Corona | CSH refocuses its research - CSH

Corona | CSH refocuses its research


Mar 17, 2020

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.

 


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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

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F. Papst

Privacy-preserving machine learning for time series data

in: SenSys '20: The 18th ACM Conf on Embedded Networked Sensor Systems (2020) 813–814

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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

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Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes

[submitted Nov. 19, 2020]

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Schöne Bescherung?!


News, Nov 26, 2020

Press

Lockdown: Wie man sich vom Frust befreit [print]


Bezirksblätter (österreichweit), Nov 25, 2020

Press

Wissenschaft zu Massentests: interessiert, aber skeptisch


Wiener Zeitung, Nov 25, 2020

News

Nov 25, 2020

Which measures work best? The final results

Press

Wie fix ist das Aufsperren am 7. Dezember? [print]


Neue Vorarlberger Tageszeitung, Nov 24, 2020

News

Nov 22, 2020

Blog | Elma Dervic: “Diabetic women at high risk for depression”

Publication

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

Publication

F. Papst

Privacy-preserving machine learning for time series data

in: SenSys '20: The 18th ACM Conf on Embedded Networked Sensor Systems (2020) 813–814

Publication

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

Publication

J. Lasser, et al.

Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes

[submitted Nov. 19, 2020]

News

Nov 19, 2020

New theory of social fragmentation

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Nov 5, 2020

Dealing with social media’s influence on democracy

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Nov 25, 2020

Which measures work best? The final results

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Nov 22, 2020

Blog | Elma Dervic: “Diabetic women at high risk for depression”

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Nov 19, 2020

New theory of social fragmentation

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Nov 5, 2020

Dealing with social media’s influence on democracy

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Oct 9, 2020

70% less damage in case of financial collapse? The Hub knows the trick

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Oct 8, 2020

AND THE WINNER IS: New data-driven method to fight corruption!

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Austrian “Scientists of the Year”: More funding for blue sky research!

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Aug 3, 2020

Crazy ideas, brilliant minds, good times!

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Schöne Bescherung?!


News, Nov 26, 2020

Press

Lockdown: Wie man sich vom Frust befreit [print]


Bezirksblätter (österreichweit), Nov 25, 2020

Press

Wissenschaft zu Massentests: interessiert, aber skeptisch


Wiener Zeitung, Nov 25, 2020

Press

Wie fix ist das Aufsperren am 7. Dezember? [print]


Neue Vorarlberger Tageszeitung, Nov 24, 2020

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Hoffen auf viel weniger Infektionen [print]


Tiroler Tageszeitung, Nov 24, 2020

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Wollen nicht “in eine dritte Welle stolpern” [print]


Salzburger Nachrichten, Nov 24, 2020

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Südtirol Online, Nov 23, 2020

Publication

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

Publication

F. Papst

Privacy-preserving machine learning for time series data

in: SenSys '20: The 18th ACM Conf on Embedded Networked Sensor Systems (2020) 813–814

Publication

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

Publication

J. Lasser, et al.

Agent-based simulations for optimized prevention of the spread of SARS-CoV-2 in nursing homes

[submitted Nov. 19, 2020]

Publication

T.M. Pham, I. Kondor, R. Hanel, S. Thurner

The effect of social balance on social fragmentation

J. R. Soc. Interface Vol. 17, Issue 171 (2020)

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J.-P. Aguilar, J. Kirkby, J. Korbel

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Risks 8(4) (2020) 124

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Á. Corral, I. Serra, R. Ferrer-i-Cancho

Distinct flavors of Zipf’s law and its maximum likelihood fitting: Rank-size and size-distribution representations

Phys. Rev. E 102 (2020) 052113

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X. Dai, X. Li, et al.

Discontinuous Transitions and Rhythmic States in the D-Dimensional Kuramoto Model Induced by a Positive Feedback with the Global Order Parameter

Phys. Rev. Lett. 125 (2020) 194101

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R. Hanel, S. Thurner

Boosting test-efficiency by pooled testing strategies for SARS-CoV-2—Formula for optimal pool size

PLoS ONE 15(11) (2020) e0240652

Publication

L. Zenk, G. Steiner, et al.

Fast Response to Superspreading: Uncertainty and Complexity in the Context of COVID-19

Int. J. Environ. Res. Public Health 17(21) (2020) 7884

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S. Lewandowsky, L. Smillie, D. Garcia, et al.

Technology and Democracy: Understanding the influence of online technologies on political behaviour and decision-making

EUR 30422 EN, Publications Office of the European Union, Luxembourg (2020)