DATA 
SCIENCE
FOR
HEALTH
EQUITY

Socioeconomic status (SES) is part of the default demographic toolkit in health research — right up there with age and sex. And much like those, it’s often included reflexively, adjusted for automatically, and measured using whatever data happen to be available. Part 1 lays out the limits of income-based SES measures and introduces alternative ways to capture deprivation, including household-level metrics and geographic proxies.

Recording of the launch of the Data Diversity Theme, a new initiative from Data Science for Health Equity (DSxHE) in partnership with Cancer Research UK. Don't want to miss out on any future Data Diversity theme activities? Stay up to date by joining the #theme-data-diversity channel on our Slack workspace .

We were delighted to host Jake Hightower, data science and global health innovator, for the latest instalment of our webinar series on statistical methods for fairness and equity in healthcare. Topic:   Preserving Health Equity in a Global Pandemic Model Abstract  In an era of increasingly complex global health threats, pandemic modelling must evolve to reflect not only the spread of disease but the lived realities of those most affected. This talk presents a ground-breaking