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What is Public Health Modeling?

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Rotavirus transmission dynamics and potential impact of vaccination in developing countries by Virginia Pitzer.

The Public Health Modeling Concentration at Yale was founded on the belief that a systems-based, modeling perspective offers a useful lens through which the next generation of public health professionals may better understand and manage the complex forces that drive the health of populations.

The health of populations depends on so much more than simple biology or the behavior of individual human beings. Systems thinking – seeking to identify, to understand, and to transform the underlying processes/mechanisms that leave populations vulnerable to risk and disease – springs from the core of the public health mindset. Modeling implements this mindset and serves as an essential tool in the public health practitioner’s repertoire.

Public Health Modeling is the development and study of systems described by mathematical relationships that account for the observed behavior of real-world processes in health and medicine. Modeling seeks to link data across scales to understand (and explicitly represent) the processes underlying observed patterns and how those patterns may change under future scenarios, with or without intervention. Such processes include but are not limited to:

  • the propagation of an epidemic through an at-risk population;
  • the natural history of chronic disease in an individual patient;
  • the clinical and economic effects of expanded testing for a health condition in a target community;
  • or the allocation of a limited supply of beds in a hospital.

The Public Health Modeling Concentration provides rigorous training in systems thinking. Students will be trained to focus on the explicit portrayal of real-world processes – their “physics,” their interactions, and their dynamics – to generate evidence about how those processes might behave under different specifications. Modeling serves as a practical means of assembling the existing evidence base about mechanisms and conducting formal assessments in situations where financial, logistical, temporal, and/or ethical obstacles may conspire against the implementation and study of those mechanisms in real life. Students will learn to integrate the mechanistic modeling approaches needed to describe underlying systems with the inferential methods necessary to motivate and inform model structure and parameterization. Viewed in this context, the Public Health Modeling Concentration offers students the third pillar of public health investigation, alongside analysis of observational data and experimentation (i.e., randomized controlled studies).

Contact Information

For additional information about either the Public Health Modeling Unit or the Modeling Concentration, please contact:

  • A. David Paltiel, Professor of Public Health (Health Policy) 
  • Ted Cohen, Associate Professor of Epidemiology (Microbial Diseases)