Steven Riley

37.1k citations
187 papers · 11.9k indexed · 5 hit papers · h-index 55

Impact in

Papers in

Steven Riley

183 papers receiving 11.6k citations

Hit Papers

Persistent COVID-19 symptoms in a community study of 606,434 people in England 2022 · 231 citations
23120032026201020184008001.2k

Peers

Steven Riley
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
Replace Jacco Wallinga with:
Jacco Wallinga Netherlands
Simon Cauchemez France
Christophe Fraser United Kingdom
Joseph T. Wu Hong Kong
Gerardo Chowell United States
Hongjie Yu China
Derek A. T. Cummings United States
W. John Edmunds United Kingdom
Jeffrey Shaman United States
M. Elizabeth Halloran United States
Steven Riley relative to Jacco Wallinga Netherlands Jacco Wallinga's profile →
Citations per field
00.5×1.5×1.8×
Jacco Wallinga · 1×
Citations per year

Countries citing papers authored by Steven Riley

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Steven Riley Line = papers co-authored together Steven Riley links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20229
2 202214
3 202290
4 202113
5 20219
6 20217
7 202165
8 20213
9 202158
10 202010
11 202011
12 20207
13 20202
14 20208
15 202065
16 201666
17 201418
18 201310
19 201154
20
Factors that make an infectious disease outbreak controllable
Hit paper breakdown →
2004745

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.

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