969 resultados para STOCHASTIC CORRECTOR MODEL
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Knowledge on the relative importance of alternative sources of human campylobacteriosis is important in order to implement effective disease prevention measures. The objective of this study was to assess the relative importance of three key exposure pathways (travelling abroad, poultry meat, pet contact) for different patient age groups in Switzerland. With a stochastic exposure model data on Campylobacter incidence for the years 2002-2007 were linked with data for the three exposure pathways and the results of a case-control study. Mean values for the population attributable fractions (PAF) over all age groups and years were 27% (95% CI 17-39) for poultry consumption, 27% (95% CI 22-32) for travelling abroad, 8% (95% CI 6-9) for pet contact and 39% (95% CI 25-50) for other risk factors. This model provided robust results when using data available for Switzerland, but the uncertainties remained high. The output of the model could be improved if more accurate input data are available to estimate the infection rate per exposure. In particular, the relatively high proportion of cases attributed to 'other risk factors' requires further attention.
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In this paper we first show that the gains achievable by integrating pricing and inventory control are usually small for classical demand functions. We then introduce reference price models and demonstrate that for this class of demand functions the benefits of integration with inventory control are substantially increased due to the price dynamics. We also provide some analytical results for this more complex model. We thus conclude that integrated pricing/inventory models could repeat the success of revenue management in practice if reference price effects are included in the demand model and the properties of this new model are better understood.
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OBJECTIVES: Treatment as prevention depends on retaining HIV-infected patients in care. We investigated the effect on HIV transmission of bringing patients lost to follow up (LTFU) back into care. DESIGN: Mathematical model. METHODS: Stochastic mathematical model of cohorts of 1000 HIV-infected patients on antiretroviral therapy (ART), based on data from two clinics in Lilongwe, Malawi. We calculated cohort viral load (CVL; sum of individual mean viral loads each year) and used a mathematical relationship between viral load and transmission probability to estimate the number of new HIV infections. We simulated four scenarios: 'no LTFU' (all patients stay in care); 'no tracing' (patients LTFU are not traced); 'immediate tracing' (after missed clinic appointment); and, 'delayed tracing' (after six months). RESULTS: About 440 of 1000 patients were LTFU over five years. CVL (million copies/ml per 1000 patients) were 3.7 (95% prediction interval [PrI] 2.9-4.9) for no LTFU, 8.6 (95% PrI 7.3-10.0) for no tracing, 7.7 (95% PrI 6.2-9.1) for immediate, and 8.0 (95% PrI 6.7-9.5) for delayed tracing. Comparing no LTFU with no tracing the number of new infections increased from 33 (95% PrI 29-38) to 54 (95% PrI 47-60) per 1000 patients. Immediate tracing prevented 3.6 (95% PrI -3.3-12.8) and delayed tracing 2.5 (95% PrI -5.8-11.1) new infections per 1000. Immediate tracing was more efficient than delayed tracing: 116 and to 142 tracing efforts, respectively, were needed to prevent one new infection. CONCLUSION: Tracing of patients LTFU enhances the preventive effect of ART, but the number of transmissions prevented is small.
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OBJECTIVES Mortality in patients starting antiretroviral therapy (ART) is higher in Malawi and Zambia than in South Africa. We examined whether different monitoring of ART (viral load [VL] in South Africa and CD4 count in Malawi and Zambia) could explain this mortality difference. DESIGN Mathematical modelling study based on data from ART programmes. METHODS We used a stochastic simulation model to study the effect of VL monitoring on mortality over 5 years. In baseline scenario A all parameters were identical between strategies except for more timely and complete detection of treatment failure with VL monitoring. Additional scenarios introduced delays in switching to second-line ART (scenario B) or higher virologic failure rates (due to worse adherence) when monitoring was based on CD4 counts only (scenario C). Results are presented as relative risks (RR) with 95% prediction intervals and percent of observed mortality difference explained. RESULTS RRs comparing VL with CD4 cell count monitoring were 0.94 (0.74-1.03) in scenario A, 0.94 (0.77-1.02) with delayed switching (scenario B) and 0.80 (0.44-1.07) when assuming a 3-times higher rate of failure (scenario C). The observed mortality at 3 years was 10.9% in Malawi and Zambia and 8.6% in South Africa (absolute difference 2.3%). The percentage of the mortality difference explained by VL monitoring ranged from 4% (scenario A) to 32% (scenarios B and C combined, assuming a 3-times higher failure rate). Eleven percent was explained by non-HIV related mortality. CONCLUSIONS VL monitoring reduces mortality moderately when assuming improved adherence and decreased failure rates.
