938 resultados para optimal-stocking model


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BACKGROUND: Drugs are routinely combined in anesthesia and pain management to obtain an enhancement of the desired effects. However, a parallel enhancement of the undesired effects might take place as well, resulting in a limited therapeutic usefulness. Therefore, when addressing the question of optimal drug combinations, side effects must be taken into account. METHODS: By extension of a previously published interaction model, the authors propose a method to study drug interactions considering also their side effects. A general outcome parameter identified as patient's well-being is defined by superposition of positive and negative effects. Well-being response surfaces are computed and analyzed for varying drugs pharmacodynamics and interaction types. In particular, the existence of multiple maxima and of optimal drug combinations is investigated for the combination of two drugs. RESULTS: Both drug pharmacodynamics and interaction type affect the well-being surface and the deriving optimal combinations. The effect of the interaction parameters can be explained in terms of synergy and antagonism and remains unchanged for varying pharmacodynamics. For all simulations performed for the combination of two drugs, the presence of more than one maximum was never observed. CONCLUSIONS: The model is consistent with clinical knowledge and supports previously published experimental results on optimal drug combinations. This new framework improves understanding of the characteristics of drug combinations used in clinical practice and can be used in clinical research to identify optimal drug dosing.

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Stem cell regeneration of damaged tissue has recently been reported in many different organs. Since the loss of retinal pigment epithelium (RPE) in the eye is associated with a major cause of visual loss - specifically, age-related macular degeneration - we investigated whether hematopoietic stem cells (HSC) given systemically can home to the damaged subretinal space and express markers of RPE lineage. Green fluorescent protein (GFP) cells of bone marrow origin were used in a sodium iodate (NaIO(3)) model of RPE damage in the mouse. The optimal time for adoptive transfer of bone marrow-derived stem cells relative to the time of injury and the optimal cell type [whole bone marrow, mobilized peripheral blood, HSC, facilitating cells (FC)] were determined by counting the number of GFP(+) cells in whole eye flat mounts. Immunocytochemistry was performed to identify the bone marrow origin of the cells in the RPE using antibodies for CD45, Sca-1, and c-kit, as well as the expression of the RPE-specific marker, RPE-65. The time at which bone marrow-derived cells were adoptively transferred relative to the time of NaIO(3) injection did not significantly influence the number of cells that homed to the subretinal space. At both one and two weeks after intravenous (i.v.) injection, GFP(+) cells of bone marrow origin were observed in the damaged subretinal space, at sites of RPE loss, but not in the normal subretinal space. The combined transplantation of HSC+FC cells appeared to favor the survival of the homed stem cells at two weeks, and RPE-65 was expressed by adoptively transferred HSC by four weeks. We have shown that systemically injected HSC homed to the subretinal space in the presence of RPE damage and that FC promoted survival of these cells. Furthermore, the RPE-specific marker RPE-65 was expressed on adoptively transferred HSC in the denuded areas.

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BACKGROUND: Bone morphogenetic protein (BMP) is a potent differentiating agent for cells of the osteoblastic lineage. It has been used in the oral cavity under a variety of indications and with different carriers. However, the optimal carrier for each indication is not known. This study examined a synthetic bioabsorbable carrier for BMP used in osseous defects around dental implants in the canine mandible. METHODS: Twelve canines had their mandibular four premolars and first molar teeth extracted bilaterally. After 5 months, four implants were placed with standardized circumferential defects around the coronal 4 mm of each implant. One-half of the defects received a polylactide/glycolide (PLGA) polymer carrier with or without recombinant human BMP-2 (rhBMP-2), and the other half received a collagen carrier with or without rhBMP-2. Additionally, one-half of the implants were covered with a non-resorbable (expanded polytetrafluoroethylene [ePTFE]) membrane to exclude soft tissues. Animals were sacrificed either 4 or 12 weeks later. Histomorphometric analysis included the percentage of new bone contact with the implant, the area of new bone, and the percentage of defect fill. This article describes results with the PLGA carrier. RESULTS: All implants demonstrated clinical and radiographic success with the amount of new bone formed dependent on the time and presence/absence of rhBMP-2 and presence/absence of a membrane. The percentage of bone-to-implant contact was greater with rhBMP-2, and after 12 weeks of healing, there was approximately one-third of the implant contacting bone in the defect site. After 4 weeks, the presence of a membrane appeared to slow new bone area formation. The percentage of fill in membrane-treated sites with rhBMP-2 rose from 24% fill to 42% after 4 and 12 weeks, respectively. Without rhBMP-2, the percentage of fill was 14% rising to 36% fill, respectively. CONCLUSIONS: After 4 weeks, the rhBMP-2-treated sites had a significantly higher percentage of contact, more new bone area, and higher percentage of defect fill than the sites without rhBMP-2. After 12 weeks, there was no significant difference in sites with or without rhBMP-2 regarding percentage of contact, new bone area, or percentage of defect fill. In regard to these three outcomes, comparing the results with this carrier to the results reported earlier with a collagen carrier in this study, only the area of new bone was significantly different with the collagen carrier resulting in greater bone than the PLGA carrier. Thus, the PLGA carrier for rhBMP-2 significantly stimulated bone formation around dental implants in this model after 1 month but not after 3 months of healing. The use of this growth factor and carrier combination appears to stimulate early bone healing events around the implants but not quite to the same degree as a collagen carrier.

