Oliver D. Eales
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
- Infectious Diseases top 5%
- SARS-CoV-2 and COVID-19 Research
- COVID-19 Clinical Research Studies
- SARS-CoV-2 detection and testing
Papers in
-
- COVID-19 epidemiological studies 17
-
- SARS-CoV-2 and COVID-19 Research 12
- SARS-CoV-2 detection and testing 3
- COVID-19 Clinical Research Studies 1
- Co-authors
- Lord Ara Darzi (9 shared papers)Graham Cooke (9 shared papers)Paul Elliott (9 shared papers)Helen Ward (9 shared papers)Steven Riley (10 shared papers)William Barclay (8 shared papers)Christina Joanne Atchison (8 shared papers)Haowei Wang (8 shared papers)
- Journals
- Nature Communications (4 papers)Science (4 papers)Wellcome Open Research (2 papers)Epidemics (2 papers)PLoS Computational Biology (2 papers)
- Partner nations
- United KingdomAustraliaNetherlands
In The Last Decade
Oliver D. Eales
29 papers receiving 1.5k citations
Oliver D. Eales's Hit Papers
Peers
Comparison fields: 5 of 110
- Modeling and Simulation 714
- Infectious Diseases 493
- Transportation 119
- Health 29
- Epidemiology 90
Countries citing papers authored by Oliver D. Eales
This map shows the geographic impact of Oliver D. Eales'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 Oliver D. Eales with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver D. Eales more than expected).
Fields of papers citing papers by Oliver D. Eales
This network shows the impact of papers produced by Oliver D. Eales. 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 Oliver D. Eales. The network helps show where Oliver D. Eales may publish in the future.
Co-authors
The 25 scholars most cited alongside Oliver D. Eales, 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 33 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Reduction in mobility and COVID-19 transmission Hit paper breakdown → | 2021 | 443 |
| 2 | 2020 | 152 | |
| 3 | 2021 | 132 | |
| 4 | 2020 | 115 | |
| 5 | 2022 | 100 | |
| 6 | 2021 | 91 | |
| 7 | 2022 | 84 | |
| 8 | 2021 | 65 | |
| 9 | 2020 | 52 | |
| 10 | 2022 | 42 | |
| 11 | 2022 | 32 | |
| 12 | 2022 | 29 | |
| 13 | 2023 | 25 | |
| 14 | 2022 | 24 | |
| 15 | 2023 | 24 | |
| 16 | 2024 | 22 | |
| 17 | 2022 | 21 | |
| 18 | 2022 | 20 | |
| 19 | 2022 | 15 | |
| 20 | 2020 | 14 |
About Oliver D. Eales
Oliver D. Eales is a scholar working on Modeling and Simulation, Infectious Diseases, Epidemiology, Transportation and Astronomy and Astrophysics, having authored 33 papers that have together received 1.6k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (17 papers), SARS-CoV-2 and COVID-19 Research (12 papers), Data-Driven Disease Surveillance (4 papers), Influenza Virus Research Studies (4 papers), SARS-CoV-2 detection and testing (3 papers), Respiratory viral infections research (2 papers), COVID-19 Clinical Research Studies (1 paper) and Mathematical and Theoretical Epidemiology and Ecology Models (1 paper). The work is most often cited by research in Modeling and Simulation (714 citations), Infectious Diseases (493 citations), Transportation (119 citations), Health (29 citations) and Epidemiology (90 citations). Oliver D. Eales has collaborated with scholars based in United Kingdom, Australia and Netherlands. Frequent co-authors include Lord Ara Darzi, Graham Cooke, Paul Elliott, Helen Ward, Steven Riley, William Barclay, Christina Joanne Atchison, Haowei Wang, Deborah Ashby and Christl Ann Donnelly. Their work appears in journals such as Nature Communications, Science, Wellcome Open Research, Epidemics and PLoS Computational Biology.
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.