An Agent-Based Model for assessment of Aedes Aegypti pupal productivity

Borges, Francisco; Gutierrez-Milla, Albert; Suppi, Remo; Luque, Emilio; Arduíno, Marylene de Brito

doi:10.1109/wsc.2015.7408161

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Albopictus mosquitoes which apart from being dengue vectors, are responsible for spreading other pathogens such as Zika, yellow fever, chikungunya, and others [ 24 , 32 , 62 , 69 , 70 , 71 , 72 ]. Ten studies modeled dengue disease using either ABM or other modeling techniques as represented in Table A1 in Appendix C [ 14 , 25 , 26 , 73 , 74 , 75 , 76 , 77 , 78 ]. Eighteen studies have considered climatic factors in modeling the diseases, thirteen studies have involved environmental factors in modeling the diseases, out of which, eleven studies have included both climatic and environmental factors.…”

Section: Resultsmentioning

confidence: 99%

Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models

Pascoe

Clemen

Bradshaw

et al. 2022

IJERPH

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The study sought to review the works of literature on agent-based modeling and the influence of climatic and environmental factors on disease outbreak, transmission, and surveillance. Thus, drawing the influence of environmental variables such as vegetation index, households, mosquito habitats, breeding sites, and climatic variables including precipitation or rainfall, temperature, wind speed, and relative humidity on dengue disease modeling using the agent-based model in an African context and globally was the aim of the study. A search strategy was developed and used to search for relevant articles from four databases, namely, PubMed, Scopus, Research4Life, and Google Scholar. Inclusion criteria were developed, and 20 articles met the criteria and have been included in the review. From the reviewed works of literature, the study observed that climatic and environmental factors may influence the arbovirus disease outbreak, transmission, and surveillance. Thus, there is a call for further research on the area. To benefit from arbovirus modeling, it is crucial to consider the influence of climatic and environmental factors, especially in Africa, where there are limited studies exploring this phenomenon.

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Section: Resultsmentioning

confidence: 99%

Review of Importance of Weather and Environmental Variables in Agent-Based Arbovirus Models

Pascoe

Clemen

Bradshaw

et al. 2022

IJERPH

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“…Studying the mosquito population in different scenarios and under various conditions allows health agents to plan prevention and control tasks in connection with the vector, in an effort to reduce the number of infection sources and, therefore, reducing the transmission and dissemination of the corresponding diseases. The first version of the model was implemented on NetLogo (developed on Java) [24], which is an agentbased model simulation environment. The implemented model allows simulating a reduced number of individuals and containers, which translates to reduced areas within a city.…”

Section: Modeling and Simulationmentioning

confidence: 99%

Green High Performance Simulation for AMB models of Aedes aegypti

Suppi

Gisuti

et al. 2020

JC&ST

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The increase in temperature caused by the climate change has resulted in the rapid dissemination of infectious diseases. Given the alert for the current situation, the World Health Organization (WHO) has declared a state of health emergency, highlighting the severity of the situation in some countries. For this reason, coming up with knowledge and tools that can help control and eradicate the vectors propagating these diseases is of the utmost importance. High-performance modeling and simulation can be used to produce knowledge and strategies that allow predicting infections, guiding actions and/or training health/civil protection agents. The model developed as part of this research work is aimed at assisting the decision-making process for disease prevention and control, as well as evaluating the reproduction and predicting the evolution of the Aedes aegypti mosquito, which is the transmitting vector of the dengue, Zika and chikungunya diseases. Since a large number of simulation runs are required to achieve results with statistical variability, GPU has been used. This platform has enough computational power to reduce execution time while maintaining a lower energy consumption. Different scenarios and experiments are proposed to corroborate the benefits of the architecture proposed.

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