Pascal Crépey

1.5k citations
62 papers · 751 · h-index 17

Impact in

Papers in

    • Influenza Virus Research Studies 27
    • Respiratory viral infections research 13
    • Data-Driven Disease Surveillance 4
    • COVID-19 epidemiological studies 29

Pascal Crépey

56 papers receiving 732 citations

Peers

Pascal Crépey
Comparison fields: 5 of 106
  • Modeling and Simulation 237
  • Health 176
  • Epidemiology 422
  • Infectious Diseases 212
  • Applied Microbiology and Biotechnology 23
Replace Frederik Verelst with:
Frederik Verelst Belgium
John Edmunds United Kingdom
Harvey B. Lipman United States
Amalie Dyda Australia
Lilith K. Whittles United Kingdom
William John Edmunds United Kingdom
Steven Abrams Belgium
Maurizio Barbeschi Switzerland
Alessandra Løchen United Kingdom
Maria Grazia Pompa Italy
Pascal Crépey relative to Frederik Verelst Belgium Frederik Verelst's profile →
Citations per field
00.5×4.6×
Frederik Verelst · 1×
Citations per year

Countries citing papers authored by Pascal Crépey

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Pascal Crépey Line = papers co-authored together Pascal Crépey links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 62 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200955
2 201747
3 200644
4 200740
5 202240
6 202139
7 201536
8 201736
9 201628
10 202026
11 202225
12 202225
13 201424
14 201220
15 201717
16 202016
17 202116
18 201714
19 202111
20 201811

About Pascal Crépey

Pascal Crépey is a scholar working on Epidemiology, Modeling and Simulation, Infectious Diseases, Health and Economics and Econometrics, having authored 62 papers that have together received 751 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (29 papers), Influenza Virus Research Studies (27 papers), Vaccine Coverage and Hesitancy (14 papers), Respiratory viral infections research (13 papers), SARS-CoV-2 and COVID-19 Research (8 papers), Long-Term Effects of COVID-19 (4 papers), COVID-19 Pandemic Impacts (4 papers) and Data-Driven Disease Surveillance (4 papers). The work is most often cited by research in Modeling and Simulation (237 citations), Health (176 citations), Epidemiology (422 citations), Infectious Diseases (212 citations) and Applied Microbiology and Biotechnology (23 citations). Pascal Crépey has collaborated with scholars based in France, United States and United Kingdom. Frequent co-authors include Marc Barthélemy, Maarten J. Postma, Pieter T. de Boer, Fabián P. Alvarez, Richard Pitman, Laura Temime, Narimane Nekkab, Pascal Astagneau, Avner Bar‐Hen and Laurent Coudeville. Their work appears in journals such as PLoS ONE, Influenza and Other Respiratory Viruses, Value in Health, Scientific Reports 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.

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