Rossella Della Marca
- Modeling and Simulation top 1%
- Public Health, Environmental and Occupational Health top 10%
- Genetics
- Infectious Diseases
- Statistical and Nonlinear Physics top 10%
- Co-authors
- Bruno BuonomoAlberto d’OnofrioMaria GroppiLuca BolzoniAndrea TosinAna Jacinta SoaresAlessandra GragnaniR. Travaglini
- Topics
- COVID-19 epidemiological studies (16 papers)Mathematical and Theoretical Epidemiology and Ecology Models (15 papers)Evolution and Genetic Dynamics (7 papers)
- Cited by
- Modeling and SimulationPublic Health, Environmental and Occupational HealthStatistical and Nonlinear Physics
In The Last Decade
Rossella Della Marca
21 papers receiving 301 citations
Peers
Comparison fields: 5 of 62
- Modeling and Simulation 233
- Public Health, Environmental and Occupational Health 193
- Genetics 61
- Infectious Diseases 59
- Statistical and Nonlinear Physics 47
Countries citing papers authored by Rossella Della Marca
This map shows the geographic impact of Rossella Della Marca'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 Rossella Della Marca with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rossella Della Marca more than expected).
Fields of papers citing papers by Rossella Della Marca
This network shows the impact of papers produced by Rossella Della Marca. 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 Rossella Della Marca. The network helps show where Rossella Della Marca may publish in the future.
Co-authorship network of co-authors of Rossella Della Marca
This figure shows the co-authorship network connecting the top 25 collaborators of Rossella Della Marca. A scholar is included among the top collaborators of Rossella Della Marca 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 Rossella Della Marca. Rossella Della Marca is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 12 | |
| 5 | 7 | |
| 6 | 11 | |
| 7 | 8 | |
| 8 | 1 | |
| 9 | 9 | |
| 10 | 2 | |
| 11 | 11 | |
| 12 | 37 | |
| 13 | 10 | |
| 14 | 62 | |
| 15 | 4 | |
| 16 | 34 | |
| 17 | 24 | |
| 18 | 13 | |
| 19 | Modelli epidemiologici e vaccinazioni:da Bernoulli a oggi | 1 |
| 20 | 36 |
About Rossella Della Marca
Rossella Della Marca is a scholar working on Modeling and Simulation, Public Health, Environmental and Occupational Health and Statistical and Nonlinear Physics, having authored 22 papers that have together received 305 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (16 papers), Mathematical and Theoretical Epidemiology and Ecology Models (15 papers) and Evolution and Genetic Dynamics (7 papers). The work is most often cited by research in Modeling and Simulation (233 citations), Public Health, Environmental and Occupational Health (193 citations) and Statistical and Nonlinear Physics (47 citations). Rossella Della Marca has collaborated with scholars based in Italy, France and Portugal. Frequent co-authors include Bruno Buonomo, Alberto d’Onofrio, Maria Groppi, Luca Bolzoni, Andrea Tosin, Ana Jacinta Soares, Alessandra Gragnani, R. Travaglini, Francesco Sannino and B. Buonomo. Their work appears in journals such as Journal of Theoretical Biology, Physica D Nonlinear Phenomena and Physica A Statistical Mechanics and its Applications.
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.