Beyond clustering: mean-field dynamics on networks with arbitrary subgraph composition

Clustering is the propensity of nodes that share a common neighbour to be connected. It is ubiquitous in many networks but poses many modelling challenges. Clustering typically manifests itself by a higher than expected frequency of triangles, and this has led to the principle of constructing networks from such building blocks. This approach has been generalised to networks being constructed from a set of more exotic subgraphs. As long as these are fully connected, it is then possible to derive mean-field models that approximate epidemic dynamics well. However, there are virtually no results for non-fully connected subgraphs. In this paper, we provide a general and automated approach to deriving a set of ordinary differential equations, or mean-field model, that describes, to a high degree of accuracy, the expected values of system-level quantities, such as the prevalence of infection. Our approach offers a previously unattainable degree of control over the arrangement of subgraphs and network characteristics such as classical node degree, variance and clustering. The combination of these features makes it possible to generate families of networks with different subgraph compositions while keeping classical network metrics constant. Using our approach, we show that higher-order structure realised either through the introduction of loops of different sizes or by generating networks based on different subgraphs but with identical degree distribution and clustering, leads to non-negligible differences in epidemic dynamics

Edge-Based Compartmental Modeling for Infectious Disease Spread Part III: Disease and Population Structure

We consider the edge-based compartmental models for infectious disease spread introduced in Part I. These models allow us to consider standard SIR diseases spreading in random populations. In this paper we show how to handle deviations of the disease or population from the simplistic assumptions of Part I. We allow the population to have structure due to effects such as demographic detail or multiple types of risk behavior the disease to have more complicated natural history. We introduce these modifications in the static network context, though it is straightforward to incorporate them into dynamic networks. We also consider serosorting, which requires using the dynamic network models. The basic methods we use to derive these generalizations are widely applicable, and so it is straightforward to introduce many other generalizations not considered here

Fast variables determine the epidemic threshold in the pairwise model with an improved closure

Pairwise models are used widely to model epidemic spread on networks. These include the modelling of susceptible-infected-removed (SIR) epidemics on regular networks and extensions to SIS dynamics and contact tracing on more exotic networks exhibiting degree heterogeneity, directed and/or weighted links and clustering. However, extra features of the disease dynamics or of the network lead to an increase in system size and analytical tractability becomes problematic. Various `closures' can be used to keep the system tractable. Focusing on SIR epidemics on regular but clustered networks, we show that even for the most complex closure we can determine the epidemic threshold as an asymptotic expansion in terms of the clustering coefficient.We do this by exploiting the presence of a system of fast variables, specified by the correlation structure of the epidemic, whose steady state determines the epidemic threshold. While we do not find the steady state analytically, we create an elegant asymptotic expansion of it. We validate this new threshold by comparing it to the numerical solution of the full system and find excellent agreement over a wide range of values of the clustering coefficient, transmission rate and average degree of the network. The technique carries over to pairwise models with other closures [1] and we note that the epidemic threshold will be model dependent. This emphasises the importance of model choice when dealing with realistic outbreaks

An intervention modelling experiment to change GP's intentions to implement evidence-based practice : using theory-based interventions to promote GP management of upper respiratory tract infection without prescribing antibiotics #2

