D Lévy-Brühl
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
- Microbiology top 0.2%
- Bacterial Infections and Vaccines
Papers in
- Epidemiology 122
- Influenza Virus Research Studies 56
- Pneumonia and Respiratory Infections 24
- Virology and Viral Diseases 23
- Hepatitis B Virus Studies 17
- Health 59
- Vaccine Coverage and Hesitancy 59
- Co-authors
- Isabelle Bonmarin (26 shared papers)Denise Antona (24 shared papers)Yann Le Strat (19 shared papers)Jean‐Paul Guthmann (24 shared papers)Isabelle Parent du Châtelet (22 shared papers)Pierre‐Yves Boëlle (13 shared papers)Laure Fonteneau (26 shared papers)Simon Cauchemez (18 shared papers)
In The Last Decade
D Lévy-Brühl
234 papers receiving 6.0k citations
D Lévy-Brühl's Hit Papers
Peers
Comparison fields: 5 of 149
- Modeling and Simulation 846
- Microbiology 949
- Health 1.1k
- Epidemiology 3.1k
- Infectious Diseases 1.5k
Countries citing papers authored by D Lévy-Brühl
This map shows the geographic impact of D Lévy-Brühl'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 D Lévy-Brühl with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D Lévy-Brühl more than expected).
Fields of papers citing papers by D Lévy-Brühl
This network shows the impact of papers produced by D Lévy-Brühl. 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 D Lévy-Brühl. The network helps show where D Lévy-Brühl may publish in the future.
Co-authors
The 25 scholars most cited alongside D Lévy-Brühl, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 242 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Estimating the burden of SARS-CoV-2 in France Hit paper breakdown → | 2020 | 638 |
| 2 | 2020 | 202 | |
| 3 | 2014 | 148 | |
| 4 | 2015 | 127 | |
| 5 | 2013 | 117 | |
| 6 | 2008 | 115 | |
| 7 | 2010 | 113 | |
| 8 | 2004 | 112 | |
| 9 | 2007 | 109 | |
| 10 | 2008 | 104 | |
| 11 | 2011 | 104 | |
| 12 | 2014 | 99 | |
| 13 | 2015 | 95 | |
| 14 | 2022 | 88 | |
| 15 | 2021 | 87 | |
| 16 | 2010 | 86 | |
| 17 | 2011 | 85 | |
| 18 | 2011 | 83 | |
| 19 | 2012 | 80 | |
| 20 | 2016 | 77 |
About D Lévy-Brühl
D Lévy-Brühl is a scholar working on Epidemiology, Health, Infectious Diseases, Microbiology and Immunology, having authored 242 papers that have together received 6.2k indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (59 papers), Influenza Virus Research Studies (56 papers), Bacterial Infections and Vaccines (42 papers), Pneumonia and Respiratory Infections (24 papers), Virology and Viral Diseases (23 papers), COVID-19 epidemiological studies (21 papers), Immune responses and vaccinations (18 papers) and Hepatitis B Virus Studies (17 papers). The work is most often cited by research in Modeling and Simulation (846 citations), Microbiology (949 citations), Health (1.1k citations), Epidemiology (3.1k citations) and Infectious Diseases (1.5k citations). D Lévy-Brühl has collaborated with scholars based in France, Italy and Sweden. Frequent co-authors include Isabelle Bonmarin, Denise Antona, Yann Le Strat, Jean‐Paul Guthmann, Isabelle Parent du Châtelet, Pierre‐Yves Boëlle, Laure Fonteneau, Simon Cauchemez, D O’Flanagan and Juliette Paireau. Their work appears in journals such as Eurosurveillance, Vaccine, The International Journal of Health Planning and Management, Epidemiology and Infection and BMC Public Health.
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.