35 research outputs found

    Mechanisms of Avian Influenza virus transmission between farms: combining data collection and mathematical modelling

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    The lack of sufficient knowledge on the mechanisms of between-farm spread of livestock diseases hampers the development of much needed effective and fast control strategies. Some of the mechanisms responsible for pathogen spread can be deduced from epidemic tracing reports and literature while others can only be hypothesized from findings of studies on daily farm practices throughout the production round. For outbreaks without known/traced transmission routes, the concept of ‘neighbourhood’ infection is often adopted. This concept was founded based on the distance-dependence of the transmission risk with geographical proximity to an infectious farm being the key determinant of risk. Mathematical modelling plays an important role in obtaining quantitative insights into the contributions of the different mechanisms to disease spread. This can be by ranking the contributions of the individual transmission routes and/or obtaining a generic distance-dependent transmission risk. The models can guide the design of control strategies by providing a means to assess the efficacy of intervention strategies. In this thesis, modelling was used to assess the contributions of the wind-borne route and the other (traced) between-farm contacts to the transmission of highly pathogenic avian influenza during an epidemic in the Netherlands in 2003. It was found that these two routes together could only explain approximately 31% of the infections/cases. Visits by epidemic control teams were the least risky indicating the effectiveness of their biosecurity protocols in preventing transmission. New data on day-to-day farm practices and farmer opinion was collected in an attempt to generate hypotheses on transmission pathways and mechanisms that were yet to be appreciated. Indeed relevant unappreciated practices were found. They include irregularities in compliance to biosecurity as well as a broad category of neighbourhood-related risks. A new modelling approach to study neighbourhood transmission was developed guided by indirect transmission experiments. It involves the approximation of the pathogen dispersal process by a diffusive transport mechanism. Applying this diffusion model to the outbreak data of 2003, it was found that assuming delayed transmission, as opposed to instantaneous transmission, is an important phenomenon to be considered when modelling disease spread between locations. This modelling approach has the added advantage of availing an opportunity to assess the performance of intervention strategies without detailed mechanism-specific information. </p

    Modelling the wind-borne spread of highly pathogenic avian influenza virus between farms

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    A quantitative understanding of the spread of contaminated farm dust between locations is a prerequisite for obtaining much-needed insight into one of the possible mechanisms of disease spread between farms. Here, we develop a model to calculate the quantity of contaminated farm-dust particles deposited at various locations downwind of a source farm and apply the model to assess the possible contribution of the wind-borne route to the transmission of Highly Pathogenic Avian Influenza virus (HPAI) during the 2003 epidemic in the Netherlands. The model is obtained from a Gaussian Plume Model by incorporating the dust deposition process, pathogen decay, and a model for the infection process on exposed farms. Using poultry- and avian influenza-specific parameter values we calculate the distance-dependent probability of between-farm transmission by this route. A comparison between the transmission risk pattern predicted by the model and the pattern observed during the 2003 epidemic reveals that the wind-borne route alone is insufficient to explain the observations although it could contribute substantially to the spread over short distance ranges, for example, explaining 24% of the transmission over distances up to 25 km

    Estimating the per-contact probability of infection by highly pathogenic avian influenza (H7N7) virus during the 2003 epidemic in the Netherlands.

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    Estimates of the per-contact probability of transmission between farms of Highly Pathogenic Avian Influenza virus of H7N7 subtype during the 2003 epidemic in the Netherlands are important for the design of better control and biosecurity strategies. We used standardized data collected during the epidemic and a model to extract data for untraced contacts based on the daily number of infectious farms within a given distance of a susceptible farm. With these data, we used a maximum likelihood estimation approach to estimate the transmission probabilities by the individual contact types, both traced and untraced. The estimated conditional probabilities, conditional on the contact originating from an infectious farm, of virus transmission were: 0.000057 per infectious farm within 1 km per day, 0.000413 per infectious farm between 1 and 3 km per day, 0.0000895 per infectious farm between 3 and 10 km per day, 0.0011 per crisis organisation contact, 0.0414 per feed delivery contact, 0.308 per egg transport contact, 0.133 per other-professional contact and, 0.246 per rendering contact. We validate these outcomes against literature data on virus genetic sequences for outbreak farms. These estimates can be used to inform further studies on the role that improved biosecurity between contacts and/or contact frequency reduction can play in eliminating between-farm spread of the virus during future epidemics. The findings also highlight the need to; 1) understand the routes underlying the infections without traced contacts and, 2) to review whether the contact-tracing protocol is exhaustive in relation to all the farm’s day-to-day activities and practices

