Optimal release strategies for biological control agents: an application of stochastic dynamic programming to population management

1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.

A landscape-scale test of the predictive ability of a spatially explicit model for population viability analysis

1. Although population viability analysis (PVA) is widely employed, forecasts from PVA models are rarely tested. This study in a fragmented forest in southern Australia contrasted field data on patch occupancy and abundance for the arboreal marsupial greater glider Petauroides volans with predictions from a generic spatially explicit PVA model. This work represents one of the first landscape-scale tests of its type. 2. Initially we contrasted field data from a set of eucalypt forest patches totalling 437 ha with a naive null model in which forecasts of patch occupancy were made, assuming no fragmentation effects and based simply on remnant area and measured densities derived from nearby unfragmented forest. The naive null model predicted an average total of approximately 170 greater gliders, considerably greater than the true count (n = 81). 3. Congruence was examined between field data and predictions from PVA under several metapopulation modelling scenarios. The metapopulation models performed better than the naive null model. Logistic regression showed highly significant positive relationships between predicted and actual patch occupancy for the four scenarios (P = 0.001-0.006). When the model-derived probability of patch occupancy was high (0.50-0.75, 0.75-1.00), there was greater congruence between actual patch occupancy and the predicted probability of occupancy. 4. For many patches, probability distribution functions indicated that model predictions for animal abundance in a given patch were not outside those expected by chance. However, for some patches the model either substantially over-predicted or under-predicted actual abundance. Some important processes, such as inter-patch dispersal, that influence the distribution and abundance of the greater glider may not have been adequately modelled. 5. Additional landscape-scale tests of PVA models, on a wider range of species, are required to assess further predictions made using these tools. This will help determine those taxa for which predictions are and are not accurate and give insights for improving models for applied conservation management.

Using stochastic dynamic programming to determine optimal fire management for Banksia ornata

1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.

Optimal reserve management and sovereign debt

Most models currently used to determine optimal foreign reserve holdings take the level of international debt as given. However, given the sovereign`s willingness-to-pay incentive problems, reserve accumulation may reduce sustainable debt levels. In addition, assuming constant debt levels does not allow addressing one of the puzzles behind using reserves as a means to avoid the negative effects of crisis: why do not sovereign countries reduce their sovereign debt instead? To study the joint decision of holding sovereign debt and reserves, we construct a stochastic dynamic equilibrium model calibrated to a sample of emerging markets. We obtain that the reserve accumulation does not play a quantitatively important role in this model. In fact, we find the optimal policy is not to hold reserves at all. This finding is robust to considering interest rate shocks, sudden stops, contingent reserves and reserve dependent output costs. (c) 2008 Elsevier B.V. All rights reserved.

Environmental impact evaluation using a cooperative model for implementing EMS (ISO 14001) in small and medium-sized enterprises

Certification of an ISO 14001 Environmental Management System (EMS) is currently an important requirement for those enterprises wishing to sell their products in the context of a global market. The system`s structure is based on environmental impact evaluation (EIE). However, if an erroneous or inadequate methodology is applied, the entire process may be jeopardized. Many methodologies have been developed for making of EIEs, some of them are fairly complex and unsuitable for EMS implementation in an organizational context, principally when small and medium size enterprises (SMEs) are involved. The proposed methodology for EIE is part of a model for implementing EMS. The methodological approach used was a qualitative exploratory research method based upon sources of evidence such as document analyses, semi-structured interviews and participant observations. By adopting a cooperative implementation model based on the theory of system engineering, difficulties relating to implementation of the sub-system were overcome thus encouraging SMEs to implement EMS. (C) 2007 Elsevier Ltd. All rights reserved.

