EpiMDE: A-Model Driven Engineering Platform for Epidemiological Modeling

Modeling is a critical step in studying epidemics. It allows us to better understand and predict the progression of a disease, design interventions such as vaccination, and assess their impact. Current epidemics are modeled using compartmental and mathematical models. While these are enough to achieve the primary goal of modeling, they suffer from shortcomings with respect to communicating and sharing the models, comparison and validation, and reproducibility. In this work, we propose the use of model-driven software engineering principles, to better represent disease models and facilitate the model management operations. We present an extensible metamodel for epidemics and an integrated development environment to allow epidemiologists to create and manage their models and simulations. We present the use of our platform on a COVID-19 model, where we show that the resulting model is more concise yet structurally and functionally equivalent to the original.

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Publication Details

Published
2024-09-22
DOI
https://doi.org/10.1145/3640310.3674104
Citations
2
Primary Topic
demographic modeling and climate adaptation
Type
article
Field-Weighted Citation Impact
0.98
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article

EpiMDE: A-Model Driven Engineering Platform for Epidemiological Modeling

Mohammad Hamdaqa, Michalis Famelis, Marios Fokaefs, Bruno Curzi-Laliberté
2 citations
demographic modeling and climate adaptation
0.98
article

EpiMDE: A-Model Driven Engineering Platform for Epidemiological Modeling

Mohammad Hamdaqa, Michalis Famelis, Marios Fokaefs, Bruno Curzi-Laliberté
article en
2 citations

Abstract

Modeling is a critical step in studying epidemics. It allows us to better understand and predict the progression of a disease, design interventions such as vaccination, and assess their impact. Current epidemics are modeled using compartmental and mathematical models. While these are enough to achieve the primary goal of modeling, they suffer from shortcomings with respect to communicating and sharing the models, comparison and validation, and reproducibility. In this work, we propose the use of model-driven software engineering principles, to better represent disease models and facilitate the model management operations. We present an extensible metamodel for epidemics and an integrated development environment to allow epidemiologists to create and manage their models and simulations. We present the use of our platform on a COVID-19 model, where we show that the resulting model is more concise yet structurally and functionally equivalent to the original.

York University (CA), Polytechnique Montréal (CA), Université de Montréal (CA)
Good health and well-being
Openalex Percentile: Top 21%
demographic modeling and climate adaptation
0.98
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EpiMDE: A-Model Driven Engineering Platform for Epidemiological Modeling — Mohammad Hamdaqa, Michalis Famelis, et al. · (2024) | TGRS Research Map | TGRS