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  • Professors Nilay Argon, Yufeng Liu and Serhan Ziya, together with graduate student Qian Cheng, have developed a tool for hospital and emergency department (ED) managers, physicians, and health care workers to quickly convert predictions of future COVID-19 patient arrivals into predictions of future COVID-19 census levels in the ED, main hospital, and the ICU. The software is available on this website.
  • Professor Serhan Ziya is collaborating with Omar El Housni (Columbia University), Mika Sumida and Huseyin Topaloglu (Cornell Tech), and Paat Rusmevichientong (USC) on developing models for analyzing and developing insights into how limited testing and contact tracing capacity along with social distancing measures can be used in managing the spread of COVID-19. You can read the results of some of their analysis on this blog post. Also see their paper on North Carolina.
  • Professor Jan Hannig is collaborating with professor Corbin Jones from the Department of Biology on detecting evolution in SARS-CoV-2. They are using a Bayesian algorithm designed to detect change in the distribution of the RNA sequences.
  • Professor Steve Marron, together with Dirk Dittmer from Department of Microbiology and Immunology and Biostatistics graduate studente Yue Pan, have been looking at infection rates over time (using a time varying version of the SIR model), and trying to understand how they are impacted by the myriad of state policies and restrictions.
  • Professors Jan Hannig, Serhan Ziya and Richard Smith, along with graduate student Alexander Murph, will combine to teach a new remote-learning course “Data Science for COVID-19″┬áin Fall 2020. The course is one of a set of 11 new “COVID investigation classes” announced by the College of Arts and Sciences. The course will highlight many ways that data scientists have been involved in COVID-19 research, including mathematical and computational models for the spread of the disease, statistical analyses of data on cases, hospitalizations and deaths, and models for studying such questions as the impact of testing on the effectiveness of social distancing.

 

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