Ben Swallow
Impact in
- Modeling and Simulation top 5%
- COVID-19 epidemiological studies
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- Viral Infections and Outbreaks Research
- SARS-CoV-2 and COVID-19 Research
Papers in
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- COVID-19 epidemiological studies 10
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- Data-Driven Disease Surveillance 6
- Influenza Virus Research Studies 5
- Co-authors
- Jasmina Panovska‐Griffiths (8 shared papers)Mike P. Toms (4 shared papers)Lorenzo Pellis (4 shared papers)S. T. Buckland (4 shared papers)Ruth King (3 shared papers)Glenn Marion (3 shared papers)Daniel Antunes Maciel Villela (3 shared papers)Peter Challenor (3 shared papers)
- Journals
- Epidemics (7 papers)Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences (2 papers)Journal of Theoretical Biology (2 papers)Ecology and Evolution (2 papers)Journal of Global Health (2 papers)
- Partner nations
- United KingdomUnited StatesBrazil
In The Last Decade
Ben Swallow
24 papers receiving 213 citations
Peers
Comparison fields: 5 of 83
- Modeling and Simulation 94
- Infectious Diseases 50
- Ecological Modeling 11
- Health Informatics 3
- Statistics and Probability 16
Countries citing papers authored by Ben Swallow
This map shows the geographic impact of Ben Swallow'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 Ben Swallow with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Swallow more than expected).
Fields of papers citing papers by Ben Swallow
This network shows the impact of papers produced by Ben Swallow. 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 Ben Swallow. The network helps show where Ben Swallow may publish in the future.
Co-authors
The 25 scholars most cited alongside Ben Swallow, 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 27 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 43 | |
| 2 | 2022 | 27 | |
| 3 | 2015 | 20 | |
| 4 | 2022 | 19 | |
| 5 | 2022 | 19 | |
| 6 | 2021 | 18 | |
| 7 | 2017 | 11 | |
| 8 | 2022 | 11 | |
| 9 | 2016 | 7 | |
| 10 | 2020 | 6 | |
| 11 | 2023 | 6 | |
| 12 | 2022 | 5 | |
| 13 | 2022 | 5 | |
| 14 | 2022 | 4 | |
| 15 | 2025 | 3 | |
| 16 | 2024 | 2 | |
| 17 | 2022 | 2 | |
| 18 | 2019 | 2 | |
| 19 | 2022 | 1 | |
| 20 | 2022 | 1 |
About Ben Swallow
Ben Swallow is a scholar working on Modeling and Simulation, Epidemiology, Infectious Diseases, Artificial Intelligence and Ecology, having authored 27 papers that have together received 216 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (10 papers), Data-Driven Disease Surveillance (6 papers), Influenza Virus Research Studies (5 papers), Statistical Methods and Bayesian Inference (4 papers), Viral Infections and Outbreaks Research (4 papers), SARS-CoV-2 and COVID-19 Research (3 papers), Vaccine Coverage and Hesitancy (3 papers) and Ecology and Vegetation Dynamics Studies (3 papers). The work is most often cited by research in Modeling and Simulation (94 citations), Infectious Diseases (50 citations), Ecological Modeling (11 citations), Health Informatics (3 citations) and Statistics and Probability (16 citations). Ben Swallow has collaborated with scholars based in United Kingdom, United States and Brazil. Frequent co-authors include Jasmina Panovska‐Griffiths, Mike P. Toms, Lorenzo Pellis, S. T. Buckland, Ruth King, Glenn Marion, Daniel Antunes Maciel Villela, Peter Challenor, Francesca Scarabel and Christopher E. Overton. Their work appears in journals such as Epidemics, Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences, Journal of Theoretical Biology, Ecology and Evolution and Journal of Global Health.
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.