213 research outputs found

    Phandango: an interactive viewer for bacterial population genomics.

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    Summary: Fully exploiting the wealth of data in current bacterial population genomics datasets requires synthesising and integrating different types of analysis across millions of base pairs in hundreds or thousands of isolates. Current approaches often use static representations of phylogenetic, epidemiological, statistical and evolutionary analysis results that are difficult to relate to one another. Phandango is an interactive application running in a web browser allowing fast exploration of large-scale population genomics datasets combining the output from multiple genomic analysis methods in an intuitive and interactive manner. Availability: Phandango is a web application freely available for use at www.phandango.net and includes a diverse collection of datasets as examples. Source code together with a detailed wiki page is available on GitHub at https://github.com/jameshadfield/phandango. Contact: [email protected], [email protected]

    The Virtual Teacher (VT) Paradigm: Learning New Patterns of Interpersonal Coordination Using the Human Dynamic Clamp

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    The Virtual Teacher paradigm, a version of the Human Dynamic Clamp (HDC), is introduced into studies of learning patterns of inter-personal coordination. Combining mathematical modeling and experimentation, we investigate how the HDC may be used as a Virtual Teacher (VT) to help humans co-produce and internalize new inter-personal coordination pattern(s). Human learners produced rhythmic finger movements whilst observing a computer-driven avatar, animated by dynamic equations stemming from the well-established Haken-Kelso-Bunz (1985) and Schöner-Kelso (1988) models of coordination. We demonstrate that the VT is successful in shifting the pattern co-produced by the VT-human system toward any value (Experiment 1) and that the VT can help humans learn unstable relative phasing patterns (Experiment 2). Using transfer entropy, we find that information flow from one partner to the other increases when VT-human coordination loses stability. This suggests that variable joint performance may actually facilitate interaction, and in the long run learning. VT appears to be a promising tool for exploring basic learning processes involved in social interaction, unraveling the dynamics of information flow between interacting partners, and providing possible rehabilitation opportunities

    Psychological interventions in asthma

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    Asthma is a multifactorial chronic respiratory disease characterised by recurrent episodes of airway obstruction. The current management of asthma focuses principally on pharmacological treatments, which have a strong evidence base underlying their use. However, in clinical practice, poor symptom control remains a common problem for patients with asthma. Living with asthma has been linked with psychological co-morbidity including anxiety, depression, panic attacks and behavioural factors such as poor adherence and suboptimal self-management. Psychological disorders have a higher-than-expected prevalence in patients with difficult-to-control asthma. As psychological considerations play an important role in the management of people with asthma, it is not surprising that many psychological therapies have been applied in the management of asthma. There are case reports which support their use as an adjunct to pharmacological therapy in selected individuals, and in some clinical trials, benefit is demonstrated, but the evidence is not consistent. When findings are quantitatively synthesised in meta-analyses, no firm conclusions are able to be drawn and no guidelines recommend psychological interventions. These inconsistencies in findings may in part be due to poor study design, the combining of results of studies using different interventions and the diversity of ways patient benefit is assessed. Despite this weak evidence base, the rationale for psychological therapies is plausible, and this therapeutic modality is appealing to both patients and their clinicians as an adjunct to conventional pharmacological treatments. What are urgently required are rigorous evaluations of psychological therapies in asthma, on a par to the quality of pharmaceutical trials. From this evidence base, we can then determine which interventions are beneficial for our patients with asthma management and more specifically which psychological therapy is best suited for each patient

    Non-monotonicity on a spatio-temporally defined cyclic task: evidence of two movement types?

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    We tested 23 healthy participants who performed rhythmic horizontal movements of the elbow. The required amplitude and frequency ranges of the movements were specified to the participants using a closed shape on a phase-plane display, showing angular velocity versus angular position, such that participants had to continuously control both the speed and the displacement of their forearm. We found that the combined accuracy in velocity and position throughout the movement was not a monotonic function of movement speed. Our findings suggest that specific combinations of required movement frequency and amplitude give rise to two distinct types of movements: one of a more rhythmic nature, and the other of a more discrete nature

    The Impact of Case Diagnosis Coverage and Diagnosis Delays on the Effectiveness of Antiviral Strategies in Mitigating Pandemic Influenza A/H1N1 2009

