Daniela De Angelis

10.9k total citations · 2 hit papers
157 papers, 5.2k citations indexed

About

Daniela De Angelis is a scholar working on Epidemiology, Infectious Diseases and Statistics and Probability. According to data from OpenAlex, Daniela De Angelis has authored 157 papers receiving a total of 5.2k indexed citations (citations by other indexed papers that have themselves been cited), including 90 papers in Epidemiology, 39 papers in Infectious Diseases and 38 papers in Statistics and Probability. Recurrent topics in Daniela De Angelis's work include HIV, Drug Use, Sexual Risk (35 papers), COVID-19 epidemiological studies (32 papers) and HIV/AIDS Research and Interventions (25 papers). Daniela De Angelis is often cited by papers focused on HIV, Drug Use, Sexual Risk (35 papers), COVID-19 epidemiological studies (32 papers) and HIV/AIDS Research and Interventions (25 papers). Daniela De Angelis collaborates with scholars based in United Kingdom, United States and Italy. Daniela De Angelis's co-authors include Anne M. Presanis, Matthew Hickman, A. E. Ades, Michael Sweeting, Paul Birrell, John Macleod, André Charlett, Ross Harris, Katy Turner and Nicky J. Welton and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of the American Statistical Association.

In The Last Decade

Daniela De Angelis

149 papers receiving 5.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Hospital admission and emergency care attendance risk for SARS-CoV-2 delta (B.1.617.2) compared with alpha (B.1.1.7) variants of concern: a cohort study

2021 372 citations Tommy Nyberg, Asad Zaidi et al. profile →
The natural history of Chlamydia trachomatis infection in women: a multi-parameter evidence synthesis

2016 342 citations A. E. Ades, Nicky J. Welton et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniela De Angelis United Kingdom	39	2.9k	1.7k	924	762	578	157	5.2k
Paddy Farrington United Kingdom	44	3.7k 1.3×	2.4k 1.4×	336 0.4×	783 1.0×	723 1.3×	147	8.9k
Neal A. Halsey United States	49	4.4k 1.5×	2.9k 1.7×	354 0.4×	343 0.5×	459 0.8×	177	8.7k
Marc Aerts Belgium	41	1.8k 0.6×	1.1k 0.7×	267 0.3×	631 0.8×	609 1.1×	227	6.7k
Eric Weintraub United States	47	6.9k 2.3×	3.8k 2.2×	329 0.4×	950 1.2×	465 0.8×	176	11.5k
Claúdio J. Struchiner Brazil	40	1.4k 0.5×	1.8k 1.1×	154 0.2×	1.1k 1.5×	1.8k 3.2×	214	6.1k
Emma S. McBryde Australia	42	2.4k 0.8×	2.5k 1.4×	477 0.5×	1.0k 1.3×	641 1.1×	194	5.5k
Alain‐Jacques Valleron France	42	3.6k 1.2×	1.4k 0.8×	398 0.4×	2.5k 3.3×	819 1.4×	136	6.9k
Pierre‐Yves Boëlle France	56	4.4k 1.5×	3.1k 1.8×	920 1.0×	4.1k 5.3×	1.4k 2.4×	302	12.7k
Eduardo Massad Brazil	41	1.4k 0.5×	2.1k 1.2×	294 0.3×	1.3k 1.7×	3.4k 5.8×	302	6.3k
Fabrice Carrat France	58	9.0k 3.1×	2.4k 1.4×	3.6k 3.8×	1.9k 2.5×	1.3k 2.2×	332	14.3k

Countries citing papers authored by Daniela De Angelis

Since Specialization

Citations

This map shows the geographic impact of Daniela De Angelis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniela De Angelis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniela De Angelis more than expected).

Fields of papers citing papers by Daniela De Angelis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniela De Angelis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniela De Angelis. The network helps show where Daniela De Angelis may publish in the future.

Co-authorship network of co-authors of Daniela De Angelis

This figure shows the co-authorship network connecting the top 25 collaborators of Daniela De Angelis. A scholar is included among the top collaborators of Daniela De Angelis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniela De Angelis. Daniela De Angelis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Bowers, K. J., Daniela De Angelis, & Paul Birrell. (2025). Modelling with SPEED: a Stochastic Predictor of Early Epidemic Detection. Journal of Theoretical Biology. 607. 112120–112120.