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Time-dependent refractoriness of calcium (Ca2+) release in cardiac myocytes is an important factor in determining whether pro-arrhythmic release patterns develop. At the subcellular level of the Ca2+ spark, recent studies have suggested that recovery of spark amplitude is controlled by local sarcoplasmic reticulum (SR) refilling whereas refractoriness of spark triggering depends on both refilling and the sensitivity of the ryanodine receptor (RyR) release channels that produce sparks. Here we studied regulation of Ca2+ spark refractoriness in mouse ventricular myocytes by examining how β-adrenergic stimulation influenced sequences of Ca2+ sparks originating from individual RyR clusters. Our protocol allowed us to separately measure recovery of spark amplitude and delays between successive sparks, and data were interpreted quantitatively through simulations with a stochastic mathematical model. We found that, compared with spark sequences measured under control conditions: (1) β-adrenergic stimulation with isoproterenol accelerated spark amplitude recovery and decreased spark-to-spark delays; (2) activating protein kinase A (PKA) with forskolin accelerated amplitude recovery but did not affect spark-to-spark delays; (3) inhibiting PKA with H89 retarded amplitude recovery and increased spark- to-spark delays; (4) preventing phosphorylation of the RyR at serine 2808 with a knock-in mouse prevented the decrease in spark-to-spark delays seen with β-adrenergic stimulation; (5) inhibiting either PKA or Ca2+/calmodulin-dependent protein kinase II (CaMKII) during β-adrenergic stimulation prevented the decrease in spark-to-spark delays seen) without inhibition. The results suggest that activation of either PKA or CaMKII is sufficient to speed SR refilling, but activation of both kinases appears necessary to observe increased RyR sensitivity. The data provide novel insight into β-adrenergic regulation of Ca2+ release refractoriness in mouse myocytes.
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Foot-and-mouth disease (FMD) is a highly contagious disease that caused several large outbreaks in Europe in the last century. The last important outbreak in Switzerland took place in 1965/66 and affected more than 900 premises and more than 50,000 animals were slaughtered. Large-scale emergency vaccination of the cattle and pig population has been applied to control the epidemic. In recent years, many studies have used infectious disease models to assess the impact of different disease control measures, including models developed for diseases exotic for the specific region of interest. Often, the absence of real outbreak data makes a validation of such models impossible. This study aimed to evaluate whether a spatial, stochastic simulation model (the Davis Animal Disease Simulation model) can predict the course of a Swiss FMD epidemic based on the available historic input data on population structure, contact rates, epidemiology of the virus, and quality of the vaccine. In addition, the potential outcome of the 1965/66 FMD epidemic without application of vaccination was investigated. Comparing the model outcomes to reality, only the largest 10% of the simulated outbreaks approximated the number of animals being culled. However, the simulation model highly overestimated the number of culled premises. While the outbreak duration could not be well reproduced by the model compared to the 1965/66 epidemic, it was able to accurately estimate the size of the area infected. Without application of vaccination, the model predicted a much higher mean number of culled animals than with vaccination, demonstrating that vaccination was likely crucial in disease control for the Swiss FMD outbreak in 1965/66. The study demonstrated the feasibility to analyze historical outbreak data with modern analytical tools. However, it also confirmed that predicted epidemics from a most carefully parameterized model cannot integrate all eventualities of a real epidemic. Therefore, decision makers need to be aware that infectious disease models are useful tools to support the decision-making process but their results are not equal valuable as real observations and should always be interpreted with caution.
