To see Qianying’s presentation, “COVID-19 Outbreak in Wuhan, China: in Retrospect and in Prospect” please click here. A captioned version will be available soon.
Abstract: Since first confirmation in December 2019, the novel coronavirus diseases (COVID-19) infected more than 50,000 people and claimed over 2000 lives in Wuhan, China. It was transmitted across the whole country shortly, and now swept the world by causing more 20,000 infections in countries other than China. Using official reported cases and assuming changing reporting ratio, we investigated the early stage of the epidemic of COVID-19 in Wuhan and analysed its transmissibility. We then built up a conceptual model and incorporated the zoonotic introduction, emigration, individual reaction, and governmental action to simulate the trends of the outbreak in Wuhan and predicted the disease would be completely controlled by the end of April under current policies. These studies provide insights into not only the characteristics of COVID-19 itself, but the impact of governmental actions.
Rada Mihalcea, has been named a Fellow of the Association for Computing Machinery (ACM). ACM Fellows comprise an elite group that represents less than 1% of the Association’s global membership. This distinction recognizes those with far-reaching accomplishments that define the digital age.
443 leading scientists are elected in 2019 as Fellows of the American Association for the Advancement of Science (AAAS), in honor of their invaluable contributions to science and technology. U-M leads the way with 22 elected Fellows, including three MIDAS faculty members:
Brian Athey, Computational Medicine and Bioinformatics
Bill Currie, School for Environment and Sustainability
Jun Li, Computational Medicine and Bioinformatics
The 2019 Discover Innovate Impact (DII) National Data Science Challenge winning teams were recently announced and the GuanLab Team (Yuanfang Guan and Xianghao Chen) won the Task 1, Sepsis Onset Prediction prize. This was a national data science challenge established to advance human health through machine learning hosted by The University of Texas (UTHealth) School of Biomedical Informatics, sponsored by Cerner Corporation, and powered by AWS. Congratulations to GuanLab Team!