Seaman, Shaun R., Tommy Nyberg, Christopher E. Overton, et al.. (2022). Adjusting for time of infection or positive test when estimating the risk of a post-infection outcome in an epidemic. Statistical Methods in Medical Research. 31(10). 1942–1958. 9 indexed citations

Seaman, Shaun R., et al.. (2022). Nowcasting COVID-19 Deaths in England by Age and Region. Journal of the Royal Statistical Society Series C (Applied Statistics). 71(5). 1266–1281. 7 indexed citations

Nyberg, Tommy, Katie Harman, Asad Zaidi, et al.. (2022). Hospitalization and Mortality Risk for COVID-19 Cases With SARS-CoV-2 AY.4.2 (VUI-21OCT-01) Compared to Non-AY.4.2 Delta Variant Sublineages. The Journal of Infectious Diseases. 226(5). 808–811. 6 indexed citations

Morbey, Roger, Gillian Smith, Karen Exley, et al.. (2022). Estimating the Impact of Air Pollution on Healthcare-Seeking Behaviour by Applying a Difference-in-Differences Method to Syndromic Surveillance Data. International Journal of Environmental Research and Public Health. 19(12). 7097–7097. 2 indexed citations

Webster, Harriet, Tommy Nyberg, Mary Sinnathamby, et al.. (2022). Hospitalisation and mortality risk of SARS-COV-2 variant omicron sub-lineage BA.2 compared to BA.1 in England. Nature Communications. 13(1). 6053–6053. 18 indexed citations

Birrell, Paul, et al.. (2021). Variational inference for nonlinear ordinary differential equations.. International Conference on Artificial Intelligence and Statistics. 2719–2727. 1 indexed citations

Gruttola, Victor De, Frank de Vocht, Sharon Hutchinson, et al.. (2021). Evaluating the power of the causal impact method in observational studies of HCV treatment as prevention. PubMed. 13(1). 20200005–20200005. 2 indexed citations

Jones, Hayley E, Ross Harris, Matthias Pierce, et al.. (2020). Estimating the prevalence of problem drug use from drug‐related mortality data. Addiction. 115(12). 2393–2404. 23 indexed citations

10.

Vocht, Frank de, Cheryl McQuire, Alan Brennan, et al.. (2020). Evaluating the causal impact of individual alcohol licensing decisions on local health and crime using natural experiments with synthetic controls. Addiction. 115(11). 2021–2031. 28 indexed citations

11.

Harris, Ross, H Harris, Sema Mandal, et al.. (2019). Monitoring the hepatitis C epidemic in England and evaluating intervention scale‐up using routinely collected data. Journal of Viral Hepatitis. 26(5). 541–551. 31 indexed citations

12.

Zhang, Xu‐Sheng, Paul Birrell, Nicki L. Boddington, et al.. (2018). Exploiting routinely collected severe case data to monitor and predict influenza outbreaks. BMC Public Health. 18(1). 790–790. 4 indexed citations

13.

Nash, Sophie, N. Connor, Peter Kirwan, et al.. (2018). Towards elimination of HIV transmission, AIDS and HIV‐related deaths in the UK. HIV Medicine. 19(8). 505–512. 48 indexed citations

14.

Goudie, Robert J. B., Rebecca Turner, Daniela De Angelis, & Andrew C. Thomas. (2017). MultiBUGS: Massively parallel MCMC for Bayesian hierarchical models. arXiv (Cornell University). 4 indexed citations

15.

Kassanjee, Reshma, Daniela De Angelis, Debra L. Hanson, et al.. (2017). Cross-Sectional HIV Incidence Surveillance: A Benchmarking of Approaches for Estimating the ‘Mean Duration of Recent Infection’. PubMed. 9(1). 6 indexed citations

16.

Worby, Colin J., Dakshika Jeyaratnam, Julie V. Robotham, et al.. (2013). Estimating the Effectiveness of Isolation and Decolonization Measures in Reducing Transmission of Methicillin-resistant Staphylococcus aureus in Hospital General Wards. American Journal of Epidemiology. 177(11). 1306–1313. 38 indexed citations

17.

Birrell, Paul, et al.. (2012). Estimating Trends in Incidence, Time-to-Diagnosis and Undiagnosed Prevalence using a CD4-based Bayesian Back-calculation. 4(1). 10 indexed citations

18.

Nenna, Raffaella, Massimo Battaglia, Daniela De Angelis, et al.. (2011). 7% hypertonic saline and hyaluronic acid and in the treatment of infants mild-moderate bronchiolitis. European Respiratory Journal. 38(Suppl 55). 1717–1717. 4 indexed citations

19.

Sweeting, Michael, Vernon T. Farewell, & Daniela De Angelis. (2010). Multi‐state Markov models for disease progression in the presence of informative examination times: An application to hepatitis C. Statistics in Medicine. 29(11). 1161–1174. 38 indexed citations

20.

Cooper, Joseph D., Sheila M. Bird, & Daniela De Angelis. (2000). Prevalence of detectable abnormal prion protein in persons incubating vCJD: plausible incubation periods and cautious inference.. PubMed. 5(4). 209–19. 13 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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