Estimation of Influenza Vaccine Effectiveness from Routine Surveillance Data

BACKGROUND: Influenza vaccines are reviewed each year, and often changed, in an effort to maintain their effectiveness against drifted influenza viruses. There is however no regular review of influenza vaccine effectiveness during, or at the end of, Australian influenza seasons. It is possible to use a case control method to estimate vaccine effectiveness from surveillance data when all patients in a surveillance system are tested for influenza and their vaccination status is known. METHODOLOGY/PRINCIPAL FINDINGS: Influenza-like illness (ILI) surveillance is conducted during the influenza season in sentinel general practices scattered throughout Victoria, Australia. Over five seasons 2003-7, data on age, sex and vaccination status were collected and nose and throat swabs were offered to patients presenting within three days of the onset of their symptoms. Swabs were tested using a reverse transcriptase polymerase chain reaction (RT-PCR) test. Those positive for influenza were sent to the World Health Organization (WHO) Collaborating Centre for Reference and Research on Influenza where influenza virus culture and strain identification was attempted. We used a retrospective case control design in five consecutive influenza seasons, and estimated influenza vaccine effectiveness (VE) for patients of all ages to be 53% (95% CI 38-64), but 41% (95% CI 19-57) adjusted for age group and year. The adjusted VE for all adults aged at least 20 years, the age groups for whom a benefit of vaccination could be shown, was 51% (95% CI 34-63). Comparison of VE estimates with vaccine and circulating strain matches across the years did not reveal any significant differences. CONCLUSIONS/SIGNIFICANCE: These estimates support other field studies of influenza vaccine effectiveness, given that theoretical considerations suggest that these values may underestimate true effectiveness, depending on test specificity and the ratio of the influenza ILI attack rate to the non-influenza ILI attack rate. Incomplete recording of vaccination status and under-representation of children in patients from whom a swab was collected limit the data. Improvements have been implemented for prospective studies

Nitrogen doping into titanium dioxide by the sol–gel method using nitric acid

N-doped TiO(2) has been prepared by use of sol-gel systems containing titanium alkoxide, with nitric acid as the nitrogen source. The time needed for gelation of the systems was drastically reduced by ultrasonic irradiation. The peaks assigned to the nitrate and nitrous ions were observed by FT-IR measurement during the sol-gel reaction. The N-doping was confirmed by the observation of N-O peaks in the XPS spectrum of the sample heated at 400 A degrees C. The nitrate ion acted as an oxidizer of the ethanol solvent and titanium species. The TiO(2) became doped with nitrogen oxide species as a result of reduction of nitrate ion incorporated into the dried gel samples. These results indicated that the added nitric acid was reduced during the sol-gel transition and heating process, and the resulting NO species were situated in the titania networks. The UV and visible photocatalytic activity of the samples was confirmed by the degradation of trichloroethylene.ArticleRESEARCH ON CHEMICAL INTERMEDIATES. 37(8):869-881 (2011)journal articl

Stopping Antiepileptic Drugs: When and Why?

After a patient has initiated an antiepileptic drug (AED) and achieved a sustained period of seizure freedom, the bias towards continuing therapy indefinitely can be substantial. Studies show that the rate of seizure recurrence after AED withdrawal is about two to three times the rate in patients who continue AEDs, but there are many benefits to AED withdrawal that should be evaluated on an individualized basis. AED discontinuation may be considered in patients whose seizures have been completely controlled for a prolonged period, typically 1 to 2 years for children and 2 to 5 years for adults. For children, symptomatic epilepsy, adolescent onset, and a longer time to achieve seizure control are associated with a worse prognosis. In adults, factors such as a longer duration of epilepsy, an abnormal neurologic examination, an abnormal EEG, and certain epilepsy syndromes are known to increase the risk of recurrence. Even in patients with a favorable prognosis, however, the risk of relapse can be as high as 20% to 25%. Before withdrawing AEDs, patients should be counseled about their individual risk for relapse and the potential implications of a recurrent seizure, particularly for safety and driving

Using Basic Science to Design a Clinical Trial: Baseline Characteristics of Women Enrolled in the Kronos Early Estrogen Prevention Study (KEEPS)

