Group | Sensoring and Environmental Epidemiology

Technologies allow us to capture ever more data about our environment from many distributed sources and in real-time. The Sensoring and Environmental Epidemiology group is interested in how to capture, analyze and present these data to elucidate new insights into the relationship between environmental exposure and human health. The ongoing shift from sparse, expensive time-averaged or occasional spot measurement data to more abundant, affordable and real-time data presents unique opportunities and challenges in environmental epidemiology.

Our expertise lies in leveraging data science for public health benefit. We work with a diversity of e-health data collection tools like personal measurement devices, wearables, real-time sensors, apps and online data capturing systems. We use these tools to gather high-resolution data on cardiovascular and pulmonary health, sleep, and cognitive function first hand in order to study short-term and triggering impacts of environment on health. In addition, we leverage the statistical power of existing registries and databases such as the Swiss National Cohort, to look at health effects at a national level.

We also work on the measurement and geospatial modelling of a diversity of environmental exposures, such as pollen, air pollution, environmental noise, RF-EMF, aided by ground-level targeted measurements and routine monitoring data as well as satellite-observed GIS data. These high-resolution exposure data can be readily included to explore new hypotheses about associations between our environment and health.

A major current focus area is the determination of the true human health impact of airborne pollen in light of air pollution and especially of climate change influences. In the POCHAS and EPOCHAL projects, we are modelling exposure to pollen, air pollution, and weather retroactively in both space and time, and investigating a diversity of health outcomes.