DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics

Tiago França Melo De Lima, Raquel Martins Lana, Tiago Garcia De Senna Carneiro, Cláudia Torres Codeço, Gabriel Souza Machado, Lucas Saraiva Ferreira, Líliam César De Castro Medeiros and Clodoveu Augusto Davis Junior
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Tiago França Melo De Lima: Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil
Raquel Martins Lana: Programa Pós-Graduação em Epidemiologia em Saúde Pública, Escola Nacional de Saúde Pública Sérgio Arouca (ENSP), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ 21045-900, Brasil
Tiago Garcia De Senna Carneiro: Departamento de Computação (DECOM), Instituto de Ciências Exatas e Biológicas (ICEB), Universidade Federal de Ouro Preto (UFOP) - Campus Morro do Cruzeiro, Ouro Preto, MG 35400-000, Brasil
Cláudia Torres Codeço: Programa de Computação Científica (PROCC), Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, RJ 21045-900, Brasil
Gabriel Souza Machado: Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil
Lucas Saraiva Ferreira: Departamento de Computação e Sistemas (DECSI), Instituto de Ciências Exatas e Aplicadas (ICEA), Universidade Federal de Ouro Preto (UFOP) - Campus João Monlevade, João Monlevade, MG 35931-008, Brasil
Líliam César De Castro Medeiros: Instituto de Ciência e Tecnologia, Universidade Estadual Paulista Júlio de Mesquita Filho (UNESP), São José dos Campos, SP 12247-004, Brasil
Clodoveu Augusto Davis Junior: Departamento de Ciência da Computação (DCC), Instituto de Ciências Exatas (ICEx), Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, MG 31270-010, Brasil

IJERPH, 2016, vol. 13, issue 9, 1-21

Abstract: The prevention and control of dengue are great public health challenges for many countries, particularly since 2015, as other arboviruses have been observed to interact significantly with dengue virus. Different approaches and methodologies have been proposed and discussed by the research community. An important tool widely used is modeling and simulation, which help us to understand epidemic dynamics and create scenarios to support planning and decision making processes. With this aim, we proposed and developed DengueME, a collaborative open source platform to simulate dengue disease and its vector’s dynamics. It supports compartmental and individual-based models, implemented over a GIS database, that represent Aedes aegypti population dynamics, human demography, human mobility, urban landscape and dengue transmission mediated by human and mosquito encounters. A user-friendly graphical interface was developed to facilitate model configuration and data input, and a library of models was developed to support teaching-learning activities. DengueME was applied in study cases and evaluated by specialists. Other improvements will be made in future work, to enhance its extensibility and usability.

Keywords: modeling; simulation; dengue; Aedes aegypti; framework; spatiotemporal; model; DengueME (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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