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Page 1 of 1 (7 Total Results)
Collection: COVID-19 Response at the University of Illinois
Description: Webpage discussing the Safer Illinois app that was developed to provide pandemic resources to support health and safety in the University of Illinois community.
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Subject: COVID-19 (Disease), Apps (Computer software), Contact tracing (Epidemiology)
Creator: Board of Trustees, University of Illinois
Source: Safer Illinois
Language: English
Coverage: COVID-19 Pandemic, 2020-, University of Illinois System
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
subject: Contact tracing (epidemiology)
Collection: COVID-19 Response at the University of Illinois
Description: Webpage sharing news about the debut of rapid COVID at-home tests.
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Subject: COVID-19 (Disease), Medical tests (Diagnosis), Epidemiology
Creator: College of Veterinary Medicine, University of Illinois
Source: College of Veterinary Medicine, University of Illinois at Urbana-Champaign
Language: English
Coverage: COVID-19 Pandemic, 2020-, University of Illinois System
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Collection: COVID-19 Response at the University of Illinois
Description: Webpage sharing a University of Illinois employee's presence in the news discussing the COVID-19 risks that college students can pose by traveling for Thanksgiving.
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Subject: COVID-19 (Disease), Health, Pandemics
Creator: College of Veterinary Medicine, University of Illinois at Urbana-Champaign
Source: College of Veterinary Medicine, University of Illinois at Urbana-Champaign
Language: English
Coverage: COVID-19 Pandemic, 2020-, University of Illinois System
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Collection: COVID-19 Response at the University of Illinois
Description: Webpage sharing a University of Illinois employee's presence in the news discussing the potential pitfalls of rapid at-home COVID-19 testing.
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Subject: Epidemiology, PCR (Biochemistry), Medical tests (Diagnosis), COVID-19 (Disease)
Creator: College of Veterinary Medicine, University of Illinois at Urbana-Champaign
Source: College of Veterinary Medicine, University of Illinois at Urbana-Champaign
Language: English
Coverage: COVID-19 Pandemic, 2020-
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Collection: COVID-19 Response at the University of Illinois
Description: Webpage sharing that students must receive two negative tests before going home for Fall break.
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Subject: Epidemiology, Health, Pandemics, COVID-19 (Disease)
Creator: Board of Trustees, University of Illinois
Source: University of Illinois at Urbana-Champaign
Language: English
Coverage: COVID-19 Pandemic, 2020-, University of Illinois System
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Collection: COVID-19 Response at the University of Illinois
Description: News article reporting on the validation of saliva-based testing for COVID-19 in Illinois.
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Subject: Health, Medical tests (Diagnosis), PCR (biochemistry), COVID-19 (Disease)
Creator: Liz Ahlberg Touchstone, Illinois News Bureau
Source: Illinois News Bureau
Language: English
Coverage: COVID-19 Pandemic, 2020-, University of Illinois System
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Collection: COVID-19 Response at the University of Illinois
Description: Preprint article. Abstract— The COVID-19 pandemic has generated an enormous amount of data, providing a unique opportunity for modeling and analysis. In this paper, we present a data-informed approach for building stochastic compartmental models that is grounded in the Markovian processes underlying these models. Our initial data analyses reveal that the SIRD model – susceptiple (S), infected (I), recovered (R), and death (D) – is not consistent with the data. In particular, the transition times expressed in the dataset do not obey exponential distributions, implying that there exist unmodeled (hidden) states. We make use of the available epidemiological data to inform the location of these hidden states, allowing us to develop an augmented compartmental model which includes states for hospitalization (H) and end of infectious viral shedding (V). Using the proposed model, we characterize delay distributions analytically and match model parameters to empirical quantities in the data to obtain a good model fit. Insights from an epidemiological perspective are presented, as well as their implications for mitigation and control strategies.
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Subject: Quantitative research, Information modeling, COVID-19 (Disease)
Creator: S. Yagiz Olmez, Jameson Mori, Erik Miehling, Tamer Ba¸sar, Rebecca L. Smith, Matthew West, Prashant G. Mehta
Publisher: medRxiv
Source: medRxiv
Language: English
Coverage: COVID-19 Pandemic, 2020-
Format: WARC
Type: Web archives
Date: 2020-11-17
Collector: University Archives, University of Illinois at Urbana-Champaign
Rights: The copyright holder for this preprint is the author/funder. All rights reserved. No reuse allowed without permission.
Page 1 of 1 (7 Total Results)
