Riley O. Mummah
- Modeling and Simulation top 2%
- Infectious Diseases top 10%
- Radiology, Nuclear Medicine and Imaging
- Public Health, Environmental and Occupational Health
- Clinical Psychology
- Co-authors
- James O. Lloyd‐SmithKatelyn M. GosticAna C. R. GomezAdam J. KucharskiMatthew J. FerrariChristopher FonnesbeckMichael C. RungeWilliam J. M. Probert
- Topics
- COVID-19 epidemiological studies (3 papers)Animal Disease Management and Epidemiology (3 papers)Viral Infections and Vectors (3 papers)
- Journals
- Proceedings of the National Academy of SciencesSHILAP Revista de lepidopterologíaConservation Biology
- Partner nations
- United StatesBelgiumUnited Kingdom
In The Last Decade
Riley O. Mummah
9 papers receiving 341 citations
Peers
Comparison fields: 5 of 94
- Modeling and Simulation 154
- Infectious Diseases 151
- Radiology, Nuclear Medicine and Imaging 56
- Public Health, Environmental and Occupational Health 52
- Clinical Psychology 42
Countries citing papers authored by Riley O. Mummah
This map shows the geographic impact of Riley O. Mummah'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 Riley O. Mummah with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Riley O. Mummah more than expected).
Fields of papers citing papers by Riley O. Mummah
This network shows the impact of papers produced by Riley O. Mummah. 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 Riley O. Mummah. The network helps show where Riley O. Mummah may publish in the future.
Co-authorship network of co-authors of Riley O. Mummah
This figure shows the co-authorship network connecting the top 25 collaborators of Riley O. Mummah. A scholar is included among the top collaborators of Riley O. Mummah 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 Riley O. Mummah. Riley O. Mummah is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 5 | |
| 6 | 13 | |
| 7 | 271 | |
| 8 | 10 | |
| 9 | 34 |
About Riley O. Mummah
Riley O. Mummah is a scholar working on Modeling and Simulation, Parasitology and Agronomy and Crop Science, having authored 9 papers that have together received 349 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (3 papers), Animal Disease Management and Epidemiology (3 papers) and Viral Infections and Vectors (3 papers). The work is most often cited by research in Modeling and Simulation (154 citations), Infectious Diseases (151 citations) and General Dentistry (10 citations). Riley O. Mummah has collaborated with scholars based in United States, Belgium and United Kingdom. Frequent co-authors include James O. Lloyd‐Smith, Katelyn M. Gostic, Ana C. R. Gomez, Adam J. Kucharski, Matthew J. Ferrari, Christopher Fonnesbeck, Michael C. Runge, William J. M. Probert, Ottar N. Bjørnstad and Katriona Shea. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Conservation 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.