Our Communications Manager, Katie M. Kanagawa, interviewed Associate Professor of Epidemiology & Population Health (E&PH), Lorene (Lori) Nelson, about her epidemiological research on the unequal burden of COVID-19 by income, race/ethnicity, household crowding, and other social determinants of health.
Can you start by telling us a bit about yourself? How did you get here (to Stanford Epidemiology)? Was there something in particular that attracted you to the fields of science, health and disease?
Getting here to Stanford epidemiology occurred right after completing my doctoral program in epidemiology at the University of Washington, and I feel very lucky to have chosen from the very beginning a university where I have been able to thrive. Prior to my doctoral program, I took a somewhat meandering path to choose epidemiology as my final career because so many other fields interested me. I have always had a fascination with the brain and nervous system. I did my bachelor’s degree at Colorado State University in Fort Collins, Colorado, with a major in Physiological Psychology (nowadays known as Neuroscience), working in a laboratory where I did stereotactic surgery on animals and studied the neural basis of attention. Then I worked for 7 years doing clinical research on multiple sclerosis at the University of Colorado Health Sciences Center in Denver, during which time I also completed a master’s degree in biostatistics. After 5 years in that position, I knew that I wanted to get a PhD in a field where I could lead my own research, because I was frustrated working under physicians with little research training who knew less than I did about research methodology.
I thought I wanted to be an epidemiologist, but every time I sat down to prepare my application for epi doctoral programs, I felt a bit claustrophobic because by making that final choice, it meant that my second and third choices would never be realized (#2 was artificial intelligence, #3 was clinical psychology). Ultimately, I decided that epidemiology was the perfect fit because of my love of biology and math, and a passion for wanting to do something involving those two disciplines that would improve the human condition.
I understand you have shifted your research focus in recent months to COVID-19. Can you please give us an overview of your research on this subject? How would you describe your unique approach to this incredibly important subject?
Well, unique might be an overstretch, but I have ended up substantially expanding my research program, which was already very busy and focused on neuroepidemiology, to work on 4 studies of COVID-19. I am a co-investigator on two studies, both of which are using home kit testing paradigms to extend the reach of diagnostic and serology testing as a means to track the spread of SARS-CoV-2 in nearby counties. The study called CATCH (Community Alliance to Test Coronavirus at Home, with Bonnie Maldonado and Steve Quake as Co-PIs) is using a rapid in-home test kit protocol to estimate the incidence of SARS-CoV-2 infection in 12 Bay-area counties, and the study called CA-FACTS (Californians Fighting against Coronavirus Together Study, led by Julie Parsonnet) is estimating seroprevalence in California (Santa Clara, Solano, and Placer) counties. On two other studies, I am principal (or co-principal) investigator. The one closest to launch is the California COVID-19 Public Health Data (PHD) Ecosystem.
Let’s turn our focus to your COVID-19 Public Health Data (PHD) Ecosystem project. Can you tell us about how this project got started, and what particular problem(s) it is seeking to address?
With the onset of the COVID-19 pandemic, I realized that the work I had been doing for several years as Faculty Director of Research for the Center for Population Health Sciences (PHS) could really take a leap forward. In that role, I and my team from PHS had been working with the public health officer of Solano county, Dr. Bela Matyas, to set up an advanced data ecosystem whereby the electronic health data for community residents in a population could be harnessed in a privacy-protected way to improve the health of the underlying population. Bela shares the beliefs of PHS on the tremendous effects that “place,” social and environmental factors in a geographic location, have on the health of individual and community health. We had been planning to set up a population health data ecosystem that would include anonymized electronic health data on county residents as well as detailed “contextual information” down to the census tract or zip code level that characterizes the effects of local social and environmental factors on health outcomes.
When COVID-19 came along, I realized that we had the opportunity to set up such a data ecosystem not just for Solano county, but for all 57 other counties in California. Our team, which includes the leaders of EPH and PHS along with post-docs and doctoral students, has been very fortunate to attract the interest and substantial in-kind support of Google Cloud for this project.
Can you tell us more about Google Cloud’s role in this project, and how will a Stanford/Google partnership take this research to the next level?
Google Cloud will take about 16 weeks to build this data ecosystem and platform, working closely with us while we work with California’s public health departments to define the critical elements and visualizations needed. We have spent the last several weeks working with Google Cloud to develop a charter and to select sociodemographic and environmental data sources containing information at refined geographic levels (census blocks, zip codes, neighborhoods). These include data on social determinants of health, environmental factors (weather, air pollution, smoke from wild fires), built environment factors, and crowding indices that may help give public health departments and county policy makers the actionable insight necessary to identify areas in need of proactive public health outreach to reduce SARS-CoV-2 infection rates. County health departments will be able to choose from standardized data views and reports, or build their own county-specific dashboards that will help public health officials manage the pandemic in their county.
We believe that the platform we are building in partnership with Google Cloud will serve as a scalable model for other U.S. communities to enhance their public health response to COVID-19, and, looking to the future, to any other infectious or chronic diseases in their populations.
What is driving you to pursue this research at this point in time? What are you loving the most, or finding the most rewarding or challenging, about it?
This unprecedented pandemic offers an amazing opportunity to have a significant impact on the human condition, perhaps even more so than the research on neurological conditions I have pursued all of these years, if you think of it in terms of the opportunity to save lives and reduce human suffering.
What I am loving the most?...being able to work directly with people I’ve admired so long, including Julie Parsonnet, Bonnie Maldonado, and Lisa Goldman Rosas. Besides being wonderful people, they are all complete standouts in their fields of infectious disease epidemiology and community-based research. What is most challenging?... is the incredibly long hours each day without much relief, working through each weekend. But Dave and I have a 5-day vacation to the Oregon coast planned for October, so there is relief in sight!
What do you hope to accomplish with this new line of research? What larger impacts do you hope to make, scientifically and perhaps societally speaking, and who do you hope will benefit from this work?
I believe that the public health infrastructure we are adding with the Google Cloud project has the potential to serve as a scalable model that could benefit the more than 3000 U.S. counties where public health officers and their staffs are on the front line of trying to slow and stop this pandemic. Even when COVID-19 fades in importance, the ecosystem we are setting up will benefit public health departments and community-based organizations who are seeking to improve the health of populations in terms of other infectious and chronic diseases.