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La vulnerabilidad de los sistemas ganaderos de pastoreo pone en evidencia la necesidad de herramientas para evaluar y mitigar los efectos de la sequía. El avance en la teledetección ha despertado el interés por explotar potenciales aplicaciones, y está dando lugar a un intenso desarrollo de innovaciones en distintos campos. Una de estas áreas es la gestión del riesgo climático, en donde la utilización de índices de vegetación permite la evaluación de la sequía. En esta investigación, se analiza el impacto de la sequía y se evalúa el potencial de nuevas tecnologías como la teledetección para la gestión del riesgo de sequía en sistemas de ganadería extensiva. Para ello, se desarrollan tres aplicaciones: (i) evaluar el impacto económico de la sequía en una explotación ganadera extensiva de la dehesa de Andalucía, (ii) elaborar mapas de vulnerabilidad a la sequía en pastos de Chile y (iii) diseñar y evaluar el potencial de un seguro indexado para sequía en pastos en la región de Coquimbo en Chile. En la primera aplicación, se diseña un modelo dinámico y estocástico que integra aspectos climáticos, ecológicos, agronómicos y socioeconómicos para evaluar el riesgo de sequía. El modelo simula una explotación ganadera tipo de la dehesa de Andalucía para el período 1999-2010. El método de Análisis Histórico y la simulación de MonteCarlo se utilizan para identificar los principales factores de riesgo de la explotación, entre los que destacan, los periodos de inicios del verano e inicios de invierno. Los resultados muestran la existencia de un desfase temporal entre el riesgo climático y riesgo económico, teniendo este último un periodo de duración más extenso en el tiempo. También, revelan que la intensidad, frecuencia y duración son tres atributos cruciales que determinan el impacto económico de la sequía. La estrategia de reducción de la carga ganadera permite aminorar el riesgo, pero conlleva una disminución en el margen bruto de la explotación. La segunda aplicación está dedicada a la elaboración de mapas de vulnerabilidad a la sequia en pastos de Chile. Para ello, se propone y desarrolla un índice de riesgo económico (IRESP) sencillo de interpretar y replicable, que integra factores de riesgo y estrategias de adaptación para obtener una medida del Valor en Riesgo, es decir, la máxima pérdida esperada en un año con un nivel de significación del 5%.La representación espacial del IRESP pone en evidencia patrones espaciales y diferencias significativas en la vulnerabilidad a la sequía a lo largo de Chile. Además, refleja que la vulnerabilidad no siempre esta correlacionada con el riesgo climático y demuestra la importancia de considerar las estrategias de adaptación. Las medidas de autocorrelación espacial revelan que el riesgo sistémico es considerablemente mayor en el sur que en el resto de zonas. Los resultados demuestran que el IRESP transmite información pertinente y, que los mapas de vulnerabilidad pueden ser una herramienta útil en el diseño de políticas y toma de decisiones para la gestión del riesgo de sequía. La tercera aplicación evalúa el potencial de un seguro indexado para sequía en pastos en la región de Coquimbo en Chile. Para lo cual, se desarrolla un modelo estocástico para estimar la prima actuarialmente justa del seguro y se proponen y evalúan pautas alternativas para mejorar el diseño del contrato. Se aborda el riesgo base, el principal problema de los seguros indexados identificado en la literatura y, que está referido a la correlación imperfecta del índice con las pérdidas de la explotación. Para ello, se sigue un enfoque bayesiano que permite evaluar el impacto en el riesgo base de las pautas de diseño propuestas: i) una zonificación por clúster que considera aspectos espacio-temporales, ii) un período de garantía acotado a los ciclos fenológicos del pasto y iii) umbral de garantía. Los resultados muestran que tanto la zonificación como el periodo de garantía reducen el riesgo base considerablemente. Sin embargo, el umbral de garantía tiene un efecto ambiguo sobre el riesgo base. Por otra parte, la zonificación por clúster contribuye a aminorar el riesgo sistémico que enfrentan las aseguradoras. Estos resultados han puesto de manifiesto que un buen diseño de contrato puede tener un doble dividendo, por un lado aumentar su utilidad y, por otro, reducir el coste del seguro. Un diseño de contrato eficiente junto con los avances en la teledetección y un adecuado marco institucional son los pilares básicos para el buen funcionamiento de un programa de seguro. Las nuevas tecnologías ofrecen un importante potencial para la innovación en la gestión del riesgo climático. Los avances en este campo pueden proporcionar importantes beneficios sociales en los países en desarrollo y regiones vulnerables, donde las herramientas para gestionar eficazmente los riesgos sistémicos como la sequía pueden ser de gran ayuda para el desarrollo. The vulnerability of grazing livestock systems highlights the need for tools to assess and mitigate the adverse impact of drought. The recent and rapid progress in remote sensing has awakened an interest for tapping into potential applications, triggering intensive efforts to develop innovations in a number of spheres. One of these areas is climate risk management, where the use of vegetation indices facilitates