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Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.

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The purpose of this study is to develop statistical methodology to facilitate indirect estimation of the concentration of antiretroviral drugs and viral loads in the prostate gland and the seminal vesicle. The differences in antiretroviral drug concentrations in these organs may lead to suboptimal concentrations in one gland compared to the other. Suboptimal levels of the antiretroviral drugs will not be able to fully suppress the virus in that gland, lead to a source of sexually transmissible virus and increase the chance of selecting for drug resistant virus. This information may be useful selecting antiretroviral drug regimen that will achieve optimal concentrations in most of male genital tract glands. Using fractionally collected semen ejaculates, Lundquist (1949) measured levels of surrogate markers in each fraction that are uniquely produced by specific male accessory glands. To determine the original glandular concentrations of the surrogate markers, Lundquist solved a simultaneous series of linear equations. This method has several limitations. In particular, it does not yield a unique solution, it does not address measurement error, and it disregards inter-subject variability in the parameters. To cope with these limitations, we developed a mechanistic latent variable model based on the physiology of the male genital tract and surrogate markers. We employ a Bayesian approach and perform a sensitivity analysis with regard to the distributional assumptions on the random effects and priors. The model and Bayesian approach is validated on experimental data where the concentration of a drug should be (biologically) differentially distributed between the two glands. In this example, the Bayesian model-based conclusions are found to be robust to model specification and this hierarchical approach leads to more scientifically valid conclusions than the original methodology. In particular, unlike existing methods, the proposed model based approach was not affected by a common form of outliers.

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Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

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To mitigate greenhouse gas (GHG) emissions and reduce U.S. dependence on imported oil, the United States (U.S.) is pursuing several options to create biofuels from renewable woody biomass (hereafter referred to as “biomass”). Because of the distributed nature of biomass feedstock, the cost and complexity of biomass recovery operations has significant challenges that hinder increased biomass utilization for energy production. To facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization and tapping unused forest residues, it is proposed to develop biofuel supply chain models based on optimization and simulation approaches. The biofuel supply chain is structured around four components: biofuel facility locations and sizes, biomass harvesting/forwarding, transportation, and storage. A Geographic Information System (GIS) based approach is proposed as a first step for selecting potential facility locations for biofuel production from forest biomass based on a set of evaluation criteria, such as accessibility to biomass, railway/road transportation network, water body and workforce. The development of optimization and simulation models is also proposed. The results of the models will be used to determine (1) the number, location, and size of the biofuel facilities, and (2) the amounts of biomass to be transported between the harvesting areas and the biofuel facilities over a 20-year timeframe. The multi-criteria objective is to minimize the weighted sum of the delivered feedstock cost, energy consumption, and GHG emissions simultaneously. Finally, a series of sensitivity analyses will be conducted to identify the sensitivity of the decisions, such as the optimal site selected for the biofuel facility, to changes in influential parameters, such as biomass availability and transportation fuel price. Intellectual Merit The proposed research will facilitate the exploration of a wide variety of conditions that promise profitable biomass utilization in the renewable biofuel industry. The GIS-based facility location analysis considers a series of factors which have not been considered simultaneously in previous research. Location analysis is critical to the financial success of producing biofuel. The modeling of woody biomass supply chains using both optimization and simulation, combing with the GIS-based approach as a precursor, have not been done to date. The optimization and simulation models can help to ensure the economic and environmental viability and sustainability of the entire biofuel supply chain at both the strategic design level and the operational planning level. Broader Impacts The proposed models for biorefineries can be applied to other types of manufacturing or processing operations using biomass. This is because the biomass feedstock supply chain is similar, if not the same, for biorefineries, biomass fired or co-fired power plants, or torrefaction/pelletization operations. Additionally, the research results of this research will continue to be disseminated internationally through publications in journals, such as Biomass and Bioenergy, and Renewable Energy, and presentations at conferences, such as the 2011 Industrial Engineering Research Conference. For example, part of the research work related to biofuel facility identification has been published: Zhang, Johnson and Sutherland [2011] (see Appendix A). There will also be opportunities for the Michigan Tech campus community to learn about the research through the Sustainable Future Institute.

