Professor Daniela De Angelis
(she/her)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 31 to 40 of 200 publications
Hospitalisation and mortality risk of SARS-COV-2 variant omicron sub-lineage BA.2 compared to BA.1 in England.
Authors: HH Webster, T Nyberg, MA Sinnathamby, NA Aziz, N Ferguson, G Seghezzo, PB Blomquist, J Bridgen, M Chand, N Groves, R Myers, R Hope, E Ashano, J Lopez-Bernal, D De Angelis, G Dabrera, AM Presanis, S Thelwall
Published:
Journal: Nat Commun
DOI: 10.1038/s41467-022-33740-9
Misclassification bias in estimating clinical severity of SARS-CoV-2 variants - Authors' reply.
Authors: T Nyberg, NM Ferguson, J Blake, W Hinsley, S Bhatt, D De Angelis, S Thelwall, AM Presanis
Published:
Journal: Lancet
DOI: 10.1016/S0140-6736(22)01432-5
Editorial.
Authors: D De Angelis, P Birrell, S Funk, T House
Journal: Stat Methods Med Res
DOI: 10.1177/09622802221118613
Methods for modelling excess mortality across England during the COVID-19 pandemic.
Authors: S Barnard, C Chiavenna, S Fox, A Charlett, Z Waller, N Andrews, P Goldblatt, P Burton, D De Angelis
Journal: Stat Methods Med Res
DOI: 10.1177/09622802211046384
Trends in COVID-19 hospital outcomes in England before and after vaccine introduction, a cohort study.
Authors: PD Kirwan, A Charlett, P Birrell, S Elgohari, R Hope, S Mandal, D De Angelis, AM Presanis
Published:
Journal: Nat Commun
DOI: 10.1038/s41467-022-32458-y
Spatial growth rate of emerging SARS-CoV-2 lineages in England, September 2020-December 2021.
Authors: MR Smallman-Raynor, AD Cliff, COVID-19 Genomics UK (COG-UK) Consortium
Published:
Journal: Epidemiol Infect
DOI: 10.1017/S0950268822001285
Estimating the Impact of Air Pollution on Healthcare-Seeking Behaviour by Applying a Difference-in-Differences Method to Syndromic Surveillance Data.
Authors: R Morbey, G Smith, K Exley, A Charlett, D de Angelis, S Harcourt, F Gonzalez, I Lake, A Dobney, A Elliot
Published:
Journal: Int J Environ Res Public Health
DOI: 10.3390/ijerph19127097
Challenges in estimation, uncertainty quantification and elicitation for pandemic modelling.
Authors: B Swallow, P Birrell, J Blake, M Burgman, P Challenor, LE Coffeng, P Dawid, D De Angelis, M Goldstein, V Hemming, G Marion, TJ McKinley, CE Overton, J Panovska-Griffiths, L Pellis, W Probert, K Shea, D Villela, I Vernon
Journal: Epidemics
DOI: 10.1016/j.epidem.2022.100547
Lineage replacement and evolution captured by three years of the United Kingdom Covid Infection Survey
Authors: K Lythgoe, T Golubchik, M Hall, T House, R Cahuantzi, G MacIntyre-Cockett, H Fryer, L Thomson, A Nurtay, M Ghafani, D Buck, A Green, A Trebes, P Piazza, LJ Lonie, R Studley, E Rourke, D Smith, M Bashton, A Nelson, M Crown, C McCann, GR Young, RAN dos Santos, Z Richards, A Tariq, WSICS Team, CIS Group, TCGU Consortium, C Fraser, I Diamond, J Barrett, AS Walker, D Bonsall
DOI: 10.1101/2022.01.05.21268323
The hyper-transmissible SARS-CoV-2 Omicron variant exhibits significant antigenic change, vaccine escape and a switch in cell entry mechanism
Authors: BJ Willett, J Grove, OA MacLean, C Wilkie, N Logan, G De Lorenzo, W Furnon, S Scott, M Manali, A Szemiel, S Ashraf, E Vink, WT Harvey, C Davis, R Orton, J Hughes, P Holland, V Silva, D Pascall, K Puxty, A da Silva Filipe, G Yebra, S Shaaban, MTG Holden, RM Pinto, R Gunson, K Templeton, PR Murcia, AH Patel, TCGU Consortium, J Haughney, DL Robertson, M Palmarini, S Ray, EC Thomson
DOI: 10.1101/2022.01.03.21268111