• April 4: California Leads the Way on Expanding Health Insurance Coverage to Undocumented Immigrants (Dr. Dylan H. Roby)
• April 5: Every Breath We Take -- Is the Next Generation's Health at Risk? (Dr. Andrea de Vizcaya Ruiz)
• April 6: What does an Epidemiologist do post-COVID? (Dr. Karen Edwards)
• April 7: Revising the Electronic Revolution: From E-Wasteland to E-Wonderland (Dr. Dele Ogunseitan)

Director and Founding Dean, Program in Public Health
Susan & Henry Samueli College of Health Sciences

Let’s face it. We have a love affair with data. With the rise in data science, machine learning, and artificial intelligence, public health has increasingly become a numbers and data-driven field. We aspire to create studies where we can get the most data points, because the more we have, the more reliable our inferences about a population become, and the better we are able to help our respective populations. As such, doing anything that brings us closer to working with “big data” is considered good for public health.

However, even as someone who thinks big data is the next greatest thing to happen in public health, I want to caution that big data has its limitations. Let’s start with a hypothetical scenario: If you were to ask someone to rate their pain on a scale from 1-10 (with 10 being “excruciating pain”), the pain that someone would rate a 5 could be a 7 to someone else, or if their pain tolerance is really high, maybe a 3. Could a number describe whether someone’s pain is more dull or sharp? What about that pain’s impact on how a person is able to function in their daily life?

Moving into more recent matters, can you use numbers to fully describe the impact that the COVID-19 pandemic has on individuals? How can you use numbers to capture the feeling of anguish after losing a loved one? How about the ways in which people have to change their daily routines and practices in response to the pandemic?

You can try, but chances are, numbers alone cannot fully capture these kinds of sentiments. As much as big data’s strengths are in telling the stories of the population as a whole, and as much as we want to use the most robust quantitative methods for telling these stories, data itself fails to provide the whole picture of experiences. When we are supposed to center our work on the communities we are trying to help, big data creates a vast sea of numbers for the voices and stories of those communities to get lost in. It is up to us to ensure that those voices don’t get lost, not only because doing so would be an incredible disservice to the communities we work with, but also because we would lose our sense of purpose for working in the field in the first place.

This is the reason why, along with colleagues from other universities and medical schools, I co-founded the AAPI Community COVID Archival Project last year, where we gather and archive the vast experiences of the Asian American and Pacific Islander communities during the COVID-19 pandemic. If we do not gather these stories from the community now, they will be told by others in the future and may paint a misrepresented picture of experiences during the pandemic. We have the infrastructure to do our communities this kind of justice, and my work is just one of many ways to ensure that while we work with  numbers and data points, we also capture the experiences that numbers themselves cannot tell.

For the sake of justice and equity, for empowering the very people that we work with, and for maintaining our purpose in this field, let us not forget the value of words and stories in our work here in public health.

• The Planet's Health and Our Health is One Health - Vandana Shiva, PhD
• Deep medicine and the care revolution - Rupa Marya, MD
• Centering the Disadvantaged: Reflections on Community Partnership & Solidarity as Research Praxis - Ricky Blumenthal, PhD, MA
• Relational Approaches in Indigenous Health: From Paternalism to Partnership - Adriann Begay, MD and Cristina Rivera Carpenter, PhD, MSN, RN-BC
• Evening performance by Rupa & the April Fishes