About me
Hi! I’m a PhD student in demography and economic history at the London School of Economics. I am also an affiliate of the Leverhulme Centre for Demographic Science at the University of Oxford, and throughout 2024, I was a Research Fellow (Forsker III) at Oslo Metropolitan University’s Centre for Research on Pandemics & Society (PANSOC).
Most of my work focuses on the societal impacts of social and demographic crises. I have a particular focus on better understanding the 1918 influenza pandemic, but I have also worked on the trends in high-income national fertility after the 2009 global financial crisis and on the geography of mental health around the 2016 Brexit referendum in the UK. One of my bigger collaborative projects uses census microdata data from 1880s through the 2010s to test how polygyny affects marriage markets and might impact social conflict.
My PhD thesis focuses on re-estimating the mortality of the 1918 influenza pandemic, using new methods and data.
At LSE, I am based in the Department of Economic History. Further afield, I am involved in the community of demographers spread across the university and beyond, serving on the Board of the Association of Young Historical Demographers and the EU-funded GreatLeap project.
Before landing at LSE, I completed a MPhil in Demography at Nuffield College, University of Oxford. During my MPhil, I was also affiliated with Oxford’s Department of Sociology. Before that, I completed a BA in Human Sciences at the University of Oxford, an interdisciplinary programme of biology and social science.
Latest publication
- Gaddy, H., Sear, R., & Fortunato, L. (2025). High rates of polygyny do not lock large proportions of men out of the marriage market. PNAS, 122(40): e2508091122. doi:10.1073/pnas.2508091122
Current projects
If you want to read what I am working on at the moment, here are preprints of a few of my current projects!
- “The missing Pacific influenza epidemics, 1918–21” (with Svenn-Erik Mamelund and Michael G. Baker), doi:10.31235/osf.io/4mb5a
- “We are our memory: Quantifying the demographic imprints of the past”, doi:10.31235/osf.io/6r5b8