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    BACKGROUND: Neuraminidase inhibitors were used to reduce the transmission of pandemic influenza A/H1N1 2009 at the early stages of the 2009/2010 pandemic. Policies for diagnosis of influenza for the purposes of antiviral intervention differed markedly between and within countries, leading to differences in the timing and scale of antiviral usage. METHODOLOGY/PRINCIPAL FINDINGS: The impact of the percentage of symptomatic infected individuals who were diagnosed, and of delays to diagnosis, for three antiviral intervention strategies (each with and without school closure) were determined using a simulation model of an Australian community. Epidemic characteristics were based on actual data from the A/H1N1 2009 pandemic including reproduction number, serial interval and age-specific infection rate profile. In the absence of intervention an illness attack rate (AR) of 24.5% was determined from an estimated R(0) of 1.5; this was reduced to 21%, 16.5% or 13% by treatment-only, treatment plus household prophylaxis, or treatment plus household plus extended prophylaxis antiviral interventions respectively, assuming that diagnosis occurred 24 hours after symptoms arose and that 50% of symptomatic cases were diagnosed. If diagnosis occurred without delay, ARs decreased to 17%, 12.2% or 8.8% respectively. If 90% of symptomatic cases were diagnosed (with a 24 hour delay), ARs decreased to 17.8%, 11.1% and 7.6%, respectively. CONCLUSION: The ability to rapidly diagnose symptomatic cases and to diagnose a high proportion of cases was shown to improve the effectiveness of all three antiviral strategies. For epidemics with R(0)< = 1.5 our results suggest that when the case diagnosis coverage exceeds ∼70% the size of the antiviral stockpile required to implement the extended prophylactic strategy decreases. The addition of at least four weeks of school closure was found to further reduce cumulative and peak attack rates and the size of the required antiviral stockpile

    Analysis of the effectiveness of interventions used during the 2009 A/H1N1 influenza pandemic

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    <p>Abstract</p> <p>Background</p> <p>Following the emergence of the A/H1N1 2009 influenza pandemic, public health interventions were activated to lessen its potential impact. Computer modelling and simulation can be used to determine the potential effectiveness of the social distancing and antiviral drug therapy interventions that were used at the early stages of the pandemic, providing guidance to public health policy makers as to intervention strategies in future pandemics involving a highly pathogenic influenza strain.</p> <p>Methods</p> <p>An individual-based model of a real community with a population of approximately 30,000 was used to determine the impact of alternative interventions strategies, including those used in the initial stages of the 2009 pandemic. Different interventions, namely school closure and antiviral strategies, were simulated in isolation and in combination to form different plausible scenarios. We simulated epidemics with reproduction numbers R<sub>0</sub>of 1.5, which aligns with estimates in the range 1.4-1.6 determined from the initial outbreak in Mexico.</p> <p>Results</p> <p>School closure of 1 week was determined to have minimal effect on reducing overall illness attack rate. Antiviral drug treatment of 50% of symptomatic cases reduced the attack rate by 6.5%, from an unmitigated rate of 32.5% to 26%. Treatment of diagnosed individuals combined with additional household prophylaxis reduced the final attack rate to 19%. Further extension of prophylaxis to close contacts (in schools and workplaces) further reduced the overall attack rate to 13% and reduced the peak daily illness rate from 120 to 22 per 10,000 individuals. We determined the size of antiviral stockpile required; the ratio of the required number of antiviral courses to population was 13% for the treatment-only strategy, 25% for treatment and household prophylaxis and 40% for treatment, household and extended prophylaxis. Additional simulations suggest that coupling school closure with the antiviral strategies further reduces epidemic impact.</p> <p>Conclusions</p> <p>These results suggest that the aggressive use of antiviral drugs together with extended school closure may substantially slow the rate of influenza epidemic development. These strategies are more rigorous than those actually used during the early stages of the relatively mild 2009 pandemic, and are appropriate for future pandemics that have high morbidity and mortality rates.</p