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Focusing optical beams on a target through random propagation media is very important in many applications such as free space optical communica- tions and laser weapons. Random media effects such as beam spread and scintillation can degrade the optical system's performance severely. Compensation schemes are needed in these applications to overcome these random media effcts. In this research, we investigated the optimal beams for two different optimization criteria: one is to maximize the concentrated received intensity and the other is to minimize the scintillation index at the target plane. In the study of the optimal beam to maximize the weighted integrated intensity, we derive a similarity relationship between pupil-plane phase screen and extended Huygens-Fresnel model, and demonstrate the limited utility of maximizing the average integrated intensity. In the study ofthe optimal beam to minimize the scintillation index, we derive the first- and second-order moments for the integrated intensity of multiple coherent modes. Hermite-Gaussian and Laguerre-Gaussian modes are used as the coherent modes to synthesize an optimal partially coherent beam. The optimal beams demonstrate evident reduction of scintillation index, and prove to be insensitive to the aperture averaging effect.

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This dissertation presents the competitive control methodologies for small-scale power system (SSPS). A SSPS is a collection of sources and loads that shares a common network which can be isolated during terrestrial disturbances. Micro-grids, naval ship electric power systems (NSEPS), aircraft power systems and telecommunication system power systems are typical examples of SSPS. The analysis and development of control systems for small-scale power systems (SSPS) lacks a defined slack bus. In addition, a change of a load or source will influence the real time system parameters of the system. Therefore, the control system should provide the required flexibility, to ensure operation as a single aggregated system. In most of the cases of a SSPS the sources and loads must be equipped with power electronic interfaces which can be modeled as a dynamic controllable quantity. The mathematical formulation of the micro-grid is carried out with the help of game theory, optimal control and fundamental theory of electrical power systems. Then the micro-grid can be viewed as a dynamical multi-objective optimization problem with nonlinear objectives and variables. Basically detailed analysis was done with optimal solutions with regards to start up transient modeling, bus selection modeling and level of communication within the micro-grids. In each approach a detail mathematical model is formed to observe the system response. The differential game theoretic approach was also used for modeling and optimization of startup transients. The startup transient controller was implemented with open loop, PI and feedback control methodologies. Then the hardware implementation was carried out to validate the theoretical results. The proposed game theoretic controller shows higher performances over traditional the PI controller during startup. In addition, the optimal transient surface is necessary while implementing the feedback controller for startup transient. Further, the experimental results are in agreement with the theoretical simulation. The bus selection and team communication was modeled with discrete and continuous game theory models. Although players have multiple choices, this controller is capable of choosing the optimum bus. Next the team communication structures are able to optimize the players’ Nash equilibrium point. All mathematical models are based on the local information of the load or source. As a result, these models are the keys to developing accurate distributed controllers.

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A range of societal issues have been caused by fossil fuel consumption in the transportation sector in the United States (U.S.), including health related air pollution, climate change, the dependence on imported oil, and other oil related national security concerns. Biofuels production from various lignocellulosic biomass types such as wood, forest residues, and agriculture residues have the potential to replace a substantial portion of the total fossil fuel consumption. This research focuses on locating biofuel facilities and designing the biofuel supply chain to minimize the overall cost. For this purpose an integrated methodology was proposed by combining the GIS technology with simulation and optimization modeling methods. The GIS based methodology was used as a precursor for selecting biofuel facility locations by employing a series of decision factors. The resulted candidate sites for biofuel production served as inputs for simulation and optimization modeling. As a precursor to simulation or optimization modeling, the GIS-based methodology was used to preselect potential biofuel facility locations for biofuel production from forest biomass. Candidate locations were selected based on a set of evaluation criteria, including: county boundaries, a railroad transportation network, a state/federal road transportation network, water body (rivers, lakes, etc.) dispersion, city and village dispersion, a population census, biomass production, and no co-location with co-fired power plants. The simulation and optimization models were built around key supply activities including biomass harvesting/forwarding, transportation and storage. The built onsite storage served for spring breakup period where road restrictions were in place and truck transportation on certain roads was limited. Both models were evaluated using multiple performance indicators, including cost (consisting of the delivered feedstock cost, and inventory holding cost), energy consumption, and GHG emissions. The impact of energy consumption and GHG emissions were expressed in monetary terms to keep consistent with cost. Compared with the optimization model, the simulation model represents a more dynamic look at a 20-year operation by considering the impacts associated with building inventory at the biorefinery to address the limited availability of biomass feedstock during the spring breakup period. The number of trucks required per day was estimated and the inventory level all year around was tracked. Through the exchange of information across different procedures (harvesting, transportation, and biomass feedstock processing procedures), a smooth flow of biomass from harvesting areas to a biofuel facility was implemented. The optimization model was developed to address issues related to locating multiple biofuel facilities simultaneously. The size of the potential biofuel facility is set up with an upper bound of 50 MGY and a lower bound of 30 MGY. The optimization model is a static, Mathematical Programming Language (MPL)-based application which allows for sensitivity analysis by changing inputs to evaluate different scenarios. It was found that annual biofuel demand and biomass availability impacts the optimal results of biofuel facility locations and sizes.

