Slightly generalized Generalized Contagion: Unifying simple models of biological and social spreading

We motivate and explore the basic features of generalized contagion, a model mechanism that unifies fundamental models of biological and social contagion. Generalized contagion builds on the elementary observation that spreading and contagion of all kinds involve some form of system memory. We discuss the three main classes of systems that generalized contagion affords, resembling: simple biological contagion; critical mass contagion of social phenomena; and an intermediate, and explosive, vanishing critical mass contagion. We also present a simple explanation of the global spreading condition in the context of a small seed of infected individuals.Comment: 8 pages, 5 figures; chapter to appear in "Spreading Dynamics in Social Systems"; Eds. Sune Lehmann and Yong-Yeol Ahn, Springer Natur

Clinical impact of early post-transplant red cell transfusions in kidney transplantation: a systematic review and meta-analysis

Introduction: Red blood cell transfusions (RBCT) represent a potentially modifiable risk factor for HLA sensitisation and adverse outcomes post transplantation. Evidence of the clinical impact of post-transplant RBCT has been infrequently reported. Herein, we performed a systematic review of available literature to assess the prevalence of RBCT post kidney transplant, and the effect of transfusion on transplant outcomes. Methods: We included studies from 2000 to July 2022, published on Medline, Embase and the Transplant Library. Results: Ten studies were analysed which included a total of 32,817 kidney transplant recipients, with a median transfusion prevalence of 40% (range 18-64%). There was significant heterogeneity between studies in terms of patient and allograft characteristics, immunological risk, and immunosuppression protocols. Analysis of unadjusted outcomes showed that post-transplant RBCTs are associated with inferior patient survival, allograft loss, rejection and donor specific antibodies. Adjusted outcomes were described where available, and supported the adverse associations seen in the unadjusted models in many studies. Discussion: This review demonstrates that RBCT post-transplant are common and maybe associated with inferior outcomes, highlighting the urgent need for high quality prospective evidence of the effect of RBCTs on transplant outcomes. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier, CRD42022348763767

Network segregation in a model of misinformation and fact checking

Misinformation under the form of rumor, hoaxes, and conspiracy theories spreads on social media at alarming rates. One hypothesis is that, since social media are shaped by homophily, belief in misinformation may be more likely to thrive on those social circles that are segregated from the rest of the network. One possible antidote is fact checking which, in some cases, is known to stop rumors from spreading further. However, fact checking may also backfire and reinforce the belief in a hoax. Here we take into account the combination of network segregation, finite memory and attention, and fact-checking efforts. We consider a compartmental model of two interacting epidemic processes over a network that is segregated between gullible and skeptic users. Extensive simulation and mean-field analysis show that a more segregated network facilitates the spread of a hoax only at low forgetting rates, but has no effect when agents forget at faster rates. This finding may inform the development of mitigation techniques and overall inform on the risks of uncontrolled misinformation online

A General Model of Dynamics on Networks with Graph Automorphism Lumping

In this paper we introduce a general Markov chain model of dynamical processes on networks. In this model, nodes in the network can adopt a finite number of states and transitions can occur that involve multiple nodes changing state at once. The rules that govern transitions only depend on measures related to the state and structure of the network and not on the particular nodes involved. We prove that symmetries of the network can be used to lump equivalent states in state-space. We illustrate how several examples of well-known dynamical processes on networks correspond to particular cases of our general model. This work connects a wide range of models specified in terms of node-based dynamical rules to their exact continuous-time Markov chain formulation

NetPyNE, a tool for data-driven multiscale modeling of brain circuits.

