199 resultados para Communicable diseases Mathematical models


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There are limited community-based data on the burden of influenza and influenza-like illnesses during pregnancy to inform disease surveillance and control. We aimed to determine the incidence of medically-attended respiratory illnesses (MARI) in pregnant women and the proportion of women who are tested for respiratory pathogens at these visits. We conducted a nested retrospective cohort study of a non-random sample of women aged ≥18 years who had a live birth in maternity units in Brisbane, Queensland, from March 2012 to October 2014. The primary outcomes were self-reported doctor visits for MARI and laboratory investigations for respiratory pathogens. Descriptive analyses were performed. Among 1202 participants, 222 (18.5%, 95%CI 16.3%-20.7%) self-reported MARI during their pregnancy. Of those with an MARI, 20.3% (45/222) self-reported a laboratory test was performed. We were able to confirm with health service providers that 46.7% (21/45) of tests were undertaken, responses from providers were not received for the remainder. Whilst one in five women in this population reported a MARI in pregnancy, only 3.7% (45/1202) reported a clinical specimen had been arranged at the consultation and the ability to validate that self-report was problematic. As the focus on maternal immunisation increases, ascertainment of the aetiological agent causing MARI in this population will be required and efficient and reliable methods for obtaining those data at the community level need to be established.

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This thesis develops comprehensive mathematical models for an advanced drying technology Intermittent Microwave Convective Drying (IMCD). The models provide an improved physical understanding of the heat and mass transport during the drying process, which will help to improve the quality of dried food and energy efficiency of the process, as well as will increase the ability of automation and optimization. The final model in this thesis represents the most comprehensive fundamental multiphase model for IMCD that considers 3D electromagnetics coupled with multiphase porous media transport processes. The 3D electromagnetics considers Maxwell's equation and multiphase transport model considers three different phases: solid matrix, liquid water and gas consisting water vapour and air. The multiphase transport includes pressure-driven flow, capillary diffusion, binary diffusion, and evaporation. The models developed in this thesis were validated with extensive experimental investigations.

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This project developed three mathematical models for scheduling ambulances and ambulance crews and proceeded to solve each model for test scenarios based on real data. Results from these models can serve as decision aids for dispatching or relocating ambulances; and for strategic decisions on the ambulance crews needed each shift. This thesis used Flexible Flow Shop Scheduling techniques to formulate strategic, dynamic and real time models. Metaheuristic solutions techniques were applied for a case study with realistic data. These models are suitable for ambulance planners and dispatchers.

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Non-communicable diseases – Matthew Rimmer examines plain packaging as a way to curb tobacco use. Smoking is one of the biggest causes of non-communicable diseases.

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This research investigates how to obtain accurate and reliable positioning results with global navigation satellite systems (GNSS). The work provides a theoretical framework for reliability control in GNSS carrier phase ambiguity resolution, which is the key technique for precise GNSS positioning in centimetre levels. The proposed approach includes identification and exclusion procedures of unreliable solutions and hypothesis tests, allowing the reliability of solutions to be controlled in the aspects of mathematical models, integer estimation and ambiguity acceptance tests. Extensive experimental results with both simulation and observed data sets effectively demonstrate the reliability performance characteristics based on the proposed theoretical framework and procedures.

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Oxygen flux between aquatic ecosystems and the water column is a measure of ecosystem metabolism. However, the oxygen flux varies during the day in a “hysteretic” pattern: there is higher net oxygen production at a given irradiance in the morning than in the afternoon. In this study, we investigated the mechanism responsible for the hysteresis in oxygen flux by measuring the daily pattern of oxygen flux, light, and temperature in a seagrass ecosystem (Zostera muelleri in Swansea Shoals, Australia) at three depths. We hypothesised that the oxygen flux pattern could be due to diel variations in either gross primary production or respiration in response to light history or temperature. Hysteresis in oxygen flux was clearly observed at all three depths. We compared this data to mathematical models, and found that the modification of ecosystem respiration by light history is the best explanation for the hysteresis in oxygen flux. Light history-dependent respiration might be due to diel variations in seagrass respiration or the dependence of bacterial production on dissolved organic carbon exudates. Our results indicate that the daily variation in respiration rate may be as important as the daily changes of photosynthetic characteristics in determining the metabolic status of aquatic ecosystems.

