Clinical and Molecular Characterization of BSCL2 Mutations in a Taiwanese Cohort with Hereditary Neuropathy

Background

A small group of patients with inherited neuropathy that has been shown to be caused by mutations in the BSCL2 gene. However, little information is available about the role of BSCL2 mutations in inherited neuropathies in Taiwan.

Methodology and Principal Findings

Utilizing targeted sequencing, 76 patients with molecularly unassigned Charcot-Marie-Tooth disease type 2 (CMT2) and 8 with distal hereditary motor neuropathy (dHMN), who were selected from 348 unrelated patients with inherited neuropathies, were screened for mutations in the coding regions of BSCL2. Two heterozygous BSCL2 mutations, p.S90L and p.R96H, were identified, of which the p.R96H mutation is novel. The p.S90L was identified in a pedigree with CMT2 while the p.R96H was identified in a patient with apparently sporadic dHMN. In vitro studies demonstrated that the p.R96H mutation results in a remarkably low seipin expression and reduced cell viability.

Conclusion

BSCL2 mutations account for a small number of patients with inherited neuropathies in Taiwan. The p.R96H mutation is associated with dHMN. This study expands the molecular spectrum of BSCL2 mutations and also emphasizes the pathogenic role of BSCL2 mutations in molecularly unassigned hereditary neuropathies.     

Influenza Surveillance and Incidence in a Rural Area in China during the 2009/2010 Influenza Pandemic

Background

Most influenza surveillance is based on data from urban sentinel hospitals; little is known about influenza activity in rural communities. We conducted influenza surveillance in a rural region of China with the aim of detecting influenza activity in the 2009/2010 influenza season.

Methods

The study was conducted from October 2009 to March 2010. Real-time polymerase chain reaction was used to confirm influenza cases. Over-the-counter (OTC) drug sales were daily collected in drugstores and hospitals/clinics. Space-time scan statistics were used to identify clusters of ILI in community. The incidence rate of ILI/influenza was estimated on the basis of the number of ILI/influenza cases detected by the hospitals/clinics.

Results

A total of 434 ILI cases (3.88% of all consultations) were reported; 64.71% of these cases were influenza A (H1N1) pdm09. The estimated incidence rate of ILI and influenza were 5.19/100 and 0.40/100, respectively. The numbers of ILI cases and OTC drug purchases in the previous 7 days were strongly correlated (Spearman rank correlation coefficient [r] = 0.620, P = 0.001). Four ILI outbreaks were detected by space-time permutation analysis.

Conclusions

This rural community surveillance detected influenza A (H1N1) pdm09 activity and outbreaks in the 2009/2010 influenza season and enabled estimation of the incidence rate of influenza. It also provides a scientific data for public health measures.     

Molecular Surveillance of Antiviral Drug Resistance of Influenza A/H3N2 Virus in Singapore, 2009-2013

Adamantanes and neuraminidase inhibitors (NAIs) are two classes of antiviral drugs available for the chemoprophylaxis and treatment of influenza infections. To determine the frequency of drug resistance in influenza A/H3N2 viruses in Singapore, large-scale sequencing of neuraminidase (NA) and matrix protein (MP) genes was performed directly without initial culture amplification. 241 laboratory-confirmed influenza A/H3N2 clinical samples, collected between May 2009 and November 2013 were included. In total, 229 NA (95%) and 241 MP (100%) complete sequences were obtained. Drug resistance mutations in the NA and MP genes were interpreted according to published studies. For the NAIs, a visual inspection of the aligned NA sequences revealed no known drug resistant genotypes (DRGs). For the adamantanes, the well-recognised S31N DRG was identified in all 241 MP genes. In addition, there was an increasing number of viruses carrying the combination of D93G+Y155F+D251V (since May 2013) or D93G (since March 2011) mutations in the NA gene. However, in-vitro NAI testing indicated that neither D93G+Y155F+D251V nor D93G alone conferred any changes in NAI susceptibility. Lastly, an I222T mutation in the NA gene that has previously been reported to cause oseltamivir-resistance in influenza A/H1N1/2009, B, and A/H5N1, was detected from a treatment-naïve patient. Further in-vitro NAI testing is required to confirm the effect of this mutation in A/H3N2 virus.     