assessment of drought. This research analyzes drought impacts and evaluates the potential of new technologies such as remote sensing to manage drought risk in extensive livestock systems. Three essays in drought risk management are developed to: (i) assess the economic impact of drought on a livestock farm in the Andalusian Dehesa, (ii) build drought vulnerability maps in Chilean grazing lands, and (iii) design and evaluate the potential of an index insurance policy to address the risk of drought in grazing lands in Coquimbo, Chile. In the first essay, a dynamic and stochastic farm model is designed combining climate, agronomic, socio-economic and ecological aspects to assess drought risk. The model is developed to simulate a representative livestock farm in the Dehesa of Andalusia for the time period 1999-2010. Burn analysis and MonteCarlo simulation methods are used to identify the significance of various risk sources at the farm. Most notably, early summer and early winter are identified as periods of peak risk. Moreover, there is a significant time lag between climate and economic risk and this later last longer than the former. It is shown that intensity, frequency and duration of the drought are three crucial attributes that shape the economic impact of drought. Sensitivity analysis is conducted to assess the sustainability of farm management strategies and demonstrates that lowering the stocking rate reduces farmer exposure to drought risk but entails a reduction in the expected gross margin. The second essay, mapping drought vulnerability in Chilean grazing lands, proposes and builds an index of economic risk (IRESP) that is replicable and simple to interpret. This methodology integrates risk factors and adaptation strategies to deliver information on Value at Risk, maximum expected losses at 5% significance level. Mapping IRESP provides evidence about spatial patterns and significant differences in drought vulnerability across Chilean grazing lands. Spatial autocorrelation measures reveal that systemic risk is considerably larger in the South as compared to Northern or Central Regions. Furthermore, it is shown that vulnerability is not necessarily correlated with climate risk and that adaptation strategies do matter. These results show that IRESP conveys relevant information and that vulnerability maps may be useful tools to assess policy design and decision-making in drought risk management. The third essay develops a stochastic model to estimate the actuarially fair premium and evaluates the potential of an indexed insurance policy to manage drought risk in Coquimbo, a relevant livestock farming region of Chile. Basis risk refers to the imperfect correlation of the index and farmer loses and is identified in the literature as a main limitation of index insurance. A Bayesian approach is proposed to assess the impact on basis risk of alternative guidelines in contract design: i) A cluster zoning that considers space-time aspects, ii) A guarantee period bounded to fit phenological cycles, and iii) the triggering index threshold. Results show that both the proposed zoning and guarantee period considerably reduces basis risk. However, the triggering index threshold has an ambiguous effect on basis risk. On the other hand, cluster zoning contributes to ameliorate systemic risk faced by the insurer. These results highlighted that adequate contract design is important and may result in double dividend. On the one hand, increasing farmers’ utility and, secondly, reducing the cost of insurance. An efficient contract design coupled with advances in remote sensing and an appropriate institutional framework are the basis for an efficient operation of an insurance program. The new technologies offer significant potential for innovation in climate risk managements. Progress in this field is capturing increasing attention and may provide important social gains in developing countries and vulnerable regions where the tools to efficiently manage systemic risks, such as drought, may be a means to foster development.
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The Kolmogorov approach to turbulence is applied to the Burgers turbulence in the stochastic adhesion model of large-scale structure formation. As the perturbative approach to this model is unreliable, here a new, non-perturbative approach, based on a suitable formulation of Kolmogorov's scaling laws, is proposed. This approach suggests that the power-law exponent of the matter density two-point correlation function is in the range 1–1.33, but it also suggests that the adhesion model neglects important aspects of the gravitational dynamics.
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The impact of transmission events from patients with shingles (zoster) on the epidemiology of varicella is examined before and after the introduction of mass immunization by using a stochastic mathematical model of transmission dynamics. Reactivation of the virus is shown to damp stochastic fluctuations and move the dynamics toward simple annual oscillations. The force of infection due to zoster cases is estimated by comparison of simulated and observed incidence time series. The presence of infectious zoster cases reduces the tendency for mass immunization to increase varicella incidence at older ages when disease severity is typically greater.