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing and disparate experimental datasets at multiple scales. The NetPyNE tool (www.netpyne.org) provides both programmatic and graphical interfaces to develop data-driven multiscale network models in NEURON. NetPyNE clearly separates model parameters from implementation code. Users provide specifications at a high level via a standardized declarative language, for example connectivity rules, to create millions of cell-to-cell connections. NetPyNE then enables users to generate the NEURON network, run efficiently parallelized simulations, optimize and explore network parameters through automated batch runs, and use built-in functions for visualization and analysis - connectivity matrices, voltage traces, spike raster plots, local field potentials, and information theoretic measures. NetPyNE also facilitates model sharing by exporting and importing standardized formats (NeuroML and SONATA). NetPyNE is already being used to teach computational neuroscience students and by modelers to investigate brain regions and phenomena

The communication of a secondary care diagnosis of autoimmune hepatitis to primary care practitioners: a population-based study

Background Autoimmune Hepatitis is a chronic liver disease which affects young people and can result in liver failure leading to death or transplantation yet there is a lack of information on the incidence and prevalence of this disease and its natural history in the UK. A means of obtaining this information is via the use of clinical databases formed of electronic primary care records. How reliably the diagnosis is coded in such records is however unknown. The aim of this study therefore was to assess the proportion of consultant hepatologist diagnoses of Autoimmune Hepatitis which were accurately recorded in General Practice computerised records. Methods Our study population were patients with Autoimmune Hepatitis diagnosed by consultant hepatologists in the Queens Medical Centre, Nottingham University Hospitals (UK) between 2004 and 2009. We wrote to the general practitioners of these patients to obtain the percentage of patients who had a valid READ code specific for Autoimmune Hepatitis. Results We examined the electronic records of 51 patients who had biopsy evidence and a possible diagnosis of Autoimmune Hepatitis. Forty two of these patients had a confirmed clinical diagnosis of Autoimmune Hepatitis by a consultant hepatologist: we contacted the General Practitioners of these patients obtaining a response rate of 90.5% (39/42 GPs). 37/39 of these GPs responded with coding information and 89% of these patients (33/37) used Read code J638.00 (Autoimmune Hepatitis) to record a diagnosis. Conclusions The diagnosis of Autoimmune Hepatitis made by a Consultant Hepatologist is accurately communicated to and electronically recorded by primary care in the UK. As a large proportion of cases of Autoimmune Hepatitis are recorded in primary care, this minimises the risk of introducing selection bias and therefore selecting cases using these data will be a valid method of conducting population based studies on Autoimmune Hepatitis

Exact analysis of summary statistics for continuous-time discrete-state Markov processes on networks using graph-automorphism lumping

We propose a unified framework to represent a wide range of continuous-time discrete-state Markov processes on networks, and show how many network dynamics models in the literature can be represented in this unified framework. We show how a particular sub-set of these models, referred to here as single-vertex-transition (SVT) processes, lead to the analysis of quasi-birth-and-death (QBD) processes in the theory of continuous-time Markov chains. We illustrate how to analyse a number of summary statistics for these processes, such as absorption probabilities and first-passage times. We extend the graph-automorphism lumping approach [Kiss, Miller, Simon, Mathematics of Epidemics on Networks, 2017; Simon, Taylor, Kiss, J. Math. Bio. 62(4), 2011], by providing a matrix-oriented representation of this technique, and show how it can be applied to a very wide range of dynamical processes on networks. This approach can be used not only to solve the master equation of the system, but also to analyse the summary statistics of interest. We also show the interplay between the graph-automorphism lumping approach and the QBD structures when dealing with SVT processes. Finally, we illustrate our theoretical results with examples from the areas of opinion dynamics and mathematical epidemiology

Pre-cooling for endurance exercise performance in the heat: a systematic review.

PMCID: PMC3568721The electronic version of this article is the complete one and can be found online at: http://www.biomedcentral.com/1741-7015/10/166. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Endurance exercise capacity diminishes under hot environmental conditions. Time to exhaustion can be increased by lowering body temperature prior to exercise (pre-cooling). This systematic literature review synthesizes the current findings of the effects of pre-cooling on endurance exercise performance, providing guidance for clinical practice and further research

Online and social networking interventions for the treatment of depression in young people: a systematic review