Economic Analysis of Pandemic Influenza Vaccination Strategies in Singapore

Background

All influenza pandemic plans advocate pandemic vaccination. However, few studies have evaluated the cost-effectiveness of different vaccination strategies. This paper compares the economic outcomes of vaccination compared with treatment with antiviral agents alone, in Singapore.

Methodology

We analyzed the economic outcomes of pandemic vaccination (immediate vaccination and vaccine stockpiling) compared with treatment-only in Singapore using a decision-based model to perform cost-benefit and cost-effectiveness analyses. We also explored the annual insurance premium (willingness to pay) depending on the perceived risk of the next pandemic occurring.

Principal Findings

The treatment-only strategy resulted in 690 deaths, 13,950 hospitalization days, and economic cost of USD$497 million. For immediate vaccination, at vaccine effectiveness of >55%, vaccination was cost-beneficial over treatment-only. Vaccine stockpiling is not cost-effective in most scenarios even with 100% vaccine effectiveness. The annual insurance premium was highest with immediate vaccination, and was lower with increased duration to the next pandemic. The premium was also higher with higher vaccine effectiveness, attack rates, and case-fatality rates. Stockpiling with case-fatality rates of 0.4–0.6% would be cost-beneficial if vaccine effectiveness was >80%; while at case-fatality of >5% stockpiling would be cost-beneficial even if vaccine effectiveness was 20%. High-risk sub-groups warrant higher premiums than low-risk sub-groups.

Conclusions

The actual pandemic vaccine effectiveness and lead time is unknown. Vaccine strategy should be based on perception of severity. Immediate vaccination is most cost-effective, but requires vaccines to be available when required. Vaccine stockpiling as insurance against worst-case scenarios is also cost-effective. Research and development is therefore critical to develop and stockpile cheap, readily available effective vaccines.     

Characterization of Regional Influenza Seasonality Patterns in China and Implications for Vaccination Strategies: Spatio-Temporal Modeling of Surveillance Data

Background

The complexity of influenza seasonal patterns in the inter-tropical zone impedes the establishment of effective routine immunization programs. China is a climatologically and economically diverse country, which has yet to establish a national influenza vaccination program. Here we characterize the diversity of influenza seasonality in China and make recommendations to guide future vaccination programs.

Methods and Findings

We compiled weekly reports of laboratory-confirmed influenza A and B infections from sentinel hospitals in cities representing 30 Chinese provinces, 2005–2011, and data on population demographics, mobility patterns, socio-economic, and climate factors. We applied linear regression models with harmonic terms to estimate influenza seasonal characteristics, including the amplitude of annual and semi-annual periodicities, their ratio, and peak timing. Hierarchical Bayesian modeling and hierarchical clustering were used to identify predictors of influenza seasonal characteristics and define epidemiologically-relevant regions. The annual periodicity of influenza A epidemics increased with latitude (mean amplitude of annual cycle standardized by mean incidence, 140% [95% CI 128%–151%] in the north versus 37% [95% CI 27%–47%] in the south, p<0.0001). Epidemics peaked in January–February in Northern China (latitude ≥33°N) and April–June in southernmost regions (latitude <27°N). Provinces at intermediate latitudes experienced dominant semi-annual influenza A periodicity with peaks in January–February and June–August (periodicity ratio >0.6 in provinces located within 27.4°N–31.3°N, slope of latitudinal gradient with latitude −0.016 [95% CI −0.025 to −0.008], p<0.001). In contrast, influenza B activity predominated in colder months throughout most of China. Climate factors were the strongest predictors of influenza seasonality, including minimum temperature, hours of sunshine, and maximum rainfall. Our main study limitations include a short surveillance period and sparse influenza sampling in some of the southern provinces.

