The hospital ‘superbug’: social representations of MRSA

The so-called ‘hospital superbug’ methcillin resistant staphylococcus aureus (MRSA) became a topic of media and political concern from the middle of the 1990’s. It was increasingly politicised in the period leading up to the British General Election of 2005. This study examines the meanings of MRSA that circulate in Britain by analysing newspaper coverage of the disease over a ten year period. It utilises social representations theory and contextualises MRSA within existing research on representations of emerging infectious diseases (EIDs). A key pattern in the representation of EIDs is to externalise the threat they pose by linking the origin, risk and blame to ‘the other’ of those who represent them. In this light the study investigates who and what MRSA is associated with and the impact that these associations have on levels of alarm and blame. Key findings are that MRSA is represented as a potentially lethal ‘superbug’, marking the end of a ‘golden age of medicine’ in which the story of the discovery of antibiotics has played such a key role. Furthermore, MRSA is constructed around an “it could be you / me” set of assumptions by way of the plethora of human interest stories that dominate the coverage. Finally, the blame for MRSA focuses not on its genesis, but rather on why it spreads. This is attributed to poor hygiene in hospitals, which is ultimately caused by mismanagement of the National Health Service and erosion of the authority and morality symbolised by the ‘matron’ role. This constellation of meanings speaks to a somewhat different pattern of response to MRSA when compared to many past EIDs

Newark Engineering Notes, Volume 1, No. 1, April 1938

A journal by the administration, faculty and alumni of the Newark College of Engineering. This issue includes the following: The President\u27s Diary Great Range Portable Vibration Instrument by Eastman Smith Parallels In Progress Prognostic Tests by Frank N. Entwisle Constant Head Tanks For Hydraulic Laboratory by H. N. Cummings The Equilibrium Of A Rectangular Horizontal Piece Of Canvas Under Water Pressure by Josepb Joffe A Good Record A New Physics Text Book Retrospect and Prospect by Robert W. Van Houten The Way We See It What Our Professors and Graduates Are Doinghttps://digitalcommons.njit.edu/nen/1000/thumbnail.jp

Representations of swine flu: Perspectives from a Malaysian pig farm

© The Author(s), 2010. This is the author's accepted manuscript. The final published article is available from the link below.Novel influenza viruses are seen, internationally, as posing considerable health challenges, but public responses to such viruses are often rooted in cultural representations of disease and risk. However, little research has been conducted in locations associated with the origin of a pandemic. We examined representations and risk perceptions associated with swine flu amongst 120 Malaysian pig farmers. Thirty-seven per cent of respondents felt at particular risk of infection, two-thirds were somewhat or very concerned about being infected. Those respondents who were the most anxious believed particular societal “out-groups” (homosexuals, the homeless and prostitutes) to be at higher infection risk. Although few (4%) reported direct discrimination, 46% claimed friends had avoided them since the swine flu outbreak. Findings are discussed in the context of evolutionary, social representations and terror management theories of response to pandemic threat

Causal inference for continuous-time processes when covariates are observed only at discrete times

Most of the work on the structural nested model and g-estimation for causal inference in longitudinal data assumes a discrete-time underlying data generating process. However, in some observational studies, it is more reasonable to assume that the data are generated from a continuous-time process and are only observable at discrete time points. When these circumstances arise, the sequential randomization assumption in the observed discrete-time data, which is essential in justifying discrete-time g-estimation, may not be reasonable. Under a deterministic model, we discuss other useful assumptions that guarantee the consistency of discrete-time g-estimation. In more general cases, when those assumptions are violated, we propose a controlling-the-future method that performs at least as well as g-estimation in most scenarios and which provides consistent estimation in some cases where g-estimation is severely inconsistent. We apply the methods discussed in this paper to simulated data, as well as to a data set collected following a massive flood in Bangladesh, estimating the effect of diarrhea on children's height. Results from different methods are compared in both simulation and the real application.Comment: Published in at http://dx.doi.org/10.1214/10-AOS830 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Defining and Estimating Intervention Effects for Groups that will Develop an Auxiliary Outcome

