Josep Casanovas-Garcia

Individual-Based Modeling of Tuberculosis in a User-Friendly Interface: Understanding the Epidemiological Role of Population Heterogeneity in a City

For millennia tuberculosis (TB) has shown a successful strategy to survive, making it one of the world’s deadliest infectious diseases. This resilient behavior is based not only on remaining hidden in most of the infected population, but also by showing slow evolution in most sick people. The course of the disease within a population is highly related to its heterogeneity. Thus, classic epidemiological approaches with a top-down perspective have not succeeded in understanding its dynamics. In the past decade a few individual-based models were built, but most of them preserved a top-down view that makes it difficult to study a heterogeneous population. We propose an individual-based model developed with a bottom-up approach to studying the dynamics of pulmonary TB in a certain population, considered constant. Individuals may belong to the following classes: healthy, infected, sick, under treatment, and treated with a probability of relapse. Several variables and parameters account for their age, origin (native or immigrant), immunodeficiency, diabetes, and other risk factors (smoking and alcoholism). The time within each infection state is controlled, and sick individuals may show a cavitated disease or not that conditions infectiousness. It was implemented in NetLogo because it allows non-modelers to perform virtual experiments with a user-friendly interface. The simulation was conducted with data from Ciutat Vella, a district of Barcelona with an incidence of 67 TB cases per 100,000 inhabitants in 2013. Several virtual experiments were performed to relate the disease dynamics with the structure of the infected subpopulation (e.g., the distribution of infected times). Moreover, the short-term effect of health control policies on modifying that structure was studied. Results show that the characteristics of the population are crucial for the local epidemiology of TB. The developed user-friendly tool is ready to test control strategies of disease in any city in the short-term.

Modeling tuberculosis in Barcelona: a solution to speed-up agent-based simulations

Tuberculosis remains one of the worlds deadliest infectious diseases. About one-third of the worlds population is infected with tuberculosis bacteria. Understanding the dynamics of transmission at different spatial scales is critical to progress in its control. We present an agent-based model for tuberculosis epidemics in Barcelona, which has an observatory on this disease. Our model considers high heterogeneity within the population, including risk factors for developing an active disease, and it tracks the individual behavior once diagnosed. We incorporated the immunodeficiency and smoking/alcoholism, as well as the individuals origin (foreigner or not) for its contagion and infection as risks factors. We implemented the model in Netlogo, a useful tool for interaction with physicians. However, the platform has some computational limitations, and we propose a solution to overcome them.

A User Interface for Large-Scale Demographic Simulation

Agent-based modeling is one of the promising modeling tools that can be used in the study of population dynamics. Two of the main obstacles hindering the use of agent-based simulation in practice are its scalability when the analysis requires large-scale models as in policy research, and its ease-of-use especially for users with no programming experience. While there has been a significant work on the scalability issue, ease-of-use aspect has not been addressed in the same intensity. This paper presents a graphical user interface designed for a simulation tool which allows modelers with no programming background to specify agent-based demographic models and run them on parallel environments. The interface eases the definition of models to describe individual and group dynamics processes with both qualitative and quantitative data. The main advantage is to allow users to transparently run the models on high performance computing infrastructures.

Teaching system modelling and simulation through petri nets and arena

This paper describes our experience teaching discrete-event simulation to several Engineering branches and Computer Science students. In our courses we emphasize the importance of conceptual modelling rather than the simulation tools used to build a model. We think that in discrete-event simulation university courses it is more important to provide knowledge to students to develop and analyze conceptual models than focusing in a specific simulation tool that will be industry dependent. Focusing in conceptual modelling with the support of a well-known simulation software provide the student with skills to create a model and then translate it to any simulator. Our courses use the Petri Net (PN) methodology by incrementing the complexity of models and PN using: Place-Transition PN, Timed PN and Colored Timed PN. A PN simulator is used to analyze the conceptual model and different rules and procedures are provided to match PN conceptual model to Arena simulation software.

Simulation analysis of a dynamic ridesharing model

A dynamic ridesharing service is a system that enables drivers and riders to arrange one-time shared rides, with sufficient convenience and flexibility to be used on a daily basis. The quality of a dynamic ridesharing service is critical for commuters who need to reach their end destination on time every day. To ensure satisfactory quality, the waiting times in a ridesharing service must be low. This paper describes a dynamic ridesharing model proposal for commuters living in a small community in the Barcelona metropolitan area. The proposal solves transport problems between the community and a communication hub served by trains and buses. A survey was sent to community residents to find out whether they would be interested in the idea and willing to participate in a pilot test. A simulation model was built to determine to most suitable type of dynamic ridesharing model given the limited numbers of responses received and the heterogeneous mobility patterns of drivers and riders in the community. Reasonable good results are obtained for the morning commute but improvements are needed for the return commute in the afternoon. Further work will be required to increase the number of drivers interested in the ridesharing service.