Conclusions

Regional-specific influenza vaccination strategies would be optimal in China; in particular, annual campaigns should be initiated 4–6 months apart in Northern and Southern China. Influenza surveillance should be strengthened in mid-latitude provinces, given the complexity of seasonal patterns in this region. More broadly, our findings are consistent with the role of climatic factors on influenza transmission dynamics. Please see later in the article for the Editors'' Summary     

Evaluation of Two Influenza Surveillance Systems in South Africa

Background

The World Health Organisation recommends outpatient influenza-like illness (ILI) and inpatient severe acute respiratory illness (SARI) surveillance. We evaluated two influenza surveillance systems in South Africa: one for ILI and another for SARI.

Methodology

The Viral Watch (VW) programme has collected virological influenza surveillance data voluntarily from patients with ILI since 1984 in private and public clinics in all 9 South African provinces. The SARI surveillance programme has collected epidemiological and virological influenza surveillance data since 2009 in public hospitals in 4 provinces by dedicated personnel. We compared nine surveillance system attributes from 2009–2012.

Results

We analysed data from 18,293 SARI patients and 9,104 ILI patients. The annual proportion of samples testing positive for influenza was higher for VW (mean 41%) than SARI (mean 8%) and generally exceeded the seasonal threshold from May to September (VW: weeks 21–40; SARI: weeks 23–39). Data quality was a major strength of SARI (most data completion measures >90%; adherence to definitions: 88–89%) and a relative weakness of the VW programme (62% of forms complete, with limited epidemiologic data collected; adherence to definitions: 65–82%). Timeliness was a relative strength of both systems (e.g. both collected >93% of all respiratory specimens within 7 days of symptom onset). ILI surveillance was more nationally representative, financially sustainable and expandable than the SARI system. Though the SARI programme is not nationally representative, the high quality and detail of SARI data collection sheds light on the local burden and epidemiology of severe influenza-associated disease.

Conclusions

To best monitor influenza in South Africa, we propose that both ILI and SARI should be under surveillance. Improving ILI surveillance will require better quality and more systematic data collection, and SARI surveillance should be expanded to be more nationally representative, even if this requires scaling back on information gathered.     

Birds and Viruses at a Crossroad - Surveillance of Influenza A Virus in Portuguese Waterfowl

During recent years, extensive amounts of data have become available regarding influenza A virus (IAV) in wild birds in northern Europe, while information from southern Europe is more limited. Here, we present an IAV surveillance study conducted in western Portugal 2008–2009, analyzing 1653 samples from six different species of waterfowl, with the majority of samples taken from Mallards (Anas platyrhynchos). Overall 4.4% of sampled birds were infected. The sampling results revealed a significant temporal variation in the IAV prevalence, including a pronounced peak among predominantly young birds in June, indicating that IAV circulate within breeding populations in the wetlands of western Portugal. The H10N7 and H9N2 subtypes were predominant among isolated viruses. Phylogenetic analyses of the hemagglutinin and neuraminidase sequences of H10N7, H9N2 and H11N3 virus showed that sequences from Portugal were closely related to viral sequences from Central Europe as well as to IAVs isolated in the southern parts of Africa, reflecting Portugal’s position on the European-African bird migratory flyway. This study highlights the importance of Portugal as a migratory crossroad for IAV, connecting breeding stationary waterfowl with birds migrating between continents which enable transmission and spread of IAV.     

Systematic Study on Genetic and Epimutational Profile of a Cohort of Amsterdam Criteria-Defined Lynch Syndrome in Singapore

Background

Germline defects of mismatch repair (MMR) genes underlie Lynch Syndrome (LS). We aimed to gain comprehensive genetic and epigenetic profiles of LS families in Singapore, which will facilitate efficient molecular diagnosis of LS in Singapore and the region.

