Pieter Trapman
Impact in
- Modeling and Simulation top 0.2%
- COVID-19 epidemiological studies
-
- Complex Network Analysis Techniques
- Opinion Dynamics and Social Influence
Papers in
-
- COVID-19 epidemiological studies 24
-
- Complex Network Analysis Techniques 16
- Opinion Dynamics and Social Influence 6
- Co-authors
- Frank BallTom BrittonDavid SirlValerie IshamKen EamesLorenzo PellisHans HeesterbeekDenis Mollison
- Journals
- Advances in Applied Probability (6 papers)Mathematical Biosciences (4 papers)Epidemics (4 papers)Journal of Mathematical Biology (3 papers)Journal of Applied Probability (3 papers)
- Partner nations
- SwedenNetherlandsUnited Kingdom
In The Last Decade
Pieter Trapman
34 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 115
- Modeling and Simulation 751
- Statistical and Nonlinear Physics 370
- Infectious Diseases 388
- Public Health, Environmental and Occupational Health 395
- Mathematical Physics 118
Countries citing papers authored by Pieter Trapman
This map shows the geographic impact of Pieter Trapman'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 Pieter Trapman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pieter Trapman more than expected).
Fields of papers citing papers by Pieter Trapman
This network shows the impact of papers produced by Pieter Trapman. 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 Pieter Trapman. The network helps show where Pieter Trapman may publish in the future.
Co-authors
The 25 scholars most cited alongside Pieter Trapman, 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 | 11 | |
| 2 | 2021 | 2 | |
| 3 | 2021 | 25 | |
| 4 | 2018 | 3 | |
| 5 | 2017 | 7 | |
| 6 | 2015 | 3 | |
| 7 | 2014 | 113 | |
| 8 | 2014 | 33 | |
| 9 | 2014 | 4 | |
| 10 | 2014 | 22 | |
| 11 | 2014 | 117 | |
| 12 | 2013 | 7 | |
| 13 | 2013 | 8 | |
| 14 | 2011 | 11 | |
| 15 | 2010 | 66 | |
| 16 | On the growth of the supercritical long-range percolation cluster on $\mathbb{Z}^d$ and an application for spatial epidemics | 2009 | 1 |
| 17 | 2009 | 25 | |
| 18 | 2009 | 100 | |
| 19 | 2008 | 141 | |
| 20 | 2007 | 21 |
About Pieter Trapman
Pieter Trapman is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics, Mathematical Physics, Public Health, Environmental and Occupational Health and Infectious Diseases, having authored 37 papers that have together received 1.4k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (24 papers), Complex Network Analysis Techniques (16 papers), Mathematical and Theoretical Epidemiology and Ecology Models (12 papers), Stochastic processes and statistical mechanics (10 papers), Opinion Dynamics and Social Influence (6 papers), Evolution and Genetic Dynamics (3 papers), SARS-CoV-2 and COVID-19 Research (3 papers) and Viral Infections and Outbreaks Research (3 papers). The work is most often cited by research in Modeling and Simulation (751 citations), Statistical and Nonlinear Physics (370 citations), Infectious Diseases (388 citations), Public Health, Environmental and Occupational Health (395 citations) and Mathematical Physics (118 citations). Pieter Trapman has collaborated with scholars based in Sweden, Netherlands and United Kingdom. Frequent co-authors include Frank Ball, Tom Britton, David Sirl, Valerie Isham, Ken Eames, Lorenzo Pellis, Hans Heesterbeek, Denis Mollison, Steven Riley and Michael Begon. Their work appears in journals such as Advances in Applied Probability, Mathematical Biosciences, Epidemics, Journal of Mathematical Biology and Journal of Applied Probability.
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.