Maylis Layan
Impact in
- Modeling and Simulation top 0.1%
- COVID-19 epidemiological studies
- Transportation top 1%
- Human Mobility and Location-Based Analysis
- Urban Transport and Accessibility
Papers in
-
- COVID-19 epidemiological studies 5
- Virology 4
- Rabies epidemiology and control 4
- Co-authors
- Louis du Plessis (1 shared paper)David M. Pigott (1 shared paper)Nuno R. Faria (1 shared paper)Huaiyu Tian (1 shared paper)Moritz U. G. Kraemer (1 shared paper)Bernardo Gutiérrez (1 shared paper)John S. Brownstein (1 shared paper)Ruoran Li (1 shared paper)
- Journals
- American Journal of Epidemiology (2 papers)Molecular Ecology (1 paper)The Journal of Infectious Diseases (1 paper)Proceedings of the National Academy of Sciences (1 paper)PLoS neglected tropical diseases (1 paper)
- Partner nations
- FranceBelgiumUnited Kingdom
In The Last Decade
Maylis Layan
9 papers receiving 2.1k citations
Maylis Layan's Hit Papers
Peers
Comparison fields: 5 of 141
- Modeling and Simulation 1.3k
- Transportation 334
- Economics and Econometrics 605
- Infectious Diseases 263
- Global and Planetary Change 312
Countries citing papers authored by Maylis Layan
This map shows the geographic impact of Maylis Layan'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 Maylis Layan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maylis Layan more than expected).
Fields of papers citing papers by Maylis Layan
This network shows the impact of papers produced by Maylis Layan. 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 Maylis Layan. The network helps show where Maylis Layan may publish in the future.
Co-authors
The 25 scholars most cited alongside Maylis Layan, 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 | The effect of human mobility and control measures on the COVID-19 epidemic in China Hit paper breakdown → | 2020 | 2016 |
| 2 | 2022 | 32 | |
| 3 | 2023 | 31 | |
| 4 | 2022 | 30 | |
| 5 | 2021 | 15 | |
| 6 | 2021 | 11 | |
| 7 | 2022 | 3 | |
| 8 | 2023 | 2 | |
| 9 | 2024 | 1 | |
| 10 | 2025 | 0 |
About Maylis Layan
Maylis Layan is a scholar working on Modeling and Simulation, Virology, Infectious Diseases, Epidemiology and Health, having authored 10 papers that have together received 2.1k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (5 papers), Rabies epidemiology and control (4 papers), Vaccine Coverage and Hesitancy (2 papers), Microbial infections and disease research (2 papers), COVID-19 Pandemic Impacts (2 papers), SARS-CoV-2 and COVID-19 Research (2 papers), Streptococcal Infections and Treatments (1 paper) and Data-Driven Disease Surveillance (1 paper). The work is most often cited by research in Modeling and Simulation (1.3k citations), Transportation (334 citations), Economics and Econometrics (605 citations), Infectious Diseases (263 citations) and Global and Planetary Change (312 citations). Maylis Layan has collaborated with scholars based in France, Belgium and United Kingdom. Frequent co-authors include Louis du Plessis, David M. Pigott, Nuno R. Faria, Huaiyu Tian, Moritz U. G. Kraemer, Bernardo Gutiérrez, John S. Brownstein, Ruoran Li, Christopher Dye and Chieh‐Hsi Wu. Their work appears in journals such as American Journal of Epidemiology, Molecular Ecology, The Journal of Infectious Diseases, Proceedings of the National Academy of Sciences and PLoS neglected tropical diseases.
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.