Systemic Model for Diagnosis of the Micro, Small and Medium Enterprises from Two Cities from the Countryside of the State of So Paulo in Brazil

This article presents a proposal of a systemic model composed for the micro and small companies (MSE) of the region of Ribeiro Preto and the agents which influenced their environment. The proposed model was based on Stafford Beer`s (Diagnosing the system for organizations. Chichester, Wiley, 1985) systemic methodologies VSM (Viable System Model) and on Werner Ulrich`s (1983) CSH (Critical Systems Heuristics). The VSM is a model for the diagnosis of the structure of an organization and of its flows of information through the application of the cybernetics concepts (Narvarte, In El Modelo del Sistema Viable-MSV: experiencias de su aplicacin en Chile. Proyecto Cerebro Colectivo del IAS, Santiago, 2001). On the other hand, CSH focus on the context of the social group applied to the systemic vision as a counterpoint to the organizational management view considered by the VSM. MSE of Ribeiro Preto and Sertozinho had been analyzed as organizations inserted in systems that relate and integrate with other systems concerning the public administration, entities of representation and promotion agencies. The research questions: which are the bonds of interaction among the subsystems in this process and who are the agents involved? The systemic approach not only diagnosed a social group, formed by MSE of Ribeiro Preto and Sertozinho, public authorities and support entities, but could also delineate answers that aimed the clarification of obscure questions generating financial assistance to the formularization of efficient actions for the development of this system.

Comparing predictions of extinction risk using models and subjective judgement

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models. (C) 2004 Elsevier SAS. All rights reserved.

Coping with stereotype threat: Denial as an impression management strategy

Four experiments tested the hypothesis that people who are concerned with impression management cope with stereotype threat through denial. Consistent with this hypothesis, temporary employees threatened by a stereotype of incompetence (Study 1) and hostel-dwelling older adults (Study 2) were more likely to deny incompetence if they were high in impression management. African Americans (Study 3) showed a similar pattern of denying cognitive incompetence, which emerged primarily when they were interviewed by a White experimenter and had attended a predominantly Black high school. In Study 4, White students who expected to take an IQ test and were threatened by a stereotype of being less intelligent than Asians were more likely to deny that intelligence is important if they were high in impression management.

Acute care surgeon South American model

Background In the World Health Organization book by Murray and Lopez (The Global Burden of Disease), the authors make the point that there are major regional differences across the world for death from injury. In the European market economies, injuries accounted for 6% of all deaths, of which the majority were the result of road traffic accidents. In stark contrast, in Latin America and the Caribbean, injuries account for 12-13% of all deaths, and most of these are the result of violence. An estimated 30% of all male deaths are from external causes, and road traffic accidents are the number two cause of death. Within South American countries, trauma is the second most common cause of death in Columbia, Venezuela, Ecuador, and Brazil. In other South American countries, it is the third or fourth most common cause of death. If one examines the Disability Adjusted Life Years, South America is the third highest in the world. Death from injury primarily affects people in the middle- and low-income group. Traffic accidents and suicide are the main causes of trauma in the high-income population. South America is made up of developing and poor countries that have trauma as a very important cause of death and disability. Methods The author has reviewed information on injury from the World Health Organization, Pan American Health Organization, and Brazilian Health Ministry. In addition, a search of injury was performed through MEDLINE. Results and Conclusions The results of this review show that trauma is a major public health problem in South America. At the present time, there is a lack of statewide system development. In addition, there are difficulties in training surgeons to cope with these problems.

A Comparison Between Pulse Pressure Variation and Right End Diastolic Volume Index as Guides to Resuscitation in a Model of Hemorrhagic Shock in Pigs

Background: Different hemodynamic parameters including static indicators of cardiac preload as right ventricular end-diastolic volume index (RVEDVI) and dynamic parameters as pulse pressure variation (PPV) have been used in the decision-making process regarding volume expansion in critically ill patients. The objective of this study was to compare fluid resuscitation guided by either PPV or RVEDVI after experimentally induced hemorrhagic shock. Methods: Twenty-six anesthetized and mechanically ventilated pigs were allocated into control (group I), PPV (group II), or RVEDVI (group III) group. Hemorrhagic shock was induced by blood withdrawal to target mean arterial pressure of 40 mm Hg, maintained for 60 minutes. Parameters were measured at baseline, time of shock, 60 minutes after shock, immediately after resuscitation with hydroxyethyl starch 6% (130/0.4), 1 hour and 2 hours thereafter. The endpoint of fluid resuscitation was determined as the baseline values of PPV and RVEDVI. Statistical analysis of data was based on analysis of variance for repeated measures followed by the Bonferroni test (p < 0.05). Results: Volume and time to resuscitation were higher in group III than in group II (group III = 1,305 +/- 331 mL and group II = 965 +/- 245 mL, p < 0.05; and group III = 24.8 +/- 4.7 minutes and group II = 8.8 +/- 1.3 minutes, p < 0.05, respectively). All static and dynamic parameters and biomarkers of tissue oxygenation were affected by hemorrhagic shock and nearly all parameters were restored after resuscitation in both groups. Conclusion: In the proposed model of hemorrhagic shock, resuscitation to the established endpoints was achieved within a smaller amount of time and with less volume when guided by PPV than when guided by pulmonary artery catheter-derived RVEDVI.

