Filippo Trentini

3.8k citations
37 papers · 1.6k indexed · 2 hit papers · h-index 17
Topics
COVID-19 epidemiological studies (25 papers)SARS-CoV-2 and COVID-19 Research (11 papers)Vaccine Coverage and Hesitancy (9 papers)
Partner nations
ItalyUnited StatesChina

In The Last Decade

Filippo Trentini

33 papers receiving 1.5k citations

Hit Papers

Coexpression of CD49b and LAG-3 identifies human and mous...201320262017202120132023200400600

Peers

Filippo Trentini
Comparison fields: 5 of 122
  • Immunology 535
  • Infectious Diseases 504
  • Modeling and Simulation 499
  • Epidemiology 246
  • Oncology 232
Replace Neta S. Zuckerman with:
Neta S. Zuckerman Israel
Aaron Sutherland United States
Sydney I. Ramirez United States
Carolyn Rydyznski Moderbacher United States
Daniel Marrama United States
Siaw Shi Boon Hong Kong
Oliver J. Watson United Kingdom
Jayachandran Radhakrishnan United Kingdom
Mark Frank Germany
Alexandra B. Hogan United Kingdom
Filippo Trentini relative to Neta S. Zuckerman Israel Neta S. Zuckerman's profile →
Citations per field
00.5×1.5×2.5×
Neta S. Zuckerman · 1×
Citations per year

Countries citing papers authored by Filippo Trentini

Since Specialization
Citations

This map shows the geographic impact of Filippo Trentini'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 Filippo Trentini with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Filippo Trentini more than expected).

Fields of papers citing papers by Filippo Trentini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Filippo Trentini. 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 Filippo Trentini. The network helps show where Filippo Trentini may publish in the future.

Co-authorship network of co-authors of Filippo Trentini

This figure shows the co-authorship network connecting the top 25 collaborators of Filippo Trentini. A scholar is included among the top collaborators of Filippo Trentini 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 Filippo Trentini. Filippo Trentini 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 0
3 0
4 15
5 1
6 4
7 1
8 29
9 6
10 15
11 5
12 41
13 62
14 46
15
Effectiveness of regional restrictions in reducing SARS-CoV-2 transmission during the second wave of COVID-19, Italy
5
16 65
17 6
18 9
19 10
20 52

About Filippo Trentini

Filippo Trentini is a scholar working on Modeling and Simulation, Infectious Diseases and Health, having authored 37 papers that have together received 1.6k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (25 papers), SARS-CoV-2 and COVID-19 Research (11 papers) and Vaccine Coverage and Hesitancy (9 papers). The work is most often cited by research in Modeling and Simulation (499 citations), Infectious Diseases (504 citations) and Health (223 citations). Filippo Trentini has collaborated with scholars based in Italy, United States and China. Frequent co-authors include Stefano Merler, Piero Poletti, Marco Ajelli, Giorgio Guzzetta, Valentina Marziano, Alessia Melegaro, Clelia Di Serio, Silvia Gregori, De’Broski R. Herbert and Monica E. Gianolini. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Medicine and Nature Communications.

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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