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Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

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OBJECTIVE: In search of an optimal compression therapy for venous leg ulcers, a systematic review and meta-analysis was performed of randomized controlled trials (RCT) comparing compression systems based on stockings (MCS) with divers bandages. METHODS: RCT were retrieved from six sources and reviewed independently. The primary endpoint, completion of healing within a defined time frame, and the secondary endpoints, time to healing, and pain were entered into a meta-analysis using the tools of the Cochrane Collaboration. Additional subjective endpoints were summarized. RESULTS: Eight RCT (published 1985-2008) fulfilled the predefined criteria. Data presentation was adequate and showed moderate heterogeneity. The studies included 692 patients (21-178/study, mean age 61 years, 56% women). Analyzed were 688 ulcerated legs, present for 1 week to 9 years, sizing 1 to 210 cm(2). The observation period ranged from 12 to 78 weeks. Patient and ulcer characteristics were evenly distributed in three studies, favored the stocking groups in four, and the bandage group in one. Data on the pressure exerted by stockings and bandages were reported in seven and two studies, amounting to 31-56 and 27-49 mm Hg, respectively. The proportion of ulcers healed was greater with stockings than with bandages (62.7% vs 46.6%; P < .00001). The average time to healing (seven studies, 535 patients) was 3 weeks shorter with stockings (P = .0002). In no study performed bandages better than MCS. Pain was assessed in three studies (219 patients) revealing an important advantage of stockings (P < .0001). Other subjective parameters and issues of nursing revealed an advantage of MCS as well. CONCLUSIONS: Leg compression with stockings is clearly better than compression with bandages, has a positive impact on pain, and is easier to use.

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The execution of a project requires resources that are generally scarce. Classical approaches to resource allocation assume that the usage of these resources by an individual project activity is constant during the execution of that activity; in practice, however, the project manager may vary resource usage over time within prescribed bounds. This variation gives rise to the project scheduling problem which consists in allocating the scarce resources to the project activities over time such that the project duration is minimized, the total number of resource units allocated equals the prescribed work content of each activity, and various work-content-related constraints are met. We formulate this problem for the first time as a mixed-integer linear program. Our computational results for a standard test set from the literature indicate that this model outperforms the state-of-the-art solution methods for this problem.