Low Hematocrit Levels Increase Intracranial Pressure in an Animal Model of Cryogenic Brain Injury

Background: Brain injury is responsible for significant morbidity and mortality in trauma patients, but controversy still exists over optimal fluid management for these patients. This study aimed to investigate the effects of acute hemodilution with hydroxyethyl starch (HES) or lactated Ringer`s solution (LR) in intracranial pressure (ICP) and cerebral perfusion pressure (CPP) in dogs submitted to a cryogenic brain injury model. Methods: Design-Prospective laboratory animal study. Setting-Research laboratory in a teaching hospital. Subjects-Thirty-five male mongrel dogs. Interventions-Animals were enrolled to five groups: control, hemodilution with LR or HES 6% to an hematocrit target of 27% or 35%. Results: ICP and CPP levels were measured after cryogenic brain injury. Hemodilution promotes an increment of ICP levels, which decreases CPP when hematocrit target was estimated in 27.% after hemodilution. However, no differences were observed regarding crystalloid or colloid solution used for hemodilution in ICP and CPP levels. Conclusions: Hemodilution to a low hematocrit level increases ICP and decreases CPP scores in dogs submitted to a cryogenic brain injury. These results suggest that excessive hemodilution to a hematocrit below 30% should be avoided in traumatic brain injury patients.

Early identification of leptospirosis-associated pulmonary hemorrhage syndrome by use of a validated prediction model

Objective: To identify prediction factors for the development of leptospirosis-associated pulmonary hemorrhage syndrome (LPHS). Methods: We conducted a prospective cohort study. The study comprised of 203 patients, aged >= 14 years, admitted with complications of the severe form of leptospirosis at the Emilio Ribas Institute of Infectology (Sao Paulo, Brazil) between 1998 and 2004. Laboratory and demographic data were obtained and the severity of illness score and involvement of the lungs and others organs were determined. Logistic regression was performed to identify independent predictors of LPHS. A prospective validation cohort of 97 subjects with severe form of leptospirosis admitted at the same hospital between 2004 and 2006 was used to independently evaluate the predictive value of the model. Results: The overall mortality rate was 7.9%. Multivariate logistic regression revealed that five factors were independently associated with the development of LPHS: serum potassium (mmol/L) (OR = 2.6; 95% CI = 1.1-5.9); serum creatinine (mmol/L) (OR = 1.2; 95% CI = 1.1-1.4); respiratory rate (breaths/min) (OR = 1.1; 95% CI = 1.1-1.2); presenting shock (OR = 69.9; 95% CI = 20.1-236.4), and Glasgow Coma Scale Score (GCS) < 15 (OR = 7.7; 95% CI = 1.3-23.0). We used these findings to calculate the risk of LPHS by the use of a spreadsheet. In the validation cohort, the equation classified correctly 92% of patients (Kappa statistic = 0.80). Conclusions: We developed and validated a multivariate model for predicting LPHS. This tool should prove useful in identifying LPHS patients, allowing earlier management and thereby reducing mortality. (C) 2009 The British Infection Society. Published by Elsevier Ltd. All rights reserved.

