Daniela De Angelis

Professor Daniela De Angelis

(she/her)
Principal investigator

MRC Biostatistics Unit

About Professor Daniela De Angelis

I am a Professor of Statistical Science for Health at the University of Cambridge in the Department of Primary Care and Public Health, and Group Leader at the MRC Biostatistics Unit, where I lead the Population Health research theme.

I have over 25 years of experience of working at the interface between statistics and infectious disease epidemiology. Marrying epidemiology and cutting-edge statistical/computational techniques, I have established and led multi-disciplinary teams developing novel methodology and tools to enable epidemic monitoring and prediction. An important focus of my research has been on the statistical questions posed by the combination of heterogeneous data, which are generally of different types, relevance, and quality, affected by observational biases, and present “big data” and privacy challenges. My methodologies have been adopted as methods of choice by national and international Health Agencies to monitor epidemics, informing the implementation and evaluation of public health policies.

I am a member of several scientific advisory groups including the Statistical Expert Group for the Infected Blood Inquiry; the Scientific Pandemic Influenza Advisory Committee (SPI-M); the Royal Statistical Society Task Force for Covid-19. In 2022, for my work during the SARS-CoV2 pandemic, I was awarded the Weldon Memorial Prize as core member of SPI-M; received the University of Cambridge Vice-Chancellor’s Award for Impact and Engagement in the Established Academic category; and became Member of the Most Excellent Order of the British Empire (MBE), Honorary Awards to Foreign Nationals in recognition of her services to Medical Research and Public Health.

Publications

Showing 191 to 200 of 200 publications

Journal-article

AIDS predictions in the UK.

Authors: ON Gill, K Porter, D de Angelis, CL Bartlett, NE Day

Published:

Journal: Lancet

DOI: 10.1016/0140-6736(93)90735-y

Journal-article

AIDS predictions in the UK.

Authors: D Goldberg, ST Green

Published:

Journal: Lancet

DOI: 10.1016/0140-6736(93)90735-y

Journal-article

AIDS predictions.

Authors: ON Gill, D De Angelis, CL Bartlett, NE Day

Published:

Journal: Lancet

DOI: 10.1016/0140-6736(93)91196-s