1,265 research outputs found

    The origins of a new Trypanosoma brucei rhodesiense sleeping sickness outbreak in eastern Uganda.

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    BACKGROUND: Sleeping sickness, caused by two trypanosome subspecies, Trypanosoma brucei gambiense and Trypanosoma brucei rhodesiense, is a parasitic disease transmitted by the tsetse fly in sub-Saharan Africa. We report on a recent outbreak of T b rhodesiense sleeping sickness outside the established south-east Ugandan focus, in Soroti District where the disease had previously been absent. Soroti District has been the subject of large-scale livestock restocking activities and, because domestic cattle are important reservoirs of T b rhodesiense, we investigated the role of cattle in the origins of the outbreak. METHODS: We identified the origins of cattle entering the outbreak area in the 4 years preceding the outbreak. A matched case-control study was conducted to assess whether the distance of villages from the main market involved with restocking was a risk factor for sleeping sickness. We investigated the spatial clustering of sleeping sickness cases at the start of the outbreak. FINDINGS: Over 50% (1510 of 2796) of cattle traded at the market were reported to have originated from endemic sleeping sickness areas. The case-control study revealed that distance to the cattle market was a highly significant risk factor for sleeping sickness (p<0.001) and that there was a significant clustering of cases (27 of 28) close to the market at the start of the outbreak (p<0.001). As the outbreak progressed, the average distance of cases moved away from the cattle market (0.014 km per day, 95% CI 0.008-0.020 km per day, p<0.001). INTERPRETATIONS: The results are consistent with the disease being introduced by cattle infected with T b rhodesiense imported to the market from the endemic sleeping sickness focus. The subsequent spread of the disease away from the market suggests that sleeping sickness is becoming established in this new focus. Public health measures directed at controlling the infection in the animal reservoir should be considered to prevent the spread of sleeping sickness

    Modelling the impact of curtailing antibiotic usage in food animals on antibiotic resistance in humans

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    Effect of curtailing antibiotic consumption in human

    Failure of vaccination to prevent outbreaks of foot-and-mouth disease

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    Outbreaks of foot-and-mouth disease persist in dairy cattle herds in Saudi Arabia despite revaccination at intervals of 4-6 months. Vaccine trials provide data on antibody responses following vaccination. Using this information we developed a mathematical model of the decay of protective antibodies with which we estimated the fraction of susceptible animals at a given time after vaccination. The model describes the data well, suggesting over 95% take with an antibody half-life of 43 days. Farm records provided data on the time course of five outbreaks. We applied a 'SLIR' epidemiological model to these data, fitting a single parameter representing disease transmission rate. The analysis provides estimates of the basic reproduction number R(0), which may exceed 70 in some cases. We conclude that the critical intervaccination interval which would provide herd immunity against FMDV is unrealistically short, especially for heterologous challenge. We suggest that it may not be possible to prevent foot-and-mouth disease outbreaks on these farms using currently available vaccines

    Computational Fluid Dynamic Studies of Vortex Amplifier Design for the Nuclear Industry—II. Transient Conditions

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    In this paper computational fluid dynamics (CFD) techniques have been used to investigate the effect of changes to the geometry of a vortex amplifier (VXA) in the context of glovebox operations in the nuclear industry. These investigations were required because of anomalous behavior identified when, for operational reasons, a long-established VXA design was reduced in scale. The study simulates the transient aspects of two effects: back-flow into the glovebox through the VXA supply ports, and the precessing vortex core in the amplifier outlet. A temporal convergence error study indicates that there is little to be gained from reducing the time step duration below 0.1 ms. Based upon this criterion, the results of the simulation show that the percentage imbalance in the domain was well below the required figure of 1, and imbalances for momentum in all three axes were all below measurable values. Furthermore, there was no conclusive evidence of periodicity in the flow perturbations at the glovebox boundary, although good evidence of periodicity in the device itself and in the outlet pipe was seen. Under all conditions the modified geometry performed better than the control geometry with regard to aggregate reversed supply flow. The control geometry exhibited aggregate nonaxisymmetric supply port back-flow for almost all of the simulated period, unlike the alternative geometry for which the flow through the supply ports was positive, although still nonaxisymmetric, for most of the period. The simulations show how transient flow structures in the supply ports can cause flow to be reversed in individual ports, whereas aggregate flow through the device remains positive. Similar to the supply ports, flow through the outlet of the VXA under high swirl conditions is also nonaxisymmetric. A time-dependent reverse flow region was observed in both the outlet and the diffuser. It is possible that small vortices in the outlet, coupled with the larger vortex in the chamber, are responsible for the oscillations, which cause the shift in the axis of the precessing vortex core (and ultimately in the variations of mass flow in the individual supply ports). Field trials show that the modified geometry reduces the back-flow of oxygen into the glovebox by as much as 78. At purge rates of 0.65 m 3h the modified geometry was found to be less effective, the rate of leakage from the VXA increasing by 16-20. Despite this reduced performance, leakage from the modified geometry was still 63 less than the control geometry. © 2012 American Society of Mechanical Engineers

    How to make predictions about future infectious disease risks

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    Formal, quantitative approaches are now widely used to make predictions about the likelihood of an infectious disease outbreak, how the disease will spread, and how to control it. Several well-established methodologies are available, including risk factor analysis, risk modelling and dynamic modelling. Even so, predictive modelling is very much the ‘art of the possible’, which tends to drive research effort towards some areas and away from others which may be at least as important. Building on the undoubted success of quantitative modelling of the epidemiology and control of human and animal diseases such as AIDS, influenza, foot-and-mouth disease and BSE, attention needs to be paid to developing a more holistic framework that captures the role of the underlying drivers of disease risks, from demography and behaviour to land use and climate change. At the same time, there is still considerable room for improvement in how quantitative analyses and their outputs are communicated to policy makers and other stakeholders. A starting point would be generally accepted guidelines for ‘good practice’ for the development and the use of predictive models

    Explaining Observed Infection and Antibody Age-Profiles in Populations with Urogenital Schistosomiasis

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    Urogenital schistosomiasis is a tropical disease infecting more than 100 million people in sub-Saharan Africa. Individuals in endemic areas endure repeated infections with long-lived schistosome worms, and also encounter larval and egg stages of the life cycle. Protective immunity against infection develops slowly with age. Distinctive age-related patterns of infection and specific antibody responses are seen in endemic areas, including an infection ‘peak shift’ and a switch in the antibody types produced. Deterministic models describing changing levels of infection and antibody with age in homogeneously exposed populations were developed to identify the key mechanisms underlying the antibody switch, and to test two theories for the slow development of protective immunity: that (i) exposure to dying (long-lived) worms, or (ii) experience of a threshold level of antigen, is necessary to stimulate protective antibody. Different model structures were explored, including alternative stages of the life cycle as the main antigenic source and the principal target of protective antibody, different worm survival distributions, antigen thresholds and immune cross-regulation. Models were identified which could reproduce patterns of infection and antibody consistent with field data. Models with dying worms as the main source of protective antigen could reproduce all of these patterns, but so could some models with other continually-encountered life stages acting as the principal antigen source. An antigen threshold enhanced the ability of the model to replicate these patterns, but was not essential for it to do so. Models including either non-exponential worm survival or cross-regulation were more likely to be able to reproduce field patterns, but neither of these was absolutely required. The combination of life cycle stage stimulating, and targeted by, antibody was found to be critical in determining whether models could successfully reproduce patterns in the data, and a number of combinations were excluded as being inconsistent with field data
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