Prior to 2020, data science was a mystery to many of us, far removed from our daily lives. That perception changed, however, when COVID-19 swept across the globe. The pandemic brought into focus how data science informs our understanding and mitigation of public health issues.
Data science is an essential tool in preventing disease, improving social justice, and defining systemic public health concerns and the policies required to address them. Through AI and predictive analysis, “data science has had a tremendous impact on people’s daily lives,” says Valeria Tivnan. Tivnan, an ardent champion of using the power of data to improve human health and well-being, is an adjunct professor in the Master of Science in Data Science program at Merrimack College and the director of population health strategy and well-being for EBS. A plaque in Tivnan’s office reads: “In God We Trust, All Others Must Bring Data.”
What is Public Health?
As goes the health of its individuals, so goes the health of a nation. This is the essence of public health. The American Public Health Association (APHA) defines public health as promoting and protecting “the health of people and the communities where they live, learn, work and play.”
We are accustomed to seeing a doctor when we get sick or injured. Public health professionals, collaborating across many disciplines and economic sectors, help us all stay healthy in the first place.
Crucially, public health considers the vital signs of communities and how those signals influence individual health and well-being. These considerations include all socio-economic factors within a community.
Insights in Data
The word “data” goes as far back as the 17th century. Its use in relation to modern computing dates to the 1940s. While there is an obvious nuance between what it meant in the 1640s vs. the 1940s, let alone today in our world of Big Data, a common thread remains.
That thread is information, a “fact given” in the old world transforms into “transmittable and storable information by which computer operations are performed” in the new. Old or new, it’s all information; collected, stored, retrieved, and analyzed in the service of finding hidden connections and solving problems.
Public health is only effective through the insights gleaned from the analysis of multiple levels and sources of information. While the statistical analysis of public health data began in the 19th century, modern data science in the 21st century opens up whole new avenues of discovery for improved public health.
Let’s look at just a few examples.
Disease Prevention and Predictive Analysis
AI and predictive analysis are powerful tools for disease prevention. Predictive models built with AI, machine learning, and big data analyze and interpret existing data, establishing correlations, accurate predictions, and diagnoses.
Tivnan cites IDx-DR AI technology as one example. The FDA-approved device provides a diabetic retinopathy diagnosis without the need for a clinician.
“Diabetes is very costly and can potentially be a chronic incapacitating condition,” says Tivnan. “This device is an artificial intelligence system that can tell in minutes whether a person has more than a mild case of diabetic retinopathy.”
Another example of predictive analysis is Spatiotemporal Epidemiological Modeler or STEM. Developed by IBM, the technology helps researchers predict disease trajectories through populations. STEM and other predictive technologies have been critical in projecting the direction of COVID-19.
Behavior, Health Literacy, and Lifestyle Medicine
Of the many factors driving health outcomes, behavior ranks among the most important. Far too often, physicians rely on prescribing expensive drugs instead of “first considering lifestyle changes,” Tivnan says.
Lifestyle medicine and healthcare education are two aspects of public health that lead to better outcomes. “Unfortunately, healthcare illiteracy is still prevalent in our country,” Tivnan cautions. Tivnan works with her corporate clients, helping them design programs and policies where “healthy behavior is a default,” says Tivnan. “This includes educating people to be advocates of their health and healthcare finances.”
Mental Health, Addiction and “Deaths of Despair”
From drug addiction to loneliness, mental health is an increasingly urgent public health issue. If a silver lining can be wrested from the pandemic, it is the increased awareness of psychological health. “In my practice, data science has helped identify the urgency to address mental health issues in the workplace during the pandemic,” says Tivnan.
Of all the examples of data science improving public health over the decades, Tivnan points out the impact of data analytics in addressing the rise in opioid deaths in America. When pharmaceutical companies claimed in the late 90s that opioid use wouldn’t lead to addiction, physicians prescribed them at ever-increasing rates.
