Risk Estimates of Dengue in Travelers to Dengue Endemic Areas Using Mathematical Models

Dengue has emerged as a frequent problem in international travelers. The risk depends on destination, duration, and season of travel. However, data to quantify the true risk for travelers to acquire dengue are lacking. We used mathematical models to estimate the risk of nonimmune persons to acquire dengue when traveling to Singapore. From the force of infection, we calculated the risk of dengue dependent on duration of stay and season of arrival. Our data highlight that the risk for nonimmune travelers to acquire dengue in Singapore is substantial but varies greatly with seasons and epidemic cycles. For instance, for a traveler who stays in Singapore for 1 week during the high dengue season in 2005, the risk of acquiring dengue was 0.17%, but it was only 0.00423% during the low season in a nonepidemic year such as 2002. Risk estimates based on mathematical modeling will help the travel medicine provider give better evidence-based advice for travelers to dengue endemic countries.

PAH biomarkers for human health risk assessment: a review of the state-of-the-art

Polycyclic aromatic hydrocarbons (PAH) are widely distributed in the environment, and some are carcinogenic to human beings. The study of biomarkers has helped clarify the nature and magnitude of the human health risks posed by such substances. This article provides a review of the state-of-the-art on PAH biomarkers for human health risk assessment and also discusses their applicability within the context of environmental management in Brazil. The article discusses the methodologies for determination of some biomarkers such as 1-hydroxypyrene and PAH-DNA adducts. Cytogenetic markers, frequency of chromosomal aberrations, and micronucleus induction were considered for the evaluation of cancer risk. The current stage of studies on validation of such biomarkers was also approached.

Flood Risk Assessment in Coastal Drainage Basins through a Multivariate Analysis within a GIS-Based Model

This paper presents a GIS-based multicriteria flood risk assessment and mapping approach applied to coastal drainage basins where hydrological data are not available. It involves risk to different types of possible processes: coastal inundation (storm surge), river, estuarine and flash flood, either at urban or natural areas, and fords. Based on the causes of these processes, several environmental indicators were taken to build-up the risk assessment. Geoindicators include geological-geomorphologic proprieties of Quaternary sedimentary units, water table, drainage basin morphometry, coastal dynamics, beach morphodynamics and microclimatic characteristics. Bioindicators involve coastal plain and low slope native vegetation categories and two alteration states. Anthropogenic indicators encompass land use categories properties such as: type, occupation density, urban structure type and occupation consolidation degree. The selected indicators were stored within an expert Geoenvironmental Information System developed for the State of Sao Paulo Coastal Zone (SIIGAL), which attributes were mathematically classified through deterministic approaches, in order to estimate natural susceptibilities (Sn), human-induced susceptibilities (Sa), return period of rain events (Ri), potential damages (Dp) and the risk classification (R), according to the equation R=(Sn.Sa.Ri).Dp. Thematic maps were automatically processed within the SIIGAL, in which automata cells (""geoenvironmental management units"") aggregating geological-geomorphologic and land use/native vegetation categories were the units of classification. The method has been applied to the Northern Littoral of the State of Sao Paulo (Brazil) in 32 small drainage basins, demonstrating to be very useful for coastal zone public politics, civil defense programs and flood management.

The constrained compartmentalized knapsack problem: mathematical models and solution methods

The constrained compartmentalized knapsack problem can be seen as an extension of the constrained knapsack problem. However, the items are grouped into different classes so that the overall knapsack has to be divided into compartments, and each compartment is loaded with items from the same class. Moreover, building a compartment incurs a fixed cost and a fixed loss of the capacity in the original knapsack, and the compartments are lower and upper bounded. The objective is to maximize the total value of the items loaded in the overall knapsack minus the cost of the compartments. This problem has been formulated as an integer non-linear program, and in this paper, we reformulate the non-linear model as an integer linear master problem with a large number of variables. Some heuristics based on the solution of the restricted master problem are investigated. A new and more compact integer linear model is also presented, which can be solved by a branch-and-bound commercial solver that found most of the optimal solutions for the constrained compartmentalized knapsack problem. On the other hand, heuristics provide good solutions with low computational effort. (C) 2011 Elsevier BM. All rights reserved.

