Daniela De Angelis
| Daniela De Angelis | |
|---|---|
| Born | |
| 🏳️ Nationality | Italian |
| 💼 Occupation | |
| Known for | Infectious disease modelling |
Daniela De Angelis is an Italian biostatistician in the area of infectious disease modelling. Her current roles are Professor of Statistical Science for Health at the University of Cambridge in the Department of Primary Care and Public Health and Deputy Director and Programme Leader at the Medical Research Council Biostatistics Unit.[1]. She has published research on the development and application of statistical methods to monitor infectious diseases such as SARS COVID-19, influenza, HIV and hepatitis C[2]. Daniela is member of scientific advisory groups such as NICE, WHO, and UNAIDS. She is a member of SPI-M (Scientific Pandemic Influenza Advisory Committee, subgroup on Modelling) and the Royal Statistical Society Task Force for COVID-19[1]
Career history
In 2017, the Infected Blood Inquiry was launched.[3] Daniela De Angelis is a member of the Statistics Expert Group as part of this inquiry.[4]
In 2019, De Angelis was appointed Professor of Statistical Science for Health at the University of Cambridge.[5]
Research
HIV
In HIV modelling, Daniela De Angelis was the senior author of a study that found that England is set to have diagnosed 95% of people living with HIV by 2025[6]. This is one of three aspects of UNAIDS' 90-90-90 goal: to have 90% of people with HIV diagnosed, 90% of people diagnosed with HIV receiving antiretroviral therapy and 90% of people receiving this therapy having viral suppresion[7].
SARS COVID-19
Daniela De Angelis was the senior statistician for the MRC Biostatistics Unit's ″nowcasting″ and forecasting of COVID-19 data: using statistical modelling to estimate current (and predict future) numbers of infections, Rt, numbers of hospital admissions and more, by age and region in England[8][9]. This information was fed directly to the SAGE sub-group, SPI-M and to regional teams at UK Health Security Agency (UK HSA)[8].
Recognition
In 2018, Prof. De Angelis received the Suffrage Science Award in Maths & Computing[10].
In 2021 she was given the University of Cambridge Vice-Chancellor's Established Academic Award for her work on real-time monitoring of the SARS-COV2 pandemic[11].
In 2022, Prof. De Angelis was awarded an honorary MBE for services to medical research and public health[12]. In this year she was also awarded the Weldon Memorial Prize as a member of the Scientific Pandemic Influenza Group on Modelling, Operational sub-group (SPI-M-O)[13]
See also
- Medical Research Council
References/Notes and references
- ↑ 1.0 1.1 "Daniela De Angelis". www.mrc-bsu.cam.ac.uk. Archived from the original on 2022-11-04. Retrieved 2023-01-16.
- ↑ "Daniela De Angelis". scholar.google.co.uk.
- ↑ https://www.theguardian.com/society/2017/jul/11/contaminated-blood-scandal-theresa-may-orders-inquiry
- ↑ https://www.infectedbloodinquiry.org.uk/about/inquiry-experts
- ↑ "Notices by the General Board - Cambridge University Reporter 6557". www.admin.cam.ac.uk.
- ↑ "England set to eradicate HIV by 2030, research suggests". Independent.co.uk. 24 September 2021.
- ↑ "90-90-90: treatment for all". www.unaids.org.
- ↑ 8.0 8.1 "Nowcasting and Forecasting of the COVID-19 Pandemic". Archived from the original on 2022-11-14. Retrieved 2023-01-16.
- ↑ Birrell, Paul; Blake, Joshua; van Leeuwen, Edwin; Gent, Nick; De Angelis, Daniela (July 19, 2021). "Real-time nowcasting and forecasting of COVID-19 dynamics in England: the first wave". Philosophical Transactions of the Royal Society B: Biological Sciences. 376 (1829): 20200279. doi:10.1098/rstb.2020.0279. PMC 8165585 Check
|pmc=value (help). PMID 34053254 Check|pmid=value (help). - ↑ "M&C 2018 AWARD HANDOVER". suffragescience.
- ↑ Gaughan, Helen (March 3, 2022). "Vice Chancellor's Awards 2021". www.research-strategy.admin.cam.ac.uk.
- ↑ "Honorary awards to foreign nationals in 2022". GOV.UK.
- ↑ "Modelling the Covid-19 Pandemic in the UK: The Weldon Memorial Prize Lecture 2022 | University of Oxford". www.ox.ac.uk.
Further reading
Modeling infectious disease dynamics in the complex landscape of global health
External links
Medical Research Council Biostatistics Unit
References
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