Edward Combes
Impact in
- Infectious Diseases top 1%
- COVID-19 Clinical Research Studies
- SARS-CoV-2 and COVID-19 Research
- Genetics top 5%
- Genetic Associations and Epidemiology
Papers in
-
- COVID-19 Clinical Research Studies 10
- SARS-CoV-2 and COVID-19 Research 1
- Genetics 6
- Genetic Associations and Epidemiology 6
Edward Combes
14 papers receiving 2.6k citations
Edward Combes's Hit Papers
Peers
Comparison fields: 5 of 97
- Infectious Diseases 1.8k
- Genetics 515
- Applied Microbiology and Biotechnology 35
- Internal Medicine 28
- Immunology 129
Countries citing papers authored by Edward Combes
This map shows the geographic impact of Edward Combes'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 Edward Combes with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward Combes more than expected).
Fields of papers citing papers by Edward Combes
This network shows the impact of papers produced by Edward Combes. 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 Edward Combes. The network helps show where Edward Combes may publish in the future.
No co-authors to show.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | Mapping the human genetic architecture of COVID-19 Hit paper breakdown → | 2021 | 656 |
| 2 | Azithromycin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial Hit paper breakdown → | 2021 | 411 |
| 3 | Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial Hit paper breakdown → | 2021 | 393 |
| 4 | Casirivimab and imdevimab in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial Hit paper breakdown → | 2022 | 282 |
| 5 | Whole-genome sequencing reveals host factors underlying critical COVID-19 Hit paper breakdown → | 2022 | 233 |
| 6 | Baricitinib in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial and updated meta-analysis Hit paper breakdown → | 2022 | 231 |
| 7 | 2021 | 213 | |
| 8 | GWAS and meta-analysis identifies 49 genetic variants underlying critical COVID-19 Hit paper breakdown → | 2023 | 125 |
| 9 | Higher dose corticosteroids in patients admitted to hospital with COVID-19 who are hypoxic but not requiring ventilatory support (RECOVERY): a randomised, controlled, open-label, platform trial Hit paper breakdown → | 2023 | 84 |
| 10 | 2023 | 60 | |
| 11 | 2023 | 25 | |
| 12 | 2024 | 24 | |
| 13 | 2024 | 8 | |
| 14 | 2025 | 5 | |
| 15 | 2021 | 0 |
About Edward Combes
Edward Combes is a scholar working on Infectious Diseases, Genetics, Surgery, Nuclear Energy and Engineering and Waste Management and Disposal, having authored 15 papers that have together received 2.8k indexed citations. Recurring topics across this work include COVID-19 Clinical Research Studies (10 papers), Genetic Associations and Epidemiology (6 papers), SARS-CoV-2 and COVID-19 Research (1 paper) and Kawasaki Disease and Coronary Complications (1 paper). The work is most often cited by research in Infectious Diseases (1.8k citations), Genetics (515 citations), Applied Microbiology and Biotechnology (35 citations), Internal Medicine (28 citations) and Immunology (129 citations). Edward Combes has collaborated with scholars based in United Kingdom, Vietnam and Nepal. Their work appears in journals such as The Lancet, Nature, The Lancet Infectious Diseases, Human Genetics and Genomics Advances and The Lancet Diabetes & Endocrinology.
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.