Raphael Cuomo
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
- Communication top 5%
Papers in ⓘ
- Health 11
- Social Media in Health Education 7
- Co-authors
- Tim K. Mackey (59 shared papers)Vidya Purushothaman (23 shared papers)Bryan A. Liang (6 shared papers)Jiawei Li (15 shared papers)Qing Xu (8 shared papers)Mingxiang Cai (9 shared papers)Cedric F. Garland (7 shared papers)Daniel E. Lee (1 shared paper)
- Journals
- PLoS ONE (5 papers)Tobacco Induced Diseases (3 papers)The Journal of Steroid Biochemistry and Molecular Biology (3 papers)JMIR Public Health and Surveillance (3 papers)Journal of Medical Internet Research (3 papers)
- Partner nations
- United StatesGermanyAustralia
In The Last Decade
Raphael Cuomo
69 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 156
- Modeling and Simulation 75
- Communication 88
- Health 104
- Public Health, Environmental and Occupational Health 264
- Parasitology 52
Countries citing papers authored by Raphael Cuomo
This map shows the geographic impact of Raphael Cuomo'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 Raphael Cuomo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raphael Cuomo more than expected).
Fields of papers citing papers by Raphael Cuomo
This network shows the impact of papers produced by Raphael Cuomo. 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 Raphael Cuomo. The network helps show where Raphael Cuomo may publish in the future.
Co-authors
The 25 scholars most cited alongside Raphael Cuomo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2014 | 150 | |
| 2 | 2020 | 126 | |
| 3 | 2015 | 105 | |
| 4 | 2020 | 101 | |
| 5 | 2015 | 86 | |
| 6 | 2015 | 70 | |
| 7 | 2014 | 49 | |
| 8 | 2020 | 49 | |
| 9 | 2015 | 36 | |
| 10 | 2015 | 33 | |
| 11 | 2020 | 29 | |
| 12 | 2015 | 22 | |
| 13 | 2017 | 20 | |
| 14 | 2020 | 18 | |
| 15 | 2020 | 18 | |
| 16 | 2021 | 17 | |
| 17 | 2022 | 16 | |
| 18 | 2013 | 15 | |
| 19 | 2021 | 14 | |
| 20 | 2023 | 14 |
About Raphael Cuomo
Raphael Cuomo is a scholar working on Health, Applied Psychology, Modeling and Simulation, Physiology and Public Health, Environmental and Occupational Health, having authored 82 papers that have together received 1.2k indexed citations. Recurring topics across this work include Smoking Behavior and Cessation (16 papers), Misinformation and Its Impacts (12 papers), Data-Driven Disease Surveillance (10 papers), Vitamin D Research Studies (7 papers), Social Media in Health Education (7 papers), Pharmaceutical Economics and Policy (7 papers), Cannabis and Cannabinoid Research (5 papers) and HIV, Drug Use, Sexual Risk (5 papers). The work is most often cited by research in Modeling and Simulation (75 citations), Communication (88 citations), Health (104 citations), Public Health, Environmental and Occupational Health (264 citations) and Parasitology (52 citations). Raphael Cuomo has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Tim K. Mackey, Vidya Purushothaman, Bryan A. Liang, Jiawei Li, Qing Xu, Mingxiang Cai, Cedric F. Garland, Daniel E. Lee, Ryan Hafen and Kimberly C. Brouwer. Their work appears in journals such as PLoS ONE, Tobacco Induced Diseases, The Journal of Steroid Biochemistry and Molecular Biology, JMIR Public Health and Surveillance and Journal of Medical Internet Research.
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.