Meeting ID:2517 399 1717
The traditional approach of epidemiology emphasizes the temporal dimension for setting up causal inference. The spatial dimension can provide a different perspective on where diseases occur and how environmental factors interact with behaviors and genetic traits. The recent concept of precision public health tries to target the right people by appropriate intervention as early as possible. If public health researchers or policy makers want to target the population in place, the geo-spatial approach might be a good choice. In this presentation, I will show four examples to share our experience on leveraging the power of data visualization, spatial statistics and health informatics for public health research and practice including spatio-temporal ring maps, the risk factors for out-of-hospital cardiac arrests (OHCA), the air pollution effects on chronic kidney diseases, and the health impacts from noise exposure. With the geo-spatial approach, the information for decision-making can be projected on vivid maps linking the nature, nurture and exposure for understanding the dynamic process of disease onset.
Dr. Ta-Chien Chan is a research fellow at the Center for Geographic Information Science of Research Center for Humanities and Social Sciences in Academia Sinica since November 2020. He graduated with a doctoral degree (Ph.D) from the Institute of Epidemiology, National Taiwan University in 2010. Before Dr. Chan join Academia Sinica as an assistant research fellow in 2012, he worked at the Committee on Chinese Medicine and Pharmacy, Department of Health from 2010-2012. Dr. Chan is an interdisciplinary scholar in both health and spatial science. He took advantage of these two specialties and devoted himself to interdisciplinary research, and also translated scientific findings to aid in first-line disease control and prevention. In the past five years, Dr. Chan focused on five major research topics including geo-data visualization, infectious disease surveillance, health impacts from air pollution and noise, behavioral contagion through social networks, and spatial accessibility of the health care. Starting from 2016, he has been building up a smart dengue surveillance system with epidemiological intelligences in six cities of Taiwan to reduce the risk of dengue epidemics locally, and has won many prestigious information technology and smart city awards. He has also set up community-based disease surveillance systems in Taipei and Kaohsiung City. He has devoted his career not only to academic research but also to improving first-line public health systems.