Background: Psychological theories of behaviour may provide a framework to guide the design of interventions to change professional behaviour. Behaviour change interventions, designed using psychological theory and targeting important motivational beliefs, were experimentally evaluated for effects on the behavioural intention and simulated behaviour of GPs in the management of uncomplicated upper respiratory tract infection (URTI). Methods: The design was a 2 × 2 factorial randomised controlled trial. A postal questionnaire was developed based on three theories of human behaviour: Theory of Planned Behaviour; Social Cognitive Theory and Operant Learning Theory. The beliefs and attitudes of GPs regarding the management of URTI without antibiotics and rates of prescribing on eight patient scenarios were measured at baseline and post-intervention. Two theory-based interventions, a "graded task" with "action planning" and a "persuasive communication", were incorporated into the post-intervention questionnaire. Trial groups were compared using co-variate analyses. Results: Post-intervention questionnaires were returned for 340/397 (86%) GPs who responded to the baseline survey. Each intervention had a significant effect on its targeted behavioural belief: compared to those not receiving the intervention GPs completing Intervention 1 reported stronger self-efficacy scores (Beta = 1.41, 95% CI: 0.64 to 2.25) and GPs completing Intervention 2 had more positive anticipated consequences scores (Beta = 0.98, 95% CI = 0.46 to 1.98). Intervention 2 had a significant effect on intention (Beta = 0.90, 95% CI = 0.41 to 1.38) and simulated behaviour (Beta = 0.47, 95% CI = 0.19 to 0.74). Conclusion: GPs' intended management of URTI was significantly influenced by their confidence in their ability to manage URTI without antibiotics and the consequences they anticipated as a result of doing so. Two targeted behaviour change interventions differentially affected these beliefs. One intervention also significantly enhanced GPs' intentions not to prescribe antibiotics for URTI and resulted in lower rates of prescribing on patient scenarios compared to a control group. The theoretical frameworks utilised provide a scientific rationale for understanding how and why the interventions had these effects, improving the reproducibility and generalisability of these findings and offering a sound basis for an intervention in a "real world" trial. Trial registration: Clinicaltrials.gov NCT00376142This study is funded by the European Commission Research Directorate as part of a multi-partner program: Research Based Education and Quality Improvement (ReBEQI): A Framework and tools to develop effective quality improvement programs in European healthcare. (Proposal No: QLRT-2001-00657)

Consistent approximation of epidemic dynamics on degree-heterogeneous clustered networks

Realistic human contact networks capable of spreading infectious disease, for example studied in social contact surveys, exhibit both significant degree heterogeneity and clustering, both of which greatly affect epidemic dynamics. To understand the joint effects of these two network properties on epidemic dynamics, the effective degree model of Lindquist et al. [28] is reformulated with a new moment closure to apply to highly clustered networks. A simulation study comparing alternative ODE models and stochastic simulations is performed for SIR (Susceptible–Infected–Removed) epidemic dynamics, including a test for the conjectured error behaviour in [40], providing evidence that this novel model can be a more accurate approximation to epidemic dynamics on complex networks than existing approaches

Newsprint coverage of smoking in cars carrying children : a case study of public and scientific opinion driving the policy debate

Acknowledgements Date of Acceptance:17/10/2014 Acknowledgements: This project was funded by Cancer Research UK (MC_U130085862) and the Scottish School of Public Health Research. Cancer Research UK and the Scottish School of Public Health Research was not involved in the collection, analysis, and interpretation of data, writing of the manuscript or the decision to submit the manuscript for publication. Shona Hilton, Karen Wood, Josh Bain and Chris Patterson are funded by the UK Medical Research Council as part of the Understandings and Uses of Public Health Research programme (MC_UU_12017/6) at the MRC/CSO Social and Public Health Sciences Unit, University of Glasgow. We thank Alan Pollock who provided assistance with coding.Peer reviewedPublisher PD

Knowledge and exposure to complementary and alternative medicine in paediatric doctors: a questionnaire survey

<p>Abstract</p> <p>Background</p> <p>Complementary and alternative medicines are increasingly used by the general population. A survey was conducted to ascertain the knowledge of Complementary and Alternative Medicines (CAMs) amongst paediatric physicians, and whether seniority increases the likelihood of its use being considered in consultations, or of families discussing it.</p> <p>Methods</p> <p>Anonymous survey of general paediatric doctors in a large inner-city district general hospital (DGH) and tertiary children's centre (TC) using a questionnaire. Statistical analysis was calculated using Minitab.</p> <p>Results</p> <p>43/49 (88%) questionnaires were returned correctly. 13 (30%, CI 17 – 46%) doctors had personally used CAMs. 24 (56%, CI 40 – 71%) of their families had used CAMs. 13 (30%, CI 17 – 46%) had received formal CAMs education. 21 (49%, CI 40 – 71%) could name a total of 5 types of CAMs. Consultants were significantly more likely to ask about CAM use than middle-grades and juniors (p < 0.05, CI 48 – 93%, 35 – 90%, 8 – 33% respectively) and have had a clinical encounter where they felt it was significant. 32 (74%, CI 59 – 86%) of the clinicians had been asked about CAMs. 33 (77%, CI 61 – 88%) of doctors had successful CAM use reported to them, and 20 (47%, CI 31 – 62%) had failure of CAMs reported to them.</p> <p>Conclusion</p> <p>CAM use is relatively common in paediatric doctors and their families. They have received little formal CAMs education. Consultants were more likely than juniors to ask about CAM use and have had a clinical encounter where it played a significant part. Around half of all doctors irrespective of grade have been asked about CAMs in a clinical encounter.</p