Methods

Fifty nine unrelated families were studied. Mutations in exons, splice-site junctions and promoters of five MMR genes were scanned by high resolution melting assay followed by DNA sequencing, large fragment deletions/duplications and promoter methylation in MLH1, MSH2, MSH6 and PMS2 were evaluated by multiplex ligation-dependent probe amplification. Tumor microsatellite instability (MSI) was assessed with five mononucleotide markers and immunohistochemical staining (IHC) was also performed.

Results

Pathogenic defects, all confined to MLH1 and MSH2, were identified in 17 out of 59 (28.8%) families. The mutational spectrum was highly heterogeneous and 28 novel variants were identified. One recurrent mutation in MLH1 (c.793C>T) was also observed. 92.9% sensitivity for indication of germline mutations conferred by IHC surpassed 64.3% sensitivity by MSI. Furthermore, 15.6% patients with MSS tumors harbored pathogenic mutations.

Conclusions

Among major ethnic groups in Singapore, all pathogenic germline defects were confined to MLH1 and MSH2. Caution should be applied when the Amsterdam criteria and consensus microsatellite marker panel recommended in the revised Bethesda guidelines are applied to the local context. We recommend a screening strategy for the local LS by starting with tumor IHC and the hotspot mutation testing at MLH1 c.793C>T followed by comprehensive mutation scanning in MLH1 and MSH2 prior to proceeding to other MMR genes.     

Influenza Virus Surveillance in Pakistan during 2008-2011

Background

There is little information about influenza among the Pakistani population. In order to assess the trends of Influenza-like-Illness (ILI) and to monitor the predominant circulating strains of influenza viruses, a country-wide lab-based surveillance system for ILI and Severe Acute Respiratory Illness (SARI) with weekly sampling and reporting was established in 2008. This system was necessary for early detection of emerging novel influenza subtypes and timely response for influenza prevention and control.

Methods

Five sentinel sites at tertiary care hospitals across Pakistan collected epidemiological data and respiratory samples from Influenza-like illness (ILI) and severe acute respiratory illness (SARI) cases from January 2008 to December 2011. Samples were typed and sub-typed by Real-Time RT-PCR assay.

Results

A total of 6258 specimens were analyzed; influenza virus was detected in 1489 (24%) samples, including 1066 (72%) Influenza type A and 423 (28%) influenza type B viruses. Amongst influenza A viruses, 25 (2%) were seasonal A/H1N1, 169 (16%) were A/H3N2 and 872 (82 %) were A(H1N1)pdm09. Influenza B virus circulation was detected throughout the year along with few cases of seasonal A/H1N1 virus during late winter and spring. Influenza A/H3N2 virus circulation was mainly observed during summer months (August-October).

Conclusions

The findings of this study emphasize the need for continuous and comprehensive influenza surveillance. Prospective data from multiple years is needed to predict seasonal trends for vaccine development and to further fortify pandemic preparedness.     

Exploring a Proposed WHO Method to Determine Thresholds for Seasonal Influenza Surveillance

Introduction

Health authorities find thresholds useful to gauge the start and severity of influenza seasons. We explored a method for deriving thresholds proposed in an influenza surveillance manual published by the World Health Organization (WHO).

Methods

For 2002-2011, we analysed two routine influenza-like-illness (ILI) datasets, general practice sentinel surveillance and a locum medical service sentinel surveillance, plus laboratory data and hospital admissions for influenza. For each sentinel dataset, we created two composite variables from the product of weekly ILI data and the relevant laboratory data, indicating the proportion of tested specimens that were positive. For all datasets, including the composite datasets, we aligned data on the median week of peak influenza or ILI activity and assigned three threshold levels: seasonal threshold, determined by inspection; and two intensity thresholds termed average and alert thresholds, determined by calculations of means, medians, confidence intervals (CI) and percentiles. From the thresholds, we compared the seasonal onset, end and intensity across all datasets from 2002-2011. Correlation between datasets was assessed using the mean correlation coefficient.