Hypervolemia induces and potentiates lung damage after recruitment maneuver in a model of sepsis-induced acute lung injury

Introduction: Recruitment maneuvers (RMs) seem to be more effective in extrapulmonary acute lung injury (ALI), caused mainly by sepsis, than in pulmonary ALI. Nevertheless, the maintenance of adequate volemic status is particularly challenging in sepsis. Since the interaction between volemic status and RMs is not well established, we investigated the effects of RMs on lung and distal organs in the presence of hypovolemia, normovolemia, and hypervolemia in a model of extrapulmonary lung injury induced by sepsis. Methods: ALI was induced by cecal ligation and puncture surgery in 66 Wistar rats. After 48 h, animals were anesthetized, mechanically ventilated and randomly assigned to 3 volemic status (n = 22/group): 1) hypovolemia induced by blood drainage at mean arterial pressure (MAP)approximate to 70 mmHg; 2) normovolemia (MAP approximate to 100 mmHg), and 3) hypervolemia with colloid administration to achieve a MAP approximate to 130 mmHg. In each group, animals were further randomized to be recruited (CPAP = 40 cm H(2)O for 40 s) or not (NR) (n = 11/group), followed by 1 h of protective mechanical ventilation. Echocardiography, arterial blood gases, static lung elastance (Est, L), histology (light and electron microscopy), lung wet-to-dry (W/D) ratio, interleukin (IL)-6, IL-1 beta, caspase-3, type III procollagen (PCIII), intercellular adhesion molecule-1 (ICAM-1), and vascular cell adhesion molecule-1 (VCAM-1) mRNA expressions in lung tissue, as well as lung and distal organ epithelial cell apoptosis were analyzed. Results: We observed that: 1) hypervolemia increased lung W/D ratio with impairment of oxygenation and Est, L, and was associated with alveolar and endothelial cell damage and increased IL-6, VCAM-1, and ICAM-1 mRNA expressions; and 2) RM reduced alveolar collapse independent of volemic status. In hypervolemic animals, RM improved oxygenation above the levels observed with the use of positive-end expiratory pressure (PEEP), but increased lung injury and led to higher inflammatory and fibrogenetic responses. Conclusions: Volemic status should be taken into account during RMs, since in this sepsis-induced ALI model hypervolemia promoted and potentiated lung injury compared to hypo-and normovolemia.

Mucosal leishmaniasis: description of case management approaches and analysis of risk factors for treatment failure in a cohort of 140 patients in Brazil

Background Mucosal leishmaniasis is caused mainly by Leishmania braziliensis and it occurs months or years after cutaneous lesions. This progressive disease destroys cartilages and osseous structures from face, pharynx and larynx. Objective and methods The aim of this study was to analyse the significance of clinical and epidemiological findings, diagnosis and treatment with the outcome and recurrence of mucosal leishmaniasis through binary logistic regression model from 140 patients with mucosal leishmaniasis from a Brazilian centre. Results The median age of patients was 57.5 and systemic arterial hypertension was the most prevalent secondary disease found in patients with mucosal leishmaniasis (43%). Diabetes, chronic nephropathy and viral hepatitis, allergy and coagulopathy were found in less than 10% of patients. Human immunodeficiency virus (HIV) infection was found in 7 of 140 patients (5%). Rhinorrhea (47%) and epistaxis (75%) were the most common symptoms. N-methyl-glucamine showed a cure rate of 91% and recurrence of 22%. Pentamidine showed a similar rate of cure (91%) and recurrence (25%). Fifteen patients received itraconazole with a cure rate of 73% and recurrence of 18%. Amphotericin B was the drug used in 30 patients with 82% of response with a recurrence rate of 7%. The binary logistic regression analysis demonstrated that systemic arterial hypertension and HIV infection were associated with failure of the treatment (P < 0.05). Conclusion The current first-line mucosal leishmaniasis therapy shows an adequate cure but later recurrence. HIV infection and systemic arterial hypertension should be investigated before start the treatment of mucosal leishmaniasis. Conflicts of interest The authors are not part of any associations or commercial relationships that might represent conflicts of interest in the writing of this study (e.g. pharmaceutical stock ownership, consultancy, advisory board membership, relevant patents, or research funding).

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.