Departmental Research Seminars
Via Zoom: link will be provided upon successful registration
[ 09:30-10:15 ]
Effect modification of greenness on PM2.5 associated all-cause mortality in a multidrug-resistant tuberculosis cohort
Evidence for the association between PM2.5 and mortality among patients with tuberculosis (TB) is limited. Whether greenness protects air pollution-related mortality among patients with multidrug-resistant tuberculosis (MDR-TB) is completely unknown. We conducted a cohort study that integrated geospatial and epidemiological data to evaluate the impact of air pollution on survival among patients after infections with MDR-TB. We also evaluated the effect modification by greenness. The hazard ratio (HR) of 1.702 (95% CI, 1.680 to 1.725) was observed for PM2.5 associated with mortality for the full cohort. The risk was reduced for patients at the greatest level of greenness exposures with HR of 1.169 (1.162 to 1.175). Our findings suggested that individuals with MDR-TB could benefit from greenness by having attenuated associations between PM2.5 and mortality. Improving greener space and air quality, along with effective treatments, could contribute to lower the risk of mortality from TB/MDR-TB and other respiratory diseases.
Dr. Erjia GE
Assistant Professor, Dalla Lana School of Public Health, University of Toronto, Canada
Dr. Erjia Ge is an Assistant Professor of Spatial Epidemiology in the Dalla Lana School of Public Health, University of Toronto, Canada. She is also a research fellow of the Institute of Clinical Evaluative Sciences which hosts health and related data for 15 million Ontarians. Her research is focused on geospatial sciences and data analytics in response to air pollution, climate change, and environmental health challenges. Her current study on exploring inequity in greenness accessibility and childhood asthma, funded by the Canadian Institute for Health Research, aims to inform policy makers for relevant changes in urban planning and effective intervention to promoting healthy cities in Canada and globally.
[ 10:45–11:30 ]
Urban forestry for sustainable communities: Evidence from New York City
Urban trees could provide multiple ecosystem services (e.g., carbon storage and sequestration, air pollution removal, urban heat island effect mitigation, and residential energy conservation) for building ecologically vital and socially just cities. However, simply increasing tree cover does not necessarily guarantee the provision of expected ecosystem services to various groups of people as trees are often unequally distributed. Spatial distribution of trees has important implications for many aspects of urban sustainability, such as environmental justice and public safety. This seminar will focus on the roles of street trees for environmental justice and urban crime in New York City. Through the combined use of remote sensing imageries, google street view, citizen science, and socioeconomic data, I will first introduce how the underprivileged and vulnerable subpopulations are disproportionately affected by uneven distribution of street trees. Then the impacts of street trees on crime, as well as how their associations are moderated by tree structure, streetscape elements, and tree management, will be presented. The revealed findings have important implications for the implementation of tree-planting programs in tackling the dual tasks of alleviating environmental inequity and reducing crime, and could help translate sustainable urban planning into specific actions of tree management and streetscape design that can be taken by government and local stakeholders.
Dr. Jian LIN
Postdoctoral Scholar, Sierra Nevada Research Institute, University of California, Merced, United States
Dr. Jian Lin is a Postdoctoral Scholar at the University of California, Merced. He obtained his PhD degree in Urban Forestry from the State University of New York. His research focuses on urban forest modeling and ecosystem service quantification, and nature-based solutions for sustainable cities (e.g., social justice, public safety, and human well-being). He has published 11 articles on prestigious peer-reviewed journals and served as a reviewer for about 10 journals. He was a member of the i-Tree team and led the development of the uncertainty framework for the i-Tree model (https://www.itreetools.org/) for better assessing and managing urban forestry.
[ 12:00–12:45 ]
Contributing geography to our understanding of health and wellbeing
In public health and epidemiology, “Where” matters significantly as we expect to know which places have disease burden and high transmission rates, where suspected individuals are traveling to, where adequate treatment facilities are located, where medical staff shortages are, and where to buy medicine. These concepts rely heavily on geography. This talk includes four aspects of research in health geography: 1) disease disparities and trends over space and time; 2) spatial access to health care services; 3) spatial and temporal associations with socially-sensed neighborhood characteristics; and 4) disease predictions. I will deliver my previous and ongoing research on integrating geospatial approaches with public health topics including substance use disorder, end-stage renal disease, and typhoid fever. This talk will also introduce my future research plan in precision health and global health.
Dr. Yanjia CAO
Postdoctoral Scholar, School of Public Health and Human Longevity Science, University of California, San Diego, United States
Dr. Yanjia Cao received her PhD in Geography from University of Maryland, and MS in Geography from University at Buffalo-SUNY. As a health geographer, she had cross-disciplinary training in public health science during her postdoctoral scholarship, at Stanford University School of Medicine, Division of Infectious Diseases and Geographic Medicine, and also University of California San Diego, School of Public Health. She has been working in the field of Health Geography since her graduate school, and has published peer-reviewed papers in various geography and health journals. She serves board of directors (BOD) for the Health and Medical Geography specialty group at AAG since 2019. She was also the BOD student member for the International Association of Chinese Professionals in Geographic Information Sciences during 2019-2020.
[ 15:30–16:15 ]
Tackling climate risks and climate adaptation in agroecosystem with integrated approach
Food security is a global concern, especially considering global warming. Many agroecosystem models have been developed to project how future crop production will be changed; however, model projections are often subject to large uncertainties due to lack of observational constraint. Recent advances in satellite observations open the door for better modeling crop production and agroecosystem dynamics through providing direct observational evidence. In this seminar, I will present a framework for integrating satellite observations, field observations and computational models to address two important questions in agroecosystem: (1) how will climate change impact crop production? (2) how can human management practices help agroecosystem adapt to climate change? For the first question, satellite derived crop physiological parameters, crop area dynamics and model-data fusion framework are employed to gain insight into how climate stresses influence crop yield and the underlying yield formation processes and how socioeconomic factors mediate climate change risks to crop production. For the second one, satellite derived human management practices (cultivar renewal and double cropping) will be evaluated in a coherent modeling framework to shed light on the climate adaptation potential of these management practices.
Dr. Peng ZHU
Postdoctoral Scholar, Laboratory of Climate and Environmental Sciences (LSCE), France
Dr. Peng Zhu is a Postdoctoral Fellow at Laboratory of Climate and Environmental Sciences (LSCE), France. His research interests are climate impacts and adaptation in agroecosystem, environmental remote sensing, ecosystem modeling, food-water-carbon nexus. Through integrating satellite data, field observations and computational models, he aims to help stakeholders to better tackle climate risks, design effective climate adaptation strategies in agroecosystem and finally achieve agricultural sustainability. Prior to joining LSCE, he worked as a Postdoctoral Fellow at UC San Diego. He received a doctoral degree in Earth Science from Purdue University.