Maylis Layan

9 papers receiving 2.1k citations

Maylis Layan's Hit Papers

The effect of human mobility and control measures on the COVID-19 epidemic in China 2020 · 2.0k citations
2.0k0+2+4Years since publication50010001.5k

Peers

Maylis Layan
Comparison fields: 5 of 140
  • Modeling and Simulation 1.3k
  • Transportation 324
  • Economics and Econometrics 585
  • Infectious Diseases 254
  • Global and Planetary Change 303
Replace Chia-Hung Yang with:
Chia-Hung Yang United States
Ruoran Li China
Brennan Klein United States
Kunpeng Mu China
Xinyue Xiong China
Corrado Gioannini Italy
Nick Ruktanonchai United Kingdom
Jessica T. Davis United States
Bernardo Gutiérrez Ecuador
Jessica Floyd United Kingdom
Maylis Layan relative to Chia-Hung Yang United States Chia-Hung Yang's profile →
Citations per field
00.5×1.6×
Chia-Hung Yang · 1×
Citations per year

Countries citing papers authored by Maylis Layan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

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

All Works

10 of 10 papers shown
#Work
1
The effect of human mobility and control measures on the COVID-19 epidemic in China
Hit paper breakdown →
20201962
2 202232
3 202331
4 202229
5 202113
6 202111
7 20223
8 20232
9 20241
10 20250

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 (324 citations), Economics and Econometrics (585 citations), Infectious Diseases (254 citations) and Global and Planetary Change (303 citations). Maylis Layan has collaborated with scholars based in France, Belgium and United Kingdom. Frequent co-authors include Brennan Klein, John S. Brownstein, William P. Hanage, Bernardo Gutiérrez, Alessandro Vespignani, Christopher Dye, Samuel V. Scarpino, Chieh‐Hsi Wu, Chia-Hung Yang and Oliver G. Pybus. Their work appears in journals such as American Journal of Epidemiology, Viruses, PLoS neglected tropical diseases, Molecular Ecology 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.

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