The formation of professional identity in medical students: considerations for educators

&lt;b&gt;Context&lt;/b&gt; Medical education is about more than acquiring an appropriate level of knowledge and developing relevant skills. To practice medicine students need to develop a professional identity – ways of being and relating in professional contexts.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Objectives&lt;/b&gt; This article conceptualises the processes underlying the formation and maintenance of medical students’ professional identity drawing on concepts from social psychology.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Implications&lt;/b&gt; A multi-dimensional model of identity and identity formation, along with the concepts of identity capital and multiple identities, are presented. The implications for educators are discussed.&lt;p&gt;&lt;/p&gt; &lt;b&gt;Conclusions&lt;/b&gt; Identity formation is mainly social and relational in nature. Educators, and the wider medical society, need to utilise and maximise the opportunities that exist in the various relational settings students experience. Education in its broadest sense is about the transformation of the self into new ways of thinking and relating. Helping students form, and successfully integrate their professional selves into their multiple identities, is a fundamental of medical education

Management of allergic rhinitis symptoms in the pharmacy Pocket guide 2022

Allergic rhinitis (AR) management requires a coordinated effort from healthcare providers and patients. Pharmacists are key members of these integrated care pathways resolving medication-related problems, optimizing regimens, improving adherence and recommending therapies while establishing liaisons between patients and physicians.Allergic Rhinitis and its Impact on Asthma (ARIA) first published a reference document on the pharmacist's role in allergic rhinitis management in 2004. Several guidelines were developed over the past 20 years improving the care of allergic rhinitis patients through an evidence-based, integrated care approach.This ARIA/EAACI/FIP Position Paper is based on the latest ARIA in the Pharmacy guidelines and provides: (a) a structured approach to pharmacists identifying people with AR and/or allergic conjunctivitis as well as those at risk of poor disease control; (b) an evidence-based clinical decision support tool for optimising the management of allergic rhinitis in the community pharmacy; and (c) a framework of referral to the physician.This document is not intended to be a mandatory standard of care but is provided as a basis for pharmacists and their staff to develop relevant local standards of care for their patients, within their local practice environment. Pharmacy care varies between countries, and the guide should be adapted to the local situation.© 2022 The Authors. Clinical and Translational Allergy published by John Wiley & Sons Ltd on behalf of European Academy of Allergy and Clinical Immunology

A comparison of liver fat fraction measurement on MRI at 3T and 1.5T

Purpose Volumetric liver fat fraction (VLFF) measurements were made using the HepaFat-Scan® technique at 1.5T and 3T to determine the agreement between the measurements obtained at the two fields. Methods Sixty patients with type 2 diabetes (67% male, mean age 50.92 ± 6.56yrs) and thirty healthy volunteers (50% male, mean age 48.63 ± 6.32yrs) were scanned on 1.5T Aera and 3T Skyra (Siemens, Erlangen, Germany) MRI scanners on the same day using the HepaFat-Scan® gradient echo protocol with modification of echo times for 3T (TEs 2.38, 4.76, 7.14 ms at 1.5T and 1.2, 2.4, 3.6 ms at 3T). The 3T analyses were performed independently of the 1.5T analyses by a different analyst, blinded from the 1.5T results. Data were analysed for agreement and bias using Bland-Altman methods and intraclass correlation coefficients (ICC). A second cohort of 17 participants underwent interstudy repeatability assessment of VLFF measured by HepaFat-Scan® at 3T. Results A small, but statistically significant mean bias of 0.48% was observed between 3T and 1.5T with 95% limits of agreement -2.2% to 3.2% VLFF. The ICC for agreement between field strengths was 0.983 (95% CI 0.972–0.989). In the repeatability cohort studied at 3T the repeatability coefficient was 4.2%. The ICC for agreement was 0.971 (95% CI 0.921–0.989). Conclusion There is minimal bias and excellent agreement between the measures of VLFF using the HepaFat-Scan® at 1.5 and 3T. The test retest repeatability coefficient at 3T is comparable to the 95% limits of agreement between 1.5T and 3T suggesting that measurements can be made interchangeably between field strengths