in 1955 and was appointed chief of the Surveillance Section in 1961. In this paper, I describe Langmuir's redefinition of surveillance. Langmuir asserted that its proper use in public health meant the systematic reporting of infectious diseases, the analysis and epidemiologic interpretation of data, and both prompt and widespread dissemination of results. I outline the Communicable Disease Center's first surveillance systems for malaria, poliomyelitis, and influenza. I also discuss the role of surveillance in the global smallpox eradication program, emphasizing that the establishment of systematic reporting systems and prompt action based on results were critical factors of the program.

What Is the Added Benefit of Oropharyngeal Swabs Compared to Nasal Swabs Alone for Respiratory Virus Detection in Hospitalized Children Aged <10 Years?

We evaluated the added value of collecting both nasal and oropharyngeal swabs, compared with collection of nasal swabs alone, for detection of common respiratory viruses by reverse transcription-polymerase chain reaction in hospitalized children aged <10 years. Nasal swabs had equal or greater sensitivity than oropharyngeal swabs for detection of respiratory syncytial virus, adenovirus, human metapneumovirus, rhinovirus, and influenza virus but not parainfluenza virus. The addition of an oropharyngeal swab, compared with use of a nasal swab alone, increased the frequency of detection of each respiratory virus by no more than 10% in children aged <10 years.

Performance of influenza-specific triage tools in an H1N1-positive cohort: P/F ratio better predicts the need for mechanical ventilation and critical care admission

BACKGROUND

Pandemic influenza presents a major threat to global health and socioeconomic well-being. Future demand for critical care may outstrip supply and force clinicians to triage patients for admission. We evaluated the Simple Triage Scoring System (STSS), Ontario Health Plan for an Influenza Epidemic (OHPIP) and PaO2 /FiO2  (P/F) ratio to determine utility in predicting need for mechanical ventilation.

METHODS

We conducted a retrospective case note review of patients admitted to two centres, Royal Liverpool University Hospital and Countess of Chester Hospital, during the UK influenza pandemic of 2010-11. Demand for critical care during this period forced hospitals in Cheshire and Merseyside to implement escalation policies and increase capacity. Inclusion criteria were polymerase chain reaction-confirmed H1N1 influenza and age >18 years. Exclusion criteria were no evidence of treatment for influenza, patient not admitted to hospital or the inability to locate case notes.

RESULTS

One hundred and one patients were included, 29 were admitted to critical care and 23 required mechanical ventilation. The P/F ratio predicted the need for mechanical ventilation with a receiver operating characteristic area under the curve (ROC AUC) of 0.885 (CI 0.817-0.952). Predictive ability was not reduced when the P/F ratio had to be estimated using the Pandharipande tool. The STSS score predicted the need for mechanical ventilation [ROC AUC 0.798 (CI 0.704-0.891)]. The reverse triage component of the OHPIP tool was a poor predictor of patient outcome.

CONCLUSIONS

The P/F ratio was a better predictor of need for mechanical ventilation than STSS. The P/F ratio is a simple and accepted determinant of hypoxaemia and should be used if secondary triaging becomes necessary during future influenza pandemics.

Severe Acute Respiratory Illness Deaths in Sub-Saharan Africa and the Role of Influenza: A Case Series From 8 Countries

Background. Data on causes of death due to respiratory illness in Africa are limited.

Methods. From January to April 2013, 28 African countries were invited to participate in a review of severe acute respiratory illness (SARI)–associated deaths identified from influenza surveillance during 2009–2012.

Results. Twenty-three countries (82%) responded, 11 (48%) collect mortality data, and 8 provided data. Data were collected from 37 714 SARI cases, and 3091 (8.2%; range by country, 5.1%–25.9%) tested positive for influenza virus. There were 1073 deaths (2.8%; range by country, 0.1%–5.3%) reported, among which influenza virus was detected in 57 (5.3%). Case-fatality proportion (CFP) was higher among countries with systematic death reporting than among those with sporadic reporting. The influenza-associated CFP was 1.8% (57 of 3091), compared with 2.9% (1016 of 34 623) for influenza virus–negative cases (P < .001). Among 834 deaths (77.7%) tested for other respiratory pathogens, rhinovirus (107 [12.8%]), adenovirus (64 [6.0%]), respiratory syncytial virus (60 [5.6%]), and Streptococcus pneumoniae (57 [5.3%]) were most commonly identified. Among 1073 deaths, 402 (37.5%) involved people aged 0–4 years, 462 (43.1%) involved people aged 5–49 years, and 209 (19.5%) involved people aged ≥50 years.

