Webinar Series on COVID-19 Impact Analysis
10:30AM-12:00 PM, Friday, Jan 8-Feb 5, 2021 (US Eastern Time)
11:30PM-1:00 AM, Friday, Jan 9-Feb 5, 2021 (Beijing Time)
Co-sponsors：
l NSF Spatiotemporal Innovation Center
l Department of Earth Sciences, Tsinghua University
l School of Geography, Nanjing Normal University
l China Data Institute
l Future Data Lab
l Annals of GIS
Register Now
https://www.eventbrite.com/e/132751745043
10:30AM-12:00 PM, Friday, January 8, 2021 (US EDT)
l COVID-19 Metrics for the US Congressional Districts and India Parliament Constituencies
S V Subramanian and Weixing Zhang, Harvard University
l Global COVID-19 pandemic demands joint interventions for the suppression of future waves
Peng Gong, University of Hong Kong
Chair: Wendy Guan, Harvard University
10:30AM-12:00 PM, Friday, January 15, 2021 (US EDT)
l Intergenerational residence patterns and COVID-19 fatalities in the EU and the US
Shoshana Grossbard, San Diego State University; Ainoa Aparicio Fenoll, University of Turin
l An overview of COVID-19 modeling and applications
Jian Li, Tulane University
Chair: Xi Chen, Yale University
10:30AM-12:00 PM, Friday, January 22, 2021 (US EDT)
l COVID-19’s Second-Order Impacts on Global Vulnerable Urban Areas
Melinda Laituri, Colorado State University
l An overview of human mobility and COVID-19 transmission
Mengxi Zhang, Ball State University
Chair: Lizheng Shi, Tulane University
10:30AM-12:00 PM, Friday, January 29, 2021 (US EDT)
l Assessing Household Readiness for COVID-19 in Developing Countries
Chunling Lu, Harvard University
l Taking the pulse of COVID-19: a spatiotemporal perspective
Chaowei Yang, Georgia Mason University
Chair: A-Xing Zhu, University of Wisconsin Madison
10:30AM-12:00 PM, Friday, Feb 5, 2021 (US EDT)
l Interiorization of COVID-19 in Brazil
Marcia C.de Castro, Harvard University
l Spatiotemporal pattern of COVID-19 and government response in South Korea
Sun Kim, Harvard University
Chair: Shuming Bao, China Data Institute
Background:
As a joint effort by scholars and professionals from the Center for Geographical Analysis at Harvard University, the Geo-Computation Center for Social Sciences at Wuhan University, the China Data Institute, the NSF Spatiotemporal Innovation Center, RMDS Lab, and some other institutions, an initiative on “Resources for COVID-19 Study” was sponsored by the China Data Lab project (http://chinadatalab.net). The objectives of this project are: (1) to provide data support for the spatial study of COVID-19 at local, regional and global levels with information collected and integrated from different sources; (2) to facilitate quantitative research on spatial spreading and impacts of COVID-19 with advanced methodology and technology; (3) to promote collaborative research on the spatial study of COVID-19 on the Spatial Data Lab and Dataverse platforms; and (4) to build research capacity for future collaborative projects. The project has sponsored two webinar series on Covid-19 data and modeling (see links to recorded webinars below). This is the 3rd webinar series with a focus on the impact analysis of COVID-19 pandemic.
1. "Webinars for "Resources for COVID-19 Study", https://doi.org/10.7910/DVN/OTYQUY, Harvard Dataverse
2. "Webinars on Modeling COVID-19 Pandemic：Resources, Methodology and Applications", https://doi.org/10.7910/DVN/NXF45W, Harvard Dataverse
Contact:
office@chinadatacenter.net