Ken Eames
Impact in
- Modeling and Simulation top 0.05%
- COVID-19 epidemiological studies
- Statistical and Nonlinear Physics top 0.5%
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in ⓘ
-
- COVID-19 epidemiological studies 29
- Health 7
- Vaccine Coverage and Hesitancy 5
- Co-authors
- Matt J. Keeling (8 shared papers)P E Fine (1 shared paper)DL Heymann (1 shared paper)W. John Edmunds (12 shared papers)Jonathan M. Read (5 shared papers)Natasha L. Tilston‐Lunel (4 shared papers)Ellen Brooks‐Pollock (3 shared papers)Shweta Bansal (3 shared papers)
- Journals
- Epidemics (8 papers)PLoS ONE (5 papers)Proceedings of the Royal Society B Biological Sciences (3 papers)Epidemiology and Infection (3 papers)BMC Infectious Diseases (3 papers)
- Partner nations
- United KingdomUnited StatesItaly
In The Last Decade
Ken Eames
43 papers receiving 4.4k citations
Hit Papers
Peers
Comparison fields: 5 of 168
- Modeling and Simulation 2.2k
- Statistical and Nonlinear Physics 1.2k
- Health 561
- Infectious Diseases 824
- Epidemiology 1.4k
Countries citing papers authored by Ken Eames
This map shows the geographic impact of Ken Eames'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 Ken Eames with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ken Eames more than expected).
Fields of papers citing papers by Ken Eames
This network shows the impact of papers produced by Ken Eames. 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 Ken Eames. The network helps show where Ken Eames may publish in the future.
Co-authors
The 25 scholars most cited alongside Ken Eames, 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 44 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Networks and epidemic models Hit paper breakdown → | 2005 | 1215 |
| 2 | "Herd Immunity": A Rough Guide Hit paper breakdown → | 2011 | 804 |
| 3 | 2002 | 322 | |
| 4 | 2003 | 257 | |
| 5 | 2008 | 220 | |
| 6 | 2014 | 151 | |
| 7 | 2012 | 140 | |
| 8 | 2013 | 120 | |
| 9 | 2014 | 117 | |
| 10 | 2014 | 113 | |
| 11 | 2007 | 82 | |
| 12 | 2011 | 76 | |
| 13 | 2015 | 75 | |
| 14 | 2013 | 74 | |
| 15 | 2004 | 62 | |
| 16 | 2014 | 62 | |
| 17 | 2010 | 60 | |
| 18 | 2011 | 59 | |
| 19 | 2014 | 56 | |
| 20 | 2008 | 51 |
About Ken Eames
Ken Eames is a scholar working on Modeling and Simulation, Health, Epidemiology, Statistical and Nonlinear Physics and Transportation, having authored 44 papers that have together received 4.6k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (29 papers), Influenza Virus Research Studies (17 papers), Data-Driven Disease Surveillance (10 papers), Complex Network Analysis Techniques (8 papers), Respiratory viral infections research (7 papers), Mathematical and Theoretical Epidemiology and Ecology Models (6 papers), Vaccine Coverage and Hesitancy (5 papers) and Smoking Behavior and Cessation (4 papers). The work is most often cited by research in Modeling and Simulation (2.2k citations), Statistical and Nonlinear Physics (1.2k citations), Health (561 citations), Infectious Diseases (824 citations) and Epidemiology (1.4k citations). Ken Eames has collaborated with scholars based in United Kingdom, United States and Italy. Frequent co-authors include Matt J. Keeling, P E Fine, DL Heymann, W. John Edmunds, Jonathan M. Read, Natasha L. Tilston‐Lunel, Ellen Brooks‐Pollock, Shweta Bansal, Dominic Thorrington and Sebastian Funk. Their work appears in journals such as Epidemics, PLoS ONE, Proceedings of the Royal Society B Biological Sciences, Epidemiology and Infection and BMC Infectious Diseases.
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.