New Faculty Q&A: Jeff Imai-Eaton

April 1, 2023 – We are excited to welcome Jeff Imai-Eaton as Associate Professor of Epidemiology. Learn more about Eaton in the following Q&A.

I love sleuthing through multiple, disparate, and often imperfect data sources to understand the stories that lie beneath, which I think characterizes a wide range of the work we do in epidemiology.

What led you to epidemiology? What is it about the field that attracts you?

I discovered epidemiology as an undergraduate at the University of Washington weaving together majors in Math and Sociology. I took a course in demographic methods and started a research project with Professor Sam Clark (now at The Ohio State University) on modelling the potential impact of voluntary medical male circumcision on reducing HIV incidence, for which the first RCT had just been published.

The next year (perhaps as I was taking up a bit too much time in office hours), Professor Clark sent me to the Agincourt Health and Population Unit, a rural Health and Demographic Surveillance Site affiliated with the University of Witwatersrand in South Africa, where I spent a year in the data management team preparing for the annual household census, managing and cleaning the study database, and preparing datasets for analysis.

During that year, I also came to Imperial College London for a two-week short course in infectious disease modelling—which hooked me (two weeks is just enough, before the months of code debugging that follows). After completing a Master’s degree in Statistics at the University of Washington, I was fortunate to have the opportunity to return to Imperial College London for PhD and beyond.

I became fascinated by the complex interaction of human behavior, pathogen natural history, and demographic processes that underlie HIV and other epidemics—and how mathematical models could be used to disentangle these. During the year working in a dusty data room in Acornhoek, I also discovered that I love sleuthing through multiple, disparate, and often imperfect data sources to understand the stories that lie beneath, which I think characterizes a wide range of the work we do in epidemiology.

Can you tell us a little about your research background? How did you get started in your current field?

My research interests involve developing new mathematical models, statistical methods, and surveillance tools to characterize HIV epidemic trends, transmission dynamics, and the demographic impacts of HIV epidemics, especially in sub-Saharan Africa. A lot of my work involves integrating Bayesian spatiotemporal statistical methods with dynamic models for evidence synthesis from multiple data sources. I also have a longstanding interest in demographic surveillance, population cohort studies and methods for collecting and analysing longitudinal data. Key collaborations have been with the Manicaland Centre for Public Health Research in eastern Zimbabwe and the ALPHA Network of population HIV cohort studies.

A large focus of this work is developing models that are used by national HIV programs to produce official national HIV statistics. My group works closely with UNAIDS, national HIV programs, and other partners to implement these models as software tools. National teams use these tools to input their HIV surveillance and program data, generate and review model results, and disseminate to partners and stakeholders.

What questions/problems are you working on that you are most excited to explore?

HIV epidemics in sub-Saharan Africa are at a really interesting moment. For the past decade, HIV programs have focused intensely on massive expansions in HIV testing and antiretroviral treatment coverage, which has been extremely successful at reducing new HIV infections and AIDS-related deaths in Eastern and Southern Africa.

Now, in many settings, attention is turning to how to sustain these successes, identify and effectively reach the populations that have been left behind, and understand what additional prevention activities need to be prioritized to continue this progress, which, in some respects, becomes much harder to monitor as the margins become smaller. At the same time, largely through the expansion of digital health data systems to support implementation of HIV programs, there are a wealth of new data through which to understand HIV dynamics and population health with granularity not previously possible.

At the moment, I am especially interested in understanding how HIV epidemic dynamics will evolve over the next two decades, what outcomes or indicators are the best leading indicators for important epidemiologic changes, and how to integrate these within health systems to sustainably monitor program effectiveness. Through this work, I am eager to expand beyond mathematical modelling and statistical inference, to also design and pilot more efficient and targeted surveillance approaches integrated with routine health system data and model-based approaches to understanding infection transmission dynamics.

What plans do you have for the first few years of your new role as associate professor at the Harvard Chan School?

I’m really excited to continue to build on current work in global HIV surveillance, estimates, and projections, and especially new opportunities for this work through the exceptional breadth of interdisciplinary activity in HIV and global health research at the Harvard Chan School, the Longwood medical area, and the global Harvard community. I am also eager for opportunities through the Center for Communicable Disease Dynamics (CCDD) and the Epi Methods groups to find new opportunities to apply and develop the methodological tools we have underpinned this work—especially thinking about how to integrate causal inference with dynamic disease transmission models.

I look forward to the unparalleled teaching and training environment at the Harvard Chan School, participating in and contributing to these programs (including hopefully finding some causal inference courses for myself!!), and finding opportunities to expand their engagement and reach among the global public health community through which I have had the opportunity to work.

Can you tell us one thing (e.g hobbies/interests) that colleagues may not know already about you?

We love walking holidays and good food. We are super excited for the access to the outdoors and hiking in New England. When we were considering the opportunity to move, we searched “Best food in Boston” and the first four hits on Google all returned “Boston Baked Beans” as top of the list. So we are looking forward to recommendations for where to find the best baked beans, and (hopefully?) suggestions for other good things to eat in Boston!  I am not a ‘runner’, but Saturday morning Parkrun is an important fixture in my weekly mental health routine, so hoping to find a neighborhood where I can be enjoying coffee in bed at 8:30 and at the start line by 9:00!

–Coppelia Liebenthal