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Thesis (Ph.D.)--University of Washington, 2016-08
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In this paper we utilise a stochastic address model of broadcast oligopoly markets to analyse the Australian broadcast television market. In particular, we examine the effect of the presence of a single government market participant in this market. An examination of the dynamics of the simulations demonstrates that the presence of a government market participant can simultaneously generate positive outcomes for viewers as well as for other market suppliers. Further examination of simulation dynamics indicates that privatisation of the government market participant results in reduced viewer choice and diversity. We also demonstrate that additional private market participants would not result in significant benefits to viewers.
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The dynamic lateral segregation of signaling proteins into microdomains is proposed to facilitate signal transduction, but the constraints on microdomain size, mobility, and diffusion that might realize this function are undefined. Here we interrogate a stochastic spatial model of the plasma membrane to determine how microdomains affect protein dynamics. Taking lipid rafts as representative microdomains, we show that reduced protein mobility in rafts segregates dynamically partitioning proteins, but the equilibrium concentration is largely independent of raft size and mobility. Rafts weakly impede small-scale protein diffusion but more strongly impede long-range protein mobility. The long-range mobility of raft-partitioning and raft-excluded proteins, however, is reduced to a similar extent. Dynamic partitioning into rafts increases specific interprotein collision rates, but to maximize this critical, biologically relevant function, rafts must be small (diameter, 6 to 14 nm) and mobile. Intermolecular collisions can also be favored by the selective capture and exclusion of proteins by rafts, although this mechanism is generally less efficient than simple dynamic partitioning. Generalizing these results, we conclude that microdomains can readily operate as protein concentrators or isolators but there appear to be significant constraints on size and mobility if microdomains are also required to function as reaction chambers that facilitate nanoscale protein-protein interactions. These results may have significant implications for the many signaling cascades that are scaffolded or assembled in plasma membrane microdomains.
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Classical metapopulation theory assumes a static landscape. However, empirical evidence indicates many metapopulations are driven by habitat succession and disturbance. We develop a stochastic metapopulation model, incorporating habitat disturbance and recovery, coupled with patch colonization and extinction, to investigate the effect of habitat dynamics on persistence. We discover that habitat dynamics play a fundamental role in metapopulation dynamics. The mean number of suitable habitat patches is not adequate for characterizing the dynamics of the metapopulation. For a fixed mean number of suitable patches, we discover that the details of how disturbance affects patches and how patches recover influences metapopulation dynamics in a fundamental way. Moreover, metapopulation persistence is dependent not only oil the average lifetime of a patch, but also on the variance in patch lifetime and the synchrony in patch dynamics that results from disturbance. Finally, there is an interaction between the habitat and metapopulation dynamics, for instance declining metapopulations react differently to habitat dynamics than expanding metapopulations. We close, emphasizing the importance of using performance measures appropriate to stochastic systems when evaluating their behavior, such as the probability distribution of the state of the. metapopulation, conditional on it being extant (i.e., the quasistationary distribution).
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Using the risk measure CV aR in �nancial analysis has become more and more popular recently. In this paper we apply CV aR for portfolio optimization. The problem is formulated as a two-stage stochastic programming model, and the SRA algorithm, a recently developed heuristic algorithm, is applied for minimizing CV aR.
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A CV aR kockázati mérték egyre nagyobb jelentőségre tesz szert portfóliók kockázatának megítélésekor. A portfolió egészére a CVaR kockázati mérték minimalizálását meg lehet fogalmazni kétlépcsős sztochasztikus feladatként. Az SRA algoritmus egy mostanában kifejlesztett megoldó algoritmus sztochasztikus programozási feladatok optimalizálására. Ebben a cikkben az SRA algoritmussal oldottam meg CV aR kockázati mérték minimalizálást. ___________ The risk measure CVaR is becoming more and more popular in recent years. In this paper we use CVaR for portfolio optimization. We formulate the problem as a two-stage stochastic programming model. We apply the SRA algorithm, which is a recently developed heuristic algorithm, to minimizing CVaR.