BACKGROUND: Major depression accounts for the greatest burden of all diseases globally. The peak onset of depression occurs between adolescence and young adulthood, and for many individuals, depression displays a relapse-remitting and increasingly severe course. Given this, the development of cost-effective, acceptable, and population-focused interventions for depression is critical. A number of online interventions (both prevention and acute phase) have been tested in young people with promising results. As these interventions differ in content, clinician input, and modality, it is important to identify key features (or unhelpful functions) associated with treatment outcomes. OBJECTIVE: A systematic review of the research literature was undertaken. The review was designed to focus on two aspects of online intervention: (1) standard approaches evaluating online intervention content in randomized controlled designs (Section 1), and (2) second-generation online interventions and services using social networking (eg, social networking sites and online support groups) in any type of research design (Section 2). METHODS: Two specific literature searches were undertaken. There was no date range specified. The Section 1 search, which focused on randomized controlled trials, included only young people (12-25 years) and yielded 101 study abstracts, of which 15 met the review inclusion criteria. The Section 2 search, which included all study design types and was not restricted in terms of age, yielded 358 abstracts, of which 22 studies met the inclusion criteria. Information about the studies and their findings were extracted and tabulated for review. RESULTS: The 15 studies identified in Section 1 described 10 trials testing eight different online interventions, all of which were based on a cognitive behavioral framework. All but one of the eight identified studies reported positive results; however, only five of the 15 studies used blinded interviewer administered outcomes with most trials using self-report data. Studies varied significantly in presentation of intervention content, treatment dose, and dropout. Only two studies included moderator or clinician input. Results for Section 2 were less consistent. None of the Section 2 studies reported controlled or randomized designs. With the exception of four studies, all included participants were younger than 25 years of age. Eight of the 16 social networking studies reported positive results for depression-related outcomes. The remaining studies were either mixed or negative. Findings for online support groups tended to be more positive; however, noteworthy risks were identified. CONCLUSIONS: Online interventions with a broad cognitive behavioral focus appear to be promising in reducing depression symptomology in young people. Further research is required into the effectiveness of online interventions delivering cognitive behavioral subcomponents, such as problem-solving therapy. Evidence for the use of social networking is less compelling, although limited by a lack of well-designed studies and social networking interventions. A range of future social networking therapeutic opportunities are highlighted

Effect of pre-milking teat preparation procedures on the microbial count on teats prior to cluster application

A study was carried out to investigate the effect of six pre-milking teat preparation procedures on lowering the staphylococal, streptococcal and coliform microbial count on teat skin prior to cluster application. The teat preparations included 'Iodine', 'Chlorhexidine' teat foam, 'Washing and drying' with paper, 'No preparation', 'Chlorine' teat foam, and disinfectant 'Wipes'. Teat preparations were applied for five days to 10 cows for each treatment during two herd management periods (indoors and outdoors). Teats were swabbed on day four and five before teat preparation and repeated after teat preparation. The swabs were plated on three selective agars: Baird Parker (Staphylococcus spp.), Edwards (Streptococcus spp.), and MacConkey (coliform). Following incubation, microbial counts for each pathogen type were manually counted and assigned to one of six categories depending on the microbial counts measured. The results were analysed by logistic regression using SAS [28]. The main analysis was conducted on binary improvement scores for the swabbing outcomes. There were no differences for staphylococcal, streptococcal and coliform bacterial counts between treatments, measured 'before' teat preparation. Treatments containing 'Chlorhexidine' teat foam (OR = 4.46) and 'Wipes' (OR = 4.46) resulted in a significant reduction (P < 0.01) in the staphylococcal count on teats compared to 'Washing and drying' or 'No preparation'. 'Chlorine' teat foam (OR = 3.45) and 'Wipes' (3.45) had the highest probability (P < 0.01) of reducing streptococcal counts compared to 'Washing and drying' or 'No preparation'. There was no statistical difference between any of the disinfectant treatments applied in reducing coliforms. Thus, the use of some disinfectant products for pre-milking teat preparation can have beneficial effects on reducing the levels of staphylococcal and streptococcal pathogens on teat skin