A visualization tool based on traffic simulation for the analysis and evaluation of smart city policies, innovative vehicles and mobility concepts

The CitScale tool is a software platform for visualizing, analyzing and comparing the impacts of smart city policies based on innovative mobility concepts in urban areas. It places emphasis on new automotive vehicles aimed at reducing traffic or environmental impacts. This paper introduces this traffic simulation-based tool, and two case studies developed for different scenarios in Barcelona City are briefly presented to demonstrate the capabilities of the tool when it is combined with microscopic traffic simulation software. The first case presents an extensive evaluation of new innovative vehicles (electric vehicles, bikes and three-wheeled scooters) and mobility concepts (trip-sharing). In the second one, data provided by connected cars is analyzed in order to compare different developed navigation strategies and how they affect the city. Finally, some of the obtained results from both cases are concisely presented in order to show the potential of the proposed tool.

ORCHESTRA: an asynchronous wait-free distributed GVT algorithm

Taking advantage of computing capabilities offered by modern parallel and distributed architectures is fundamental to run large-scale simulation models based on the Parallel Discrete Event Simulation (PDES) paradigm. By relying on this computing organization, it is possible to effectively overcome both the power and the memory wall, which are core limiting aspects to deliver high-performance simulations. This is even more the case when relying on the speculative Time Warp synchronization protocol, which could be particularly memory greedy. At the same time, some form of coordination, such as the computation of the Global Virtual Time (GVT), is required by Time Warp Systems. These coordination points could easily become the bottleneck of large-scale simulations, hindering an efficient exploitation of the computing power offered by large supercomputing facilities. In this paper we present ORCHESTRA, a coordination algorithm which is both wait-free and asynchronous. The nature of this algorithm allows any computing node to carry on simulation activities while the global agreement is reached, thus offering an effective building block to achieve scalable PDES. We claim that the general organization of ORCHESTRA could be adopted by different high-performance computing applications, thus paving the way to a more effective usage of modern computing infrastructures.

Programming agent-based demographic models with cross-state and message-exchange dependencies: a study with speculative PDES and automatic load-sharing

Agent-based modeling and simulation is a versatile and promising methodology to capture complex interactions among entities and their surrounding environment. A great advantage is its ability to model phenomena at a macro scale by exploiting simpler descriptions at a micro level. It has been proven effective in many fields, and it is rapidly becoming a de-facto standard in the study of population dynamics. In this article we study programmability and performance aspects of the last-generation ROOT-Sim speculative PDES environment for multi/many-core shared-memory architectures. ROOT-Sim transparently offers a programming model where interactions can be based on both explicit message passing and in-place state accesses. We introduce programming guidelines for systematic exploitation of these facilities in agent-based simulations, and we study the effects on performance of an innovative load-sharing policy targeting these types of dependencies. An experimental assessment with synthetic and real-world applications is provided, to assess the validity of our proposal.

Approaching parallel computing to simulating population dynamics in demography

We have developed a web-based parallel agent-based simulation tool for demography.The tool has been designed for social scientists who have no programming experience.The user interface uses commonly used modelling techniques in demography.The tool can be accessed by public through web-based interface for wider user tests.Experiments show the performance of the tool for large scale simulations is good. Agent-based modelling and simulation is a promising methodology that can be applied in the study of population dynamics. The main advantage of this technique is that it allows representing the particularities of the individuals that are modeled along with the interactions that take place among them and their environment. Hence, classical numerical simulation approaches are less adequate for reproducing complex dynamics. Nowadays, there is a rise of interest on using distributed computing to perform large-scale simulation of social systems. However, the inherent complexity of this type of applications is challenging and requires the study of possible solutions from the parallel computing perspective (e.g., how to deal with fine grain or irregular workload). In this paper, we discuss the particularities of simulating populating dynamics by using parallel discrete event simulation methodologies. To illustrate our approach, we present a possible solution to make transparent the use of parallel simulation for modeling demographic systems: Yades tool. In Yades, modelers can easily define models that describe different demographic processes with a web user interface and transparently run them on any computer architecture environment thanks to its demographic simulation library and code generator. Therefore, transparency is provided by two means: the provision of a web user interface where modelers and policy makers can specify their agent-based models with the tools they are familiar with, and the automatic generation of the simulation code that can be executed in any platform (cluster or supercomputer). A study is conducted to evaluate the performance of our solution in a High Performance Computing environment. The main benefit of this outline is that our findings can be generalized to problems with similar characteristics to our demographic simulation model.

Load-Sharing Policies in Parallel Simulation of Agent-Based Demographic Models

Execution parallelism in agent-Based Simulation (ABS) allows to deal with complex/large-scale models. This raises the need for runtime environments able to fully exploit hardware parallelism, while jointly offering ABS-suited programming abstractions. In this paper, we target last-generation Parallel Discrete Event Simulation (PDES) platforms for multicore systems. We discuss a programming model to support both implicit (in-place access) and explicit (message passing) interactions across concurrent Logical Processes (LPs). We discuss different load-sharing policies combining event rate and implicit/explicit LPs’ interactions. We present a performance study conducted on a synthetic test case, representative of a class of agent-based models.