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http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/12695
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Titre: | Epidemic simulation framework : design, implementation, and accracy analysis |
Auteur(s): | Idir, Amel Kroudir, Nacer Otmani, Abdeldjallal Nassim (Supervisor) |
Mots-clés: | Susceptible-Infectious-Recovered (SIR) model Epidemic desease simulation |
Date de publication: | 2023 |
Editeur: | Université M’hamed Bougara de Boumerdes : Institut de Genie Electrique et Electronique |
Résumé: | Large-scale decisions can significantly impact the health, security, and economic well-
being of a society, making it essential to provide appropriate tools and data for informed
decision-making. However, in situations of uncertainty as witnessed with COVID-19, it is
prudent to utilize simulation tools that can project future scenarios and assess their effects
on a population. With the computational capabilities available today, population
simulations can closely mimic real-world dynamics. By setting parameters and observing
their impact, decision-makers can evaluate different scenarios and assess their
consequences on the population.
In this study, we present an Epidemic Simulation Framework to replicate the spread of
infectious diseases within a population using the Susceptible-Infectious-Recovered (SIR)
model on a 2D plane, supported by a software application tool. This tool serves as a
valuable resource for researchers, policymakers, and the general public by allowing them
to create and manipulate populations with varying sizes and characteristics, incorporating
parameters such as vaccination, quarantine, and infection rates. By utilizing this tool,
users can proficiently introduce infectious individuals and closely monitor the subsequent
dynamics of disease spread. The tool not only offers real-time data concerning the
distribution of individuals across different disease stages but also presents informative
graphs and charts that vividly depict the progression of the epidemic.
To evaluate the accuracy of this framework, we gathered authentic data on the
dissemination of COVID-19 in Algeria. By comparing this data with the simulation
results generated by the tool, we observed a noteworthy correlation between the two. This
substantiates a strong correspondence between the simulation outcomes and the actual
advancement of the disease. |
Description: | 60p. |
URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/12695 |
Collection(s) : | Computer
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