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 21 to 30 of 200 publications
A genetic history of continuity and mobility in the Iron Age central Mediterranean.
Authors: HM Moots, M Antonio, S Sawyer, JP Spence, V Oberreiter, CL Weiß, M Lucci, YMS Cherifi, F La Pastina, F Genchi, E Praxmeier, B Zagorc, O Cheronet, KT Özdoğan, L Demetz, S Amrani, F Candilio, D De Angelis, G Gasperetti, D Fernandes, Z Gao, M Fantar, A Coppa, JK Pritchard, R Pinhasi
Journal: Nat Ecol Evol
DOI: 10.1038/s41559-023-02143-4
An approximate diffusion process for environmental stochasticity in infectious disease transmission modelling.
Authors: S Ghosh, PJ Birrell, D De Angelis
Journal: PLoS Comput Biol
DOI: 10.1371/journal.pcbi.1011088
High number of SARS-CoV-2 persistent infections uncovered through genetic analysis of samples from a large community-based surveillance study
Authors: M Ghafari, M Hall, T Golubchik, D Ayoubkhani, T House, G MacIntyre-Cockett, H Fryer, L Thomson, A Nurtay, 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, R Cahuantzi, WSICS Team, CIS Group, TCGU Consortium, J Barrett, C Fraser, D Bonsall, AS Walker, K Lythgoe
DOI: 10.1101/2023.01.29.23285160
SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort
Authors: E Dietz, E Pritchard, K Pouwels, M Ehsaan, J Blake, C Gaughan, E Haduli, H Boothe, K-D Vihta, T Peto, N Stoesser, P Matthews, N Taylor, I Diamond, R Studley, E Rourke, P Birrell, D De Angelis, T Fowler, C Watson, D Eyre, T House, AS Walker
DOI: 10.1101/2023.10.11.23296866
Combining models to generate a consensus effective reproduction number R for the COVID-19 epidemic status in England
Authors: H Manley, J Park, L Bevan, A Sanchez-Marroquin, G Danelian, T Bayley, V Bowman, T Maishman, T Finnie, A Charlett, NA Watkins, J Hutchinson, S Riley, NMC Group, J Panovska-Griffiths
DOI: 10.1101/2023.02.27.23286501
Modelling hepatitis C infection acquired from blood transfusions in the UK between 1970 and 1991 for the Infected Blood Inquiry
Authors: S Hayes, R McCabe, D De Angelis, CA Donnelly, SJ Evans, GF Medley, DJ Spiegelhalter, SM Bird
DOI: 10.1101/2023.11.03.23298029
Genomic assessment of invasion dynamics of SARS-CoV-2 Omicron BA.1
Authors: JL-H Tsui, B Lambert, S Bajaj, JT McCrone, RPD Inward, P Bosetti, V Hill, RE Pena, AE Zarebski, TP Peacock, L Liu, N Wu, M Davis, II Bogoch, K Khan, R Colquhoun, Á O’Toole, B Jackson, A Dasgupta, E Wilkinson, H Tegally, T de Oliveira, TCGU consortium, TR Connor, NJ Loman, V Colizza, C Fraser, E Volz, X Ji, MA Suchard, B Gutierrez, M Chand, S Dellicour, S Cauchemez, J Raghwani, P Lemey, A Rambaut, OG Pybus, MUG Kraemer
DOI: 10.1101/2023.01.02.23284109
Combining models to generate consensus medium-term projections of hospital admissions, occupancy and deaths relating to COVID-19 in England
Authors: H Manley, T Bayley, G Danelian, L Burton, T Finnie, A Charlett, NA Watkins, P Birrel, D De Angelis, M Keeling, S Funk, G Medley, L Pellis, M Baguelin, GJ Ackland, J Hutchinson, S Riley, J Panovska-Griffiths
DOI: 10.1101/2023.11.06.23298026
Authors’ Reply to the Discussion of ‘Estimation of Reproduction Numbers in Real Time: Conceptual and Statistical Challenges’ by Pellis et al. in Session 3 of The Royal Statistical Society’s Special Topic Meeting on COVID-19 Transmission: 11 June 2
Authors: L Pellis, PJ Birrell, J Blake, I Hall, TA House, CE Overton, F Scarabel, HB Stage, D De Angelis
Published:
Journal: Journal of the Royal Statistical Society Series A (Statistics in Society)
DOI: 10.1111/rssa.12984
Estimation of reproduction numbers in real time: Conceptual and statistical challenges.
Authors: L Pellis, PJ Birrell, J Blake, CE Overton, F Scarabel, HB Stage, E Brooks-Pollock, L Danon, I Hall, TA House, MJ Keeling, JM Read, JUNIPER Consortium, D De Angelis
Journal: J R Stat Soc Ser A Stat Soc
DOI: 10.1111/rssa.12955