“Using the National Vital Statistic System mortality data, the CDC has been able to increase awareness of this issue,” she says. “Thanks to population health analytics and data science, we know today that this statement is not true, and perpetrators have been held accountable.”
Social Justice and Equity
Equity and social justice are central public health issues informed by data analytics and big data.
Tivnan highlights the work done by the IBM Science for Social Good Partners initiative. Through its many research initiatives, the organization is instrumental in detecting new epidemics and diseases, understanding opioid addiction, and recognizing hate speech.
The U.S. Life Expectancy Estimates Project (USALEEP) from the National Center for Health Statistics reveals life expectancy disparities at a ZIP Code level and even provides block-by-block granularity.
“At the population level, health disparities cost billions of dollars annually,” Tivnan says. “The difference between life expectancy between the most privileged and the least ones is about 15 years, with income accounting for almost a third of mortality in the US.”
USALEEP helps reveal these disparities, guiding interventions and policy reform.
Accurately assessing the complex web of socio-economic factors influencing population health is ethically demanding. Designing algorithms for healthcare “has had its faults,” Tivnan says. “Many of them fail to account for potential bias and inequity.”
Data bias is a challenge generally, as AI and machine learning algorithms have come to increasingly shape modern society. “The need for a multi-faceted, multidisciplinary approach to ensure data science is accurately influencing healthcare equity is paramount,” says Tivnan.
“We do need data science professionals that are willing to go against the status quo, who are passionate about disseminating the truth through data, and who can start a movement that can positively impact population and public health.”
A Data Science Career in Public Health
According to the World Economic Forum, data scientist and analyst are among the fastest-growing professions. The reach of data science extends into every sector of our global economy. As such, a data scientist can market her skills to nearly any industry that uses data. Why choose public health? For starters, because “a career in public health is so rewarding!” says Trivnan. “There are so many opportunities at this time.”
In May of 2021, the White House announced a $7.4 billion investment to hire and train public health workers. Ostensibly in response to the COVID-19 pandemic, the funding will “allow the United States to expand its public health workforce, creating tens of thousands of jobs,” says the White House press release.
There are many roles for data scientists in public health. Among them are biostatisticians, epidemiologists, research scientists, and data analysts, to name a few. They all help improve lives and shape healthcare policy at the local, state, federal, and international levels.
“Population health and public health are one of the most important assets of a population,” Tivnan says. “The U.S. cannot be the number one economy for too long without having a strong public health system. Without health, its citizens cannot thrive and engage at work.” If there was any doubt before, the pandemic clarifies “the need for public health professionals is greater than ever,” she says. “This is the time to get engaged!”
Master of Science in Data Science
For those looking to get into the field, a master’s degree can open the door to a career in data science and predictive analysis. In the online Master of Science in Data Science degree program at Merrimack College graduates emerge with the skills, knowledge, and compassion to improve people’s lives and their communities.
The program provides a rigorous theoretical foundation and, crucially, a practical, skills-based, industry-aligned curriculum led by faculty currently practicing in the fields they teach. “How amazing is it to learn not only from the books,” Tivnan says, “but also from educators who are practicing what you are learning and can provide real insight?”
The 8-course, 32 credit hour program leads students from fundamental theory to advanced concepts and real-world application of data science. Students explore the following topics:
- Foundations of data management and statistical analysis
- Data visualization
- Data exploration and statistical learning
- Governance, laws, and ethics
- Predictive modeling
- Machine learning
The online M.S. in data science program culminates with a Capstone project that allows students to implement their knowledge in a directed, hands-on environment. Each project is a student-centered practicum that uses raw, real-world data to solve a specific industry problem through analytics and predictive forecasting.
The capstone project allows students to demonstrate and reinforce what they’ve learned by addressing problems in an industry of their choosing. What better way to launch or expand a career in public health?
Reflecting on the data science master’s program, Tivnan observes that her work allows her “to exercise my purpose every day and collaborate with like-minded people. Teaching at Merrimack College allows me to exercise my purpose and (hopefully) inspire the younger generation to improve the health of the population in the US and the world.”