It has recently become popular to define treatment effects for subsets of the target population characterized by variables not observable at the time a treatment decision is made. Characterizing and estimating such treatment effects is tricky; the most popular but naive approach inappropriately adjusts for variables affected by treatment and so is biased. We consider several appropriate ways to formalize the effects: principal stratification, stratification on a single potential auxiliary variable, stratification on an observed auxiliary variable and stratification on expected levels of auxiliary variables. We then outline identifying assumptions for each type of estimand. We evaluate the utility of these estimands and estimation procedures for decision making and understanding causal processes, contrasting them with the concepts of direct and indirect effects. We motivate our development with examples from nephrology and cancer screening, and use simulated data and real data on cancer screening to illustrate the estimation methods.Comment: Published at http://dx.doi.org/10.1214/088342306000000655 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Structural Nested Models and G-estimation: The Partially Realized Promise

Structural nested models (SNMs) and the associated method of G-estimation were first proposed by James Robins over two decades ago as approaches to modeling and estimating the joint effects of a sequence of treatments or exposures. The models and estimation methods have since been extended to dealing with a broader series of problems, and have considerable advantages over the other methods developed for estimating such joint effects. Despite these advantages, the application of these methods in applied research has been relatively infrequent; we view this as unfortunate. To remedy this, we provide an overview of the models and estimation methods as developed, primarily by Robins, over the years. We provide insight into their advantages over other methods, and consider some possible reasons for failure of the methods to be more broadly adopted, as well as possible remedies. Finally, we consider several extensions of the standard models and estimation methods.Comment: Published in at http://dx.doi.org/10.1214/14-STS493 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Review on Master Patient Index

In today's health care establishments there is a great diversity of information systems. Each with different specificities and capacities, proprietary communication methods, and hardly allow scalability. This set of characteristics hinders the interoperability of all these systems, in the search for the good of the patient. It is vulgar that, when we look at all the databases of each of these information systems, we come across different registers that refer to the same person; records with insufficient data; records with erroneous data due to errors or misunderstandings when inserting patient data; and records with outdated data. These problems cause duplicity, incoherence, discontinuation and dispersion in patient data. With the intention of minimizing these problems that the concept of a Master Patient Index is necessary. A Master Patient Index proposes a centralized repository, which indexes all patient records of a given set of information systems. Which is composed of a set of demographic data sufficient to unambiguously identify a person and a list of identifiers that identify the various records that the patient has in the repositories of each information system. This solution allows for synchronization between all the actors, minimizing incoherence, out datedness, lack of data, and a decrease in duplicate registrations. The Master Patient Index is an asset to patients, the medical staff and health care providers

Representations of SARS in the UK newspapers

In the Spring of 2003, there was a huge interest in the global news media following the emergence of a new infectious disease: severe acute respiratory syndrome (SARS). This study examines how this novel disease threat was depicted in the UK newspapers, using social representations theory and in particular existing work on social representations of HIV/AIDS and Ebola to analyse the meanings of the epidemic. It investigates the way that SARS was presented as a dangerous threat to the UK public, whilst almost immediately the threat was said to be ‘contained’ using the mechanism of ‘othering’: SARS was said to be unlikely to personally affect the UK reader because the Chinese were so different to ‘us’; so ‘other’. In this sense, the SARS scare, despite the remarkable speed with which it was played out in the modern global news media, resonates with the meanings attributed to other epidemics of infectious diseases throughout history. Yet this study also highlights a number of differences in the social representations of SARS compared with earlier epidemics. In particular, this study examines the phenomena of ‘emerging and re-emerging infectious diseases’ over the past 30 or so years and suggests that these have impacted on the faith once widely held that Western biomedicine could ‘conquer’ infectious disease