Toscane Fourié

934 citations
18 papers · 140 indexed · h-index 8
Topics
SARS-CoV-2 and COVID-19 Research (7 papers)Viral Infections and Vectors (7 papers)Mosquito-borne diseases and control (7 papers)
Journals
SHILAP Revista de lepidopterologíaPLoS ONEEmerging infectious diseases
Partner nations
FranceUnited KingdomMali

In The Last Decade

Toscane Fourié

17 papers receiving 138 citations

Peers

Toscane Fourié
Comparison fields: 5 of 35
  • Infectious Diseases 117
  • Public Health, Environmental and Occupational Health 55
  • Ecology, Evolution, Behavior and Systematics 14
  • Modeling and Simulation 13
  • Neurology 11
Replace Gene S. Tan with:
Gene S. Tan United States
Awadalkareem Adam United States
Ohnmar Aung United States
Diego A. Álvarez-Díaz Colombia
Victor Pimentel Portugal
Stéphane Mély France
Serena Quartu Italy
Pierina Lorencini Parise Brazil
Deshni Jayathilaka Sri Lanka
Yang Yuan China
Toscane Fourié relative to Gene S. Tan United States Gene S. Tan's profile →
Citations per field
00.5×2.6×
Gene S. Tan · 1×
Citations per year

Countries citing papers authored by Toscane Fourié

Since Specialization
Citations

This map shows the geographic impact of Toscane Fourié'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 Toscane Fourié with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Toscane Fourié more than expected).

Fields of papers citing papers by Toscane Fourié

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Toscane Fourié. 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 Toscane Fourié. The network helps show where Toscane Fourié may publish in the future.

Co-authorship network of co-authors of Toscane Fourié

This figure shows the co-authorship network connecting the top 25 collaborators of Toscane Fourié. A scholar is included among the top collaborators of Toscane Fourié based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Toscane Fourié. Toscane Fourié is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

18 of 18 papers shown
#WorkIndexed citations
1 0
2 4
3 3
4 1
5 1
6 12
7 26
8 5
9 9
10 1
11 6
12 16
13 2
14 11
15 10
16 1
17 21
18 11

About Toscane Fourié

Toscane Fourié is a scholar working on Infectious Diseases, Modeling and Simulation and Public Health, Environmental and Occupational Health, having authored 18 papers that have together received 140 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (7 papers), Viral Infections and Vectors (7 papers) and Mosquito-borne diseases and control (7 papers). The work is most often cited by research in Infectious Diseases (117 citations), Modeling and Simulation (13 citations) and Public Health, Environmental and Occupational Health (55 citations). Toscane Fourié has collaborated with scholars based in France, United Kingdom and Mali. Frequent co-authors include Isabelle Leparc-Goffart, Gilda Grard, Xavier de Lamballerie, Läétitia Ninove, Antoine Nougaırède, Sébastien Briolant, Bruno Coutard, Maxime Cochin, Franck Touret and Jean‐Sélim Driouich. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Emerging infectious 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.

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