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The contribution of open science in the fight against Coronavirus

Coronavirus, data science, Computational epidemiology, biology, artificial intelligence, machine learning, data visualization

Computational epidemiology and biology, artificial intelligence, machine learning and data visualization provide important contributions for the monitoring and management of the Covid-19 pandemic. With this awareness, Intesa Sanpaolo Innovation Center has analyzed a lots of publications on Covid19, created thanks to the contribution of new scientific disciplines that are proving to be of fundamental importance in crisis management, facilitating international and interdisciplinary collaboration.

The interdisciplinary teams of the Innovation Center - with experts in economics, management engineering, electronic engineering, computer science, physics, biology and digital graphics - who work daily with the latest scientific and technological innovations, in recent weeks have highlighted the most significant studies in the fight at Covid19, showing how the spread of the virus is improving the way of 'doing science', giving a strong boost to open science, with a marked increase in data sharing (open data), publications (open pubblication) and training courses (open educational source).

In this circumstance, the Innovation Center is proving to be an ideal structure for collaborating with scientists and doctors and dealing with the emergency in a coordinated way. In fact, Artificial Intelligence crosses heterogeneous data, from telephone cells to satellite observations to obtain hyper-precise demographic schemes on infections: there are hospitals that in this way foresee the arrival peaks of patients, while others quickly identify the severity of the patients.

Added to this, there is the "data visualization", the graphic and interactive representation of the data. Even humanoid robots can help. They can move easily in areas at risk and, no less important, they can bring psychological support to patients. For example by connecting them with relatives at home.

Please, find below a selection of publications on Coronavirus

London School of Hygiene & Tropical Medicine, stochastic model of virus transmission

https://www.thelancet.com/pdfs/journals/langlo/PIIS2214-109X(20)30074-7.pdf

Hong Kong University, study on the importance and effectiveness of 'non-pharmaceutical' measures

https://wwwnc.cdc.gov/eid/article/26/5/19-0995_article

Bradford Lab of the Fred Hutchinson Cancer Research Center in Seattle, genomic sequencing and evolution dynamics of the virus

https://bedford.io/blog/

Towards Data Science and Wired, use of artificial intelligence and data science to fight the virus

https://towardsdatascience.com/how-to-fight-the-coronavirus-with-ai-and-data-science-b3b701f8a08a

https://www.wired.com/story/chinese-hospitals-deploy-ai-help-diagnose-covid-19/

Coronavirus Dashboard COVID-19 Global Cases by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University

https://www.arcgis.com/apps/opsdashboard/index.html#/bda7594740fd40299423467b48e9ecf6

Article by Professor Giancarlo Ruffo on Big Data and Coronavirus

https://blog.certimetergroup.com/it/articolo/data_analysis/big-data-coronavirus-usare-scienza-dati-prevedere-diffusione-epidemia

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