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

Author

Listed:
  • 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)

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.

Suggested Citation

  • 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 & Clodoveu A, 2016. "DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics," IJERPH, MDPI, vol. 13(9), pages 1-21, September.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:9:p:920-:d:78252
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    Cited by:

    1. Peter Congdon, 2016. "Spatiotemporal Frameworks for Infectious Disease Diffusion and Epidemiology," IJERPH, MDPI, vol. 13(12), pages 1-4, December.

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