UCL Symposium on Statistical Methods for Health Equity

Statistical Methods Theme - DSxHE

A one-day symposium at UCL on the theme of statistical methods and data science for health equity.

Wilkins Gustave Tuck Lecture Theatre, UCL

The Institute for Mathematical and Statistical Sciences at UCL, in partnership with the <a href="https://www.datascienceforhealthequity.com/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">Data Science for Health Equity (DSxHE)</a> community, is holding a one-day symposium on "Statistical Methods for Health Equity". Our primary objective is to bring together researchers, healthcare professionals, and policymakers to help bringing the latest data-driven innovations into practice in order to better understand and ultimately reduce health inequalities. We are delighted to welcome Prof. Bhramar Mukherjee (University of Michigan) as our keynote speaker. The preliminary schedule can be found above.Please note that this will be a hybrid symposium. As spaces are limited, we ask you to only register for an in-person ticket if you are sure you will be able to join us in person. If you wish to join us online, please register <a href="https://www.datascienceforhealthequity.com/event-details/ucl-symposium-on-statistical-methods-for-health-equity" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">here</a> instead.As a satellite event, we are also hosting a "Replication Games" session on the theme of health equity on Tuesday 7th November. This is a one-day event that brings researchers together to collaborate on replicating important or recent papers in the field. To find out more about this session and to register, please click on the registration link provided <a href="https://www.eventbrite.co.uk/e/ucl-symposium-on-statistical-methods-for-health-equity-replication-game-tickets-719827131327" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">here</a>.The AI Fringe is a series of events hosted across London and the UK to complement the UK Government’s AI Safety Summit by bringing a broad and diverse range of voices into the conversation. This symposium is part of the AI Fringe series of events. By attending the symposium, you are agreeing to abide by the AI Fringe <a href="https://aifringe.org/code-of-conduct" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">code of conduct</a>. More details can be found <a href="https://aifringe.org/" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">here</a>.UCL's Departments of Mathematics and Statistical Science work together as constituent parts of UCL's Institute for Mathematical and Statistical Sciences (IMSS). The IMSS aims to become London's leading centre for research, teaching and collaboration in mathematics and statistics. Find out more about the IMSS <a href="https://www.ucl.ac.uk/mathematical-statistical-sciences/institute-mathematical-and-statistical-sciences" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">here</a>.D﻿ata Science for Health Equity (DSxHE) is a cross-sector community of academics, health and care professionals, policy-makers and enthusiasts advancing health equity through data science. Find out more about DSxHE <a href="https://www.dsxhe.com" target="_blank" data-msys-clicktrack="0" rel="nofollow noopener noreferrer">here</a>. Please direct any enquiries to Brieuc Lehmann (b.lehmann@ucl.ac.uk) and Sudipta Chowdhury (sudipta.chowdhury@ucl.ac.uk). We have a small number of travel grants available for early-career researchers (MSc and PhD students) travelling from within the UK to attend the symposium.

<h3>Prof Bhramar Mukherjee</h3>Bhramar Mukherjee is John D. Kalbfleisch Distinguished Professor, John D. Kalbfleisch Collegiate Professor and Chair of Biostatistics; Professor of Epidemiology and Global Public Health, University of Michigan School of Public Health; She also serves as the Associate Director for Quantitative Data Sciences, The University of Michigan Rogel Cancer Center. Her research interests include statistical methods for analysis of electronic health records, studies of gene-environment interaction, Bayesian methods, shrinkage estimation, analysis of high dimensional exposure data. Bhramar and her team took an active role in modeling the SARS-CoV-2 virus trajectory in India during the pandemic, with the research being covered by major media outlets like Reuters, BBC, NPR, NYT, WSJ, Der Spiegel, Australian National Radio and the Times of India. She has co-authored more than 360 articles in statistics, biostatistics, medicine, and public health. She is the founding director of the University of Michigan’s summer institute on Big Data. Bhramar is a fellow of the American Statistical Association and the American Association for the Advancement of Science. She is the recipient of many awards for her scholarship, service and teaching at the University of Michigan and beyond: including the Distinguished Woman Scholar Award from Purdue University in 2021, the Janet L. Norwood award from the University of Alabama at Birmingham and Sarah Goddard Power Award from the University of Michigan Academic Women’s Caucus in 2022. Bhramar will be inducted to the US National Academy of Medicine Fall 2023. This year she received the Karl E Peace Award for statistical contribution towards betterment of society awarded by The American Statistical Association and was named a Distinguished University Professor at the University of Michigan.

Agenda

Registration and Coffee

Introduction

Keynote (Prof Bhramar Mukherjee)

Coffee

1) Investigating inequalities for patients with cancer (Helen Blake) 2) Uncovering inequalities in the reported side effect profiles of drug formulations (David Shorthouse) 3) Assessment of the healthcare and hospital admissions of 1.2 million adult non-EU migrants and refugees in England (Rachel Burns) 4) Evaluating the effect of health visiting on child and maternal health outcomes: a target trial approach using administrative data (Catherine Bunting)

UCL Research Talks

Lunch

Cascading effects of health inequalities in AI systems

Interactive Workshop (Antonella Maia Perini) 

Coffee Break

Bridging the gap: Translating data science research into actionable impact for more equitable health policy

Panel Session

Closing Remarks

Networking Drinks

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UCL Symposium on Statistical Methods for Health Equity

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