Conclusions. Few African countries systematically collect data on outcomes of people hospitalized with respiratory illness. Stronger surveillance for deaths due to respiratory illness may identify risk groups for targeted vaccine use and other prevention strategies.

Interventions to increase influenza vaccination rates of those 60 years and older in the community

BACKGROUND

The effectiveness of interventions to increase the uptake of influenza vaccination in people aged 60 and older is uncertain.

OBJECTIVES

To assess access, provider, system and societal interventions to increase the uptake of influenza vaccination in people aged 60 years and older in the community.

SEARCH METHODS

We searched CENTRAL (2014, Issue 5), MEDLINE (January 1950 to May week 3 2014), EMBASE (1980 to June 2014), AgeLine (1978 to 4 June 2014), ERIC (1965 to June 2014) and CINAHL (1982 to June 2014).

SELECTION CRITERIA

Randomised controlled trials (RCTs) of interventions to increase influenza vaccination uptake in people aged 60 and older.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed study quality and extracted influenza vaccine uptake data.

MAIN RESULTS

This update identified 13 new RCTs; the review now includes a total of 57 RCTs with 896,531 participants. The trials included community-dwelling seniors in high-income countries. Heterogeneity limited meta-analysis. The percentage of trials with low risk of bias for each domain was as follows: randomisation (33%); allocation concealment (11%); blinding (44%); missing data (49%) and selective reporting (100%). Increasing community demand (32 trials, 10 strategies)The interventions with a statistically significant result were: three trials (n = 64,200) of letter plus leaflet/postcard compared to letter (odds ratio (OR) 1.11, 95% confidence interval (CI) 1.07 to 1.15); two trials (n = 614) of nurses/pharmacists educating plus vaccinating patients (OR 3.29, 95% CI 1.91 to 5.66); single trials of a phone call from a senior (n = 193) (OR 3.33, 95% CI 1.79 to 6.22), a telephone invitation versus clinic drop-in (n = 243) (OR 2.72, 95% CI 1.55 to 4.76), a free groceries lottery (n = 291) (OR 1.04, 95% CI 0.62 to 1.76) and nurses educating and vaccinating patients (n = 485) (OR 152.95, 95% CI 9.39 to 2490.67).We did not pool the following trials due to considerable heterogeneity: postcard/letter/pamphlets (16 trials, n = 592,165); tailored communications (16 trials, n = 388,164); customised letter/phone-call (four trials, n = 82,465) and client-based appraisals (three trials, n = 4016), although several trials showed the interventions were effective. Enhancing vaccination access (10 trials, six strategies)The interventions with a statistically significant result were: two trials (n = 2112) of home visits compared to clinic invitation (OR 1.30, 95% CI 1.05 to 1.61); two trials (n = 2251) of free vaccine (OR 2.36, 95% CI 1.98 to 2.82) and one trial (n = 321) of patient group visits (OR 24.85, 95% CI 1.45 to 425.32). One trial (n = 350) of a home visit plus vaccine encouragement compared to a home visit plus safety advice was non-significant.We did not pool the following trials due to considerable heterogeneity: nurse home visits (two trials, n = 2069) and free vaccine compared to no intervention (two trials, n = 2250). Provider- or system-based interventions (17 trials, 11 strategies)The interventions with a statistically significant result were: two trials (n = 2815) of paying physicians (OR 2.22, 95% CI 1.77 to 2.77); one trial (n = 316) of reminding physicians about all their patients (OR 2.47, 95% CI 1.53 to 3.99); one trial (n = 8376) of posters plus postcards (OR 2.03, 95% CI 1.86 to 2.22); one trial (n = 1360) of chart review/feedback (OR 3.43, 95% CI 2.37 to 4.97) and one trial (n = 27,580) of educational outreach/feedback (OR 0.77, 95% CI 0.72 to 0.81).Trials of posters plus postcards versus posters (n = 5753), academic detailing (n = 1400) and increasing staff vaccination rates (n = 26,432) were non-significant.We did not pool the following trials due to considerable heterogeneity: reminding physicians (four trials, n = 202,264) and practice facilitators (three trials, n = 2183), although several trials showed the interventions were effective. Interventions at the societal level We identified no RCTs of interventions at the societal level.

