Small-data Early warNing System for viral pathogens
In puBLic hEalth
SENSIBLE
PRIN 2022 PNRR

PROJECT CONCEPT

Time span: December 2023 - November 2025.

In March 2020, COVID-19 was declared a global pandemic, spurring intense research efforts. Genomic surveillance emerged as a crucial defense against the virus.
The SENSIBLE project, supported by the Italian Ministry of University and Research (through NextGeneration EU funding), aims to develop methods for analyzing viral genomes and implement early warning information systems based on data-driven analysis, exploiting data from past epidemics for validation.
SENSIBLE will create an integrated framework for genomic surveillance of viral pathogens, utilizing data-driven and knowledge-based analyses. By leveraging knowledge from COVID-19, it seeks to enhance understanding of viral pathogens and aid healthcare decision-making.

Objectives

Data-driven Methods

Derive effective methods for data-driven identification of emerging viral pathogens

Surveillance

Build an objective framework for genomic surveillance in current and future epidemics

Warning

Implement an early warning system, to assist decision-making in healthcare

Methodologies

SENSIBLE will explore and harness data from different domains of interest, including: analyses of available data, mapping of equivalent/matched information from similar pathogens, computation or prediction of novel features and properties of the virus under study. The framework developed by SENSIBLE will feature four tasks:

Data-driven analysis of pathogens’ evolution

The project partners will leverage previously developed methods and tools for the genomic surveillance. The range of applications of these methods wil be extended to identify minimal subsets of actionable data, and evaluate their validity and robustness.

Data and knowledge-based analysis

To translate viral evolutionary dynamics into a collection of “epidemiologically-relevant” annotations of the viral genome, different sources of information will be gathered. Annotations available from existing resources will be retrieved and integrated into an internal knowledge base; missing data will be computed (via bioinformatics tools) or predicted (via automatic learning procedures).

Ranking and prioritization

Based on the evolutionary observations and the detailed functional annotations from previous tasks, a prioritization score will be computed to assign a “level of concern” to emerging viral pathogens and or to novel viral lineages. The score will be exploited to develop a ranking system, which will be evaluated according to the heuristics to be developed.

Validation and testing

The initial development and setup of SENSIBLE will be performed on a selection of use cases from the COVID-19 pandemic. Possible candidates to showcase the system and provide an unbiased evaluation are Monkeypox (2022), Zika (2015-2016), and Swine Influenza (2009).

Expected results

We will tackle two key epidemiological questions and identify key metrics for raising alerts and early warnings in both scenarios:

Minimal actionable data

What is the minimal amount of data production/availability required to set up an effective surveillance system? Can genomic surveillance be applied even in scarce/low resources settings?

Prioritization of emerging pathogens

If a new mutation or pattern of mutations arise in a human pathogen, how does this impact its epidemiological features?

Insights for public health

How can a genomic surveillance tool based on small viral genomes dataset help inform decisions of public health institutions?

News

  • December 1st, 2023

    The project officially starts

    Our meetings have already begun!

  • February 9th, 2024

    Our preprint on biorXiv

    Here, we present RecombinHunt, a novel, automated method for the identification of recombinant genomes purely based on a data-driven approach

  • April 17th, 2024

    Paper published on NatComm

    After a long journey, our paper describing the RecombinHunt approach, has been published on the prestigious Nature Communication journal!

  • June 7th, 2024

    CAiSE 2024

    We presented SENSIBLE in the context of the research projects of the 36th International Conference on Advanced Information Systems Engineering June 03-07 2024 Limassol, Cyprus. Check out our poster here.

  • July 2nd, 2024

    Our Press Release

    The news about our research on recombinant viruses for improving warning systems is out. See Polimi website and Unimi website, X post, Linkedin post, DEIB department post.
    Il Sole 24ore is speaking about us! See the article.

  • Follow
    our
    progress!

Meetings & Events

Our meetings PoliMi + UniMi are held once a month
DEIB department, Politecnico di Milano, starting December 20th, 2023 (our kickoff)
Presentation of SENSIBLE project to Istituto Zooprofilattico Sperimentale delle Venezie
online, December 22th, 2023
Presentation of SENSIBLE project to Dott. Daniele Focosi, Dott. Federico Maggi and Federico Gueli
online, February 7th, 2024
We will present the SENSIBLE project at the CAiSE conference, see the program here
Limassol, Cyprus, 3-7 June, 2024

Publications

Data-driven recombination detection in viral genomes
Tommaso Alfonsi, Anna Bernasconi, Matteo Chiara, Stefano Ceri
Nature Communications volume 15, Article number: 3313 (2024)
Supporting data and code for "Data-driven recombination detection in viral genomes".
Tommaso Alfonsi, Anna Bernasconi, Matteo Chiara, Stefano Ceri
Zenodo. https://zenodo.org/doi/10.5281/zenodo.8123832, published March 13th, 2024
SENSIBLE: implementing data-driven early warning systems for future viral epidemics
Anna Bernasconi, Matteo Chiara, Tommaso Alfonsi, Stefano Ceri
Proceedings of the Research Projects Exhibition Papers Presented at the 36th International Conference on Advanced Information Systems Engineering (CAiSE 2024), Limassol, Cyprus, June 3-7, 2024. CEUR Workshop Proceedings, CEUR-WS.org 2024
Impact of Omicron subvariants' mutations on B cell and T cell epitopes: A systematic data analysis
Ruba Al Khalaf, Anna Bernasconi, Pietro Pinoli
Accepted for publication in Plos One
Supporting data for "Systematic analysis of SARS-CoV-2 Omicron subvariants' impact on B and T cell epitopes".
Ruba Al Khalaf, Anna Bernasconi, Pietro Pinoli
Zenodo. https://zenodo.org/doi/10.5281/zenodo.10514577, published June 25th, 2024
Tentative publication 1
We plan on testing our approach to find viral recombination on the Influenza virus, to identify intra-segment recombination events. This work could be proposed to a journal in the computational virology area.
Tentative publication 2
We plan on preparing a retrospective study on performing a codon bias data approach for the stratification of Influenza A virus clades. This will be submitted to a journal in the bioinformatics area.
Tentative publication 3
We plan on submitting a paper describing the data collection, database schema, queries, and analytics process on influenza virus genome sequences. This will be submitted to a workshop/conference in the data modeling/bioinformatics area.

TEAM

Research Units

  • Politecnico di Milano
  • Università degli Studi di Milano

PoliMi has reached a consolidated international reputation in data modeling/integration and search tools/user interfaces for genomic data management and query answering. UniMi has long-standing experience and expertise in the development and application of bioinformatics tools for genomic research. The two units will co-design methods in the project. PoliMi will be more focused on the implementation of information technologies and user interfaces, while UniMi will contribute expertise in biology and comparative genomics.

Dr. Anna Bernasconi, PI

Assistant Professor
(Politecnico di Milano)

Prof. Matteo Chiara, co-PI

Associate Professor
(Università degli Studi di Milano)

Prof. Stefano Ceri

Full Professor
(Politecnico di Milano)

Dr. Tommaso Alfonsi

Postdoc Researcher
(Politecnico di Milano)

Dr. Alessandro Campi

Assistant Professor
(Politecnico di Milano)

Luca Cassenti

Master Student
(Politecnico di Milano)

Contact Us

To get in touch, please write to: anna.bernasconi@polimi.it