Sam Moore
Impact in
- Modeling and Simulation top 0.5%
- COVID-19 epidemiological studies
- Health top 5%
- Vaccine Coverage and Hesitancy
Papers in
-
- SARS-CoV-2 and COVID-19 Research 4
- Health 4
- Vaccine Coverage and Hesitancy 4
- Co-authors
- Matt J. Keeling (7 shared papers)Edward M. Hill (6 shared papers)Michael J. Tildesley (5 shared papers)Louise Dyson (5 shared papers)Tim Rogers (1 shared paper)Lorenzo Pellis (1 shared paper)Katrina Lythgoe (1 shared paper)Jacob Curran-Sebastian (1 shared paper)
- Journals
- PLoS Computational Biology (2 papers)BMC Medicine (1 paper)Nature Medicine (1 paper)The Lancet Infectious Diseases (1 paper)Physical Review Letters (1 paper)
- Partner nations
- United KingdomUnited StatesSwitzerland
In The Last Decade
Sam Moore
8 papers receiving 708 citations
Sam Moore's Hit Papers
Peers
Comparison fields: 5 of 89
- Modeling and Simulation 440
- Health 184
- Infectious Diseases 370
- Public Health, Environmental and Occupational Health 98
- Economics and Econometrics 86
Countries citing papers authored by Sam Moore
This map shows the geographic impact of Sam Moore'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 Moore with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sam Moore more than expected).
Fields of papers citing papers by Sam Moore
This network shows the impact of papers produced by Sam Moore. 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 Moore. The network helps show where Sam Moore may publish in the future.
Co-authors
The 12 scholars most cited alongside Sam Moore, 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 | Vaccination and non-pharmaceutical interventions for COVID-19: a mathematical modelling study Hit paper breakdown → | 2021 | 399 |
| 2 | 2021 | 132 | |
| 3 | 2021 | 72 | |
| 4 | 2022 | 71 | |
| 5 | 2020 | 30 | |
| 6 | 2022 | 9 | |
| 7 | 2024 | 5 | |
| 8 | 2020 | 3 | |
| 9 | 2025 | 0 |
About Sam Moore
Sam Moore is a scholar working on Infectious Diseases, Health, Modeling and Simulation, General Health Professions and Clinical Psychology, having authored 9 papers that have together received 721 indexed citations. Recurring topics across this work include Vaccine Coverage and Hesitancy (4 papers), COVID-19 epidemiological studies (4 papers), SARS-CoV-2 and COVID-19 Research (4 papers), Evolution and Genetic Dynamics (1 paper), Complex Network Analysis Techniques (1 paper), Mental Health Research Topics (1 paper), Healthcare Systems and Challenges (1 paper) and COVID-19 Pandemic Impacts (1 paper). The work is most often cited by research in Modeling and Simulation (440 citations), Health (184 citations), Infectious Diseases (370 citations), Public Health, Environmental and Occupational Health (98 citations) and Economics and Econometrics (86 citations). Sam Moore has collaborated with scholars based in United Kingdom, United States and Switzerland. Frequent co-authors include Matt J. Keeling, Edward M. Hill, Michael J. Tildesley, Louise Dyson, Tim Rogers, Lorenzo Pellis, Katrina Lythgoe, Jacob Curran-Sebastian, Thomas House and Robin N. Thompson. Their work appears in journals such as PLoS Computational Biology, BMC Medicine, Nature Medicine, The Lancet Infectious Diseases and Physical Review Letters.
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.