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BACKGROUND The use of combination antiretroviral therapy (cART) comprising three antiretroviral medications from at least two classes of drugs is the current standard treatment for HIV infection in adults and children. Current World Health Organization (WHO) guidelines for antiretroviral therapy recommend early treatment regardless of immunologic thresholds or the clinical condition for all infants (less than one years of age) and children under the age of two years. For children aged two to five years current WHO guidelines recommend (based on low quality evidence) that clinical and immunological thresholds be used to identify those who need to start cART (advanced clinical stage or CD4 counts ≤ 750 cells/mm(3) or per cent CD4 ≤ 25%). This Cochrane review will inform the current available evidence regarding the optimal time for treatment initiation in children aged two to five years with the goal of informing the revision of WHO 2013 recommendations on when to initiate cART in children. OBJECTIVES To assess the evidence for the optimal time to initiate cART in treatment-naive, HIV-infected children aged 2 to 5 years. SEARCH METHODS We searched the Cochrane Central Register of Controlled Trials (CENTRAL), MEDLINE, EMBASE, the AEGIS conference database, specific relevant conferences, www.clinicaltrials.gov, the World Health Organization International Clinical Trials Registry platform and reference lists of articles. The date of the most recent search was 30 September 2012. SELECTION CRITERIA Randomised controlled trials (RCTs) that compared immediate with deferred initiation of cART, and prospective cohort studies which followed children from enrolment to start of cART and on cART. DATA COLLECTION AND ANALYSIS Two review authors considered studies for inclusion in the review, assessed the risk of bias, and extracted data on the primary outcome of death from all causes and several secondary outcomes, including incidence of CDC category C and B clinical events and per cent CD4 cells (CD4%) at study end. For RCTs we calculated relative risks (RR) or mean differences with 95% confidence intervals (95% CI). For cohort data, we extracted relative risks with 95% CI from adjusted analyses. We combined results from RCTs using a random effects model and examined statistical heterogeneity. MAIN RESULTS Two RCTs in HIV-positive children aged 1 to 12 years were identified. One trial was the pilot study for the larger second trial and both compared initiation of cART regardless of clinical-immunological conditions with deferred initiation until per cent CD4 dropped to <15%. The two trials were conducted in Thailand, and Thailand and Cambodia, respectively. Unpublished analyses of the 122 children enrolled at ages 2 to 5 years were included in this review. There was one death in the immediate cART group and no deaths in the deferred group (RR 2.9; 95% CI 0.12 to 68.9). In the subgroup analysis of children aged 24 to 59 months, there was one CDC C event in each group (RR 0.96; 95% CI 0.06 to 14.87) and 8 and 11 CDC B events in the immediate and deferred groups respectively (RR 0.95; 95% CI 0.24 to 3.73). In this subgroup, the mean difference in CD4 per cent at study end was 5.9% (95% CI 2.7 to 9.1). One cohort study from South Africa, which compared the effect of delaying cART for up to 60 days in 573 HIV-positive children starting tuberculosis treatment (median age 3.5 years), was also included. The adjusted hazard ratios for the effect on mortality of delaying ART for more than 60 days was 1.32 (95% CI 0.55 to 3.16). AUTHORS' CONCLUSIONS This systematic review shows that there is insufficient evidence from clinical trials in support of either early or CD4-guided initiation of ART in HIV-infected children aged 2 to 5 years. Programmatic issues such as the retention in care of children in ART programmes in resource-limited settings will need to be considered when formulating WHO 2013 recommendations.

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The study assessed the economic efficiency of different strategies for the control of post-weaning multi-systemic wasting syndrome (PMWS) and porcine circovirus type 2 subclinical infection (PCV2SI), which have a major economic impact on the pig farming industry worldwide. The control strategies investigated consisted on the combination of up to 5 different control measures. The control measures considered were: (1) PCV2 vaccination of piglets (vac); (2) ensuring age adjusted diet for growers (diets); (3) reduction of stocking density (stock); (4) improvement of biosecurity measures (bios); and (5) total depopulation and repopulation of the farm for the elimination of other major pathogens (DPRP). A model was developed to simulate 5 years production of a pig farm with a 3-weekly batch system and with 100 sows. A PMWS/PCV2SI disease and economic model, based on PMWS severity scores, was linked to the production model in order to assess disease losses. This PMWS severity scores depends on the combination post-weaning mortality, PMWS morbidity in younger pigs and proportion of PCV2 infected pigs observed on farms. The economic analysis investigated eleven different farm scenarios, depending on the number of risk factors present before the intervention. For each strategy, an investment appraisal assessed the extra costs and benefits of reducing a given PMWS severity score to the average score of a slightly affected farm. The net present value obtained for each strategy was then multiplied by the corresponding probability of success to obtain an expected value. A stochastic simulation was performed to account for uncertainty and variability. For moderately affected farms PCV2 vaccination alone was the most cost-efficient strategy, but for highly affected farms it was either PCV2 vaccination alone or in combination with biosecurity measures, with the marginal profitability between 'vac' and 'vac+bios' being small. Other strategies such as 'diets', 'vac+diets' and 'bios+diets' were frequently identified as the second or third best strategy. The mean expected values of the best strategy for a moderately and a highly affected farm were £14,739 and £57,648 after 5 years, respectively. This is the first study to compare economic efficiency of control strategies for PMWS and PCV2SI. The results demonstrate the economic value of PCV2 vaccination, and highlight that on highly affected farms biosecurity measures are required to achieve optimal profitability. The model developed has potential as a farm-level decision support tool for the control of this economically important syndrome.