Mathematical and statistical modeling offers a useful lens through which to understand and improve pressing health problems at the population level. Yale School of Public Health (YSPH) is a leader in the use of public health modeling to inform health systems, policy making, design and implementation of interventions, and assessments of disease burden and impact.
“The way we define public health modeling is really about the process of formalizing the ideas underlying how a system works into a series of mathematical relationships. We then use that information to learn about the dynamics of a system and to make possible predictions about the impact of interventions or future disease burden,” said Virginia Pitzer, ScD, associate professor of epidemiology (microbial diseases).
Modeling Responses to COVID-19
Faculty within the Public Health Modeling Unit were involved at every level of the response to the COVID-19 pandemic. For example, Forrest Crawford, co-director of the Public Health Modeling Concentration at YSPH and associate professor of biostatistics used mobility data from cell phones to better understand how people were moving around and interacting with one another, and responding to social distancing measures during the pandemic. The purpose of the research was to better understand the contacts patterns that underlie how likely it is that an infectious individual with SARS CoV-2 would contact a susceptible individual. They devised a novel contact metric based on close personal interactions (defined as a radius of 6 feet) that substantially improved the model’s accuracy in predicting infections. The research was used to inform some of the statewide, re-open Connecticut policies. A research report was published in Science Advances.
As another example, Pitzer led a research team that analyzed a large database from the second largest HMO in Israel. The data included when individuals were tested and whether they tested positive for SARS-CoV-2, their vaccine history including when they received vaccine doses, and linked individuals to their households.
“We knew who was living with one another, how many people within a household were vaccinated, and when people got infected,” Pitzer said. The researchers used this information to answer a key question: If a vaccinated individual gets infected with COVID-19, are they more or less infectious than an unvaccinated case? “By examining data on people living in the same household, we were able to estimate not only the effect of vaccination on the risk of being infected in the first place, but also the risk of transmitting SARS-CoV-2 to another household member if one does become infected. To do so, we used an approach that allowed for multiple rounds of transmission within the household and the chance that two (or more) cases in the same household were both infected outside the household, rather than relying on approaches which assume that the first person in the household to test positive for SARS CoV-2 infected everybody else who subsequently got sick in that household,” she explained. The team’s paper, Vaccination with BNT162b2 reduces transmission of SARS-CoV-2 to household contacts in Israel, published in Science, is a finalist for the Clinical Research Forum’s Top Ten Clinical Research Achievement Awards of 2023.
Summer Course in Public Health Modeling
The Yale School of Public Health’s Summer Course in Public Health Modeling is returning for in-person instruction in June 2023. The course provides an opportunity to understand and implement the latest techniques from Yale faculty and network with an international group of public health researchers.
Pitzer is one of the faculty leaders of the week-long course, which is designed to provide researchers, clinicians, industry professionals, and policymakers with the systems-based perspective and analytic tools they need to better understand and manage the complex forces that drive the health of populations. Course topics include prediction and control of infectious disease outbreaks such as COVID-19, optimal decision-making in healthcare delivery, and designing interventions to mitigate the effects of drug overdoses. Course instructors are Yale faculty experts in epidemiology, biostatistics, health policy, and health care operations who have been at the forefront of informing model-guided responses to COVID-19 locally, nationally, and around the world.
Attend A Seminar Series
A seminar series on public health modeling takes place each semester on Mondays at noon, with the option to attend via Zoom. Executive MPH students who are interested in learning more about modeling research at Yale and beyond are welcome to attend. Upcoming seminars will be on March 6 with speaker Alessandro Vespignani of Northeastern University; April 3 with speaker Lisa Prosser of the University of Michigan; and April 17 with Rachel Lowe of LSHTM. More information can be found in the YSPH Event Calendar.
Yale Professors of Public Health Modeling
The following faculty members are instructors in the summer course in public health modeling. A full list of the faculty in Public Health Modeling can be seen here.
Forrest W. Crawford, PhD
Crawford is co-director, Public Health Modeling Concentration at YSPH, associate professor of biostatistics; associate professor of ecology and evolutionary biology, management, statistics, and data science at Yale.
A. David Paltiel, MBA, PhD
Paltiel is co-director, Public Health Modeling Concentration at YSPH and professor of public health (health policy), professor of management, professor in the Institution for Social and Policy Studies, and Affiliated Faculty, Yale Institute for Global Health.
Virginia Pitzer, ScD
Pitzer is associate professor of epidemiology (microbial diseases), and affiliated faculty, Yale Institute for Global Health.