Nathan D. Grubaugh
- Infectious Diseases top 0.5%
- Public Health, Environmental and Occupational Health top 1%
- Molecular Biology
- Biomedical Engineering top 5%
- Epidemiology top 10%
- Co-authors
- Kristian G. AndersenDoug E. BrackneyGregory D. EbelAkiko IwasakiEdward C. HolmesOliver G. PybusJoseph R. FauverChantal B. F. Vogels
- Topics
- Mosquito-borne diseases and control (46 papers)Viral Infections and Vectors (36 papers)SARS-CoV-2 and COVID-19 Research (28 papers)
- Cited by
- Infectious DiseasesModeling and SimulationPublic Health, Environmental and Occupational Health
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Nathan D. Grubaugh
81 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Infectious Diseases 2.6k
- Public Health, Environmental and Occupational Health 1.2k
- Molecular Biology 568
- Biomedical Engineering 480
- Epidemiology 424
Countries citing papers authored by Nathan D. Grubaugh
This map shows the geographic impact of Nathan D. Grubaugh'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 Nathan D. Grubaugh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nathan D. Grubaugh more than expected).
Fields of papers citing papers by Nathan D. Grubaugh
This network shows the impact of papers produced by Nathan D. Grubaugh. 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 Nathan D. Grubaugh. The network helps show where Nathan D. Grubaugh may publish in the future.
Co-authorship network of co-authors of Nathan D. Grubaugh
This figure shows the co-authorship network connecting the top 25 collaborators of Nathan D. Grubaugh. A scholar is included among the top collaborators of Nathan D. Grubaugh 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 Nathan D. Grubaugh. Nathan D. Grubaugh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 12 | |
| 5 | 22 | |
| 6 | 0 | |
| 7 | 11 | |
| 8 | 6 | |
| 9 | 5 | |
| 10 | 5 | |
| 11 | 42 | |
| 12 | 27 | |
| 13 | Densely sampled viral trajectories suggest longer duration of acute infection with B.1.1.7 variant relative to non-B.1.1.7 SARS-CoV-2 | 33 |
| 14 | 88 | |
| 15 | 37 | |
| 16 | 117 | |
| 17 | 26 | |
| 18 | 23 | |
| 19 | 36 | |
| 20 | 14 |
About Nathan D. Grubaugh
Nathan D. Grubaugh is a scholar working on Infectious Diseases, Modeling and Simulation and Public Health, Environmental and Occupational Health, having authored 90 papers that have together received 3.7k indexed citations. Recurring topics across this work include Mosquito-borne diseases and control (46 papers), Viral Infections and Vectors (36 papers) and SARS-CoV-2 and COVID-19 Research (28 papers). The work is most often cited by research in Infectious Diseases (2.6k citations), Modeling and Simulation (383 citations) and Public Health, Environmental and Occupational Health (1.2k citations). Nathan D. Grubaugh has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Kristian G. Andersen, Doug E. Brackney, Gregory D. Ebel, Akiko Iwasaki, Edward C. Holmes, Oliver G. Pybus, Joseph R. Fauver, Chantal B. F. Vogels, Albert I. Ko and Jason T. Ladner. Their work appears in journals such as Cell, Proceedings of the National Academy of Sciences and Nature Medicine.
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.