Project description
Real-time reconstruction of epidemic dynamics
The COVID-19 pandemic demonstrated the importance of understanding how pandemics spread in real time for more effective public health preparedness and response. Traditional methods that rely on reported case data can be biased or incomplete, especially in regions with limited resources. With the support of the Marie Skłodowska-Curie Actions programme, the Deep EpiDyn project proposes a different approach to epidemic monitoring through the combination of viral evolution and deep learning. Researchers aim to train models to link information on viral evolution with key epidemiological indicators such as transmission rate and infectious period. This approach promises faster, more accurate and real-time analysis, enhancing disease monitoring and preparedness.
Objective
Reconstructing epidemic dynamics in real-time has become crucial for effective disease management, as demonstrated by the COVID-19 pandemic. Traditional methods rely on epidemiological data (e.g. reported cases), which can be biased or incomplete due to variable testing policies, particularly in resource-limited settings. Instead, phylodynamics has emerged as a valuable toolkit for using viral phylogenies to understand epidemic dynamics. However, conventional phylodynamic methods rely on mathematical formulas and approximations, which are not scalable to large datasets and are time-consuming, limiting their use primarily to retrospective rather than real-time analysis.
This proposal aims to transform phylodynamics by integrating it with deep learning to bypass the cumbersome likelihood calculations, thereby facilitating real-time analysis directly from sequence data. I will develop innovative deep learning models to explore the relationships between phylogenetic trees and epidemiological parameters of viruses with epidemic potential, such as SARS-CoV-2, influenza, RSV, and mpox. These models are designed to rapidly and accurately estimate time-varying epidemiological metrics, including transmission heterogeneity, basic reproduction numbers, infectious and incubation periods.
This initiative is set to revolutionize our ability to model and comprehend infectious diseases in real-time, elevating sequence data to a critical, standalone data source. It will incorporate cross-validation with epidemiological inference from reported cases and wastewater analyses, reducing reliance on any single data source and enhancing both public health responses and infectious disease surveillance. Furthermore, by simulating incremental data collection that reflects real outbreak conditions, this project will evaluate the sensitivity of real-time estimations and determine the necessary sampling proportions to accurately represent epidemic dynamics. This approach will yield crucial
Fields of science (EuroSciVoc)
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CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2024-PF-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
OX1 2JD Oxford
United Kingdom
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.