Gavin Leech
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Infectious Diseases top 10%
- SARS-CoV-2 and COVID-19 Research
- Viral Infections and Outbreaks Research
- COVID-19 Clinical Research Studies
Papers in
-
- COVID-19 epidemiological studies 4
-
- COVID-19 Pandemic Impacts 3
- Co-authors
- Joshua Teperowski Monrad (3 shared papers)Sören Mindermann (3 shared papers)Jan Brauner (3 shared papers)Mrinank Sharma (3 shared papers)Yarin Gal (2 shared papers)Tomáš Gavenčiak (2 shared papers)Jan Kulveit (2 shared papers)Hong Ge (1 shared paper)
- Journals
- PLoS Computational Biology (1 paper)Science (1 paper)Nature Communications (1 paper)EClinicalMedicine (1 paper)Proceedings of the National Academy of Sciences (1 paper)
- Partner nations
- United KingdomDenmarkUnited States
In The Last Decade
Gavin Leech
6 papers receiving 978 citations
Gavin Leech's Hit Papers
Peers
Comparison fields: 5 of 108
- Modeling and Simulation 537
- Infectious Diseases 285
- Health 85
- Economics and Econometrics 218
- Clinical Psychology 120
Countries citing papers authored by Gavin Leech
This map shows the geographic impact of Gavin Leech'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 Gavin Leech with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gavin Leech more than expected).
Fields of papers citing papers by Gavin Leech
This network shows the impact of papers produced by Gavin Leech. 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 Gavin Leech. The network helps show where Gavin Leech may publish in the future.
Co-authors
The 24 scholars most cited alongside Gavin Leech, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Inferring the effectiveness of government interventions against COVID-19 Hit paper breakdown → | 2020 | 674 |
| 2 | 2021 | 149 | |
| 3 | 2021 | 89 | |
| 4 | 2022 | 60 | |
| 5 | 2022 | 39 | |
| 6 | 2024 | 2 | |
| 7 | Safety Properties of Inductive Logic Programming | 2021 | 0 |
About Gavin Leech
Gavin Leech is a scholar working on Modeling and Simulation, Economics and Econometrics, Clinical Psychology, History and Philosophy of Science and Statistics, Probability and Uncertainty, having authored 7 papers that have together received 1.0k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (4 papers), COVID-19 Pandemic Impacts (3 papers), COVID-19 and Mental Health (2 papers), Infection Control and Ventilation (1 paper), Mental Health Research Topics (1 paper), Vaccine Coverage and Hesitancy (1 paper), Machine Learning and Algorithms (1 paper) and Logic, Reasoning, and Knowledge (1 paper). The work is most often cited by research in Modeling and Simulation (537 citations), Infectious Diseases (285 citations), Health (85 citations), Economics and Econometrics (218 citations) and Clinical Psychology (120 citations). Gavin Leech has collaborated with scholars based in United Kingdom, Denmark and United States. Frequent co-authors include Joshua Teperowski Monrad, Sören Mindermann, Jan Brauner, Mrinank Sharma, Yarin Gal, Tomáš Gavenčiak, Jan Kulveit, Hong Ge, George T. Altman and Tamay Besiroglu. Their work appears in journals such as PLoS Computational Biology, Science, Nature Communications, EClinicalMedicine and Proceedings of the National Academy of Sciences.
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.