Risk assessment of trihalomethanes from tap water in Fortaleza, Brazil

The cancer risks (CR) by oral ingestion, dermal absorption, and inhalation exposure of trihalomethanes (THM) from tap water of ten districts in Fortaleza, Brazil were estimated. The mean levels of THM compounds were obtained in Fortaleza tap water as follow: 63.9 mu g L(-1) for chloroform (CHCl(3)), 40.0 mu g L(-1) for bromodichloromethane (CHBrCl(2)), and 15.6 mu g L(-1) for dibromochloromethane (CHBr(2)Cl). Bromoform (CHBr(3)) was not detected. The mean CR for THMs in tap water is 3.96 x 10(-4). The results indicate that Fortaleza residents have a higher CR by inhalation than dermal absorption and oral ingestion. The CR for CHCl(3) contributes with 68% as compared with the total CR, followed by CHBrCl(2) (21%), and CHBr(2)Cl (11%). The hazard index (HI) is about ten times lower than unity, not indicating non-cancer effects.

GIS applied to geotechnical and environmental risk management in a Brazilian oil pipeline

The paper presents the development of a decision support system for the management of geotechnical and environmental risks in oil pipelines using a geographical information system. The system covers a 48.5 km long section of the So Paulo to Brasilia (OSBRA) oil pipeline, which crosses three municipalities in the northeast region of the So Paulo state (Brazil) and represents an area of 205.8 km(2). The spatial database was created using geo-processing procedures, surface and intrusive investigations and geotechnical reports. The risk assessment was based mainly on qualitative models (relative numeric weights and multicriteria decision analysis) and considered pluvial erosion, slope movements, soil corrosion and third party activities. The maps were produced at a scale of 1:10,000.

Risk of Giardia infection for drinking water and bathing in a peri-urban area in Sao Paulo, Brazil

A high incidence of waterborne diseases is observed worldwide and in order to address contamination problems prior to an outbreak, quantitative microbial risk assessment is a useful tool for estimating the risk of infection. The objective of this paper was to assess the probability of Giardia infection from consuming water from shallow wells in a peri-urban area. Giardia has been described as an important waterborne pathogen and reported in several water sources, including ground waters. Sixteen water samples were collected and examined according to the US EPA (1623, 2005). A Monte Carlo method was used to address the potential risk as described by the exponential dose response model. Giardia cysts occurred in 62.5% of the samples (0.1-36.1 cysts/l). A median risk of 10-1 for the population was estimated and the adult ingestion was the highest risk driver. This study illustrates the vulnerability of shallow well water supply systems in peri-urban areas.

A Dynamic Analysis of Tuberculosis Dissemination to Improve Control and Surveillance

Background: Detailed analysis of the dynamic interactions among biological, environmental, social, and economic factors that favour the spread of certain diseases is extremely useful for designing effective control strategies. Diseases like tuberculosis that kills somebody every 15 seconds in the world, require methods that take into account the disease dynamics to design truly efficient control and surveillance strategies. The usual and well established statistical approaches provide insights into the cause-effect relationships that favour disease transmission but they only estimate risk areas, spatial or temporal trends. Here we introduce a novel approach that allows figuring out the dynamical behaviour of the disease spreading. This information can subsequently be used to validate mathematical models of the dissemination process from which the underlying mechanisms that are responsible for this spreading could be inferred. Methodology/Principal Findings: The method presented here is based on the analysis of the spread of tuberculosis in a Brazilian endemic city during five consecutive years. The detailed analysis of the spatio-temporal correlation of the yearly geo-referenced data, using different characteristic times of the disease evolution, allowed us to trace the temporal path of the aetiological agent, to locate the sources of infection, and to characterize the dynamics of disease spreading. Consequently, the method also allowed for the identification of socio-economic factors that influence the process. Conclusions/Significance: The information obtained can contribute to more effective budget allocation, drug distribution and recruitment of human skilled resources, as well as guiding the design of vaccination programs. We propose that this novel strategy can also be applied to the evaluation of other diseases as well as other social processes.

Hierarchical risk scale of agribusiness activities

This study aims to elaborate a hierarchical risk scale (HRS) of agricultural and cattle breeding activities and to classify the main agricultural crops and cattle breeding activities according to their risk levels. The research is characterized as exploratory and quantitative and was based on previous risk assessment (MARKOWITZ, 1952) and capital cost calculation (SHARPE, 1964) work for other business segments. The calculations on agricultural and cattle breeding data were processed for the period from 2000 to 2006. The used methods considers simplifications and adaptations needed to achieve the proposed objective. The final result, pioneering and embryonic, provides support to improve the management of these activities that are so essential to produce food for society.

Validation of a strategy to diagnose coronary artery disease and predict cardiac events in high-risk renal transplant candidates

Background We validated a strategy for diagnosis of coronary artery disease ( CAD) and prediction of cardiac events in high-risk renal transplant candidates ( at least one of the following: age >= 50 years, diabetes, cardiovascular disease). Methods A diagnosis and risk assessment strategy was used in 228 renal transplant candidates to validate an algorithm. Patients underwent dipyridamole myocardial stress testing and coronary angiography and were followed up until death, renal transplantation, or cardiac events. Results The prevalence of CAD was 47%. Stress testing did not detect significant CAD in 1/3 of patients. The sensitivity, specificity, and positive and negative predictive values of the stress test for detecting CAD were 70, 74, 69, and 71%, respectively. CAD, defined by angiography, was associated with increased probability of cardiac events [log-rank: 0.001; hazard ratio: 1.90, 95% confidence interval (CI): 1.29-2.92]. Diabetes (P=0.03; hazard ratio: 1.58, 95% CI: 1.06-2.45) and angiographically defined CAD (P=0.03; hazard ratio: 1.69, 95% CI: 1.08-2.78) were the independent predictors of events. Conclusion The results validate our observations in a smaller number of high-risk transplant candidates and indicate that stress testing is not appropriate for the diagnosis of CAD or prediction of cardiac events in this group of patients. Coronary angiography was correlated with events but, because less than 50% of patients had significant disease, it seems premature to recommend the test to all high-risk renal transplant candidates. The results suggest that angiography is necessary in many high-risk renal transplant candidates and that better noninvasive methods are still lacking to identify with precision patients who will benefit from invasive procedures. Coron Artery Dis 21: 164-167 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.

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.

In vitro basal cytotoxicity assay applied to estimate acute oral systemic toxicity of grandisin and its major metabolite

Preclinical investigations can start with preliminary in vitro studies before using animal models. Following this approach, the number of animals used in preclinical acute toxicity testing can be reduced. In this study, we employed an in-house validated in vitro cytotoxicity test based on the Spielmann approach for toxicity evaluation of the lignan grandisin, a candidate anticancer agent, and its major metabolite. the 4-O-demethylgrandisin, by neutral red uptake (NRU) assay, on mouse fibroblasts Balb/c 3T3 cell line. Using different concentrations of grandisin and its major metabolite (2.31; 1.16; 0.58; 0.29; 0.14; 0.07; 0.04; 0.002 mu M) in Balb/c 3T3-A31 NRU cytotoxicity assay, after incubation for 48 h, we obtained IC(50) values for grandisin and its metabolite of 0.078 and 0.043 mu M, respectively. The computed LD(50) of grandisin and 4-O-demethylgrandisin were 617.72 and 429.95 mg/kg, respectively. Both were classified under the Globally Harmonized System as category 4. Since pharmacological and toxicological data are crucial in the developmental stages of drug discovery, using an in vitro assay we demonstrated that grandisin and its metabolite exhibit distinct toxicity profiles. Furthermore, results presented in this work can contribute to reduce the number of animals required in subsequent pharmacological/toxicological studies. (C) 2010 Elsevier GmbH. All rights reserved.