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

The project

Time span: December 2023 - November 2025.

SENSIBLE will develop an integrated framework for genomics surveillance of human pathogens. We aim to leverage the knowledge gained on COVID-19 for building novel methods that can handle and analyze pathogens’ genome sequencing data in current and future viral epidemics, and implement an early warning system based on data-driven analysis. It will address the following three 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

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?

Timeline

  • 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

  • March 25th, 2024

    Paper accepted on NatComm

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

  • Follow
    our
    progress!

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

Research Assistant
(Politecnico di Milano)

Prof. Matteo Chiara, co-PI

Associate Professor
(Università degli Studi di Milano)

Prof. Stefano Ceri

Full Professor
(Politecnico di Milano)

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