Daniela De Angelis

10.9k citations
157 papers · 5.2k indexed · 2 hit papers · h-index 39

Daniela De Angelis

149 papers receiving 5.1k citations

Hit Papers

Hospital admission and emergency care atten...201620262019202220212016100200300

Peers

Daniela De Angelis
Comparison fields: 5 of 177
  • Epidemiology 2.9k
  • Infectious Diseases 1.7k
  • Hepatology 924
  • Modeling and Simulation 762
  • Public Health, Environmental and Occupational Health 578
Replace Marc Aerts with:
Marc Aerts Belgium
Claúdio J. Struchiner Brazil
Paddy Farrington United Kingdom
Emma S. McBryde Australia
Eduardo Massad Brazil
Alain‐Jacques Valleron France
Pierre‐Yves Boëlle France
Timothy B. Hallett United Kingdom
Fabrice Carrat France
Eric Weintraub United States
Daniela De Angelis relative to Marc Aerts Belgium Marc Aerts's profile →
Citations per field
00.5×3.5×
Marc Aerts · 1×
Citations per year

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

20 of 20 papers shown
#WorkIndexed citations
1 0
2 9
3 7
4 6
5 2
6 18
7
Variational inference for nonlinear ordinary differential equations.
1
8 2
9 23
10 28
11 31
12 4
13 48
14
MultiBUGS: Massively parallel MCMC for Bayesian hierarchical models
4
15 6
16 38
17 10
18 4
19 38
20
Prevalence of detectable abnormal prion protein in persons incubating vCJD: plausible incubation periods and cautious inference.
13

About Daniela De Angelis

Daniela De Angelis is a scholar working on Modeling and Simulation, Statistics and Probability and Epidemiology, having authored 157 papers that have together received 5.2k indexed citations. Recurring topics across this work include HIV, Drug Use, Sexual Risk (35 papers), COVID-19 epidemiological studies (32 papers) and HIV/AIDS Research and Interventions (25 papers). The work is most often cited by research in Modeling and Simulation (762 citations), Hepatology (924 citations) and Infectious Diseases (1.7k citations). Daniela De Angelis has collaborated with scholars based in United Kingdom, United States and Italy. Frequent 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. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of the American Statistical Association.

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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