Results

The median week of peak activity was week 34 for all datasets, except hospital data (week 35). Means and medians were comparable and the 90% upper CIs were similar to the 95^th percentiles. Comparison of thresholds revealed variations in defining the start of a season but good agreement in describing the end and intensity of influenza seasons, except in hospital admissions data after the pandemic year of 2009. The composite variables improved the agreements between the ILI and other datasets. Datasets were well correlated, with mean correlation coefficients of >0.75 for a range of combinations.

Conclusions

Thresholds for influenza surveillance are easily derived from historical surveillance and laboratory data using the approach proposed by WHO. Use of composite variables is helpful for describing influenza season characteristics.     

Influenza Pneumonia Surveillance among Hospitalized Adults May Underestimate the Burden of Severe Influenza Disease

Background

Studies seeking to estimate the burden of influenza among hospitalized adults often use case definitions that require presence of pneumonia. The goal of this study was to assess the extent to which restricting influenza testing to adults hospitalized with pneumonia could underestimate the total burden of hospitalized influenza disease.

Methods

We conducted a modelling study using the complete State Inpatient Databases from Arizona, California, and Washington and regional influenza surveillance data acquired from CDC from January 2003 through March 2009. The exposures of interest were positive laboratory tests for influenza A (H1N1), influenza A (H3N2), and influenza B from two contiguous US Federal Regions encompassing the study area. We identified the two outcomes of interest by ICD-9-CM code: respiratory and circulatory hospitalizations, as well as critical illness hospitalizations (acute respiratory failure, severe sepsis, and in-hospital death). We linked the hospitalization datasets with the virus surveillance datasets by geographic region and month of hospitalization. We used negative binomial regression models to estimate the number of influenza-associated events for the outcomes of interest. We sub-categorized these events to include all outcomes with or without pneumonia diagnosis codes.

Results

We estimated that there were 80,834 (95% CI 29,214–174,033) influenza-associated respiratory and circulatory hospitalizations and 26,760 (95% CI 14,541–47,464) influenza-associated critical illness hospitalizations. When a pneumonia diagnosis was excluded, the estimated number of influenza-associated respiratory and circulatory hospitalizations was 24,816 (95% CI 6,342–92,624). The estimated number of influenza-associated critical illness hospitalizations was 8,213 (95% CI 3,764–20,799). Around 30% of both influenza-associated respiratory and circulatory hospitalizations, as well as influenza-associated critical illness hospitalizations did not have pneumonia diagnosis codes.

Conclusions

Surveillance studies which only consider hospitalizations that include a diagnosis of pneumonia may underestimate the total burden of influenza hospitalizations.     

A Multiplex Label-Free Approach to Avian Influenza Surveillance and Serology

Influenza serology has traditionally relied on techniques such as hemagglutination inhibition, microneutralization, and ELISA. These assays are complex, challenging to implement in a format allowing detection of several types of antibody-analyte interactions at once (multiplex), and troublesome to implement in the field. As an alternative, we have developed a hemagglutinin microarray on the Arrayed Imaging Reflectometry (AIR) platform. AIR provides sensitive, rapid, and label-free multiplex detection of targets in complex analyte samples such as serum. In preliminary work, we demonstrated the application of this array to the testing of human samples from a vaccine trial. Here, we report the application of an expanded label-free hemagglutinin microarray to the analysis of avian serum samples. Samples from influenza virus challenge experiments in mallards yielded strong, selective detection of antibodies to the challenge antigen in most cases. Samples acquired in the field from mallards were also analyzed, and compared with viral hemagglutinin inhibition and microneutralization assays. We find that the AIR hemagglutinin microarray can provide a simple and robust alternative to standard methods, offering substantially greater information density from a simple workflow.     