Observational and epidemiological studies suggest that menopausal hormone therapy (MHT) reduces cardiovascular disease (CVD) risk. However, results from prospective trials showed neutral or adverse effects most likely due to differences in participant demographics, such as age, timing of initiation of treatment, and preexisting cardiovascular disease, which reflected in part the lack of basic science information on mechanisms of action of hormones on the vasculature at the time clinical trials were designed. The Kronos Early Estrogen Replacement Study (KEEPS) is a prospective, randomized, controlled trial designed, using findings from basic science studies, to test the hypothesis that MHT when initiated early in menopause reduces progression of atherosclerosis. KEEPS participants are younger, healthier, and within 3 years of menopause thus matching more closely demographics of women in prior observational and epidemiological studies than women in the Women’s Health Initiative hormone trials. KEEPS will provide information relevant to the critical timing hypothesis for MHT use in reducing risk for CVD

The limits of corporate social responsibility : Techniques of neutralization, stakeholder management and political CSR

Since scholarly interest in corporate social responsibility (CSR) has primarily focused on the synergies between social and economic performance, our understanding of how (and the conditions under which) companies use CSR to produce policy outcomes that work against public welfare has remained comparatively underdeveloped. In particular, little is known about how corporate decision-makers privately reconcile the conflicts between public and private interests, even though this is likely to be relevant to understanding the limitations of CSR as a means of aligning business activity with the broader public interest. This study addresses this issue using internal tobacco industry documents to explore British-American Tobacco’s (BAT) thinking on CSR and its effects on the company’s CSR Programme. The article presents a three-stage model of CSR development, based on Sykes and Matza’s theory of techniques of neutralization, which links together: how BAT managers made sense of the company’s declining political authority in the mid-1990s; how they subsequently justified the use of CSR as a tool of stakeholder management aimed at diffusing the political impact of public health advocates by breaking up political constituencies working towards evidence-based tobacco regulation; and how CSR works ideologically to shape stakeholders’ perceptions of the relative merits of competing approaches to tobacco control. Our analysis has three implications for research and practice. First, it underlines the importance of approaching corporate managers’ public comments on CSR critically and situating them in their economic, political and historical contexts. Second, it illustrates the importance of focusing on the political aims and effects of CSR. Third, by showing how CSR practices are used to stymie evidence-based government regulation, the article underlines the importance of highlighting and developing matrices to assess the negative social impacts of CSR

Relativistic Binaries in Globular Clusters

Galactic globular clusters are old, dense star systems typically containing 10\super{4}--10\super{7} stars. As an old population of stars, globular clusters contain many collapsed and degenerate objects. As a dense population of stars, globular clusters are the scene of many interesting close dynamical interactions between stars. These dynamical interactions can alter the evolution of individual stars and can produce tight binary systems containing one or two compact objects. In this review, we discuss theoretical models of globular cluster evolution and binary evolution, techniques for simulating this evolution that leads to relativistic binaries, and current and possible future observational evidence for this population. Our discussion of globular cluster evolution will focus on the processes that boost the production of hard binary systems and the subsequent interaction of these binaries that can alter the properties of both bodies and can lead to exotic objects. Direct {\it N}-body integrations and Fokker--Planck simulations of the evolution of globular clusters that incorporate tidal interactions and lead to predictions of relativistic binary populations are also discussed. We discuss the current observational evidence for cataclysmic variables, millisecond pulsars, and low-mass X-ray binaries as well as possible future detection of relativistic binaries with gravitational radiation.Comment: 88 pages, 13 figures. Submitted update of Living Reviews articl

Scalable rule-based modelling of allosteric proteins and biochemical networks

Much of the complexity of biochemical networks comes from the information-processing abilities of allosteric proteins, be they receptors, ion-channels, signalling molecules or transcription factors. An allosteric protein can be uniquely regulated by each combination of input molecules that it binds. This "regulatory complexity" causes a combinatorial increase in the number of parameters required to fit experimental data as the number of protein interactions increases. It therefore challenges the creation, updating, and re-use of biochemical models. Here, we propose a rule-based modelling framework that exploits the intrinsic modularity of protein structure to address regulatory complexity. Rather than treating proteins as "black boxes", we model their hierarchical structure and, as conformational changes, internal dynamics. By modelling the regulation of allosteric proteins through these conformational changes, we often decrease the number of parameters required to fit data, and so reduce over-fitting and improve the predictive power of a model. Our method is thermodynamically grounded, imposes detailed balance, and also includes molecular cross-talk and the background activity of enzymes. We use our Allosteric Network Compiler to examine how allostery can facilitate macromolecular assembly and how competitive ligands can change the observed cooperativity of an allosteric protein. We also develop a parsimonious model of G protein-coupled receptors that explains functional selectivity and can predict the rank order of potency of agonists acting through a receptor. Our methodology should provide a basis for scalable, modular and executable modelling of biochemical networks in systems and synthetic biology