AUTHORS' CONCLUSIONS

There are interventions that are effective for increasing community demand for vaccination, enhancing access and improving provider/system response. Heterogeneity limited pooling of trials.

Seroprevalence of antibody to influenza A(H1N1)pdm09 attributed to vaccination or infection, before and after the second (2010) pandemic wave in Australia

Objectives

Historical records of influenza pandemics demonstrate variability in incidence and severity between waves. The influenza A(H1N1)pdm09 pandemic was the first in which many countries implemented strain-specific vaccination to mitigate subsequent seasons. Serosurveys provide opportunity to examine the constraining influence of antibody on population disease experience.

Design

Changes in the proportion of adults seropositive to influenza A(H1N1)pdm09over the 2009/10 (summer) interepidemic period and 2010 (winter) influenza season were measured to determine whether there was a temporal relationship with vaccine distribution and influenza activity, respectively.

Setting

Australia.

Sample

Plasma samples were collected from healthy blood donors from seven cities at the end of the first wave (November 2009), and before (March/April 2010) and after (November 2010) the subsequent influenza season.

Main outcome measures

Haemagglutination inhibition (HI) assays were performed to assess reactivity of plasma against A(H1N1)pdm09, and the proportion seropositive (HI titre ≥ 40) compared over time, by age group and location.

Results

Between the 2009 and 2010 influenza seasons, the seropositive proportion rose from 22% to 43%, an increase observed across all ages and sites. Brisbane alone recorded a significant rise in seropositivity over the 2010 influenza season – from a baseline of 35% to 53%. The seropositive proportion elsewhere was ≥40% pre-season, and did not rise over winter.

Conclusions

A vaccine-associated increase in seropositive proportion preceding the influenza season correlated with low levels of disease activity in winter 2010. These observations support the role of immunisation in mitigating the ‘second wave’ of A(H1N1)pdm09, with timing critical to ensure sustained herd protection.

Systematic review of influenza A(H1N1)pdm09 virus shedding: duration is affected by severity, but not age

Duration of viral shedding following infection is an important determinant of disease transmission, informing both control policies and disease modelling. We undertook a systematic literature review of the duration of influenza A(H1N1)pdm09 virus shedding to examine the effects of age, severity of illness and receipt of antiviral treatment. Studies were identified by searching the PubMed database using the keywords ‘H1N1’, ‘pandemic’, ‘pandemics’, ‘shed’ and ‘shedding’. Any study of humans with an outcome measure of viral shedding was eligible for inclusion in the review. Comparisons by age, degree of severity and antiviral treatment were made with forest plots. The search returned 214 articles of which 22 were eligible for the review. Significant statistical heterogeneity between studies precluded meta-analysis. The mean duration of viral shedding generally increased with severity of clinical presentation, but we found no evidence of longer shedding duration of influenza A(H1N1)pdm09 among children compared with adults. Shorter viral shedding duration was observed when oseltamivir treatment was administered within 48 hours of illness onset. Considerable differences in the design and analysis of viral shedding studies limit their comparison and highlight the need for a standardised approach. These insights have implications not only for pandemic planning, but also for informing responses and study of seasonal influenza now that the A(H1N1)pdm09 virus has become established as the seasonal H1N1 influenza virus.

Influenza vaccines in immunosuppressed adults with cancer

BACKGROUND

Immunosuppressed cancer patients are at increased risk of serious influenza-related complications. Guidelines, therefore, recommend influenza vaccination for these patients. However, data on vaccine effectiveness in this population is lacking, and the value of vaccination in this population remains unclear.

OBJECTIVES

To assess the effectiveness of influenza vaccine in immunosuppressed adults with malignancies. The primary review outcome is all-cause mortality, preferably at the end of the influenza season. Influenza-like illness (ILI, a clinical definition), confirmed influenza, pneumonia, any hospitalization and influenza-related mortality were defined as secondary outcomes.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE and LILACS databases up to August 2013. We searched the following conference proceedings: ICAAC, ECCMID, IDSA (infectious disease conferences), ASH, ASBMT, EBMT (hematological), and ASCO (oncological) between the years 2006 to 2010. In addition, we scanned the references of all identified studies and pertinent reviews. We searched the websites of the manufacturers of influenza vaccine. Finally, we searched for ongoing or unpublished trials in clinical trial registry databases using the website.

