Alumni spotlight on Leontine Alkema: Bridging statistics and application for global health
Dr. Leontine Alkema is a professor of biostatistics at the University of Massachusetts Amherst (UMass) School of Public Health & Health Sciences.
Alkema received her PhD in Statistics at the University of Washington (UW) in 2008, with a CSSS track concentrating on statistical demography — studying human populations. Alkema develops statistical models to assess population-level health trends in countries around the world, with a focus on family planning and child, maternal, and reproductive health.
She spoke with CSSS in Fall 2023 about her academic journey, and how she hopes to contribute to statistical demography and global health going forward. This interview has been edited for length and clarity.
Question: What was your path into your current work?
Answer: I’ve always liked math and solving problems. I went to Delft University of Technology in the Netherlands feeling confident I wanted to study mathematics for my undergrad and master’s degrees. There, my interest in statistics grew naturally, as part of making sense out of data.
So, I was clear with my foundation in statistics, but I wasn't clear on how to best use it! I knew I wanted to do “something good”. I actually started a second degree in psychology during my undergrad, but it didn’t stick for me. The only job I applied to after my master’s was a risk assessment job in Fiji Islands. I didn’t get the job, I knew I was underqualified — but it did spark my interest in considering further studies to see how my quantitative background and statistic skills might be useful for studying human populations around the world.
Coming to Seattle was a key step to develop my focus. My journey into demography really started during a project with my doctoral advisors, Adrian Raftery and Sam Clark, on the HIV/AIDS pandemic. I loved the combination of learning more about the pandemic, cool modeling, and working with real data. At one point, Adrian went on sabbatical — so I decided to try to go on a mini-sabbatical too! I was fortunate to get the opportunity to spend time at the UN Population Division in New York and research centers in Kenya and South Africa, which was a really important experience for me in terms of exposure to research outside academia. Throughout my PhD, I also received excellent training from faculty and peers in the Statistics and Biostatistics departments, CSSS, and the Center for Studies in Demography and Ecology.
After my PhD, I did a brief postdoc at Columbia University, and then joined the Department of Statistics at the National University of Singapore. My research and collaborations at the intersection of statistics and demography/global health really took off during that time. After several years I did want to return to the US and had the opportunity to join UMass, which has been a great home base since 2015.
Q: Your research has explored many different topics. What projects would you highlight?
A: My main research to date has focused on developing statistical models for demographic indicators in low- and middle-income countries. My greatest motivation for doing research is to help improve reproductive, maternal, and child health worldwide. I’ve collaborated with groups including the UN Population Division (UNPD), UNICEF, the WHO, Avenir Health, and Guttmacher Institute to develop estimation and projection methods for indicators including child and maternal mortality rates, the total fertility rate, family planning indicators such as contraceptive use, and abortion incidence.
Family planning (FP) and related reproductive health indicators are closest to my heart, because of how they connect to reproductive freedom and rights. I feel fortunate that I got introduced into this area early in my post-PhD career, when I got to work with a great group at the UNPD to develop a global family planning estimation model, shared in our 2013 paper in The Lancet. Then, working with Track20 — a global family planning project — we developed the Family Planning Estimation Tool (FPET) for countries to produce their own estimates, connected to the FP2020 and now FP2030 global initiative.
The model has evolved over time, with its use in countries and with funding from the Bill and Melinda Gates Foundation for further model development. Fast forward to the present: this academic year, we are finalizing a new version of FPET which will be used in the country workshops next year to produce subnational estimates. This is exciting in many ways. Research-wise, it’s the accumulation of years of work with students and postdocs in my group at UMass and collaborations with Avenir Health and UNPD. Substantively, it is so rewarding to know that this work can help programming in countries!
Q: Coming from your statistics training, how did your interest in interdisciplinary research and demography develop?
A: I think I've always been interested in demography and quantitative social sciences in general, I just didn’t have a label for it. In these fields, numbers are so much more than just inputs or outputs of models — it’s about people and their lives. I still find it incredible that when I’m working with data from a survey, these numbers refer to individuals answering questions about their lives — and that I’m using those data to try to learn something that can then hopefully lead to action for the better.
Given my training in mathematics and statistics, I’ve been drawn to interdisciplinary, collaborative research with social scientists because I see it as the only way to do useful applied research — to make sure that the data crunching we are doing makes sense in terms of answering the right question and interpreting the data appropriately. During my time at UW, seminars at CSSS and CSDE were important to get exposed to this kind of research. And once I started doing my own research, there was a bit of a snowball effect whereby the more I learned, the more interested I got about substantive areas.
Q: What’s one important piece of advice for trainees or graduate students?
A: I find it really difficult to give general advice because academic journeys are so personal and dependent on someone’s interests. But along those lines, one aspect that I find important looking back at my own trajectory is to stay close to your own goals. Grad school can be overwhelming and you can easily feel subject to lots of expectations and pressure. I think success in grad school comes from a combination: programs offer opportunities, but you must also actively seek out the things you need and craft your own journey, even if it goes against expectations. This advice might not work for everybody, but I’m glad that I stayed close to what I wanted to get out of the PhD program: to get training in statistics but also in other areas, to work on interdisciplinary projects, and get exposure beyond academic research.
In grad school, I would also not forget about your peers (for statisticians learning about the social sciences, those would be grad students in other departments). This can be really helpful and enjoyable in terms of learning about new areas and building connections. In my time at CSSS, we started ‘CSSSSSS’ — a CSSS student seminar series — where students from different departments would present, and I found that really interesting and fun and a low-key approach to learn about different topics.
Q: What was a favorite spot around the UW campus or the university district in Seattle?
A: Seattle was a wonderful adventure. I spent so much time in coffee shops – like Zoka in the University Village, enjoying good coffee and pastries. I didn’t drink coffee before coming to Seattle, but I started while there! I also liked biking around and just exploring the different neighborhoods. I do remember being frustrated by the hills everywhere, but I have lots of nice memories of biking around Seattle.
(1) Alkema biking around Seattle. (2) With supervisors Adrian Raftery and Sam Clark after Alkema's PhD defense. (3) Some of the first CSSS PhD track graduates in the mid-2000s, including Alkema (second from the right).