Christel Faes
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
-
- Antibiotic Use and Resistance
Papers in
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- COVID-19 epidemiological studies 62
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- Statistical Methods and Bayesian Inference 50
- Statistical Methods and Inference 19
- Statistical Methods in Clinical Trials 17
- Co-authors
- Niel Hens (82 shared papers)Marc Aerts (57 shared papers)Geert Molenberghs (53 shared papers)Tapiwa Ganyani (8 shared papers)Jacco Wallinga (5 shared papers)Andrea Torneri (6 shared papers)Philippe Beutels (31 shared papers)Cécile Kremer (6 shared papers)
- Journals
- Statistics in Medicine (14 papers)Spatial and Spatio-temporal Epidemiology (12 papers)PLoS ONE (12 papers)BMC Public Health (10 papers)Journal of Antimicrobial Chemotherapy (8 papers)
- Partner nations
- BelgiumUnited StatesUganda
In The Last Decade
Christel Faes
220 papers receiving 4.2k citations
Peers
Comparison fields: 5 of 184
- Modeling and Simulation 988
- Applied Microbiology and Biotechnology 319
- Statistics and Probability 405
- Infectious Diseases 678
- Health, Toxicology and Mutagenesis 327
Countries citing papers authored by Christel Faes
This map shows the geographic impact of Christel Faes'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 Christel Faes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christel Faes more than expected).
Fields of papers citing papers by Christel Faes
This network shows the impact of papers produced by Christel Faes. 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 Christel Faes. The network helps show where Christel Faes may publish in the future.
Co-authors
The 25 scholars most cited alongside Christel Faes, 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 239 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 392 | |
| 2 | 2011 | 225 | |
| 3 | 2020 | 160 | |
| 4 | 2006 | 147 | |
| 5 | 2011 | 128 | |
| 6 | 2009 | 91 | |
| 7 | 2012 | 89 | |
| 8 | 2011 | 86 | |
| 9 | 2011 | 83 | |
| 10 | 2007 | 81 | |
| 11 | 2013 | 79 | |
| 12 | 2015 | 74 | |
| 13 | 2009 | 69 | |
| 14 | 2020 | 67 | |
| 15 | 2005 | 61 | |
| 16 | 2021 | 61 | |
| 17 | 2021 | 54 | |
| 18 | 2011 | 52 | |
| 19 | 2011 | 52 | |
| 20 | 2014 | 52 |
About Christel Faes
Christel Faes is a scholar working on Modeling and Simulation, Statistics and Probability, Management Science and Operations Research, Infectious Diseases and Epidemiology, having authored 239 papers that have together received 4.3k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (62 papers), Statistical Methods and Bayesian Inference (50 papers), Statistical Methods and Inference (19 papers), Statistical Methods in Clinical Trials (17 papers), Data-Driven Disease Surveillance (17 papers), Spatial and Panel Data Analysis (15 papers), Animal Disease Management and Epidemiology (14 papers) and Bayesian Methods and Mixture Models (13 papers). The work is most often cited by research in Modeling and Simulation (988 citations), Applied Microbiology and Biotechnology (319 citations), Statistics and Probability (405 citations), Infectious Diseases (678 citations) and Health, Toxicology and Mutagenesis (327 citations). Christel Faes has collaborated with scholars based in Belgium, United States and Uganda. Frequent co-authors include Niel Hens, Marc Aerts, Geert Molenberghs, Tapiwa Ganyani, Jacco Wallinga, Andrea Torneri, Philippe Beutels, Cécile Kremer, Dongxuan Chen and Herman Goossens. Their work appears in journals such as Statistics in Medicine, Spatial and Spatio-temporal Epidemiology, PLoS ONE, BMC Public Health and Journal of Antimicrobial Chemotherapy.
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.