武威市2009~2012年流感样病例监测结果分析

目的:分析探讨2009~2012年武威市流行性感冒(简称流感)的流行特征,为流感的防控提供科学依据。方法:收集2009年6月~2012年12月武威市流感样病例及病原学监测资料,分析流感样病例就诊比(ILI%)的变化规律、流感样病例的年龄分布和流感病毒各亚型的变化。结果:2009~2012年,武威市的ILI%分别是1.94%、1.55%、1.12%、1.15%,ILI%高峰分别出现在6月(2009年)、7月(2010年)和10月~次年3月(2011年和2012年)。ILI年龄构成显示病例以15岁以下人群为主。2009~2012年,ILI样本病原学检测阳性率为19.00%;2009年,甲型H1N1为优势毒株,构成比是76.64%,2010年为季节性H3(60.00%)、B型(29.23%)混合流行;2011年主要是甲型H1N1(26.47%)、季节性H3(29.41%)、A未分型(29.41%);2012年为季节性H3(31.78%)、B型(53.49%)混合流行。结论:2009年甲型H1N1流感大流行之后,武威市流感的活动较为平稳,流行优势毒株不断发生变化。     

Correlation between National Influenza Surveillance Data and Google Trends in South Korea

Background

In South Korea, there is currently no syndromic surveillance system using internet search data, including Google Flu Trends. The purpose of this study was to investigate the correlation between national influenza surveillance data and Google Trends in South Korea.

Methods

Our study was based on a publicly available search engine database, Google Trends, using 12 influenza-related queries, from September 9, 2007 to September 8, 2012. National surveillance data were obtained from the Korea Centers for Disease Control and Prevention (KCDC) influenza-like illness (ILI) and virologic surveillance system. Pearson''s correlation coefficients were calculated to compare the national surveillance and the Google Trends data for the overall period and for 5 influenza seasons.

Results

The correlation coefficient between the KCDC ILI and virologic surveillance data was 0.72 (p<0.05). The highest correlation was between the Google Trends query of H1N1 and the ILI data, with a correlation coefficient of 0.53 (p<0.05), for the overall study period. When compared with the KCDC virologic data, the Google Trends query of bird flu had the highest correlation with a correlation coefficient of 0.93 (p<0.05) in the 2010-11 season. The following queries showed a statistically significant correlation coefficient compared with ILI data for three consecutive seasons: Tamiflu (r = 0.59, 0.86, 0.90, p<0.05), new flu (r = 0.64, 0.43, 0.70, p<0.05) and flu (r = 0.68, 0.43, 0.77, p<0.05).

Conclusions

In our study, we found that the Google Trends for certain queries using the survey on influenza correlated with national surveillance data in South Korea. The results of this study showed that Google Trends in the Korean language can be used as complementary data for influenza surveillance but was insufficient for the use of predictive models, such as Google Flu Trends.     

National and Local Influenza Surveillance through Twitter: An Analysis of the 2012-2013 Influenza Epidemic

Social media have been proposed as a data source for influenza surveillance because they have the potential to offer real-time access to millions of short, geographically localized messages containing information regarding personal well-being. However, accuracy of social media surveillance systems declines with media attention because media attention increases “chatter” – messages that are about influenza but that do not pertain to an actual infection – masking signs of true influenza prevalence. This paper summarizes our recently developed influenza infection detection algorithm that automatically distinguishes relevant tweets from other chatter, and we describe our current influenza surveillance system which was actively deployed during the full 2012-2013 influenza season. Our objective was to analyze the performance of this system during the most recent 2012–2013 influenza season and to analyze the performance at multiple levels of geographic granularity, unlike past studies that focused on national or regional surveillance. Our system’s influenza prevalence estimates were strongly correlated with surveillance data from the Centers for Disease Control and Prevention for the United States (r = 0.93, p < 0.001) as well as surveillance data from the Department of Health and Mental Hygiene of New York City (r = 0.88, p < 0.001). Our system detected the weekly change in direction (increasing or decreasing) of influenza prevalence with 85% accuracy, a nearly twofold increase over a simpler model, demonstrating the utility of explicitly distinguishing infection tweets from other chatter.     