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The causes of autoimmune diseases have yet to be fully elucidated. Autoantibodies, autoreactive T cell responses, the presence of a predisposing major histocompatibility complex (MHC) haplotype and responsiveness to corticosteroids are features, and some are possibly contributory causes of autoimmune disease. The most challenging question is how autoimmune diseases are triggered. Molecular mimicry of host cell determinants by epitopes of infectious agents with ensuing cross-reactivity is one of the most popular yet still controversial theories for the initiation of autoimmune diseases [1]. Throughout the 1990s, hundreds of research articles focusing to various extents on epitope mimicry, as it is more accurately described in an immunological context, were published annually. Many of these articles presented data that were consistent with the hypothesis of mimicry but that did not actually prove the theory. Other equally convincing reports indicated that epitope mimicry was not the cause of the autoimmune disease despite sequence similarity between molecules of infectious agents and the host. Some 20 years ago, Rothman [2] proposed a model for disease causation and I have used this as a framework to examine the role of epitope mimicry in the development of autoimmune disease. The thesis of Rothman’s model is that an effect, in this instance autoimmune disease, arises as a result of a cause. In most cases, multiple-component causes contribute synergistically to yield the effect, and each of these components alone is insufficient as a cause. Logically, some component causes, such as the presence of a particular autoimmune response, are also necessary causes.

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Introduction The epidemic of nutrition related non-communicable diseases such as type 2 diabetes mellitus and obesity has reached to epidemic portion in the Sri Lanka. However, to date, detailed data on food consumption in the Sri Lankan population is limited. The aim of this study is to identify energy and major nutrient intake among Sri Lankan adults. Methods A nationally-representative sample of adults was selected using a multi-stage random cluster sampling technique. Results Data from 463 participants (166 Males, 297 Females) were analyzed. Total energy intake was significantly higher in males (1913 ± 567 kcal/d) than females (1514 ± 458 kcal/d). However, there was no significant gender differences in the percentage of energy from carbohydrate (Male: 72.8 ± 6.4%, Female: 73.9 ± 6.7%), fat (Male: 19.9 ± 6.1%, Female: 18.5 ± 5.7%) and proteins (Male: 10.6 ± 2.1%, Female: 10.9 ± 5.6%). Conclusion The present study provides the first national estimates of energy and nutrient intake of the Sri Lankan adult population.

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Embryonic development involves diffusion and proliferation of cells, as well as diffusion and reaction of molecules, within growing tissues. Mathematical models of these processes often involve reaction–diffusion equations on growing domains that have been primarily studied using approximate numerical solutions. Recently, we have shown how to obtain an exact solution to a single, uncoupled, linear reaction–diffusion equation on a growing domain, 0 < x < L(t), where L(t) is the domain length. The present work is an extension of our previous study, and we illustrate how to solve a system of coupled reaction–diffusion equations on a growing domain. This system of equations can be used to study the spatial and temporal distributions of different generations of cells within a population that diffuses and proliferates within a growing tissue. The exact solution is obtained by applying an uncoupling transformation, and the uncoupled equations are solved separately before applying the inverse uncoupling transformation to give the coupled solution. We present several example calculations to illustrate different types of behaviour. The first example calculation corresponds to a situation where the initially–confined population diffuses sufficiently slowly that it is unable to reach the moving boundary at x = L(t). In contrast, the second example calculation corresponds to a situation where the initially–confined population is able to overcome the domain growth and reach the moving boundary at x = L(t). In its basic format, the uncoupling transformation at first appears to be restricted to deal only with the case where each generation of cells has a distinct proliferation rate. However, we also demonstrate how the uncoupling transformation can be used when each generation has the same proliferation rate by evaluating the exact solutions as an appropriate limit.