SELECTION CRITERIA

Randomized controlled trials (RCTs), prospective and retrospective cohort studies and case-control studies were considered, comparing inactivated influenza vaccines versus placebo, no vaccination or a different vaccine, in adults (16 years and over) with cancer. We considered solid malignancies treated with chemotherapy, haematological cancer patients treated or not treated with chemotherapy, cancer patients post-autologous (up to six months after transplantation) or allogeneic (at any time) hematopoietic stem cell transplantation.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed the risk of bias and extracted data from included studies adhering to Cochrane methodology. Meta-analysis could not be performed because of different outcome and denominator definitions in the included studies.

MAIN RESULTS

We identified four studies: one RCT and three observational studies, including 2124 participants. One study reported results in person-years while the other three reported per person. The studies were performed between 1993 and 2012 and included adults with haematological diseases (two studies), patients following bone marrow transplantation (one study) and solid malignancies (three studies). Only two observational studies reported all-cause mortality; one showing an adjusted hazard ratio (HR) of 0.88 (95% CI 0.77 to 0.99) for death with vaccination and the other reporting an odds ratio (OR) of 0.43 (95% CI 0.26 to 0.71). The RCT reported a statistically significant reduction in ILI with vaccination, while no difference was observed in one observational study. Confirmed influenza rates were lower with vaccination in the three observational studies, the difference reaching statistical significance in one. Pneumonia was observed significantly less frequently with vaccination in one observational study, but no difference was detected in another or in the RCT. The RCT showed a reduction in hospitalizations following vaccination, while an observational study found no difference. No life-threatening or persistent adverse effects from vaccination were reported. The strength of evidence is limited by the low number of included studies and by their low methodological quality (high risk of bias).

AUTHORS' CONCLUSIONS

Observational data suggests a lower mortality with influenza vaccination. Infection-related outcomes were lower or similar with influenza vaccination. The strength of evidence is limited by the small number of studies and by the fact that only one was a RCT. Influenza vaccination is safe and the evidence, although weak, is in favour of vaccinating adults with cancer receiving chemotherapy.

[Influenza-like illness. Therapeutic experience in family medicine]

BACKGROUND

influenza is a highly contagious respiratory disease. Surveillance in Mexico is based on the detection of Influenza-Like Illness (ILI) and antiviral treatment should begin within 48 hours to avoid the main complication, pneumonia. The aim was to describe the experience of treatment of ILI in a family medicine unit.

METHODS

a descriptive study included patients presented to the emergency room with ILI (38°C fever, headache and cough accompanied by other symptoms). We reviewed the reporting formats of Influenza. To follow up, we contacted them by telephone. Data are expressed as mean ± standard deviation.

RESULTS

there were 537 patients attended with diagnosis of upper airway infection, 1.3 % met criteria for ILI. 85.7 % were men. The mean age was 18 ± 24.21 years. The patients were seen in a mean time of 19.14 hours after the symptoms have started; 100 % of the patients received treatment with oseltamivir and zanamivir; 14.3 % developed pneumonia. All the patients recovered without concomitant disease or complications.

CONCLUSIONS

The use of a protocol in patients with influenza in a family medicine unit led an early diagnosis and treatment that favored the patients' health restoration.

The co-seasonality of pneumonia and influenza with Clostridium difficile infection in the United States, 1993-2008

Seasonal variations in the incidence of pneumonia and influenza are associated with nosocomial Clostridium difficile infection (CDI) incidence, but the reasons why remain unclear. Our objective was to consider the impact of pneumonia and influenza timing and severity on CDI incidence. We conducted a retrospective cohort study using the US National Hospital Discharge Survey sample. Hospitalized patients with a diagnosis of CDI or pneumonia and influenza between 1993 and 2008 were identified from the National Hospital Discharge Survey data set. Poisson regression models of monthly CDI incidence were used to measure 1) the time lag between the annual pneumonia and influenza prevalence peak and the annual CDI incidence peak and 2) the lagged effect of pneumonia and influenza prevalence on CDI incidence. CDI was identified in 18,465 discharges (8.52 per 1,000 discharges). Peak pneumonia prevalence preceded peak CDI incidence by 9.14 weeks (95% confidence interval: 4.61, 13.67). A 1% increase in pneumonia prevalence was associated with a cumulative effect of 11.3% over a 6-month lag period (relative risk = 1.113, 95% confidence interval: 1.073, 1.153). Future research could seek to understand which mediating pathways, including changes in broad-spectrum antibiotic prescribing and hospital crowding, are most responsible for the associated changes in incidence.