Determinants of Influenza Transmission in South East Asia: Insights from a Household Cohort Study in Vietnam

To guide control policies, it is important that the determinants of influenza transmission are fully characterized. Such assessment is complex because the risk of influenza infection is multifaceted and depends both on immunity acquired naturally or via vaccination and on the individual level of exposure to influenza in the community or in the household. Here, we analyse a large household cohort study conducted in 2007–2010 in Vietnam using innovative statistical methods to ascertain in an integrative framework the relative contribution of variables that influence the transmission of seasonal (H1N1, H3N2, B) and pandemic H1N1pdm09 influenza. Influenza infection was diagnosed by haemagglutination-inhibition (HI) antibody assay of paired serum samples. We used a Bayesian data augmentation Markov chain Monte Carlo strategy based on digraphs to reconstruct unobserved chains of transmission in households and estimate transmission parameters. The probability of transmission from an infected individual to another household member was 8% (95% CI, 6%, 10%) on average, and varied with pre-season titers, age and household size. Within households of size 3, the probability of transmission from an infected member to a child with low pre-season HI antibody titers was 27% (95% CI 21%–35%). High pre-season HI titers were protective against infection, with a reduction in the hazard of infection of 59% (95% CI, 44%–71%) and 87% (95% CI, 70%–96%) for intermediate (1∶20–1∶40) and high (≥1∶80) HI titers, respectively. Even after correcting for pre-season HI titers, adults had half the infection risk of children. Twenty six percent (95% CI: 21%, 30%) of infections may be attributed to household transmission. Our results highlight the importance of integrated analysis by influenza sub-type, age and pre-season HI titers in order to infer influenza transmission risks in and outside of the household.     

Influenza Morbidity and Mortality in Elderly Patients Receiving Statins: A Cohort Study

Background

Statins possess immunomodulatory properties and have been proposed for reducing morbidity during an influenza pandemic. We sought to evaluate the effect of statins on hospitalizations and deaths related to seasonal influenza outbreaks.

Methodology/Principal Findings

We conducted a population-based cohort study over 10 influenza seasons (1996 to 2006) using linked administrative databases in Ontario, Canada. We identified all adults older than 65 years who had received an influenza vaccination prior to the start of influenza season and distinguished those also prescribed statins (23%) from those not also prescribed statins (77%). Propensity-based matching, which accounted for each individual''s likelihood of receiving a statin, yielded a final cohort of 2,240,638 patients, exactly half of whom received statins. Statins were associated with small protective effects against pneumonia hospitalization (odds ratio [OR] 0.92; 95% CI 0.89–0.95), 30-day pneumonia mortality (0.84; 95% CI 0.77–0.91), and all-cause mortality (0.87; 95% CI 0.84–0.89). These protective effects attenuated substantially after multivariate adjustment and when we excluded multiple observations for each individual, declined over time, differed across propensity score quintiles and risk groups, and were unchanged during post-influenza season periods. The main limitations of this study were the observational study design, the non-specific outcomes, and the lack of information on medications while hospitalized.

Conclusions/Significance

Statin use is associated with a statistically significant but minimal protective effect against influenza morbidity that can easily be attributed to residual confounding. Public health officials and clinicians should focus on other measures to reduce morbidity and mortality from the next influenza pandemic.     

Large-Scale Avian Influenza Surveillance in Wild Birds throughout the United States

Avian influenza is a viral disease that primarily infects wild and domestic birds, but it also can be transmitted to a variety of mammals. In 2006, the United States of America Departments of Agriculture and Interior designed a large-scale, interagency surveillance effort that sought to determine if highly pathogenic avian influenza viruses were present in wild bird populations within the United States of America. This program, combined with the Canadian and Mexican surveillance programs, represented the largest, coordinated wildlife disease surveillance program ever implemented. Here we analyze data from 197,885 samples that were collected from over 200 wild bird species. While the initial motivation for surveillance focused on highly pathogenic avian influenza, the scale of the data provided unprecedented information on the ecology of avian influenza viruses in the United States, avian influenza virus host associations, and avian influenza prevalence in wild birds over time. Ultimately, significant advances in our knowledge of avian influenza will depend on both large-scale surveillance efforts and on focused research studies.