    Оксид азота и нитритные ионы в энергетике нейронов мозжечка

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    Зниження вмісту АТФ в нейронах при гіпоксії мозку і гіперстимуляції глутаматних рецепторів здатне порушити систему внутри і міжклітинної сигналізації в нейронах мозку, зокрема іонний обмін, активність ферментів гліколізу і окислювального фосфорилірування, захоплення Са2+ мітохондріями і синтез білків. В даній роботі вивчали дію ендогенного глутамат індукованого NO і дію екзогенний доданих донорів NO – нітриту натрію (NaNO2) і нітрозоцистеїну (SNOC) на вміст АТФ в 7-8 денних культивованих нейронах мозочка.Decrease of content ATPA in neurones at a hypoxia of a brain and a hyperstimulation глутаматных receptors is capable to break system inside and the intercellular signal ystem in neurones of a brain, in particular an ion exchange, activity of enzymes of glycolysis and oxidative phosphorylation, seizure Са 2+ mitochondrions and synthesis of proteins. In the given work studied action endogenic glutamate inducted NO and action of exogenous padding donors NO diazotizing salt (NaNO2) and нитрозоцистеина (SNOC) on content ATPA in 7 8 diurnal cultivated{incubated} neurones of a cerebellum

    A model of population dynamics of TB in a prison system and application to South Africa

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    BACKGROUND: Tuberculosis (TB) continues to spread in South African prisons in particular, as prisons are over-capacitated and have poor ventilation. The awaiting trial detainees are not screened on admission and are at high risk of getting infected with TB. RESULTS: We propose a compartmental model to describe the population dynamics of TB disease in prisons. Our model considers the inflow of susceptible, exposed and TB infectives into the prison population. Removal of individuals out of the prison population can be either by death or by being released from prison, as compared to a general population in which removal is only by death. We describe conditions, including non-inflow of infectives into the prison, which will ensure that TB can be eradicated from the prison population. The model is calibrated for the South African prison system, by using data in existing literature. The model can be used to make quantitative projections of TB prevalence and to measure the effect of interventions. Illustrative simulations in this regard are presented. The model can be used for other prison populations too, if data is available to calculate the model parameters. CONCLUSIONS: Various simulations generated with our model serve to illustrate how it can be utilized in making future projections of the levels of prevalence of TB, and to quantify the effect of interventions such as screening, treatment or reduction of transmission parameter values through improved living conditions for inmates. This makes it particularly useful as there are various targets set by the World Health Organization and by governments, for reduction of TB prevalence and ultimately its eradication. Towards eradication of TB from a prison system, the theorem on global stability of the disease-free state is a useful indicator

    Mathematical modelling of the transmission dynamics of contagious bovine pleuropneumonia reveals minimal target profiles for improved vaccines and diagnostic assays

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    Contagious bovine pleuropneumonia (CBPP) is a cattle disease that has hampered the development of the livestock sector in sub-Saharan Africa. Currently, vaccination with a live vaccine strain is its recommended control measure although unofficial antimicrobial use is widely practiced. Here, modelling techniques are used to assess the potential impact of early elimination of infected cattle via accurate diagnosis on CBPP dynamics. A herd-level stochastic epidemiological model explicitly incorporating test sensitivity and specificity is developed. Interventions by annual vaccination, annual testing and elimination and a combination of both are implemented in a stepwise manner and their effectiveness compared by running 1000 simulations per intervention over ten years. The model predicts that among the simulated interventions, the ones likely to eliminate the disease from an isolated herd all involved annual vaccination of more than 75% of the animals with a vaccine that protects for at least 18 months combined with annual testing (and elimination of positive reactors) of 75% of the animals every six months after vaccination. The highest probability of disease elimination was 97.5% and this could occur within a median of 2.3 years. Generally, our model predicts that regular testing and elimination of positive reactors using improved tests will play a significant role in minimizing CBPP burden especially in the current situation where improved vaccines are yet to be developed
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