Maia Martcheva
- Public Health, Environmental and Occupational Health top 0.5%
- Modeling and Simulation top 0.05%
- Genetics top 1%
- Infectious Diseases top 2%
- Epidemiology top 5%
- Co-authors
- Xue-Zhi LiCarlos Castillo‐ChávezMimmo IannelliNecibe TuncerHorst R. ThiemeXuezhi LiSergei S. PilyuginFabio Milner
- Topics
- Mathematical and Theoretical Epidemiology and Ecology Models (98 papers)COVID-19 epidemiological studies (68 papers)Evolution and Genetic Dynamics (63 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEJournal of Theoretical Biology
- Partner nations
- United StatesChinaIndia
In The Last Decade
Maia Martcheva
133 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 131
- Public Health, Environmental and Occupational Health 2.7k
- Modeling and Simulation 2.2k
- Genetics 1.4k
- Infectious Diseases 617
- Epidemiology 508
Countries citing papers authored by Maia Martcheva
This map shows the geographic impact of Maia Martcheva'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 Maia Martcheva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maia Martcheva more than expected).
Fields of papers citing papers by Maia Martcheva
This network shows the impact of papers produced by Maia Martcheva. 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 Maia Martcheva. The network helps show where Maia Martcheva may publish in the future.
Co-authorship network of co-authors of Maia Martcheva
This figure shows the co-authorship network connecting the top 25 collaborators of Maia Martcheva. A scholar is included among the top collaborators of Maia Martcheva 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 Maia Martcheva. Maia Martcheva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 13 | |
| 7 | 7 | |
| 8 | 13 | |
| 9 | 8 | |
| 10 | Optimal control in multi-group coupled within-host and between-host models | 11 |
| 11 | 18 | |
| 12 | 48 | |
| 13 | 36 | |
| 14 | 1 | |
| 15 | 27 | |
| 16 | 12 | |
| 17 | 35 | |
| 18 | 3 | |
| 19 | 4 | |
| 20 | Gender-structured Population Modeling: Mathematical Methods, Numerics, And Simulations (Frontiers in Applied Mathematics) | 18 |
About Maia Martcheva
Maia Martcheva is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Genetics, having authored 139 papers that have together received 3.7k indexed citations. Recurring topics across this work include Mathematical and Theoretical Epidemiology and Ecology Models (98 papers), COVID-19 epidemiological studies (68 papers) and Evolution and Genetic Dynamics (63 papers). The work is most often cited by research in Modeling and Simulation (2.2k citations), Public Health, Environmental and Occupational Health (2.7k citations) and Genetics (1.4k citations). Maia Martcheva has collaborated with scholars based in United States, China and India. Frequent co-authors include Xue-Zhi Li, Carlos Castillo‐Chávez, Mimmo Iannelli, Necibe Tuncer, Horst R. Thieme, Xuezhi Li, Sergei S. Pilyugin, Fabio Milner, Liming Cai and Zhilan Feng. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Theoretical Biology.
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.