Risk factors for mechanical ventilation in U.S. children hospitalized with seasonal influenza and 2009 pandemic influenza A*

OBJECTIVE

We tested the hypothesis that the use of mechanical ventilator support in children hospitalized with influenza during the 2009 H1N1 influenza A (H1N1) pandemic was higher than would be expected in children hospitalized for seasonal influenza after adjusting for patient risk.

DESIGN

Retrospective cohort study.

SETTING

Forty-three U.S. pediatric hospitals.

PATIENTS

Children <18 yrs old with a discharge diagnosis of influenza admitted July 2006 through March 2009 (seasonal influenza) and June through December 2009 (2009 pandemic influenza A).

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

We included 10,173 children hospitalized with seasonal influenza and 9837 with presumed 2009 pandemic influenza A. The 2009 pandemic influenza A cohort was older (median 5.0 vs. 1.9 yrs), more likely to have asthma (30% vs. 18%), and less likely to receive mechanical ventilation (7.1% [n = 701] vs. 9.2% [n = 940]). Using logistic regression, we created a multivariable model of risk factors associated with endotracheal mechanical ventilator support in the seasonal influenza cohort and used this model to predict the number of expected mechanical ventilation cases in children with presumed 2009 pandemic influenza A. Adjusted for underlying health conditions, race, age, and a co-diagnosis of bacterial pneumonia, the observed/expected rate of mechanical ventilation in the presumed 2009 pandemic influenza A cohort was 0.74 (95% confidence interval 0.68-0.79). Early hospital treatment with influenza antiviral medications was associated with decreased initiation of mechanical ventilation on hospital day ≥ 3 in the seasonal influenza (odds ratio 0.66; 95% confidence interval 0.45-0.97) and 2009 pandemic influenza A (odds ratio 0.23; 95% confidence interval 0.16-0.34) periods; influenza antiviral use in the 2009 pandemic influenza A period was much higher (70% vs. 20%; p < .001).

CONCLUSIONS

Although the number of children with a hospital discharge diagnosis of influenza almost tripled during the 2009 pandemic influenza A period, the risk-adjusted proportion of children receiving mechanical ventilation was lower than we would have predicted in a seasonal influenza cohort. Early hospital use of influenza antiviral medications was associated with a decrease in late-onset mechanical ventilation.

Vaccines for preventing influenza in healthy children

BACKGROUND

The consequences of influenza in children and adults are mainly absenteeism from school and work. However, the risk of complications is greatest in children and people over 65 years of age.

OBJECTIVES

To appraise all comparative studies evaluating the effects of influenza vaccines in healthy children, assess vaccine efficacy (prevention of confirmed influenza) and effectiveness (prevention of influenza-like illness (ILI)) and document adverse events associated with influenza vaccines.

SEARCH METHODS

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2011, Issue 3) which includes the Acute Respiratory Infections Group's Specialised Register, OLD MEDLINE (1950 to 1965), MEDLINE (1966 to November 2011), EMBASE (1974 to November 2011), Biological Abstracts (1969 to September 2007), and Science Citation Index (1974 to September 2007).

SELECTION CRITERIA

Randomised controlled trials (RCTs), cohort and case-control studies of any influenza vaccine in healthy children under 16 years of age.

DATA COLLECTION AND ANALYSIS

Four review authors independently assessed trial quality and extracted data.

MAIN RESULTS

We included 75 studies with about 300,000 observations. We included 17 RCTs, 19 cohort studies and 11 case-control studies in the analysis of vaccine efficacy and effectiveness. Evidence from RCTs shows that six children under the age of six need to be vaccinated with live attenuated vaccine to prevent one case of influenza (infection and symptoms). We could find no usable data for those aged two years or younger.Inactivated vaccines in children aged two years or younger are not significantly more efficacious than placebo. Twenty-eight children over the age of six need to be vaccinated to prevent one case of influenza (infection and symptoms). Eight need to be vaccinated to prevent one case of influenza-like-illness (ILI). We could find no evidence of effect on secondary cases, lower respiratory tract disease, drug prescriptions, otitis media and its consequences and socioeconomic impact. We found weak single-study evidence of effect on school absenteeism by children and caring parents from work. Variability in study design and presentation of data was such that a meta-analysis of safety outcome data was not feasible. Extensive evidence of reporting bias of safety outcomes from trials of live attenuated influenza vaccines (LAIVs) impeded meaningful analysis. One specific brand of monovalent pandemic vaccine is associated with cataplexy and narcolepsy in children and there is sparse evidence of serious harms (such as febrile convulsions) in specific situations.

