Frontiers in Data Science, Health, and the Environment
Category: The International Environmetrics Society (TIES)
Environmental conditions in rural and urban environments may dictate how populations adopt different lifestyles to maintain a healthy living. Understanding recurrent or new health threatening environmental stressors are key to adopt safety measures to support better quality of life for different communities and implementing effective disease prevention measures. Anthropogenic-caused environmental changes occurring at different temporal and spatial scales trigger a cascade of events creating a complex set of stressors undermining the well-being and welfare of people. Freshwater shortage, biodiversity loss and climate change are examples of some of these environmental changes. Massive data sets from disparate sources ranging from social networks to census data are frequently used to understand how pre-existing conditions and social disparities might undermine population responses to environmental changes in rural and urban areas, compromising health conditions and timely responses to complex environmental stressors. Professor Grace Chiu from Virginia Institute of Marine Science (VIMS), Professor Veronica Berrocal from the University of California in Irvine and Monica Pirani from Imperial College in London have approached several issues in the frontiers of data science, health, and environment. Grace Chiu is founder and director of the Environmental Statistics and Transdisciplinary Data Science Lab at VIMS. She develops integrative, holistic statistical methodologies for multi-faceted problems, stemming mainly from the environmental sciences. She will present the work “Latent-causal socio-economic health index“ using an integrative modelling approach for identifying important drivers of societal health at a the global scale (joint work with FS Kuh and AH Westveld). Professor Veronica Berrocal is an Associate Professor at the University of California in Irvine. Professor Berrocal’s research focuses on developing statistical models that extract information from data collected over space and time, including approaches to obtain spatially detailed, actionable measures of a neighborhood’s health behaviors. She will talk about “Modeling and inferring upon the effect of built environment features on children’s health outcomes”. Professor Monica Pirani is a Lecturer in Biostatistics at Imperial College London. Professor Pirani’s research is based upon the development of statistical methods driven by real-world applications, at the intersection of environment, changes in climate and population health. Her talk will be about “Climate and environmental drivers of spatio-temporal spread of arboviruses”. These talks attempt to provide different angles on the intersection between data science, health, and the environment.