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Introducing: the Statistical Methods Theme

Missed the Theme Launch event earlier this week? Fear not! You can catch the recording here, or if you're specifically interested in the Statistical Methods theme, read on to find out more about the exciting activities we have in store...

Why Statistical Methods for Health Equity?

The aim of the Statistical Methods theme is to improve our understanding of health inequalities and reduce disparities through the development of better statistical and machine learning methods. There are lots of academics and researchers in groups around the world who are developing great methodology across a huge variety of disciplines and application areas - machine learning, AI, epidemiology, statistics, genomics (to name a few).

The nature of research, however, means that often these groups aren't talking each other. So even though folks across different disciplines are working on similar problems and/or techniques, they might not know about it! What's more, while some of these tools are already being applied to issues related to health equity, in other cases there are some clear opportunities being missed.

This is where the Statistical Methods theme comes in. By bringing together these groups, we hope to:

  • Share knowledge and best practices across disparate disciplines;

  • Identify the most pressing challenges in developing and applying statistical and machine learning tools to health equity problems;

  • Match domain experts on the applied side with technical experts on the methodological side to spark fruitful collaborations.

Sounds up your street...?

What's on the horizon?

To kick things off over the next six months or so, we have some very exciting events and activities planned:

Monthly webinar series on statistical methods for health equity - 20th Oct: Dr Sonali Parbhoo (Imperial) - 10th Nov: Dr Emma Pierson (Cornell)

Fortnightly reading group Informal, and open to all! In this reading group, we'll discuss both recent and foundational papers to wrap our heads round the most important problems, techniques, and methodological developments related to health equity.

Field ‘landscaping’ exercise

We'll be working on producing a summary & visualisation of the various researchers and groups that are working on stat/ML methods applied to (or simply relevant to) health equity.

Want to get involved?

If you're interested in any of the above, there are a few ways to engage with the theme, depending on how involved you want to be:

That's all folks! Any questions, please email Brieuc Lehmann at


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