The corona virus changes everything
Who could have imagined all this only two or three weeks ago? SARS-CoV-2 has managed to change everything, literally our whole lives, in a very, very short time. Only two weeks ago we were discussing if our second Winter School in Obergurgl could still take place. Today, the whole province of Tyrol is under quarantine.
SARS-CoV-2 has also changed life at the Hub. First, we had to skip our beloved teatime—was this really only a week ago? Then people started working from home. Finally, at the weekend, we decided to put other research on hold and redirect all our man- and womanpower to deal with the challenges that the Corona crisis poses to our society.
We are now using all the expertise and knowledge we have gained over the past years—and a lot of sparkling ideas from many brilliant minds—to deal with a society in a state of emergency.
New research in times of change
The topics remain “our” topics, but the focus has changed:
- What do the developments of the past weeks mean for our healthcare system?
- How resilient is our economy? How will we deal with this crisis?
- How can we ensure basic provision of food and other necessities? What are our supply chains?
- And how are people dealing with the crisis emotionally?
In the next couple of days, weeks, perhaps even months, our scientists will produce a multitude of insights, charts, and tables, which (after being checked carefully) will be published on our website with brief explanations.
The insights will be gained directly from current events and the vast amounts of new data being released daily.
The Hub thus continues to follow its core goals: to conduct directly applicable (Big Data) research—always for the benefit of society.
Analyzing anonymized data sets incl. ca. 9 mio patients&4,5000,000 hospital stays, research by @ElmaDervicMe and #caroladeischinger (@MedUni_Vienna) found that diabetic women at higher risk of depression than men!bit.ly/3fElRK0 @DiabetesRC 👉 pubmed.ncbi.nlm.nih.gov/32973072/ pic.twitter.com/Fai1XEFymS
N. Cao, M. Meyer, L. Thiele, O. Saukh
Pollen video library for benchmarking detection, classification, tracking and novelty detection tasks: dataset
in: DATA '20: Proceedings of the Third Workshop on Data: Acquisition To Analysis. Association for Computing Machinery, NY (2020) 23–25
Privacy-preserving machine learning for time series data
in: SenSys '20: The 18th ACM Conf on Embedded Networked Sensor Systems (2020) 813–814
F. Papst, N. Stricker, O. Saukh
Localization from activity sensor data: poster abstract
in: SenSys '20: Proceedings of the 18th Conference on Embedded Networked Sensor Systems (2020) 703–704
J. Lasser, et al.
Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes
[submitted Nov. 19, 2020]