Michel Tosin
- Modeling and Simulation top 10%
- Public Health, Environmental and Occupational Health
- Infectious Diseases
- Epidemiology
- Statistical and Nonlinear Physics
- Co-authors
- Américo CunhaEber DantasMalú GraveDiego MatosFlávio Codeço CoelhoRodrigo BurgosLisandro Lovisolo
- Topics
- COVID-19 epidemiological studies (6 papers)Mosquito-borne diseases and control (4 papers)Viral Infections and Vectors (2 papers)
- Cited by
- Modeling and SimulationPublic Health, Environmental and Occupational HealthInfectious Diseases
- Journals
- Applied Mathematics and ComputationSoftware ImpactsProceeding Series of the Brazilian Society of Computational and Applied Mathematics
- Partner nations
- BrazilUnited StatesRussia
In The Last Decade
Michel Tosin
6 papers receiving 50 citations
Peers
Comparison fields: 5 of 22
- Modeling and Simulation 39
- Public Health, Environmental and Occupational Health 29
- Infectious Diseases 14
- Epidemiology 10
- Statistical and Nonlinear Physics 8
Countries citing papers authored by Michel Tosin
This map shows the geographic impact of Michel Tosin'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 Michel Tosin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michel Tosin more than expected).
Fields of papers citing papers by Michel Tosin
This network shows the impact of papers produced by Michel Tosin. 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 Michel Tosin. The network helps show where Michel Tosin may publish in the future.
Co-authorship network of co-authors of Michel Tosin
This figure shows the co-authorship network connecting the top 25 collaborators of Michel Tosin. A scholar is included among the top collaborators of Michel Tosin 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 Michel Tosin. Michel Tosin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 2 | |
| 5 | 39 | |
| 6 | Calibration of a SEIR epidemic model to describe Zika virus outbreak in Brazil | 3 |
About Michel Tosin
Michel Tosin is a scholar working on Modeling and Simulation, Infectious Diseases and Public Health, Environmental and Occupational Health, having authored 6 papers that have together received 51 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (6 papers), Mosquito-borne diseases and control (4 papers) and Viral Infections and Vectors (2 papers). The work is most often cited by research in Modeling and Simulation (39 citations), Public Health, Environmental and Occupational Health (29 citations) and Infectious Diseases (14 citations). Michel Tosin has collaborated with scholars based in Brazil, United States and Russia. Frequent co-authors include Américo Cunha, Eber Dantas, Malú Grave, Diego Matos, Flávio Codeço Coelho, Rodrigo Burgos and Lisandro Lovisolo. Their work appears in journals such as Applied Mathematics and Computation, Software Impacts and Proceeding Series of the Brazilian Society of Computational and Applied Mathematics.
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.