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

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.


Study area, Ilha do Governador. (a) Satellite image (Google Earth); (b) map of census tracts; (c) simulated map generated by DengueME. Highlighted blue areas are the sites of application of adulticide [63].
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ijerph-13-00920-f008: Study area, Ilha do Governador. (a) Satellite image (Google Earth); (b) map of census tracts; (c) simulated map generated by DengueME. Highlighted blue areas are the sites of application of adulticide [63].

Mentions: An important issue is the development of standardized metrics for monitoring and evaluating the performance of control programs [48]. Alternative strategies, such as spatially-localized chemical treatments to reduce mosquito density, could be better targeted, and the resource allocation could be optimized if computer-simulated scenarios were applied. Using DengueME, we created different intervention scenarios to explore the impact of locally-applied intervention strategies on the local and global density of Ae. aegypti. Ilha do Governador, an island in the city of Rio de Janeiro, Brazil, was used as the study area (Figure 8). All of the stages of the vector life cycle are explicitly represented through a compartmental model and using differential equations, and the transition rates between the stages are regulated by temperature. The model and its equations are described in detail by Lana et al. (2014) [56]. A map of census tracts, obtained from IBGE (Brazilian Institute of Geography and Statistics, 2010), was used to define the regions for adulticide application, based on Luz et al. (2009) [111]. The pink area in Figure 8b was chosen to simulate the intervention, due to its denser human population. Figure 8c shows the three quadrants where the ultra-low volume adulticide, with maximum efficacy of 0.9 and an average persistence of one day, was applied.


DengueME: A Tool for the Modeling and Simulation of Dengue Spatiotemporal Dynamics †
Study area, Ilha do Governador. (a) Satellite image (Google Earth); (b) map of census tracts; (c) simulated map generated by DengueME. Highlighted blue areas are the sites of application of adulticide [63].
© Copyright Policy
Related In: Results  -  Collection

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

ijerph-13-00920-f008: Study area, Ilha do Governador. (a) Satellite image (Google Earth); (b) map of census tracts; (c) simulated map generated by DengueME. Highlighted blue areas are the sites of application of adulticide [63].
Mentions: An important issue is the development of standardized metrics for monitoring and evaluating the performance of control programs [48]. Alternative strategies, such as spatially-localized chemical treatments to reduce mosquito density, could be better targeted, and the resource allocation could be optimized if computer-simulated scenarios were applied. Using DengueME, we created different intervention scenarios to explore the impact of locally-applied intervention strategies on the local and global density of Ae. aegypti. Ilha do Governador, an island in the city of Rio de Janeiro, Brazil, was used as the study area (Figure 8). All of the stages of the vector life cycle are explicitly represented through a compartmental model and using differential equations, and the transition rates between the stages are regulated by temperature. The model and its equations are described in detail by Lana et al. (2014) [56]. A map of census tracts, obtained from IBGE (Brazilian Institute of Geography and Statistics, 2010), was used to define the regions for adulticide application, based on Luz et al. (2009) [111]. The pink area in Figure 8b was chosen to simulate the intervention, due to its denser human population. Figure 8c shows the three quadrants where the ultra-low volume adulticide, with maximum efficacy of 0.9 and an average persistence of one day, was applied.

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.