Kylie Ainslie - intro

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.

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Thanks for the intro @kylieainslie!

Flagging for everyone else that the work Kylie spoke about at last weeks seminar is now up as a preprint. See @kylieainslie.bsky.social on Bluesky for a thread. Its a really nice piece of work so well worth checking out.

or the preprint directly is https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5184990 (for some reason these for profit journal specific preprint servers make me sad but there is nothing objectively wrong with them).

@samabbott thanks for the shout out. Also, it wasn’t my preference to use a paid for preprint service. I tried submitting the paper to The Lancet ID (and was rejected) and I inadvertently ticked a box to use their pre-print server. The lesson here: pay attention when submitting a manuscript. :rofl:

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Ah they got me like this as well. I think that is why I am so mad about it!

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