About the Levin Lecture Series:
During the Fall and Spring semesters, the Department of Biostatistics holds seminars, called the Levin Lecture Series, on a wide variety of topics which are of interest to both students and faculty. The speakers are occasionally departmental faculty members themselves but very often are invited guests who spend the day of their seminar discussing their research with Biostatistics faculty and students. Lectures are in-person only unless marked otherwise.
Sandrah Proctor Eckel, PhD
Associate Professor of Population and Public Health Sciences
University of Southern California, Keck School of Medicine
Biostatistics, Climate Change, and Health
Climate change poses an existential threat to human health. Public health researchers are increasingly joining multidisciplinary teams to quantify the health impacts of climate-related events, to identify key priorities for adaptation, and to provide policy-relevant information by evaluating ongoing adaptation measures as well as the public health co-benefits of mitigation efforts. I have been transitioning from research focused on methods and applications in environmental statistics - especially for air pollution epidemiology – to climate and health. In this talk, I will share my perspective on directions for biostatistical contributions to climate and health. I will provide an overview from my experience co-developing a new graduate-level, team-taught multidisciplinary course: “Data Science Methods for Climate and Health Research” and insights from ongoing research projects at the University of Southern California. For example, traffic is a key source of air pollution in Southern California. We recently related the early phase transition to electric vehicles in California to reductions in nitrogen dioxide (NO2) air pollution and reductions in asthma-related emergency department visits using classic longitudinal mixed model methods. More generally, many studies relating climate hazards to acute health outcomes have adapted methods from air pollution epidemiology. For example, analyses linking climate hazards to administrative health outcomes (e.g., daily hospitalizations or mortality) typically use methods for ecological time series analysis of counts with quasi-Poisson regression or time-stratified case-crossover sampling designs with conditional logistic regression. Case-crossover designs have been growing in popularity as they are considered individual-level rather than ecological and control for time-constant confounders by design. However, case-crossover has been noted to have worse efficiency than time series. In a simulation study, we compared case-crossover and time series methods for studying rare binary exposures (e.g., high wildfire smoke day, or extreme heat day), showing that the reduced relative efficiency for case-crossover worsened with increasingly rare extreme exposures. In summary, climate and health research is a rapidly developing field with urgent needs. More insights will be gained by continuing to adapt existing methods, but key features of climate-related hazards may require new methodological approaches. Biostatisticians will play an important role in developing data-driven solutions for a healthy future in our changing climate.
