Digital Tracing for Identifying Geospatial Temporal Hotspots of COVID-19 Transmission
Emerging computational methods and digital data sources are changing the landscape of population health research. As COVID19 continues to spread across the US and globally, it is essential to leverage digital footprints to identify novel cases and areas of high risk of transmission. In this presentation, Dr. Hswen will cover three key objectives spanning the fields of computational epidemiology and population informatics in relation to COVID19. First, Dr. Hswen will provide an overview of the application of novel computational methods for uncovering patterns of disease and exploring the links between individual behaviors and illness trajectories. Second, Dr. Hswen will demonstrate how digital data can advance our understanding of COVID19 and citizen science methods that engage and inform the public on COVID19. Last, Dr. Hswen will consider how big data and computational methods can advance our understanding of the impact of social and environmental influences related to COVID19 on human health and well-being. Across each aim in this presentation, Dr. Hswen will draw from her work to highlight digital studies on COVID19. With access to myriad sources of unconventional digital data, Dr. Hswen will conclude by highlighting the opportunities afforded by these digital sources and platforms for discovering new insights about human behaviors and the spread of disease, and why this is now one of the most exciting times in modern history of medical research as there is potential to understand human health in ways that were previously not possible.
Dr. Yulin Hswen is a Computational Epidemiologist and Faculty in the Innovation Program at Boston Children's Hospital, Harvard Medical School. Dr. Hswen completed her doctoral training as a social and computational epidemiologist at the Harvard T.H. Chan School of Public Health, where her research focused on leveraging big data to uncover hidden social determinants and patterns of disease. Her current work within the Innovation Program seeks to develop and test new methods to capture informal online data sources towards generating population health insights that can be used to predict the onset and course of various diseases and public health threats. Dr. Hswen's research involves the design and development of digital surveillance methods, as well as novel tools that can transform public practice and influence health policies. Dr. Hswen has received awards and competitive funding from the Canadian Institutes of Health Research, The Embassy of France, Harvard University, the Weatherhead Center, and the National Institutes of Health for her work in the field of social and computational epidemiology. Her work has been published in the New England Journal of Medicine, the American Journal of Public Health, Preventive Medicine, and the Journal of Medical Internet Research, and has been featured in Nature, Fast Company, Kaiser Health News, Bloomberg.