AUTHORS' CONCLUSIONS

Influenza vaccines are efficacious in preventing cases of influenza in children older than two years of age, but little evidence is available for children younger than two years of age. There was a difference between vaccine efficacy and effectiveness, partly due to differing datasets, settings and viral circulation patterns. No safety comparisons could be carried out, emphasising the need for standardisation of methods and presentation of vaccine safety data in future studies. In specific cases, influenza vaccines were associated with serious harms such as narcolepsy and febrile convulsions. It was surprising to find only one study of inactivated vaccine in children under two years, given current recommendations to vaccinate healthy children from six months of age in the USA, Canada, parts of Europe and Australia. If immunisation in children is to be recommended as a public health policy, large-scale studies assessing important outcomes, and directly comparing vaccine types are urgently required. The degree of scrutiny needed to identify all global cases of potential harms is beyond the resources of this review. This review includes trials funded by industry. An earlier systematic review of 274 influenza vaccine studies published up to 2007 found industry-funded studies were published in more prestigious journals and cited more than other studies independently from methodological quality and size. Studies funded from public sources were significantly less likely to report conclusions favourable to the vaccines. The review showed that reliable evidence on influenza vaccines is thin but there is evidence of widespread manipulation of conclusions and spurious notoriety of the studies. The content and conclusions of this review should be interpreted in the light of this finding.

Age-specific differences in influenza A epidemic curves: do children drive the spread of influenza epidemics?

There is accumulating evidence suggesting that children may drive the spread of influenza epidemics. The objective of this study was to quantify the lead time by age using laboratory-confirmed cases of influenza A for the 1995/1996-2005/2006 seasons from Canadian communities and laboratory-confirmed hospital admissions for the H1N1/2009 pandemic strain. With alignment of the epidemic curves locally before aggregation of cases, slight age-specific differences in the timing of infection became apparent. For seasonal influenza, both the 10-19- and 20-29-year age groups peaked 1 week earlier than other age groups, while during the fall wave of the 2009 pandemic, infections peaked earlier among only the 10-19-year age group. In the H3N2 seasons, infections occurred an average of 3.9 (95% confidence interval: 1.7, 6.1) days earlier in the 20-29-year age group than for youth aged 10-19 years, while during the fall pandemic wave, the 10-19-year age group had a statistically significant lead of 3 days compared with both younger children aged 4-9 years and adults aged 20-29 years (P < 0.0001). This analysis casts doubt on the hypothesis that younger school-age children actually lead influenza epidemic waves.

Planning for the control of pandemic influenza A (H1N1) in Los Angeles County and the United States

Mathematical and computer models can provide guidance to public health officials by projecting the course of an epidemic and evaluating control measures. The authors built upon an existing collaboration between an academic research group and the Los Angeles County, California, Department of Public Health to plan for and respond to the first and subsequent years of pandemic influenza A (H1N1) circulation. The use of models allowed the authors to 1) project the timing and magnitude of the epidemic in Los Angeles County and the continental United States; 2) predict the effect of the influenza mass vaccination campaign that began in October 2009 on the spread of pandemic H1N1 in Los Angeles County and the continental United States; and 3) predict that a third wave of pandemic influenza in the winter or spring of 2010 was unlikely to occur. The close collaboration between modelers and public health officials during pandemic H1N1 spread in the fall of 2009 helped Los Angeles County officials develop a measured and appropriate response to the unfolding pandemic and establish reasonable goals for mitigation of pandemic H1N1.

CXCL5 into the upper airways of children with influenza A virus infection

BACKGROUND

Neutrophil infiltration is a major feature in the pathogenesis of influenza infection. The factors regulating the neutrophil influx are not fully understood. The chemokine CXCL5/ENA-78 is a potent neutrophil chemoattractant, that has been implicated in several inflammatory diseases. Our objectives was to study the release of CXCL5 in children with natural acquired influenza.

METHODS

CXCL5 concentration was investigated by immunoenzyme assay in nasal aspirates of children (n = 18) in whom respiratory symptoms were precipitated predominantly by influenza A virus.

RESULTS

There were increased CXCL5 levels in nasal aspirates when children were symptomatic as compared with samples from the same children when they had been asymptomatic for four weeks (medians 1850 pg/mL vs. 30 pg/mL, p < 0.005). We purified CXCL5 from these samples, and demonstrated biological neutrophil chemotactic activity.

CONCLUSIONS

It is the first in vivo data that suggest an important role for CXCL5 in neutrophil influx in proven upper respiratory influenza infection. We suggest that CXCL5 might provide a target for therapeutic intervention in influenza induced respiratory diseases.

Neuraminidase inhibitors for preventing and treating influenza in healthy adults

BACKGROUND

Neuraminidase inhibitors (NI) are recommended for use against influenza and its complications in inter-pandemic years and during pandemics.

OBJECTIVES

To assess the effects of NIs in preventing and treating influenza, its transmission, and its complications in otherwise healthy adults, and to estimate the frequency of adverse effects.

SEARCH STRATEGY

We searched the Cochrane Central Register of Controlled Trials (CENTRAL) (The Cochrane Library 2009, issue 3) which contains the Acute Respiratory Infections Group's Specialised Register, MEDLINE (1950 to August 2009) and EMBASE (1980 to August 2009).

SELECTION CRITERIA

Randomised controlled trials (RCTs) or quasi-randomised placebo-controlled trials of NIs in healthy adults exposed to naturally occurring influenza.

DATA COLLECTION AND ANALYSIS

Two review authors independently applied inclusion criteria, assessed trial quality, and extracted data. We structured the comparisons into prophylaxis, treatment, and adverse events, with further subdivision by outcome and dose.

MAIN RESULTS

We identified four prophylaxis, 12 treatment and four post-exposure prophylaxis trials. In prophylaxis compared to placebo, NIs had no effect against influenza-like illnesses (ILI) (risk ratio (RR) ranging from 1.28 for oral oseltamivir 75 mg daily to 0.76 for inhaled zanamivir 10 mg daily). The efficacy of oral oseltamivir against symptomatic influenza was 76% (at 75 mg daily), and 73% (at 150 mg daily). Inhaled zanamivir 10 mg daily performed similarly. Neither NI had a significant effect on asymptomatic influenza. Oseltamivir induced nausea (odds ratio (OR) 1.79, 95% CI 1.10 to 2.93). Oseltamivir for post-exposure prophylaxis had an efficacy of 58% and 84% in two trials for households. Zanamivir performed similarly. The hazard ratios for time to alleviation of symptoms were in favour of the treated group 1.20 (1.06 to 1.35) for oseltamivir and 1.24 (1.13 to 1.36) for zanamivir. Because of the exclusion of a review of mainly unpublished trials of oseltamivir, insufficient evidence remained to reach a conclusion on the prevention of complications requiring antibiotics in influenza cases (RR 0.57, 95% CI 0.23 to 1.37). Analysis of the US FDA and Japan's PMDA regulators' pharmacovigilance dataset, revealed incomplete reporting and description of harms preventing us from reaching firm conclusions on the central nervous system toxicity of neuraminidase inhibitors.

AUTHORS' CONCLUSIONS

Numerous inconsistencies detected in the available evidence, followed by an inability to adequately access the data, has undermined confidence in our previous conclusions for oseltamivir. Independent RCTs to resolve these uncertainties are needed.

Avian influenza and poultry workers, Peru, 2006

BACKGROUND

Currently numerous countries in Asia, Africa and Europe are encountering highly pathogenic avian influenza (AI) infections in poultry and humans. In the Americas, home of the world's largest poultry exporters, contingency plans are being developed and evaluated in preparation for the arrival of these viral strains.

OBJECTIVES

With this cross-sectional study, to our knowledge the first in its kind in Central or South America, we sought to learn if Peruvian poultry workers had evidence of previous AI infection and if so, to determine risk factors for infection.

