Alyson van Raalte

Alyson van Raalte is a Research Scientist at the Max Planck Institute for Demographic Research (MPIDR) in Rostock, Germany, where she is affiliated with the Laboratory of Population Health and the MaxHel Center. Her research focuses on mortality disparities, lifespan inequality, and socioeconomic determinants of population health.

She earned her PhD in public health from Erasmus Medical Center, Rotterdam, and is an alumnus of the European Doctoral School of Demography. Her work integrates advanced demographic methods with public health applications to understand how inequalities in mortality evolve across populations and over time.

Her research interests include lifespan inequality, healthy longevity, cohort analysis, demographic methods for measuring mortality variation, and the social determinants of health. She investigates how factors such as education, region, and childhood adversity contribute to disparities in life expectancy and lifespan variation. Her methodological contributions include perturbation analysis of lifespan variability and decomposition techniques for mortality inequalities.

The trends in her recent publications reveal a strong focus on lifespan inequality, cohort mortality profiling, educational and regional disparities in mortality, and the impact of structural factors like smoking and reunification on population health. She frequently employs decomposition methods, multistate models, and innovative visualization techniques to analyze complex demographic data.

• European Demographer Award (mid-career) from Population Europe
• European Research Council (ERC) Starting Grant (LIFEINEQ)
• Max Planck Society STG Extension Award

Alyson van Raalte has been supported by significant grants, including an ERC Starting Grant and Max Planck Society funding. She collaborates extensively with international researchers and contributes to large-scale projects such as COVerAGE-DB, a global database on age-structured COVID-19 cases and deaths. While no formal students are listed, she likely mentors junior researchers through her collaborative work and leadership in methodological innovation.

She is actively involved in research groups focused on population health and contributes to software development, including R and Stata packages for Markov chain analysis. Her work bridges demographic theory, statistical methodology, and real-world public health challenges.