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

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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.

No MeSH data available.


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Compartmental model SIR-SI, where the human population is represented by three compartments: susceptible (Sh), infectious (Ih) and removed (Rh); and the mosquito population by two compartments: susceptible (Sv) and infectious (Iv).
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ijerph-13-00920-f005: Compartmental model SIR-SI, where the human population is represented by three compartments: susceptible (Sh), infectious (Ih) and removed (Rh); and the mosquito population by two compartments: susceptible (Sv) and infectious (Iv).

Mentions: The model library of DengueME offers a set of models that can be used for pedagogical purposes, to study the spatiotemporal dynamics of dengue transmission and vector ecology. As an example, a SIR-SI (Susceptible-Infectious-Removed – Susceptible-Infectious) model based on the one proposed by Nishiura (2006) [106] was developed. The conceptual model is represented in Figure 5. Human and vector populations are described using a compartmental model, where each compartment represents the amount of population in a given state (susceptible, infectious and removed). One assumption is that once a vector is infected, it remains infectious until the end of the simulation. As a simplification, the populations of humans and mosquitoes were kept constant throughout the simulation, i.e., the population dynamics of humans and mosquitoes were disregarded. The transition between states is determined by the following rates and parameters: (i) probability of transmission (vector-to-human and human-to-vector); (ii) average number of bites per mosquito per day; (iii) human recovery rate (for details about values of the parameters and equations of human and vector populations, see Nishiura (2006) [106]).


DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics †
Compartmental model SIR-SI, where the human population is represented by three compartments: susceptible (Sh), infectious (Ih) and removed (Rh); and the mosquito population by two compartments: susceptible (Sv) and infectious (Iv).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC5036753&req=5

ijerph-13-00920-f005: Compartmental model SIR-SI, where the human population is represented by three compartments: susceptible (Sh), infectious (Ih) and removed (Rh); and the mosquito population by two compartments: susceptible (Sv) and infectious (Iv).
Mentions: The model library of DengueME offers a set of models that can be used for pedagogical purposes, to study the spatiotemporal dynamics of dengue transmission and vector ecology. As an example, a SIR-SI (Susceptible-Infectious-Removed – Susceptible-Infectious) model based on the one proposed by Nishiura (2006) [106] was developed. The conceptual model is represented in Figure 5. Human and vector populations are described using a compartmental model, where each compartment represents the amount of population in a given state (susceptible, infectious and removed). One assumption is that once a vector is infected, it remains infectious until the end of the simulation. As a simplification, the populations of humans and mosquitoes were kept constant throughout the simulation, i.e., the population dynamics of humans and mosquitoes were disregarded. The transition between states is determined by the following rates and parameters: (i) probability of transmission (vector-to-human and human-to-vector); (ii) average number of bites per mosquito per day; (iii) human recovery rate (for details about values of the parameters and equations of human and vector populations, see Nishiura (2006) [106]).

View Article: PubMed Central - PubMed

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.

No MeSH data available.


Related in: MedlinePlus