Supriya Kumar
Impact in
- Modeling and Simulation top 1%
- COVID-19 epidemiological studies
- Health top 2%
- Vaccine Coverage and Hesitancy
- Health disparities and outcomes
Papers in
-
- Influenza Virus Research Studies 8
- Health 8
- Vaccine Coverage and Hesitancy 6
- Co-authors
- Sandra Crouse Quinn (10 shared papers)Vicki S. Freimuth (6 shared papers)Donald Musa (4 shared papers)Kelley M. Kidwell (2 shared papers)Kevin H. Kim (4 shared papers)Justine I. Blanford (1 shared paper)Alan M. MacEachren (1 shared paper)Wei Luo (1 shared paper)
- Journals
- PLoS ONE (4 papers)American Journal of Public Health (3 papers)Open Forum Infectious Diseases (2 papers)Clinical Infectious Diseases (1 paper)Nature Genetics (1 paper)
- Partner nations
- United StatesTaiwanUnited Kingdom
In The Last Decade
Supriya Kumar
29 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 130
- Modeling and Simulation 270
- Health 330
- Cancer Research 196
- General Health Professions 269
- Transportation 59
Countries citing papers authored by Supriya Kumar
This map shows the geographic impact of Supriya Kumar'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 Supriya Kumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Supriya Kumar more than expected).
Fields of papers citing papers by Supriya Kumar
This network shows the impact of papers produced by Supriya Kumar. 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 Supriya Kumar. The network helps show where Supriya Kumar may publish in the future.
Co-authors
The 25 scholars most cited alongside Supriya Kumar, 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 30 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2008 | 209 | |
| 2 | 2010 | 202 | |
| 3 | 2012 | 160 | |
| 4 | 2011 | 141 | |
| 5 | 2009 | 134 | |
| 6 | 2011 | 124 | |
| 7 | 2013 | 93 | |
| 8 | 2008 | 65 | |
| 9 | 2017 | 37 | |
| 10 | 2010 | 36 | |
| 11 | 2010 | 32 | |
| 12 | 2005 | 30 | |
| 13 | 2015 | 28 | |
| 14 | 2010 | 27 | |
| 15 | 2008 | 21 | |
| 16 | 2011 | 17 | |
| 17 | 2018 | 16 | |
| 18 | 2020 | 15 | |
| 19 | 2012 | 11 | |
| 20 | 2023 | 10 |
About Supriya Kumar
Supriya Kumar is a scholar working on Epidemiology, Health, Modeling and Simulation, Sociology and Political Science and Molecular Biology, having authored 30 papers that have together received 1.4k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (8 papers), COVID-19 epidemiological studies (8 papers), Vaccine Coverage and Hesitancy (6 papers), Salmonella and Campylobacter epidemiology (4 papers), RNA Research and Splicing (4 papers), Viral gastroenteritis research and epidemiology (4 papers), Smoking Behavior and Cessation (3 papers) and MicroRNA in disease regulation (3 papers). The work is most often cited by research in Modeling and Simulation (270 citations), Health (330 citations), Cancer Research (196 citations), General Health Professions (269 citations) and Transportation (59 citations). Supriya Kumar has collaborated with scholars based in United States, Taiwan and United Kingdom. Frequent co-authors include Sandra Crouse Quinn, Vicki S. Freimuth, Donald Musa, Kelley M. Kidwell, Kevin H. Kim, Justine I. Blanford, Alan M. MacEachren, Wei Luo, Yang Shen and Jian Lü. Their work appears in journals such as PLoS ONE, American Journal of Public Health, Open Forum Infectious Diseases, Clinical Infectious Diseases and Nature Genetics.
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.