31 research outputs found

    Influenza A Gradual and Epochal Evolution: Insights from Simple Models

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    The recurrence of influenza A epidemics has originally been explained by a “continuous antigenic drift” scenario. Recently, it has been shown that if genetic drift is gradual, the evolution of influenza A main antigen, the haemagglutinin, is punctuated. As a consequence, it has been suggested that influenza A dynamics at the population level should be approximated by a serial model. Here, simple models are used to test whether a serial model requires gradual antigenic drift within groups of strains with the same antigenic properties (antigenic clusters). We compare the effect of status based and history based frameworks and the influence of reduced susceptibility and infectivity assumptions on the transient dynamics of antigenic clusters. Our results reveal that the replacement of a resident antigenic cluster by a mutant cluster, as observed in data, is reproduced only by the status based model integrating the reduced infectivity assumption. This combination of assumptions is useful to overcome the otherwise extremely high model dimensionality of models incorporating many strains, but relies on a biological hypothesis not obviously satisfied. Our findings finally suggest the dynamical importance of gradual antigenic drift even in the presence of punctuated immune escape. A more regular renewal of susceptible pool than the one implemented in a serial model should be part of a minimal theory for influenza at the population level

    Combined artificial bee colony algorithm and machine learning techniques for prediction of online consumer repurchase intention

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    A novel paradigm in the service sector i.e. services through the web is a progressive mechanism for rendering offerings over diverse environments. Internet provides huge opportunities for companies to provide personalized online services to their customers. But prompt novel web services introduction may unfavorably affect the quality and user gratification. Subsequently, prediction of the consumer intention is of supreme importance in selecting the web services for an application. The aim of study is to predict online consumer repurchase intention and to achieve this objective a hybrid approach which a combination of machine learning techniques and Artificial Bee Colony (ABC) algorithm has been used. The study is divided into three phases. Initially, shopping mall and consumer characteristic’s for repurchase intention has been identified through extensive literature review. Secondly, ABC has been used to determine the feature selection of consumers’ characteristics and shopping malls’ attributes (with > 0.1 threshold value) for the prediction model. Finally, validation using K-fold cross has been employed to measure the best classification model robustness. The classification models viz., Decision Trees (C5.0), AdaBoost, Random Forest (RF), Support Vector Machine (SVM) and Neural Network (NN), are utilized for prediction of consumer purchase intention. Performance evaluation of identified models on training-testing partitions (70-30%) of the data set, shows that AdaBoost method outperforms other classification models with sensitivity and accuracy of 0.95 and 97.58% respectively, on testing data set. This study is a revolutionary attempt that considers both, shopping mall and consumer characteristics in examine the consumer purchase intention.N/

    Cost-effectiveness of insulin analogs from the perspective of the Brazilian public health system

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    ABSTRACT Human insulin is provided by the Brazilian Public Health System (BPHS) for the treatment of diabetes, however, legal proceedings to acquire insulin analogs have burdened the BPHS health system. The aim of this study was to perform a cost-effectiveness analysis to compare insulin analogs and human insulins. This is a pharmacoeconomic study of cost-effectiveness. The direct medical cost related to insulin extracted from the Ministry of Health drug price list was considered. The clinical results, i.e. reduction in glycated hemoglobin (HbA1c), were extracted by meta-analysis. Different scenarios were structured to measure the uncertainties regarding the costs and reduction in HbA1c. Decision tree was developed for sensitivity of Incremental Cost Effectiveness Ratio (ICER). A total of fifteen scenarios were structured. Given the best-case scenario for the insulin analogs, the insulins aspart, lispro, glargine and detemir showed an ICER of R1,768.59;R 1,768.59; R 3,308.54; R11,718.75andR 11,718.75 and R 2,685.22, respectively. In all scenarios in which the minimum effectiveness was proposed, lispro, glargine and detemir were dominant strategies. Sensitivity analysis showed that the aspart had R3,066.98[95 3,066.98 [95 % CI: 2339.22; 4418.53] and detemir had R 6,163.97 [95% CI: 3919.29; 11401.57] for incremental costs. We concluded there was evidence that the insulin aspart is the most cost-effective

    Guidance to 2018 good practice : ARIA digitally-enabled, integrated, person-centred care for rhinitis and asthma

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    AimsMobile Airways Sentinel NetworK (MASK) belongs to the Fondation Partenariale MACVIA-LR of Montpellier, France and aims to provide an active and healthy life to rhinitis sufferers and to those with asthma multimorbidity across the life cycle, whatever their gender or socio-economic status, in order to reduce health and social inequities incurred by the disease and to improve the digital transformation of health and care. The ultimate goal is to change the management strategy in chronic diseases.MethodsMASK implements ICT technologies for individualized and predictive medicine to develop novel care pathways by a multi-disciplinary group centred around the patients.StakeholdersInclude patients, health care professionals (pharmacists and physicians), authorities, patient's associations, private and public sectors.ResultsMASK is deployed in 23 countries and 17 languages. 26,000 users have registered.EU grants (2018)MASK is participating in EU projects (POLLAR: impact of air POLLution in Asthma and Rhinitis, EIT Health, DigitalHealthEurope, Euriphi and Vigour).Lessons learnt(i) Adherence to treatment is the major problem of allergic disease, (ii) Self-management strategies should be considerably expanded (behavioural), (iii) Change management is essential in allergic diseases, (iv) Education strategies should be reconsidered using a patient-centred approach and (v) Lessons learnt for allergic diseases can be expanded to chronic diseases.Peer reviewe

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

    Allergic Rhinitis and its Impact on Asthma (ARIA) Phase 4 (2018): Change management in allergic rhinitis and asthma multimorbidity using mobile technology

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    Allergic Rhinitis and its Impact on Asthma (ARIA) has evolved from a guideline by using the best approach to integrated care pathways using mobile technology in patients with allergic rhinitis (AR) and asthma multimorbidity. The proposed next phase of ARIA is change management, with the aim of providing an active and healthy life to patients with rhinitis and to those with asthma multimorbidity across the lifecycle irrespective of their sex or socioeconomic status to reduce health and social inequities incurred by the disease. ARIA has followed the 8-step model of Kotter to assess and implement the effect of rhinitis on asthma multimorbidity and to propose multimorbid guidelines. A second change management strategy is proposed by ARIA Phase 4 to increase self-medication and shared decision making in rhinitis and asthma multimorbidity. An innovation of ARIA has been the development and validation of information technology evidence-based tools (Mobile Airways Sentinel Network [MASK]) that can inform patient decisions on the basis of a self-care plan proposed by the health care professional
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