FDS Research Groups on COVID-19
Over the last few weeks breaking news on the spread of COVID-19 are continuously flooding us through media and social media. People around the world impatiently wait for the daily news from the official authorities and tensely browse social media in the hope to read about a big scientific discovery that allows to flatten the COVID-19 pandemic.
Data scientists have taken on this important challenge and are intensely working on approaching the COVID-19 pandemic from a data science perspective.
An increasing amount of data is available day by day, but a critical issue is about whether the available data is enough to draw conclusions. Unfortunately, data quality is not perfect: data collected from different sources are often partial and dirty and difficult to harmonize. Nevertheless, data scientists from different fields, including statistics, computer science, mathematics, engineering, and epidemiology are closely working together to draw some data-driven results that can help the fight against the COVID-19 pandemic and provide policy recommendation.
Aa members of the Florence Center for Data Science, we want to contribute to the discussion, by creating this web-page where we aim to provide a constantly up-to- date review of the existing working groups on COVID-19, in Italy and abroad, and the work that data scientists are producing through papers, technical reports and software. We aim to scientifically contribute to the debate on the COVID-19 pandemic by sharing and publishing our own work. A group of us are analyzing data on the COVID-19 by using predictive models, which may provide useful insights on the on the COVID-19 pandemic. An important objective of our research group is to clearly explain advantages and drawbacks of the available data, and the assumptions underlying the analyses and their implications, and thus, to clarify how results should be interpreted and the messages we can get from them.
FDS & Unifi activity on COVID-19
- Covid-19-@DiSIA research group from the Disia Department
- Snap4cyty has set three interesting dashboards to monitor national and regional (see also here) and Tuscan trends
- The Global Optimization Laboratory “Gerardo Poggiali” is collecting proposals on how can we help for COVID-19 emergency
- Luigi Brugnano (DIMAI) together with Felice Iavernaro webpage on Forecast of the COVID-19 epidemic spread in Italy using SIR and multi-region SIR models
- Researchgate project by Duccio Fanelli (Dipartimento di Fisica e Astronomia @Unifi) Analysis and forecast of COVID-19 spreading. See also the first paper out: Fanelli, D., & Piazza, F. (2020). Analysis and forecast of COVID-19 spreading in China, Italy and France. Chaos, Solitons & Fractals, 134
Italian research groups on COVID-19
- @Stat.group19 Facebook group
- @Analisi Numerica e Statistica Dati Covid-19 Facebook group
- @Covid-19&Mobility Facebook group
- @PhysicistsAgainstSARSCoV2 Facebook group
- Renato Guseo‘s webpage @Unipd
- Leonardo Egidi & Nicola Torelli research page on Covid-19 spreading outbreak
The Special Issue of the Statistica e Società journal on Covid-19 is out.
Give a look here
On April 2, attend the COVID-19 Data Science Zoomposium organised by the Department of Biostatistics, Harvard TH Chan School of Public Health.
Info on how to join the meeting here
Announcement and call for participation at Real-time Epidemic DatathonReal-time Epidemic Datathon is a collective open-source real-time forecasting challenge aimed at joining forces to push modeling limits further for real-time epidemic forecasting at large scale.
Participating teams can submit predictions of COVID-19 case evolutions in different countries and
evaluate/compare their modeling approaches.
Everyone can join and contribute!
The Covid-19 Open Research Dataset is a free, open resource for the Global Research Community that gathers the largest collection of scientific publications related to the Coronavirus pandemic, including over 44 thousand articles (over 29,000 with full text) of peer-reviewed journals and sources such as bioRxiv and medRxiv.
Kaggle is hosting the COVID-19 Open Research Dataset Challenge (CORD-19) to develop text and data mining tools that can help the medical community develop answers to high priority scientific questions