Cristina Montañola-Sales

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.

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.

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.

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.

Analysis and optimization of a demographic simulator for parallel environments

In the past years, the advent of multi-core machines has led to the need for adapting current simulation solutions to modern hardware architectures. In this poster, we present a solution to exploit multicore shared-memory capacities in Yades, a parallel tool for running socio-demography dynamic simulations. We propose to abandon the single-threaded programming approach addresses in Yades by using ROOT-Sim, a library which allows to apply discrete event simulation to parallel environments profiting share-memory capabilities. As a result of this new approach, our results show the improvement in Yades performance and scalability.

Simulation of the airbus 380 evacuation

A minute and a half, this is the given time to evacuate the aircraft in case of need after an emergency landing. This period is fixed no matter how many passengers are on board, no matter other considerations. The aircraft must be evacuated within 90 seconds. To improve current strategies and protocols for efficient evacuation, a comprehensive study of passengers behavior should be conducted. This study includes the analyses of different scenarios that could happen during an accident and the definition each aircrafts characteristics, taking into account external factors that may affect the evacuation time. To develop such a study nowadays, object-oriented simulation tools are used. Simulation allows us to create a close system model, so every different scenario can be studied. We present a model to analyze different scenarios for evacuating an airbus 380. Our aim is to determine the best scenarios to be considered in those situations.

Formal and operational validation of a bus stop public transport network micro simulation

We present a detailed simulation model with the purpose of analyzing the congestion and interaction between bus lines and passengers at stops. Our main goal is to perform a complete validation of a simulation model formalized in a standard language in order to use it as a basis to perform more complex experiments. The basis of the model is a queuing model that leads us to perform an operational validation. Since the model is completely represented using a formal language, the specialist can perform a formal validation of the model previously to any implementation. Thanks to the modular structure of the formal language used to define the model, the model can be easily expanded to represent more complex systems. Due to a formal representation, the implementation process can be done automatically implying that analysts should only be concerned about the correct definition of the diagrams that represent the model behavior.

Validation of a new multiclass mesoscopic simulator based on individual vehicles for dynamic network loading

The dynamic network loading problem is crucial for performing dynamic traffic assignment. It must reproduce the network flow propagation, while taking into account the time and a variable traffic demand on each path of the network. In this paper, we consider a simulation-based approach for dynamic network loading as the best-suited option. We present a multiclass multilane dynamic network loading model based on a mesoscopic scheme that uses a continuous-time link-based approach with a complete demand discretization. In order to demonstrate the correctness of the model, we computationally validate the proposed simulation model using a variety of laboratory tests. The obtained results look promising, showing the models ability to reproduce multilane multiclass traffic behaviors for medium-size urban networks.