Peter Doshi
Impact in
- Modeling and Simulation top 2%
- COVID-19 epidemiological studies
-
- Meta-analysis and systematic reviews
Papers in
- Pharmacology 25
- Pharmaceutical industry and healthcare 23
- Epidemiology 43
- Influenza Virus Research Studies 41
- Co-authors
- Tom Jefferson (36 shared papers)Mark Jones (21 shared papers)Chris Del Mar (11 shared papers)Carl J. Heneghan (9 shared papers)Igho Onakpoya (6 shared papers)Elizabeth A. Spencer (4 shared papers)T. Jefferson (3 shared papers)Rokuro Hama (7 shared papers)
- Journals
- BMJ (48 papers)JAMA Internal Medicine (10 papers)Cochrane Database of Systematic Reviews (4 papers)BMJ Evidence-Based Medicine (4 papers)The Lancet (4 papers)
- Partner nations
- United StatesUnited KingdomAustralia
In The Last Decade
Peter Doshi
121 papers receiving 3.2k citations
Peter Doshi's Hit Papers
Peers
Comparison fields: 5 of 146
- Modeling and Simulation 198
- Statistics, Probability and Uncertainty 309
- Epidemiology 1.1k
- Infectious Diseases 559
- Health 236
Countries citing papers authored by Peter Doshi
This map shows the geographic impact of Peter Doshi'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 Peter Doshi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Peter Doshi more than expected).
Fields of papers citing papers by Peter Doshi
This network shows the impact of papers produced by Peter Doshi. 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 Peter Doshi. The network helps show where Peter Doshi may publish in the future.
Co-authors
The 25 scholars most cited alongside Peter Doshi, 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 127 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Oseltamivir for influenza in adults and children: systematic review of clinical study reports and summary of regulatory comments Hit paper breakdown → | 2014 | 354 |
| 2 | 2009 | 305 | |
| 3 | 2014 | 286 | |
| 4 | 2014 | 256 | |
| 5 | 2012 | 134 | |
| 6 | 2013 | 129 | |
| 7 | 2022 | 127 | |
| 8 | 2011 | 108 | |
| 9 | 2020 | 88 | |
| 10 | 2016 | 83 | |
| 11 | 2017 | 75 | |
| 12 | 2009 | 67 | |
| 13 | 2020 | 66 | |
| 14 | 2008 | 62 | |
| 15 | 2013 | 60 | |
| 16 | 2012 | 48 | |
| 17 | 2010 | 46 | |
| 18 | 2014 | 45 | |
| 19 | 2019 | 43 | |
| 20 | 2013 | 43 |
About Peter Doshi
Peter Doshi is a scholar working on Pharmacology, Epidemiology, Statistics, Probability and Uncertainty, Health and Public Health, Environmental and Occupational Health, having authored 127 papers that have together received 3.4k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (41 papers), Pharmaceutical industry and healthcare (23 papers), Meta-analysis and systematic reviews (18 papers), Vaccine Coverage and Hesitancy (16 papers), Health Systems, Economic Evaluations, Quality of Life (15 papers), Pharmaceutical Economics and Policy (14 papers), COVID-19 epidemiological studies (11 papers) and Health and Medical Research Impacts (10 papers). The work is most often cited by research in Modeling and Simulation (198 citations), Statistics, Probability and Uncertainty (309 citations), Epidemiology (1.1k citations), Infectious Diseases (559 citations) and Health (236 citations). Peter Doshi has collaborated with scholars based in United States, United Kingdom and Australia. Frequent co-authors include Tom Jefferson, Mark Jones, Chris Del Mar, Carl J. Heneghan, Igho Onakpoya, Elizabeth A. Spencer, T. Jefferson, Rokuro Hama, Jeremy Howick and Kamal Ram Mahtani. Their work appears in journals such as BMJ, JAMA Internal Medicine, Cochrane Database of Systematic Reviews, BMJ Evidence-Based Medicine and The Lancet.
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.