Carnegie Mellon University

In Support of Public & Population Health

"As threats to population health increase in scale and complexity, they will continue to demand an adaptive response that is tailored for the modern era and focused on achieving equitable outcomes. At this pivotal moment for our global society, Carnegie Mellon embraces the opportunity to expand our impact in public and population health."

Farnam Jahanian, President

ISOPPH Charge: A Multi-Disciplinary Investigation

June 2021

Public health has made tremendous contributions to human welfare in the last century. Sanitation, vaccination, disease eradication and many other interventions and policies have saved untold lives and improved wellbeing. Yet public health spending from 2008-18 has largely been flat or declining, leaving public health agencies with a compromised ability to respond to public health emergencies of any cause.  The COVID-19 pandemic both highlighted urgent challenges and created a window of opportunity to address them. These challenges include, among others:

  1. Advanced 21st-century data-collection, technologies, and processing have not yet permeated public health to the extent they permeate the private sector. For example, real-time, fine-grained situational awareness and forecasting are crucial for data-driven management of public health threats and emergencies. Yet today, more is known about current and future demand for athletic shoes than about the current and future incidence of COVID-19 or other infectious diseases.
  2. In health catastrophes, outcomes can depend as much on human beliefs, values, cultures, attitudes, health information literacy and decision-making (public and private) as they do on other factors like the pathogen or the weather. Understanding how information, misinformation and disinformation spread during a crisis is crucial, as is developing systems-level approaches to avoid the worst and leverage the best of human decision making and behavior. These challenges highlight the need for language tracking and processing technologies along with modern social science regarding decision-making, incentives, and communications.
  3. Vulnerability to public health threats can vary greatly across social and demographic groups.  For more equitable outcomes, we must be able to rapidly identify, understand, protect, support, and engage the most vulnerable.
  4. As public health practice continues to evolve, the next generation of public health professionals will need to understand behavioral responses to health problems and policies, and be trained in new and emerging data-driven technologies and implementations, potentially requiring a revamping of public health educational programs.
  5. Health-preserving measures may clash with economic considerations and livelihoods. Data and economic theory to understand and manage this conflict at both the policy and operational levels must be an integral part of the public health response.
  6. Although public health is highly cost-effective, especially as compared with healthcare, it depends on government funding, is not easily amenable to commercialization, and thus does not easily benefit from private sector investment or disruptive market forces. Thus, there is a critical role for effective reorganization and change management at all levels of government: local, state, and federal.

Threats to the public's health in the modern era have been increasing in scale and complexity. They demand an adaptive and resilient response. Improving public and population health has become one of the biggest challenges of our generation. We applaud governments' re-focus on public and population health in the aftermath of the pandemic. However, we believe it is incumbent upon all of us — even those outside public health — to pause and consider whether our skills and expertise can help address these national and global challenges.

CMU has strengths in many areas that can be leveraged in new support of public health. These span all seven colleges and include computation, data science, genomics, risk analysis, systems engineering, sensors and embedded systems, cognitive and behavioral science, learning science, market mechanism design, health and labor economics, technology and policy, business innovation, design, communication, and many more. Many CMU faculty have long been working with public health researchers and practitioners and could expand their interactions to improve their understanding of public health’s unique needs and challenges, then bring their respective expertise more directly and effectively to bear on these needs and challenges.

The goal of the ISOPPH Working Group is thus to investigate, via discussions with public health experts, community representatives, interested faculty, and other stakeholders, whether and how CMU faculty expertise and interests can be more intentionally aligned in support of addressing the gaps and challenges facing public and population health in the 21st century.

To do this, the working group will also consider CMU faculty’s expertise, experience, and interest in areas of medical research, medical practice, healthcare, and healthcare policy, however the focus will be on population level health. Admittedly, the boundary between these fields and public and population health is not always clear. As a rule of thumb, the working group will avoid any challenge that can already adequately leverage the private sector.

The working group’s investigative focus will be on initiatives with the potential to achieve on-the-ground impact on population health and public health practice within a few years. If any such initiatives require substantial effort that is not traditionally academic in nature, the working group will note this in its report and suggest the changes in organizational structures and incentives that these efforts require.

Deliverable: Initial summary of findings, conclusions, and recommendations for next steps, if any, + supporting material within 90 days.

ISOPPH Working Group


Amelia Haviland, Professor of Statistics and Health Policy, Heinz College

Roni Rosenfeld, Professor and Head, Machine Learning Department, School of Computer Science

Working Group Members

Amesh Adalja, MD, Adjunct Assistant Professor, Biological Sciences, Mellon College of Science

David Creswell, Associate Professor of Psychology, Dietrich College

Baruch Fischhoff, Howard Heinz University Professor, Institute of Politics and Strategy, and Engineering and Public Policy, Heinz College and College of Engineering

Marty Gaynor, E.J. Barone University Professor of Economics and Public Policy, Heinz College

Rayid Ghani, Distinguished Career Professor in the Machine Learning Department and the Heinz College of Information Systems and Public Policy, School of Computer Science and Heinz College


Soo-Haeng Cho, Professor of Operation Management and Strategy, Tepper School of Business

Luisa Hiller, Eberly Family Career Development Associate Professor of Biological Sciences, Mellon College of Science

Kristin Hughes, Associate Professor, College of Fine Arts

Rema Padman, Trustees Professor of Management Science and Healthcare Informatics, Heinz College

Ryan Tibshirani, Associate Professor Statistics and Machine Learning, Dietrich College and School of Computer Science

Sarah Young, Social Sciences Librarian, Libraries

Staff to the Working Group

Pam Eichenbaum, Manager of Special Projects, President’s Office