Sam Abbott
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Virology top 5%
- Poxvirus research and outbreaks
Papers in
-
- COVID-19 epidemiological studies 25
-
- SARS-CoV-2 and COVID-19 Research 5
- Viral Infections and Outbreaks Research 3
- Co-authors
- Sebastian Funk (21 shared papers)W. John Edmunds (3 shared papers)Ruwan Ratnayake (2 shared papers)Stefan Flasche (2 shared papers)Kevin van Zandvoort (3 shared papers)Joel Hellewell (4 shared papers)Rosalind M. Eggo (3 shared papers)Adam J. Kucharski (3 shared papers)
- Journals
- PLoS Computational Biology (9 papers)Eurosurveillance (3 papers)Science (2 papers)eLife (2 papers)The Lancet Digital Health (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Sam Abbott
41 papers receiving 950 citations
Peers
Comparison fields: 5 of 96
- Modeling and Simulation 453
- Virology 126
- Infectious Diseases 357
- Epidemiology 203
- Public Health, Environmental and Occupational Health 152
Countries citing papers authored by Sam Abbott
This map shows the geographic impact of Sam Abbott'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 Sam Abbott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Abbott more than expected).
Fields of papers citing papers by Sam Abbott
This network shows the impact of papers produced by Sam Abbott. 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 Sam Abbott. The network helps show where Sam Abbott may publish in the future.
Co-authors
The 25 scholars most cited alongside Sam Abbott, 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 43 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 269 | |
| 2 | 2022 | 117 | |
| 3 | 2021 | 113 | |
| 4 | 2022 | 95 | |
| 5 | 2020 | 49 | |
| 6 | 2022 | 37 | |
| 7 | 2021 | 28 | |
| 8 | 2021 | 26 | |
| 9 | 2023 | 25 | |
| 10 | 2023 | 25 | |
| 11 | 2020 | 19 | |
| 12 | 2017 | 16 | |
| 13 | 2022 | 15 | |
| 14 | 2023 | 13 | |
| 15 | 2022 | 12 | |
| 16 | 2023 | 11 | |
| 17 | 2023 | 10 | |
| 18 | 2023 | 9 | |
| 19 | 2024 | 9 | |
| 20 | 2024 | 8 |
About Sam Abbott
Sam Abbott is a scholar working on Modeling and Simulation, Infectious Diseases, Epidemiology, Public Health, Environmental and Occupational Health and Virology, having authored 43 papers that have together received 970 indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (25 papers), Influenza Virus Research Studies (8 papers), SARS-CoV-2 and COVID-19 Research (5 papers), Data-Driven Disease Surveillance (5 papers), Zoonotic diseases and public health (4 papers), COVID-19 Pandemic Impacts (4 papers), Poxvirus research and outbreaks (4 papers) and Viral Infections and Outbreaks Research (3 papers). The work is most often cited by research in Modeling and Simulation (453 citations), Virology (126 citations), Infectious Diseases (357 citations), Epidemiology (203 citations) and Public Health, Environmental and Occupational Health (152 citations). Sam Abbott has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Sebastian Funk, W. John Edmunds, Ruwan Ratnayake, Stefan Flasche, Kevin van Zandvoort, Joel Hellewell, Rosalind M. Eggo, Adam J. Kucharski, Timothy Russell and Christopher I Jarvis. Their work appears in journals such as PLoS Computational Biology, Eurosurveillance, Science, eLife and The Lancet Digital 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.