Predictions, Role of Interventions and the Crisis of Virus in India: A Data Science Call to Arms
About this Webinar Series
The COPSS-NISS COVID-19 Data Science webinar series is co-organized by the Committee of the Presidents of Statistical Societies (COPSS) and its five charter member societies (ASA, ENAR, IMS, SSC, and WNAR), as well as NISS. This bi-weekly seminar features the latest research that is positioned on the cusp of new understanding and analysis of COVID-19 pandemic data, and promotes data-driven research and decision making to combat COVID-19. Find out more about this series and view all the previous sessions on the Webinar Series page.
India, the world's largest democracy with 1.38 billion people, underwent five phases of national lockdown from March 25-June 30, 2020 and several phases of unlocking since then. The virus curve has turned the corner from late September of 2020 without a second resurgence in the Winter. Normalcy has returned to the life of Indian people and the Oxford-AstraZeneca vaccine (called COVISHIELD in India) is being used for vaccination nationwide. Several hypotheses are postulated for this miraculous recovery of India including that of herd immunity. In this presentation, we provide a brief chronicle of the modeling experience of our study team over the last one year trying to understand the pandemic in India. We discuss methodological innovations by incorporating selective and imperfect viral testing when using case-counts in an extended SEIR model for COVID-19. We use this model to estimate the true infection fatality rate in India. We present our (incomplete) understanding of what helped India to effectively battle this public health crisis in a low-resource setting. This is joint work with many, with all supporting research materials and products available at covind19.org.
Bhramar Mukherjee, (University of Michigan)
Bhramar Mukherjee is John D. Kalbfleisch Collegiate Professor and Chair, Department of Biostatistics; Professor, Department of Epidemiology, Professor, Global Public Health, University of Michigan (UM) School of Public Health; Research Professor and Core Faculty Member, Michigan Institute of Data Science (MIDAS), University of Michigan. She also serves as the Associate Director for Quantitative Data Sciences, University of Michigan Rogel Cancer Center. She is the cohort development core co-director in the University of Michigan’s institution-wide Precision Health Initiative. Her research interests include statistical methods for analysis of electronic health records, studies of gene-environment interaction, Bayesian methods, shrinkage estimation, analysis of multiple pollutants. Bhramar is a fellow of the American Statistical Association and the American Association for the Advancement of Science. She is the recipient of many awards for her scholarship, service and teaching at the University of Michigan and beyond.
Moderator and Session Organizer
Lili Zhao, (University of Michigan)
Lili Zhao is a Research Associate Professor in the Department of Biostatistics. She received her PhD in Statistics from the University of Iowa in 2006 and joined the Department of Biostatistics in 2011 as a faculty member. She has collaborated with researchers in disease areas, including Cancer, Cardiology, Cirrhosis, Neurology, Infectious Diseases, and Diabetes. As a Principal Investigator on a NIH-funded study, her current research focuses on developing, translating and promoting the use of innovative statistical methodologies in investigating safety of COVID-19 vaccines.
Xihong Lin (Chair) (IMS), Harvard University
Karen Bandeen-Roche (NISS), Johns Hopkins University
Chris Barker (ASA), Statistical Planning and Analysis Services, Inc
Gary Chan (WNAR), University of Washington
Rob Deardon (SSC), University of Calgary
Natalie Dean (COPSS), University of Florida
Debashree Ray (COPSS), Johns Hopkins University
Jie Peng (WNAR), University of California at Davis
Nathaniel Stevens (SSC), University of Waterloo
Elizabeth Stuart (ENAR), Johns Hopkins University
Ryan Tibshirani (IMS), Carnegie Mellon University
Lily Wang (ASA), Iowa State University
Lingzhou Xue (NISS), Pennsylvania State University
Lili Zhao (ENAR), University of Michigan
Glenn Johnson (Web Communications), NISS