Multi-agent systems in epidemiology: a first step for computational biology in the study of vector-borne disease transmission

<p>Abstract</p> <p>Background</p> <p>Computational biology is often associated with genetic or genomic studies only. However, thanks to the increase of computational resources, computational models are appreciated as useful tools in many other scientific fields. Such modeling systems are particularly relevant for the study of complex systems, like the epidemiology of emerging infectious diseases. So far, mathematical models remain the main tool for the epidemiological and ecological analysis of infectious diseases, with SIR models could be seen as an implicit standard in epidemiology. Unfortunately, these models are based on differential equations and, therefore, can become very rapidly unmanageable due to the too many parameters which need to be taken into consideration. For instance, in the case of zoonotic and vector-borne diseases in wildlife many different potential host species could be involved in the life-cycle of disease transmission, and SIR models might not be the most suitable tool to truly capture the overall disease circulation within that environment. This limitation underlines the necessity to develop a standard spatial model that can cope with the transmission of disease in realistic ecosystems.</p> <p>Results</p> <p>Computational biology may prove to be flexible enough to take into account the natural complexity observed in both natural and man-made ecosystems. In this paper, we propose a new computational model to study the transmission of infectious diseases in a spatially explicit context. We developed a multi-agent system model for vector-borne disease transmission in a realistic spatial environment.</p> <p>Conclusion</p> <p>Here we describe in detail the general behavior of this model that we hope will become a standard reference for the study of vector-borne disease transmission in wildlife. To conclude, we show how this simple model could be easily adapted and modified to be used as a common framework for further research developments in this field.</p

Asymptomatic internal carotid artery stenosis and cerebrovascular risk stratification

Background The purpose of this study was to determine the cerebrovascular risk stratification potential of baseline degree of stenosis, clinical features, and ultrasonic plaque characteristics in patients with asymptomatic internal carotid artery (ICA) stenosis. Methods This was a prospective, multicenter, cohort study of patients undergoing medical intervention for vascular disease. Hazard ratios for ICA stenosis, clinical features, and plaque texture features associated with ipsilateral cerebrovascular or retinal ischemic (CORI) events were calculated using proportional hazards models. Results A total of 1121 patients with 50% to 99% asymptomatic ICA stenosis in relation to the bulb (European Carotid Surgery Trial [ECST] method) were followed-up for 6 to 96 months (mean, 48). A total of 130 ipsilateral CORI events occurred. Severity of stenosis, age, systolic blood pressure, increased serum creatinine, smoking history of more than 10 pack-years, history of contralateral transient ischemic attacks (TIAs) or stroke, low grayscale median (GSM), increased plaque area, plaque types 1, 2, and 3, and the presence of discrete white areas (DWAs) without acoustic shadowing were associated with increased risk. Receiver operating characteristic (ROC) curves were constructed for predicted risk versus observed CORI events as a measure of model validity. The areas under the ROC curves for a model of stenosis alone, a model of stenosis combined with clinical features and a model of stenosis combined with clinical, and plaque features were 0.59 (95% confidence interval [CI] 0.54-0.64), 0.66 (0.62-0.72), and 0.82 (0.78-0.86), respectively. In the last model, stenosis, history of contralateral TIAs or stroke, GSM, plaque area, and DWAs were independent predictors of ipsilateral CORI events. Combinations of these could stratify patients into different levels of risk for ipsilateral CORI and stroke, with predicted risk close to observed risk. Of the 923 patients with <70% stenosis, the predicted cumulative 5-year stroke rate was <5% in 495, 5% to 9.9% in 202, 10% to 19.9% in 142, and <20% in 84 patients. Conclusion Cerebrovascular risk stratification is possible using a combination of clinical and ultrasonic plaque features. These findings need to be validated in additional prospective studies of patients receiving optimal medical intervention alone. Copyright © 2010 by the Society for Vascular Surgery