Today, we have an unprecedented ability to collect, store, and share data. Properly collecting and analyzing data is essential for answering complex research questions and effectively responding to major health events, such as the COVID-19 pandemic. Many public health professionals in government and other sectors want to glean meaningful insights and findings from all this data, but lack the necessary computing and statistical analysis skills to do so.
To address this critical gap, the University of Minnesota School of Public Health (SPH) recently launched a Public Health Data Science MPH, offering students the opportunity to combine public health and data science into one degree.
The program is designed to accommodate students interested in public health from a wide variety of backgrounds, including those without prior exposure to college-level mathematics or computer programming. It is suited for both recent college graduates as well as experienced professionals wanting to add data science expertise.
“This program is for people who are interested in the breadth of an MPH program and want to supplement their education with data science and computing skills,” said SPH Associate Professor and Program Director Julian Wolfson. “People do not need to know about public health or data science in order to apply — they just need to be enthusiastic about using data to improve health.”
This innovative new program — one of only a handful of such programs in the U.S. — equips students with the comprehensive skills needed to use data to design, understand, implement, and analyze public health initiatives and campaigns. Students also gain the essential communication skills required to disseminate results to public health professionals, clinicians, policy makers, and the public.
“As we’ve seen with COVID-19, data is essential to understanding and making decisions about public health challenges large and small,” said SPH Dean John Finnegan. “The size and complexity of public health data has exploded in recent years, but the number of professionals who are able to harness that data has not. With this new program, we are helping fill that gap.”
Students graduating from this program will be prepared to apply their skills across a wide range of areas, including responding to infectious diseases outbreaks, addressing the growing chronic disease burden, improving access to healthcare, reducing health disparities, and much more.
The program’s emphasis on data analytics and visualization is ideal for those in government, non-profit, and for-profit organizations who would like to further develop their skills in public health analysis and communicating results to key stakeholders.
Benefits of the Program
The UMN School of Public Health is ranked among the top 10 schools in the nation and the biostatistics program is ranked #7 in the U.S. (U.S. News & World Report). The program’s data science classes are taught by world-class biostatistics faculty, and its MPH core courses are led by the school’s top researchers in other public health areas. This means students learn from instructors who are experts in their fields and on top of the latest developments. Students in this program will also receive a lot of personal attention and opportunities fostered by a low student to faculty ratio.
The program’s courses are conveniently offered in a variety of formats, with some taking place in person and others convening online. The program is STEM qualified for students wanting this important credential.
Related but Different
Public health data science differentiates itself from related fields in significant and valuable ways:
- Epidemiology involves designing, conducting, and interpreting studies to better understand specific populations and conditions. Public health data science is for analyzing existing data to make public health programs and initiatives more effective.
- Health informatics is focused on data that come from the healthcare system, such as electronic health record data. Public health data science takes a broader view working with many different data sources coming from randomized clinical trials, observational studies, surveys, and administrative records.
- Business analytics is used to solve business problems, such as optimizing supply chains. With public health data science, practitioners apply their skills to solve problems in public health.
- Data science programs are typically aimed at people with a background in math and computer programming who want to become technical experts in new approaches to large and complex data. Public health data science accommodates people who don’t have such a background and want to solve broad public health problems using modern computing and data analysis techniques.
- Biostatistics focuses on the development and application of advanced statistical methods for analyzing biomedical datasets, and requires prior training in mathematics and statistics. Public health data science has a stronger emphasis on computational tools and is accessible to those without prior mathematical training.
“Students in the Public Health Data Science MPH program will graduate with data analysis and computational skills that better prepare them to work in data-heavy organizations, such as state departments of health and the CDC,” said Wolfson. “They’ll also be ready to work as study coordinators and managers handling primary data collection and will have a strong ability to answer questions about that data.”
SPH is now accepting applications for the new Public Health Data Science MPH program for Fall Semester 2022. The deadline to apply is April 1, 2022.