Forecasting the coronavirus pandemic with help from EU projects
The whole world is currently dealing with a novel coronavirus pandemic and we all want to try to understand what the future may hold. Using computer-based models would allow us to keep up with the spread and evolution of the pandemic.
Fighting epidemics through modelling
The EPIWORK project aimed to develop a set of tools and knowledge to design infrastructures that could forecast epidemics. It resulted in the Global Epidemic and Mobility Model project (GLEAM), whose objective was to deliver the analytic and forecasting power that could minimize the impact of potentially devastating epidemics. Researchers who worked on these projects are currently using those results to try to understand how the current pandemic may spread, how it may evolve over time and how containment and prevention measures may help.
Driving ideas behind the projects
Mobility in urban societies
Back in 2009, the EPIWORK project, coordinated by the Italian Institute for Interdisciplinary Science (ISI) and the Institute’s Prof. Alessandro Vespignani, decided upon a multidisciplinary approach that focuses on the socio-demographic aspects of modern, deeply urbanized societies where mobility plays the main role. This is associated with an increased risk that infectious diseases, epidemics, outbreaks and related threats may reach global proportions.
Real-world data collection
EPIWORK, which ran from 1 February 2009 to 31 July 2013 and involved 12 teams in 8 countries, based its research on working with data collected from real-world settings. This, however, was not the first project to recognise the importance of such data. Its predecessor, Influweb.it, attempted to detect the spread of the flu in real time. This web-based project had volunteers reply to a weekly e-mail questionnaire about the state of their health and report their geographical location over a six-month period. Through their collaboration with citizens, they managed to monitor symptoms of influenza-like-illness and derive interesting conclusions, such as the fact that 90% of people with symptoms don’t even consult a doctor!
Modelling an epidemic
GLEAM provides a suite of computational tools to help create a model of how disease spreads, to understand observed epidemic patterns, and to study the effectiveness of different intervention strategies. These tools are available to researchers, healthcare professionals and policy makers.
The project combines mathematical modelling and computational science with real-world data. Researchers use real-world data on populations and human mobility to elaborate stochastic models of disease transmission. We can then use these models to develop better intervention strategies and minimise the impact of epidemics.
High performance computers make all of this possible. They allow researchers to produce computer models and simulations that would otherwise not be possible. Thanks to these in-silico experiments, we can better understand typical, non-linear behaviour and tipping points of epidemics.
The model has already been thoroughly tested and validated on historical epidemic outbreaks including the 2002/2003 SARS epidemic. In 2009, GLEAM was used to produce a real time forecast of the unfolding of the H1N1 pandemic and has been adapted for Ebola.
The EPIWORK project was successfully co-funded by the FET-Proactive scheme between 2009 and 2013. FET-Open and FET Proactive are now part of the Enhanced European Innovation Council (EIC) (specifically the Pathfinder), the new home for deep-tech research and innovation in Horizon 2020, the EU funding programme for research and innovation.
It is important to know that the mentioned conclusions are still in the preliminary phase and they need to be interpreted and validated by other scientists.
Find more information here.