Sharon K. Greene

3.5k citations
69 papers · 2.2k · h-index 23

Impact in

Papers in

    • Influenza Virus Research Studies 14
    • Data-Driven Disease Surveillance 14
    • Respiratory viral infections research 5
    • COVID-19 epidemiological studies 13

Sharon K. Greene

66 papers receiving 2.1k citations

Peers

Sharon K. Greene
Comparison fields: 5 of 129
  • Modeling and Simulation 197
  • Toxicology 93
  • Endocrinology 134
  • Infectious Diseases 437
  • Biotechnology 204
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Saki Takahashi United States
Tyra Grove Krause Denmark
Ali A. Sultan Qatar
Buddha Basnyat Nepal
Ping Ren United States
Abualgasim Elgaili Abdalla Saudi Arabia
Joel N. Kuritsky United States
Philip H. Li China
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Citations per field
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Citations per year

Countries citing papers authored by Sharon K. Greene

Since Specialization
Citations

This map shows the geographic impact of Sharon K. Greene'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 Sharon K. Greene with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sharon K. Greene more than expected).

Fields of papers citing papers by Sharon K. Greene

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sharon K. Greene. 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 Sharon K. Greene. The network helps show where Sharon K. Greene may publish in the future.

Co-authors

The 25 scholars most cited alongside Sharon K. Greene, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sharon K. Greene Line = papers co-authored together Sharon K. Greene links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 69 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007313
2 1995175
3 2013162
4 2012122
5 2020115
6 2009106
7 2011104
8 201991
9 201273
10 200658
11 201548
12 201643
13 201241
14 200941
15 201341
16 201140
17 201738
18 200837
19 201536
20 201334

About Sharon K. Greene

Sharon K. Greene is a scholar working on Epidemiology, Modeling and Simulation, Infectious Diseases, Public Health, Environmental and Occupational Health and Food Science, having authored 69 papers that have together received 2.2k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (14 papers), Data-Driven Disease Surveillance (14 papers), COVID-19 epidemiological studies (13 papers), Food Safety and Hygiene (5 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Salmonella and Campylobacter epidemiology (5 papers), Respiratory viral infections research (5 papers) and Animal Disease Management and Epidemiology (4 papers). The work is most often cited by research in Modeling and Simulation (197 citations), Toxicology (93 citations), Endocrinology (134 citations), Infectious Diseases (437 citations) and Biotechnology (204 citations). Sharon K. Greene has collaborated with scholars based in United States, Uganda and United Kingdom. Frequent co-authors include Grace M. Lee, Claudia Vellozzi, Martin Kulldorff, Kiyotaka Watanabe, Lillian Lou, Eric Weintraub, Robert M. Hoekstra, Annie D. Fine, Steven J. Jacobsen and Stacy Holzbauer. Their work appears in journals such as Epidemiology and Infection, Vaccine, Emerging infectious diseases, American Journal of Epidemiology and Influenza and Other Respiratory Viruses.

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.

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