METHODS

We performed a cross-sectional seroprevalence study among 149 workers on a Peruvian poultry farm (133 exposed to poultry and 17 non-exposed controls), serum samples were tested for human influenza virus exposure using a hemagglutination inhibition (HI) assay. Microneutralization assays were performed on all serum samples to detect antibodies against prototypic avian influenza (AI) strains H4 through H12.

RESULTS

Using multivariate proportional odds modeling we found that the prevalence of elevated titers against AI viruses was low in both groups, exposed and non-exposed controls.

CONCLUSIONS

No evidence of previous avian influenza infection among Peruvian poultry workers was found in this first cross-sectional study performed in South America. This first occupational study of AI in Latin America was encouraging, but it likely reflects the sector of poultry production with higher biosecurity.

Antiviral and antibiotic prescribing for influenza in primary care

BACKGROUND

Anti-influenza antiviral medications reduce influenza-related morbidity, but may often be used inappropriately.

OBJECTIVE

To measure the rate of antiviral and antibiotic prescribing, the appropriateness of antiviral prescribing, and evaluate independent predictors of antiviral and antibiotic prescribing for influenza in primary care.

DESIGN AND PATIENTS

Retrospective analysis of 958 visits of clinician-diagnosed influenza in 21 primary care clinics in eastern Massachusetts from 1999 to 2007. We considered antiviral prescribing appropriate if patients had symptoms for 2 or fewer days, had fever, and any 2 of headache, sore throat, cough, or myalgias.

MEASUREMENTS AND MAIN RESULTS

Clinicians prescribed antivirals in 557 (58%) visits and antibiotics in 104 visits (11%). Of antiviral prescriptions, 38% were not appropriate, most commonly because of symptoms for more than 2 days (24% of antiviral prescriptions). In multivariate modeling, selected independent predictors of antiviral prescribing were symptom duration of 2 or fewer days (odds ratio [OR], 12.4; 95% confidence interval [CI], 8.3 to 18.6), year (OR, 1.4 for each successive influenza season; 95% CI, 1.3 to 1.7), patient age (OR, 1.3 per decade; 95% CI, 1.2 to 1.5), and, compared to having no influenza testing, having a negative influenza test (OR, 5.5; 95% CI, 3.4 to 9.1) or a positive influenza test (OR, 11.4; 95% CI, 6.7 to 19.3). Independent predictors of antibiotic prescribing included otoscopic abnormalities (OR, 3.3; 95% CI, 1.8 to 6.0), abnormal lung examination (OR, 4.0; 95% CI, 2.1 to 6.2), and having a chest x-ray performed (OR, 2.2; 95% CI, 1.3 to 3.8).

CONCLUSIONS

Primary care clinicians are much more likely to prescribe antivirals to patients with symptoms for 2 or fewer days, but also commonly prescribe antivirals inappropriately.

Impact of the 2004 influenza vaccine shortage on repeat immunization rates

PURPOSE

We assessed the impact of the severe influenza vaccine shortage of 2004 on individual physicians' immunization performance.

METHODS

Using 1998-2004 Medicare claims data, we monitored the physician continuity rate (proportion of patients receiving influenza immunization from a physician in 1 year who received a subsequent immunization from the same physician the subsequent year) and other clinician rate (proportion of patients with claims from 1 physician in 1 year with a claim from another clinician the subsequent year) in West Virginia Medicare beneficiaries from 2000-2004. We examined vaccine claim trends by clinician and surveys of self-reported immunization to determine whether patients received vaccine from nonphysician clinicians or went without immunization each year.

RESULTS

Claims-based influenza vaccination rates increased from 35.5% to 41.3% from 2000-2003, reflecting historical trends, before declining 14.1% in 2004. Median continuity rates among the 723 to 849 physicians claiming 25 or more influenza immunizations from 2000-2003 increased from 47% in 2000-2001 to 54% in 2002-2003; then fell to 3% in 2003-2004. The number of physicians filing 100 or more claims declined from 337 in 2003 to 130 in 2004. More than 25% of physicians had no repeat vaccinations of the same beneficiaries in 2004. Trends in clinician type and survey data indicated a shift of many beneficiaries to mass vaccinators and institutional providers; however, compared with previous years, there was an estimated 8% increase in 2004 in the number of West Virginia beneficiaries who did not receive vaccine.

CONCLUSIONS

The 2004 vaccine shortage had a severe impact on influenza immunization rates in private physician's offices, disrupting continuity of care.