Hey y’all! I’m Kylie Ainslie. Since I’ve been roped into speaking at the Epinowcast seminar next month (2 April 2025 - mark your calendars!), I thought it was time for an introduction. I have a background in biostatistics (PhD in Biostatistics), infectious disease modelling (postdoc in flu modelling/COVID response at Imperial College London), and assessing vaccine impact.
I currently work as a Senior Researcher in the Unit for Infectious Disease Modelling at the Dutch National Institute for Public Health and the Environment (RIVM). It’s a very long winded way of saying, I’m an ID modeller. My work focuses on developing statistical and mathematical models to inform public health decision-making. I specialise in models that include vaccination and looking at the impact of vaccination on disease outcomes. I led the modelling work that informed the Dutch COVID-19 vaccine rollout and subsequent booster recommendations.
After the emergency response phase of the COVID pandemic ended, I decided to work on something unrelated and have been working on a project to estimate the epidemiological quantities that govern scabies transmission (more about this in my upcoming talk!). One of the methods that I use to estimate the serial interval of scabies, involves using mixture models, which is what peaked @samabbott’s interest and got me connected to the epinowcast community. This work has also resulted in an R package mitey.
I’m also an Honorary Assistant Professor at the University of Hong Kong.
More broadly, I’m interested in how past exposures, either through vaccination or natural infection, impacts a person’s susceptibility to future infection. I’m also interested in combining statistical approaches with mathematical modelling to determine vaccine impact at the population level and developing shared tools for Epi/ID research. While not trained as a software developer, I create R packages for most of my projects, so the code base can be shared and re-used. I’m passionate about open science and reproducibility.
For more about me and, more importantly, puppy pics, see here.