|Title||Agent-model based on flame GPU for assessing pupal productivity of the transmitting vector of Aedes aegypti infectious diseases|
|Publication Type||Conference Proceedings|
|Year of Conference||2019|
|Authors||Montes-de-Oca, E, Suppi, R, De Giusti, L, Naiouf, M|
|Conference Name||International Conference on Modeling and Applied Simulation 2019 (MAS19)|
|Publisher||DIME, Università di Genova|
|Conference Location||Lisbon, Portugal|
|ISBN Number||ISBN 978-88-85741-30-0 (paperback)|
|ISBN||ISBN 978-88-85741-29-4 (pdf)|
|Keywords||agent-based model, FLAME GPU, GPU, Infectious Diseases|
Dengue, Zika and chikungunya are among the infectious diseases that have emerged in recent years.
The common denominator to these three is their transmitting vector: the Aedes aegypti mosquito. Due to sanitary reasons, it is highly important that the vector for transmitting these diseases be controlled through the implementation of strategies specifically designed for each situation. In this article, the creation of an agent-based simulation model that allows assessing control strategies and policies through parallel computing on GPU is proposed. High Performance Computing is necessary due to the large volume of data that has to be processed (hundreds of thousands of agents) to obtain results within an acceptable time frame.
Model validation was done at small scale with an analogous model on CPU and NetLogo and using data from an real system. In this article, the implementation, scalability and potential of this model as decision support system (DSS) are presented.