Tom Britton
- Modeling and Simulation top 0.05%
- COVID-19 epidemiological studies 62
- Paleontology top 1%
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- Complex Network Analysis Techniques 19
- Opinion Dynamics and Social Influence 13
- Physiology top 1%
- Epidemiology top 1%
- Influenza Virus Research Studies 12
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- Mathematical and Theoretical Epidemiology and Ecology Models 34
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- Evolution and Genetic Dynamics 17
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- Stochastic processes and statistical mechanics 10
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- Bayesian Methods and Mixture Models 9
- Co-authors
- Håkan AnderssonPeter ArnerMikael RydénPål O. WestermarkKirsty L. SpaldingSamuel BernardJonas FrisénFrank Ball
- Journals
- Journal of Applied Probability (17 papers)Mathematical Biosciences (8 papers)Systematic Biology (5 papers)
- Partner nations
- SwedenUnited KingdomUnited States
In The Last Decade
Tom Britton
109 papers receiving 7.3k citations
Hit Papers
Peers
Comparison fields: 5 of 183
- Modeling and Simulation 2.0k
- Paleontology 650
- Statistical and Nonlinear Physics 761
- Physiology 1.5k
- Epidemiology 1.7k
Countries citing papers authored by Tom Britton
This map shows the geographic impact of Tom Britton'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 Tom Britton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Britton more than expected).
Fields of papers citing papers by Tom Britton
This network shows the impact of papers produced by Tom Britton. 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 Tom Britton. The network helps show where Tom Britton may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tom Britton, 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 | 2025 | 1 | |
| 2 | 2024 | 2 | |
| 3 | 2021 | 3 | |
| 4 | 2021 | 2 | |
| 5 | 2020 | 12 | |
| 6 | 2019 | 97 | |
| 7 | 2019 | 13 | |
| 8 | 2019 | 20 | |
| 9 | 2016 | 4 | |
| 10 | 2014 | 33 | |
| 11 | 2014 | 4 | |
| 12 | 2012 | 217 | |
| 13 | 2009 | 0 | |
| 14 | 2009 | 8 | |
| 15 | 2009 | 52 | |
| 16 | 2008 | 43 | |
| 17 | Dynamics of fat cell turnover in humansbreakdown → | 2008 | 1710 |
| 18 | 2007 | 1 | |
| 19 | 2007 | 2 | |
| 20 | 2001 | 2 |
About Tom Britton
Tom Britton is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics and Public Health, Environmental and Occupational Health, having authored 112 papers that have together received 7.5k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (62 papers), Mathematical and Theoretical Epidemiology and Ecology Models (34 papers), Complex Network Analysis Techniques (19 papers), Evolution and Genetic Dynamics (17 papers), Opinion Dynamics and Social Influence (13 papers), Influenza Virus Research Studies (12 papers), Stochastic processes and statistical mechanics (10 papers) and Bayesian Methods and Mixture Models (9 papers). The work is most often cited by research in Modeling and Simulation (2.0k citations), Paleontology (650 citations) and Statistical and Nonlinear Physics (761 citations). Tom Britton has collaborated with scholars based in Sweden, United Kingdom and United States. Frequent co-authors include Håkan Andersson, Peter Arner, Mikael Rydén, Pål O. Westermark, Kirsty L. Spalding, Samuel Bernard, Jonas Frisén, Frank Ball, Hans Heesterbeek and Odo Diekmann. Their work appears in journals such as Journal of Applied Probability, Mathematical Biosciences, Systematic Biology, Journal of Mathematical Biology and Epidemics.
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.