Thomas House
- Modeling and Simulation top 0.1%
- COVID-19 epidemiological studies 60
- Infectious Diseases top 1%
- SARS-CoV-2 and COVID-19 Research 11
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- Complex Network Analysis Techniques 24
- Opinion Dynamics and Social Influence 10
- Health top 2%
- Epidemiology top 5%
- Influenza Virus Research Studies 15
- Data-Driven Disease Surveillance 8
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- Mathematical and Theoretical Epidemiology and Ecology Models 20
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- Evolution and Genetic Dynamics 9
- Co-authors
- Matt J. KeelingLeón DanonLorenzo PellisJoshua V. RossJonathan M. ReadMatthew C. VernonKoen B. PouwelsKarina-Doris Vihta
- Journals
- Epidemics (10 papers)PLoS Computational Biology (7 papers)Journal of The Royal Society Interface (6 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Thomas House
95 papers receiving 2.8k citations
Hit Papers
Peers
Comparison fields: 5 of 153
- Modeling and Simulation 1.3k
- Infectious Diseases 980
- Statistical and Nonlinear Physics 534
- Health 295
- Epidemiology 625
Countries citing papers authored by Thomas House
This map shows the geographic impact of Thomas House'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 Thomas House with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Thomas House more than expected).
Fields of papers citing papers by Thomas House
This network shows the impact of papers produced by Thomas House. 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 Thomas House. The network helps show where Thomas House may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Thomas House, 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 | 2024 | 2 | |
| 2 | 2024 | 1 | |
| 3 | 2022 | 66 | |
| 4 | 2022 | 10 | |
| 5 | 2021 | 25 | |
| 6 | 2021 | 6 | |
| 7 | Effect of Delta variant on viral burden and vaccine effectiveness against new SARS-CoV-2 infections in the UKbreakdown → | 2021 | 330 |
| 8 | 2021 | 181 | |
| 9 | 2021 | 8 | |
| 10 | 2020 | 15 | |
| 11 | 2016 | 5 | |
| 12 | 2016 | 2 | |
| 13 | 2014 | 3 | |
| 14 | 2014 | 33 | |
| 15 | 2012 | 3 | |
| 16 | 2012 | 10 | |
| 17 | 2012 | 29 | |
| 18 | 2011 | 47 | |
| 19 | 2011 | 23 | |
| 20 | Generalised network clustering and its dynamical
\nimplications | 2010 | 4 |
About Thomas House
Thomas House is a scholar working on Modeling and Simulation, Statistical and Nonlinear Physics, Infectious Diseases, Public Health, Environmental and Occupational Health and Epidemiology, having authored 98 papers that have together received 2.9k indexed citations. Recurring topics across this work include COVID-19 epidemiological studies (60 papers), Complex Network Analysis Techniques (24 papers), Mathematical and Theoretical Epidemiology and Ecology Models (20 papers), Influenza Virus Research Studies (15 papers), SARS-CoV-2 and COVID-19 Research (11 papers), Opinion Dynamics and Social Influence (10 papers), Evolution and Genetic Dynamics (9 papers) and Data-Driven Disease Surveillance (8 papers). The work is most often cited by research in Modeling and Simulation (1.3k citations), Infectious Diseases (980 citations), Statistical and Nonlinear Physics (534 citations), Health (295 citations) and Epidemiology (625 citations). Thomas House has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Matt J. Keeling, León Danon, Lorenzo Pellis, Joshua V. Ross, Jonathan M. Read, Matthew C. Vernon, Koen B. Pouwels, Karina-Doris Vihta, Ruth Studley and Ian Diamond. Their work appears in journals such as Epidemics, PLoS Computational Biology, Journal of The Royal Society Interface, Journal of Mathematical Biology and Journal of Theoretical Biology.
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.