This Working Group intends to model population vulnerability and system-level inoperability in the context of COVID-19. The group will explore how infrastructure systems and processes, along with socio-economic and political mechanisms and institutions, influence individual and collective outcomes from pandemic events. Ultimately, this work aims to inform strategies to mitigate against future events and to provide guidance on optimal approaches for response and recovery.
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COVID-19 and Social Vulnerability: Computational Modeling, Data Analytics, and System Interoperability
Working Group Leads
Pallab Mozumder, Florida International University and Andrea Molle, Chapman University
Emails: mozumder@fiu.edu; molle@chapman.edu
Working Group Members
Alexander Bay, Chapman University
Monalisa Chatterjee, University of Southern California
Luigi Curini, University of Milano
Zhijie (Sasha) Dong, Texas State University
Nazife Ganapati, Florida International University
Nafisa Halim, Boston University
Samiul Hasan, University of Central Florida
R. Anna Hayward, Stony Brook University
Chris Kuhlman, University of Virginia
Achla Marathe, University of Virginia
Sisi Meng, University of Notre Dame
Qing Miao, Rochester Institute of Technology
Joost Santos, George Washington University
Flaminio Squazzoni, University of Milano
Joseph Toland, U.S. Geological Survey
Matthew Van, California State University, Long Beach
Working Group Resources
Online Symposium on COVID-19 Related Research in Developed and Developing Countries
CONVERGE is funded by the National Science Foundation (NSF), Division of Civil, Mechanical, and Manufacturing Innovation, Program on Humans, Disasters, and the Built Environment (Award #1841338). Any opinions, findings, conclusions, or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF.