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 51 to 60 of 200 publications
Transmission dynamics and control measures of COVID-19 outbreak in China: a modelling study.
Authors: X-S Zhang, E Vynnycky, A Charlett, D De Angelis, Z Chen, W Liu
Published:
Journal: Sci Rep
DOI: 10.1038/s41598-021-81985-z
Decreasing hospital burden of COVID-19 during the first wave in Regione Lombardia: an emergency measures context
Authors: FM Grosso, AM Presanis, K Kunzmann, C Jackson, A Corbella, G Grasselli, A Andreassi, A Bodina, M Gramegna, S Castaldi, A Zanella, M Salmoiraghi, A Castrofino, GD Castillo, L Crottogini, M Tirani, D Cereda, D De Angelis
DOI: 10.21203/rs.3.rs-288193/v1
Feasibility and efficacy of mass testing for SARS-CoV-2 in a UK university using swab pooling and PCR
Authors: B Warne, J Enright, M Metaxaki, S Fuller, RJ Samworth, G Weale, J Holgate, V Samtani, C Brierley, D Aggarwal, S Hilborne, MB Kahkeshi, S Berry, JA Douthwaite, AL Orton, R Clarke, D Danaei, R Dyer, R Glew, O Lambson, A Dahal, B Margolis, E Murphy, M Russell, VS Braithwaite, K Faulkner, E Wright, A Chaudhry, L Mactavous, M Dhada, A Parlikad, J Greatorex, I Leslie, A Neely, S Rees, A Shaw, M Vinnell, L Sheridan, E Watkins, S Baker, IG Goodfellow, PJ Lehner, K Liddell, R Clark, R Howes, MP Weekes, D McFarlane, PH Maxwell, NJ Matheson, UOCACSP Consortium
DOI: 10.21203/rs.3.rs-520626/v1
Genomic epidemiology of SARS-CoV-2 in a UK university identifies dynamics of transmission
Authors: D Aggarwal, B Warne, AS Jahun, W Hamilton, T Fieldman, L du Plessis, V Hill, B Blane, E Watkins, E Wright, G Hall, C Ludden, R Myers, M Hosmillo, Y Goodfellow, ML Pinckert, I Georgana, R Izuagbe, D Leek, O Nsonwu, G Hughes, S Packer, AJ Page, M Metaxaki, S Fuller, G Weale, J Holgate, CA Brown, R Howes, D McFarlane, G Dougan, OG Pybus, D De Angelis, PH Maxwell, SJ Peacock, M Weekes, C Illingworth, EM Harrison, NJ Matheson, IG Goodfellow, TCCT Centre, UOCACSP Consortium, TCGU Consortium
DOI: 10.21203/rs.3.rs-520627/v1
Genomics-informed outbreak investigations of SARS-CoV-2 using civet
Authors: Á O’Toole, V Hill, B Jackson, R Dewar, N Sahadeo, R Colquhoun, S Rooke, J McCrone, MP McHugh, S Nicholls, R Poplawski, TCGU Consortium, CI Project, D Aanensen, M Holden, T Connor, N Loman, I Goodfellow, CVF Carrington, K Templeton, A Rambaut
DOI: 10.1101/2021.12.13.21267267
Variational inference for nonlinear ordinary differential equations
Authors: S Ghosh, PJ Birrell, D De Angelis
Journal: 24TH INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND STATISTICS (AISTATS)
Estimating the prevalence of problem drug use from drug-related mortality data.
Authors: HE Jones, RJ Harris, BC Downing, M Pierce, T Millar, AE Ades, NJ Welton, AM Presanis, D De Angelis, M Hickman
Journal: Addiction
DOI: 10.1111/add.15111
Evaluating the causal impact of individual alcohol licensing decisions on local health and crime using natural experiments with synthetic controls.
Authors: F de Vocht, C McQuire, A Brennan, M Egan, C Angus, E Kaner, E Beard, J Brown, D De Angelis, N Carter, B Murray, R Dukes, E Greenwood, S Holden, R Jago, M Hickman
Journal: Addiction
DOI: 10.1111/add.15002
The UK hibernated pandemic influenza research portfolio: triggered for COVID-19.
Authors: CR Simpson, BD Thomas, K Challen, D De Angelis, E Fragaszy, S Goodacre, A Hayward, WS Lim, GJ Rubin, MG Semple, M Knight, NIHR hibernated pandemic studies collaborative group
Journal: Lancet Infect Dis
DOI: 10.1016/S1473-3099(20)30398-4
Forecasting the 2017/2018 seasonal influenza epidemic in England using multiple dynamic transmission models: a case study.
Authors: PJ Birrell, X-S Zhang, A Corbella, E van Leeuwen, N Panagiotopoulos, K Hoschler, AJ Elliot, M McGee, SD Lusignan, AM Presanis, M Baguelin, M Zambon, A Charlett, RG Pebody, DD Angelis
Published:
Journal: BMC Public Health
DOI: 10.1186/s12889-020-8455-9