    Controlling epidemic spread by social distancing: Do it well or not at all

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    BACKGROUND: Existing epidemiological models have largely tended to neglect the impact of individual behaviour on the dynamics of diseases. However, awareness of the presence of illness can cause people to change their behaviour by, for example, staying at home and avoiding social contacts. Such changes can be used to control epidemics but they exact an economic cost. Our aim is to study the costs and benefits of using individual-based social distancing undertaken by healthy individuals as a form of control.METHODS: Our model is a standard SIR model superimposed on a spatial network, without and with addition of small-world interactions. Disease spread is controlled by allowing susceptible individuals to temporarily reduce their social contacts in response to the presence of infection within their local neighbourhood. We ascribe an economic cost to the loss of social contacts, and weigh this against the economic benefit gained by reducing the impact of the epidemic. We study the sensitivity of the results to two key parameters, the individuals' attitude to risk and the size of the awareness neighbourhood.RESULTS: Depending on the characteristics of the epidemic and on the relative economic importance of making contacts versus avoiding infection, the optimal control is one of two extremes: either to adopt a highly cautious control, thereby suppressing the epidemic quickly by drastically reducing contacts as soon as disease is detected; or else to forego control and allow the epidemic to run its course. The worst outcome arises when control is attempted, but not cautiously enough to cause the epidemic to be suppressed. The next main result comes from comparing the size of the neighbourhood of which individuals are aware to that of the neighbourhood within which transmission can occur. The control works best when these sizes match and is particularly ineffective when the awareness neighbourhood is smaller than the infection neighbourhood. The results are robust with respect to inclusion of long-range, small-world links which destroy the spatial structure, regardless of whether individuals can or cannot control them. However, addition of many non-local links eventually makes control ineffective.CONCLUSIONS: These results have implications for the design of control strategies using social distancing: a control that is too weak or based upon inaccurate knowledge, may give a worse outcome than doing nothing

    Simulation suggests that rapid activation of social distancing can arrest epidemic development due to a novel strain of influenza

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    <p>Abstract</p> <p>Background</p> <p>Social distancing interventions such as school closure and prohibition of public gatherings are present in pandemic influenza preparedness plans. Predicting the effectiveness of intervention strategies in a pandemic is difficult. In the absence of other evidence, computer simulation can be used to help policy makers plan for a potential future influenza pandemic. We conducted simulations of a small community to determine the magnitude and timing of activation that would be necessary for social distancing interventions to arrest a future pandemic.</p> <p>Methods</p> <p>We used a detailed, individual-based model of a real community with a population of approximately 30,000. We simulated the effect of four social distancing interventions: school closure, increased isolation of symptomatic individuals in their household, workplace nonattendance, and reduction of contact in the wider community. We simulated each of the intervention measures in isolation and in several combinations; and examined the effect of delays in the activation of interventions on the final and daily attack rates.</p> <p>Results</p> <p>For an epidemic with an R<sub>0 </sub>value of 1.5, a combination of all four social distancing measures could reduce the final attack rate from 33% to below 10% if introduced within 6 weeks from the introduction of the first case. In contrast, for an R<sub>0 </sub>of 2.5 these measures must be introduced within 2 weeks of the first case to achieve a similar reduction; delays of 2, 3 and 4 weeks resulted in final attack rates of 7%, 21% and 45% respectively. For an R<sub>0 </sub>of 3.5 the combination of all four measures could reduce the final attack rate from 73% to 16%, but only if introduced without delay; delays of 1, 2 or 3 weeks resulted in final attack rates of 19%, 35% or 63% respectively. For the higher R<sub>0 </sub>values no single measure has a significant impact on attack rates.</p> <p>Conclusion</p> <p>Our results suggest a critical role of social distancing in the potential control of a future pandemic and indicate that such interventions are capable of arresting influenza epidemic development, but only if they are used in combination, activated without delay and maintained for a relatively long period.</p

    The systematicity challenge to anti-representational dynamicism

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    After more than twenty years of representational debate in the cognitive sciences, anti-representational dynamicism may be seen as offering a rival and radically new kind of explanation of systematicity phenomena. In this paper, I argue that, on the contrary, anti-representational dynamicism must face a version of the old systematicity challenge: either it does not explain systematicity, or else, it is just an implementation of representational theories. To show this, I present a purely behavioral and representation-free account of systematicity. I then consider a case of insect sensorimotor systematic behavior: communicating behavior in honey bees. I conclude that anti-representational dynamicism fails to capture the fundamental trait of systematic behaviors qua systematic, i.e., their involving exercises of the same behavioral capacities. I suggest, finally, a collaborative strategy in pursuit of a rich and powerful account of this central phenomenon of high cognition at all levels of explanation, including the representational level
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