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The 51st ANZIAM Conference was held on 1–5 February 2015 in the Outrigger Hotel, Surfers Paradise, Australia. A total of 229 people registered for the conference, with nine plenary presentations, 78 student presentations and 107 non-student presentations. Highlights of the conference included the plenary talks, presentations by the 2014 Michell and ANZIAM Medalists, the Women in Mathematics Lunch and the Conference Dinner and Awards Ceremony. The main conference was followed by a one-day workshop entitled ‘Discrete mathematical models in the life sciences’, held at Queensland University of Technology, Brisbane, on February 6, 2015.

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Many processes during embryonic development involve transport and reaction of molecules, or transport and proliferation of cells, within growing tissues. Mathematical models of such processes usually take the form of a reaction-diffusion partial differential equation (PDE) on a growing domain. Previous analyses of such models have mainly involved solving the PDEs numerically. Here, we present a framework for calculating the exact solution of a linear reaction-diffusion PDE on a growing domain. We derive an exact solution for a general class of one-dimensional linear reaction—diffusion process on 0

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Mathematical models describing the movement of multiple interacting subpopulations are relevant to many biological and ecological processes. Standard mean-field partial differential equation descriptions of these processes suffer from the limitation that they implicitly neglect to incorporate the impact of spatial correlations and clustering. To overcome this, we derive a moment dynamics description of a discrete stochastic process which describes the spreading of distinct interacting subpopulations. In particular, we motivate our model by mimicking the geometry of two typical cell biology experiments. Comparing the performance of the moment dynamics model with a traditional mean-field model confirms that the moment dynamics approach always outperforms the traditional mean-field approach. To provide more general insight we summarise the performance of the moment dynamics model and the traditional mean-field model over a wide range of parameter regimes. These results help distinguish between those situations where spatial correlation effects are sufficiently strong, such that a moment dynamics model is required, from other situations where spatial correlation effects are sufficiently weak, such that a traditional mean-field model is adequate.

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A recent study by Korolev et al. [Nat. Rev. Cancer, 14:371–379, 2014] evidences that the Allee effect—in its strong form, the requirement of a minimum density for cell growth—is important in the spreading of cancerous tumours. We present one of the first mathematical models of tumour invasion that incorporates the Allee effect. Based on analysis of the existence of travelling wave solutions to this model, we argue that it is an improvement on previous models of its kind. We show that, with the strong Allee effect, the model admits biologically relevant travelling wave solutions, with well-defined edges. Furthermore, we uncover an experimentally observed biphasic relationship between the invasion speed of the tumour and the background extracellular matrix density.

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This presentation outlines recent achievements in development of tools, protocols and methods to monitoring and benchmark food prices and affordability globally under International Network for Food and Obesity/non-communicable diseases Research, Monitoring and Action Support(INFORMAS)

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Unhealthy diets contribute at least 14% to Australia's disease burden and are driven by ‘obesogenic’ food environments. Compliance with dietary recommendations is particularly poor amongst disadvantaged populations including low socioeconomic groups, those living in rural/remote areas and Aboriginal and Torres Strait Islanders. The perception that healthy foods are expensive is a key barrier to healthy choices and a major determinant of diet-related health inequities. Available state/regional/local data (limited and non-comparable) suggests that, despite basic healthy foods not incurring GST, the cost of healthy food is higher and has increased more rapidly than unhealthy food over the last 15 years in Australia. However, there were no nationally standardised tools or protocols to benchmark, compare or monitor food prices and affordability in Australia. Globally, we are leading work to develop and test approaches to assess the price differential of healthy and less-healthy (current) diets under the food price module of the International Network for Food and Obesity/non-communicable diseases (NCDs) Research, Monitoring and Action Support (INFORMAS). This presentation describes contextualization of the INFORMAS approach to develop standardised Australian tools, survey protocols and data collection and analysis systems. The ‘healthy diet basket’ was based on the Australian Foundation Diet, 1 The ‘current diet basket’ and specific items included in each basket, were based on recent national dietary survey data.2 Data collection methods were piloted. The final tools and protocols were then applied to measure the price and affordability of healthy and less healthy (current) diets of different household groups in diverse communities across the nation. We have compared results for different geographical locations/population subgroups in Australia and assessed these against international INFORMAS benchmarks. The results inform the development of policy and practice, including those relevant to mooted changes to the GST base, to promote nutrition and healthy weight and prevent chronic disease in Australia.