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.
Authors
- Mohammad Hamdaqa (ORCID: https://orcid.org/0000-0003-4927-2755)
- Michalis Famelis (ORCID: https://orcid.org/0000-0003-3545-0274)
- Marios Fokaefs (ORCID: https://orcid.org/0000-0003-3623-5015)
- Bruno Curzi-Laliberté
Institutions
- York University (CA)
- Polytechnique Montréal (CA)
- Université de Montréal (CA)
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