Steven Riley
Impact in
- Modeling and Simulation top 0.01%
- COVID-19 epidemiological studies
- Infectious Diseases top 0.1%
- SARS-CoV-2 and COVID-19 Research
- Viral Infections and Outbreaks Research
- COVID-19 Clinical Research Studies
Papers in
-
- COVID-19 epidemiological studies 110
-
- SARS-CoV-2 and COVID-19 Research 28
- Viral Infections and Outbreaks Research 20
- COVID-19 Clinical Research Studies 19
- Co-authors
- Neil M. FergusonChristophe FraserRoy M. AndersonGM LeungDerek A. T. CummingsChristl A. DonnellySimon CauchemezAzra C. Ghani
- Journals
- Epidemics (13 papers)PLoS Computational Biology (10 papers)PLoS Medicine (8 papers)BMC Infectious Diseases (8 papers)PLoS ONE (8 papers)
- Partner nations
- United KingdomHong KongUnited States
In The Last Decade
Steven Riley
183 papers receiving 11.6k citations
Hit Papers
Peers
Comparison fields: 5 of 194
- Modeling and Simulation 6.2k
- Infectious Diseases 4.5k
- Epidemiology 5.1k
- Agronomy and Crop Science 1.4k
- Public Health, Environmental and Occupational Health 1.9k
Countries citing papers authored by Steven Riley
This map shows the geographic impact of Steven Riley'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 Steven Riley with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven Riley more than expected).
Fields of papers citing papers by Steven Riley
This network shows the impact of papers produced by Steven Riley. 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 Steven Riley. The network helps show where Steven Riley may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Steven Riley, 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 | 2022 | 9 | |
| 2 | 2022 | 14 | |
| 3 | 2022 | 90 | |
| 4 | 2021 | 13 | |
| 5 | 2021 | 9 | |
| 6 | 2021 | 7 | |
| 7 | 2021 | 65 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 58 | |
| 10 | 2020 | 10 | |
| 11 | 2020 | 11 | |
| 12 | 2020 | 7 | |
| 13 | 2020 | 2 | |
| 14 | 2020 | 8 | |
| 15 | 2020 | 65 | |
| 16 | 2016 | 66 | |
| 17 | 2014 | 18 | |
| 18 | 2013 | 10 | |
| 19 | 2011 | 54 | |
| 20 | Factors that make an infectious disease outbreak controllable Hit paper breakdown → | 2004 | 745 |
About Steven Riley
Steven Riley is a scholar working on Modeling and Simulation, Infectious Diseases, Agronomy and Crop Science, Epidemiology and Health, having authored 187 papers that have together received 11.9k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (110 papers), Influenza Virus Research Studies (86 papers), Animal Disease Management and Epidemiology (34 papers), SARS-CoV-2 and COVID-19 Research (28 papers), Respiratory viral infections research (26 papers), Viral Infections and Outbreaks Research (20 papers), COVID-19 Clinical Research Studies (19 papers) and Data-Driven Disease Surveillance (17 papers). The work is most often cited by research in Modeling and Simulation (6.2k citations), Infectious Diseases (4.5k citations), Epidemiology (5.1k citations), Agronomy and Crop Science (1.4k citations) and Public Health, Environmental and Occupational Health (1.9k citations). Steven Riley has collaborated with scholars based in United Kingdom, Hong Kong and United States. Frequent co-authors include Neil M. Ferguson, Christophe Fraser, Roy M. Anderson, GM Leung, Derek A. T. Cummings, Christl A. Donnelly, Simon Cauchemez, Azra C. Ghani, Aronrag Meeyai and Sopon Iamsirithaworn. Their work appears in journals such as Epidemics, PLoS Computational Biology, PLoS Medicine, BMC Infectious Diseases and PLoS ONE.
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.