Established Academic 2021
Professor Daniela De Angelis
MRC Biostatistics Unit
School of Clinical Medicine
The Vice-Chancellor's Awards
for Research Impact and Engagement
About the researcher
Daniela De Angelis is Professor of Statistical Science for Health at the University of Cambridge in the Department of Primary Care and Public Health, Deputy Director and Programme Leader at the Medical Research Council Biostatistics Unit (MRC-BSU).
Daniela has over 25 years of experience of working at the interface between statistics and infectious disease epidemiology, focusing on the development of statistical methods for the characterisation of epidemics, including natural history, burden and prediction of future evolution, informing the implementation and evaluation of public health policies.
The Vice-Chancellor's Awards
for Research Impact and Engagement
About the researcher
Daniela De Angelis is Professor of Statistical Science for Health at the University of Cambridge in the Department of Primary Care and Public Health, Deputy Director and Programme Leader at the Medical Research Council Biostatistics Unit (MRC-BSU).
Daniela has over 25 years of experience of working at the interface between statistics and infectious disease epidemiology, focusing on the development of statistical methods for the characterisation of epidemics, including natural history, burden and prediction of future evolution, informing the implementation and evaluation of public health policies.
This has been one of the most challenging and exciting times to be in scientific research. I am glad to be playing a role in understanding this pandemic and making a difference to public health.
Professor Daniela De Angelis
What is the research?
Real-time monitoring of the SARS-COV2 pandemic
Daniela De Angelis directs a Cambridge team of statisticians working on “Real time monitoring of the SARS-COV2 pandemic”, which has provided the official Public Health England real time estimates and projections of the state of the pandemic in England.
Research on developing the statistical model for the COVID-19 pandemic first began in response to the 2009 swine influenza pandemic, in collaboration with Public Health England (PHE). The aim was to develop models for estimating and predicting the spread of a potential influenza pandemic, using information from multiple data sources available from PHE.
Key outputs of this work were the modelling and statistical methodology, and computer code, to implement a model for the spread of influenza within a population and across geographical areas.
Using data from different streams accumulating over the course of the epidemic, the model could be used to provide timely estimation and prediction of key epidemic quantities.
In a number of publications, Daniela and her team have investigated extensions to the model, including different approaches to include regional information and alternative algorithms to reduce the computational time to produce results in a timely manner.
In February 2020, this novel model was swiftly adapted to the characteristics of COVID-19 and has been continuously developed throughout the pandemic to tackle the emerging challenges and provide the regular updates needed to inform policy and the wider public.
Daniela is a senior member of the SAGE sub-group, SPI-M, which she joined in 2009. Since the outbreak of the COVID-19 pandemic, Daniela’s group has worked tirelessly providing real time updates and projections to SPI-M. The values of this contribution, crucial to informing government decisions, has been recognised in a letter from Sir Patrick Vallance, Chief Scientific Adviser. It became clear early in the pandemic that transparency in the presentation of scientific evidence was fundamental to public trust and interpretation of the rapidly evolving situation. Therefore, Daniela decided to publish their work on the MRC Unit’s website, allowing the public to access the results her team was producing.
Between April 2020 and January 2021, the research was reported by more than 2,700 local, national and international media outlets. Many articles included a link to the published reports on the Unit’s website, which, during May 2020 alone, were viewed 65,000 times. The web page continues to be visited, with more than 250,000 hits to date.
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Rapid response, building public trust and reflective practice, I was impressed with this project.
The judges
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