Cécile Tran Kiem
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies 15
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research 12
- Health top 10%
- Vaccine Coverage and Hesitancy 6
- Economics and Econometrics top 10%
- COVID-19 Pandemic Impacts 4
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- Zoonotic diseases and public health 2
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- COVID-19 and healthcare impacts 2
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- Influenza Virus Research Studies 1
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- Insect symbiosis and bacterial influences 1
- Co-authors
- Simon CauchemezPaolo BosettiArnaud FontanetD Lévy-BrühlHenrik SaljePierre‐Yves BoëlleJuliette PaireauAlessio Andronico
- Partner nations
- FranceUnited KingdomUnited States
In The Last Decade
Cécile Tran Kiem
19 papers receiving 868 citations
Hit Papers
Peers
Comparison fields: 5 of 102
- Modeling and Simulation 491
- Infectious Diseases 488
- Health 105
- Economics and Econometrics 143
- Clinical Psychology 94
Countries citing papers authored by Cécile Tran Kiem
This map shows the geographic impact of Cécile Tran Kiem'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 Cécile Tran Kiem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cécile Tran Kiem more than expected).
Fields of papers citing papers by Cécile Tran Kiem
This network shows the impact of papers produced by Cécile Tran Kiem. 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 Cécile Tran Kiem. The network helps show where Cécile Tran Kiem may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Cécile Tran Kiem, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 8 | |
| 3 | 2024 | 24 | |
| 4 | 2023 | 4 | |
| 5 | 2022 | 11 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 11 | |
| 8 | 2022 | 23 | |
| 9 | 2021 | 28 | |
| 10 | 2021 | 16 | |
| 11 | 2021 | 39 | |
| 12 | A race between SARS-CoV-2 variants and vaccination: The case of the B.1.1.7 variant in France | 2021 | 2 |
| 13 | 2021 | 39 | |
| 14 | 2021 | 25 | |
| 15 | Short and medium-term challenges for COVID-19 vaccination: from prioritisation to the relaxation of measures | 2021 | 3 |
| 16 | 2021 | 5 | |
| 17 | 2021 | 11 | |
| 18 | Estimating the burden of SARS-CoV-2 in Francebreakdown → | 2020 | 636 |
| 19 | 2020 | 1 | |
| 20 | Evaluation des stratégies vaccinales COVID-19 avec un modèle mathématique populationnel | 2020 | 2 |
About Cécile Tran Kiem
Cécile Tran Kiem is a scholar working on Modeling and Simulation, Health and Infectious Diseases, having authored 20 papers that have together received 889 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (15 papers), SARS-CoV-2 and COVID-19 Research (12 papers), Vaccine Coverage and Hesitancy (6 papers), COVID-19 Pandemic Impacts (4 papers), Zoonotic diseases and public health (2 papers), COVID-19 and healthcare impacts (2 papers), Influenza Virus Research Studies (1 paper) and Insect symbiosis and bacterial influences (1 paper). The work is most often cited by research in Modeling and Simulation (491 citations), Infectious Diseases (488 citations) and Health (105 citations). Cécile Tran Kiem has collaborated with scholars based in France, United Kingdom and United States. Frequent co-authors include Simon Cauchemez, Paolo Bosetti, Arnaud Fontanet, D Lévy-Brühl, Henrik Salje, Pierre‐Yves Boëlle, Juliette Paireau, Alessio Andronico, Noémie Lefrancq and Nathanaël Hozé. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.
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.