Pascal Crépey
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
- Epidemiology top 10%
- Influenza Virus Research Studies
- Data-Driven Disease Surveillance
Papers in
- Epidemiology 33
- Influenza Virus Research Studies 27
- Data-Driven Disease Surveillance 6
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- COVID-19 epidemiological studies 13
- Co-authors
- Marc Barthélemy (3 shared papers)Fabián P. Alvarez (4 shared papers)Maarten Jacobus Postma (5 shared papers)Richard Pitman (3 shared papers)Pieter T. de Boer (3 shared papers)Laura Temime (5 shared papers)Narimane Nekkab (4 shared papers)Pascal Astagneau (4 shared papers)
- Journals
- Influenza and Other Respiratory Viruses (5 papers)PLoS ONE (5 papers)BMC Public Health (4 papers)Scientific Reports (3 papers)Journal of Medical Economics (3 papers)
- Partner nations
- FranceUnited StatesCanada
In The Last Decade
Pascal Crépey
62 papers receiving 888 citations
Peers
Comparison fields: 5 of 86
- Modeling and Simulation 143
- Epidemiology 345
- Health 85
- Microbiology 49
- Infectious Diseases 138
Countries citing papers authored by Pascal Crépey
This map shows the geographic impact of Pascal Crépey'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 Pascal Crépey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pascal Crépey more than expected).
Fields of papers citing papers by Pascal Crépey
This network shows the impact of papers produced by Pascal Crépey. 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 Pascal Crépey. The network helps show where Pascal Crépey may publish in the future.
Co-authors
The 25 scholars most cited alongside Pascal Crépey, 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 66 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 62 | |
| 2 | 2006 | 59 | |
| 3 | 2017 | 51 | |
| 4 | 2022 | 50 | |
| 5 | 2015 | 42 | |
| 6 | 2007 | 41 | |
| 7 | 2021 | 41 | |
| 8 | 2017 | 38 | |
| 9 | 2022 | 36 | |
| 10 | 2014 | 31 | |
| 11 | 2016 | 30 | |
| 12 | 2020 | 30 | |
| 13 | 2021 | 29 | |
| 14 | 2022 | 28 | |
| 15 | 2021 | 23 | |
| 16 | 2012 | 20 | |
| 17 | 2017 | 20 | |
| 18 | 2020 | 19 | |
| 19 | 2017 | 17 | |
| 20 | 2020 | 13 |
About Pascal Crépey
Pascal Crépey is a scholar working on Epidemiology, Modeling and Simulation, Infectious Diseases, Statistical and Nonlinear Physics and Neurology, having authored 66 papers that have together received 930 indexed citations. Recurring topics across this work include Influenza Virus Research Studies (27 papers), COVID-19 epidemiological studies (13 papers), Data-Driven Disease Surveillance (6 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Long-Term Effects of COVID-19 (3 papers), Complex Network Analysis Techniques (3 papers), Mathematical and Theoretical Epidemiology and Ecology Models (3 papers) and Risk Perception and Management (2 papers). The work is most often cited by research in Modeling and Simulation (143 citations), Epidemiology (345 citations), Health (85 citations), Microbiology (49 citations) and Infectious Diseases (138 citations). Pascal Crépey has collaborated with scholars based in France, United States and Canada. Frequent co-authors include Marc Barthélemy, Fabián P. Alvarez, Maarten Jacobus Postma, Richard Pitman, Pieter T. de Boer, Laura Temime, Narimane Nekkab, Pascal Astagneau, Simon Cauchemez and Avner Bar‐Hen. Their work appears in journals such as Influenza and Other Respiratory Viruses, PLoS ONE, BMC Public Health, Scientific Reports and Journal of Medical Economics.
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.