Daniel J. Rawle
Impact in
- Infectious Diseases top 5%
- Viral Infections and Vectors
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- Virology top 10%
- HIV Research and Treatment
Papers in
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- SARS-CoV-2 and COVID-19 Research 12
- Viral Infections and Vectors 10
- COVID-19 Clinical Research Studies 9
- Viral Infections and Outbreaks Research 5
- HIV/AIDS drug development and treatment 4
-
- Mosquito-borne diseases and control 12
- Co-authors
- Andreas Suhrbier (26 shared papers)Kexin Yan (25 shared papers)Bing Tang (17 shared papers)Troy Dumenil (12 shared papers)Cameron Bishop (8 shared papers)Thuy T. Le (12 shared papers)David Harrich (9 shared papers)Thuy T. T. Le (3 shared papers)
In The Last Decade
Daniel J. Rawle
37 papers receiving 544 citations
Peers
Comparison fields: 5 of 76
- Infectious Diseases 306
- Virology 50
- Pollution 78
- Public Health, Environmental and Occupational Health 169
- Industrial and Manufacturing Engineering 33
Countries citing papers authored by Daniel J. Rawle
This map shows the geographic impact of Daniel J. Rawle'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 Daniel J. Rawle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel J. Rawle more than expected).
Fields of papers citing papers by Daniel J. Rawle
This network shows the impact of papers produced by Daniel J. Rawle. 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 Daniel J. Rawle. The network helps show where Daniel J. Rawle may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel J. Rawle, 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 38 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 68 | |
| 2 | 2020 | 31 | |
| 3 | 2021 | 24 | |
| 4 | 2021 | 23 | |
| 5 | 2015 | 23 | |
| 6 | 2022 | 23 | |
| 7 | 2022 | 20 | |
| 8 | 2020 | 20 | |
| 9 | 2023 | 19 | |
| 10 | 2022 | 19 | |
| 11 | 2022 | 18 | |
| 12 | 2022 | 18 | |
| 13 | 2015 | 16 | |
| 14 | 2015 | 15 | |
| 15 | 2024 | 15 | |
| 16 | 2018 | 15 | |
| 17 | 2020 | 15 | |
| 18 | 2021 | 14 | |
| 19 | 2021 | 14 | |
| 20 | 2015 | 13 |
About Daniel J. Rawle
Daniel J. Rawle is a scholar working on Infectious Diseases, Public Health, Environmental and Occupational Health, Virology, Molecular Biology and Epidemiology, having authored 38 papers that have together received 546 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (12 papers), Mosquito-borne diseases and control (12 papers), Viral Infections and Vectors (10 papers), HIV Research and Treatment (9 papers), COVID-19 Clinical Research Studies (9 papers), Long-Term Effects of COVID-19 (5 papers), Viral Infections and Outbreaks Research (5 papers) and HIV/AIDS drug development and treatment (4 papers). The work is most often cited by research in Infectious Diseases (306 citations), Virology (50 citations), Pollution (78 citations), Public Health, Environmental and Occupational Health (169 citations) and Industrial and Manufacturing Engineering (33 citations). Daniel J. Rawle has collaborated with scholars based in Australia, France and China. Frequent co-authors include Andreas Suhrbier, Kexin Yan, Bing Tang, Troy Dumenil, Cameron Bishop, Thuy T. Le, David Harrich, Thuy T. T. Le, Roy A. Hall and Jody Hobson‐Peters. Their work appears in journals such as PLoS Pathogens, Virology Journal, Vaccines, The Science of The Total Environment and Cell Discovery.
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.